[{"data":1,"prerenderedAt":13042},["ShallowReactive",2],{"navigation_docs":3,"learnalog_locale_counterpart__en_microeconomics_09-behavioural-economics":1782,"-zh-microeconomics-09-behavioural-economics":1783,"-zh-microeconomics-09-behavioural-economics-surround":13037},[4,1038],{"title":5,"path":6,"stem":7,"children":8},"En","\u002Fen","en",[9,12,58,250,406,477,534,715,798,824,943],{"title":10,"path":6,"stem":11},"","en\u002Findex",{"title":13,"path":14,"stem":15,"children":16},"Research Skills and Academic Writing","\u002Fen\u002Facademic-writing","en\u002Facademic-writing\u002Findex",[17,18,22,26,30,34,38,42,46,50,54],{"title":13,"path":14,"stem":15},{"title":19,"path":20,"stem":21},"1. Research Questions, Scope, and Feasibility","\u002Fen\u002Facademic-writing\u002F01-research-questions-and-planning","en\u002Facademic-writing\u002F01-research-questions-and-planning",{"title":23,"path":24,"stem":25},"2. Search, Evaluate, and Read Evidence","\u002Fen\u002Facademic-writing\u002F02-reading-and-literature-matrix","en\u002Facademic-writing\u002F02-reading-and-literature-matrix",{"title":27,"path":28,"stem":29},"3. From Sources to Synthesis and Argument","\u002Fen\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs","en\u002Facademic-writing\u002F03-arguments-outlines-and-paragraphs",{"title":31,"path":32,"stem":33},"4. Literature Review and a Defensible Gap","\u002Fen\u002Facademic-writing\u002F04-writing-the-literature-review","en\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":35,"path":36,"stem":37},"5. Research Design, Evidence, and Core Sections","\u002Fen\u002Facademic-writing\u002F05-core-sections-and-evidence","en\u002Facademic-writing\u002F05-core-sections-and-evidence",{"title":39,"path":40,"stem":41},"6. Citation, Paraphrasing, Integrity, and AI","\u002Fen\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity","en\u002Facademic-writing\u002F06-citation-paraphrasing-and-integrity",{"title":43,"path":44,"stem":45},"7. Revision, Review, and Submission","\u002Fen\u002Facademic-writing\u002F07-revision-style-and-submission","en\u002Facademic-writing\u002F07-revision-style-and-submission",{"title":47,"path":48,"stem":49},"8. Research Workbook","\u002Fen\u002Facademic-writing\u002F08-literature-review-checklist-and-template","en\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":51,"path":52,"stem":53},"9. Research Workflow and Tools","\u002Fen\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management","en\u002Facademic-writing\u002F09-tools-for-academic-writing-and-literature-management",{"title":55,"path":56,"stem":57},"10. Worked Project — From Question to Defensible Conclusion","\u002Fen\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain","en\u002Facademic-writing\u002F10-worked-example-from-block-structure-to-question-chain",{"title":59,"path":60,"stem":61,"children":62,"page":249},"Accounting","\u002Fen\u002Faccounting","en\u002Faccounting",[63,69,87,93,193],{"title":64,"path":65,"stem":66,"children":67},"Accounting — From Evidence to Decisions","\u002Fen\u002Faccounting\u002F00-index","en\u002Faccounting\u002F00-index",[68],{"title":64,"path":65,"stem":66},{"title":70,"path":71,"stem":72,"children":73},"Accounting Appendix","\u002Fen\u002Faccounting\u002Fappendix","en\u002Faccounting\u002Fappendix\u002Findex",[74,75,79,83],{"title":70,"path":71,"stem":72},{"title":76,"path":77,"stem":78},"Worked Examples and Error Diagnosis","\u002Fen\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls","en\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls",{"title":80,"path":81,"stem":82},"Accounting Glossary","\u002Fen\u002Faccounting\u002Fappendix\u002F26-glossary","en\u002Faccounting\u002Fappendix\u002F26-glossary",{"title":84,"path":85,"stem":86},"Reading and Evidence Map","\u002Fen\u002Faccounting\u002Fappendix\u002F27-reading-map","en\u002Faccounting\u002Fappendix\u002F27-reading-map",{"title":88,"path":89,"stem":90,"children":91},"Northstar Record-to-Decision Capstone","\u002Fen\u002Faccounting\u002Fcapstone","en\u002Faccounting\u002Fcapstone\u002Findex",[92],{"title":88,"path":89,"stem":90},{"title":94,"path":95,"stem":96,"children":97},"Financial Accounting","\u002Fen\u002Faccounting\u002Ffinancial-accounting","en\u002Faccounting\u002Ffinancial-accounting\u002Findex",[98,99,117,131,165,179],{"title":94,"path":95,"stem":96},{"title":100,"path":101,"stem":102,"children":103},"1. Foundations","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002Findex",[104,105,109,113],{"title":100,"path":101,"stem":102},{"title":106,"path":107,"stem":108},"Objectives and Qualitative Characteristics","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics",{"title":110,"path":111,"stem":112},"Equation and Elements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements",{"title":114,"path":115,"stem":116},"Accrual Basis, Estimates and Periods","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles","en\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles",{"title":118,"path":119,"stem":120,"children":121},"2. Recording Transactions","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002Findex",[122,123,127],{"title":118,"path":119,"stem":120},{"title":124,"path":125,"stem":126},"Double-Entry and Debit\u002FCredit","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr",{"title":128,"path":129,"stem":130},"Accounting Cycle","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle","en\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",{"title":132,"path":133,"stem":134,"children":135},"3. Measurement and Adjustments","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002Findex",[136,137,141,145,149,153,157,161],{"title":132,"path":133,"stem":134},{"title":138,"path":139,"stem":140},"Revenue Recognition","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition",{"title":142,"path":143,"stem":144},"Inventory","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory",{"title":146,"path":147,"stem":148},"Receivables and Expected Credit Losses","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables",{"title":150,"path":151,"stem":152},"Property, Plant and Equipment","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe",{"title":154,"path":155,"stem":156},"Intangible Assets","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles",{"title":158,"path":159,"stem":160},"Leases","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases",{"title":162,"path":163,"stem":164},"Current and Deferred Income Tax","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax","en\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax",{"title":166,"path":167,"stem":168,"children":169},"4. Reporting and Cash","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002Findex",[170,171,175],{"title":166,"path":167,"stem":168},{"title":172,"path":173,"stem":174},"Linked Financial Statements","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",{"title":176,"path":177,"stem":178},"Cash, Reconciliation and Internal Control","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","en\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control",{"title":180,"path":181,"stem":182,"children":183},"5. Analysis and Comparison","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002Findex",[184,185,189],{"title":180,"path":181,"stem":182},{"title":186,"path":187,"stem":188},"Ratio Analysis","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis",{"title":190,"path":191,"stem":192},"IFRS versus US GAAP","\u002Fen\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap","en\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap",{"title":194,"path":195,"stem":196,"children":197},"Management Accounting","\u002Fen\u002Faccounting\u002Fmanagement-accounting","en\u002Faccounting\u002Fmanagement-accounting\u002Findex",[198,199,217,235],{"title":194,"path":195,"stem":196},{"title":200,"path":201,"stem":202,"children":203},"1. Cost Foundations","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002Findex",[204,205,209,213],{"title":200,"path":201,"stem":202},{"title":206,"path":207,"stem":208},"Cost Concepts and Behaviour","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",{"title":210,"path":211,"stem":212},"Costing Systems","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems",{"title":214,"path":215,"stem":216},"Variable and Absorption Costing","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption","en\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption",{"title":218,"path":219,"stem":220,"children":221},"2. Planning and Control","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002Findex",[222,223,227,231],{"title":218,"path":219,"stem":220},{"title":224,"path":225,"stem":226},"Cost–Volume–Profit Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",{"title":228,"path":229,"stem":230},"Budgeting and Variance Analysis","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",{"title":232,"path":233,"stem":234},"Performance Measurement","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement","en\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement",{"title":236,"path":237,"stem":238,"children":239},"3. Decisions and Investment","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002Findex",[240,241,245],{"title":236,"path":237,"stem":238},{"title":242,"path":243,"stem":244},"Short-Term Decisions","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions",{"title":246,"path":247,"stem":248},"Capital Budgeting","\u002Fen\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","en\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",false,{"title":251,"path":252,"stem":253,"children":254,"page":249},"Business Analytics","\u002Fen\u002Fbusiness-analytics","en\u002Fbusiness-analytics",[255,261,279,305,335,365,383,400],{"title":256,"path":257,"stem":258,"children":259},"Business Analytics — From Data to Defensible Action","\u002Fen\u002Fbusiness-analytics\u002F00-index","en\u002Fbusiness-analytics\u002F00-index",[260],{"title":256,"path":257,"stem":258},{"title":262,"path":263,"stem":264,"children":265},"0. Decision and Data Foundations","\u002Fen\u002Fbusiness-analytics\u002F00-intro","en\u002Fbusiness-analytics\u002F00-intro\u002Findex",[266,267,271,275],{"title":262,"path":263,"stem":264},{"title":268,"path":269,"stem":270},"Decision Framing","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing","en\u002Fbusiness-analytics\u002F00-intro\u002F01-decision-framing",{"title":272,"path":273,"stem":274},"Data Contracts","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts","en\u002Fbusiness-analytics\u002F00-intro\u002F02-data-contracts",{"title":276,"path":277,"stem":278},"Reproducible Analytics Workflow","\u002Fen\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow","en\u002Fbusiness-analytics\u002F00-intro\u002F03-reproducible-workflow",{"title":280,"path":281,"stem":282,"children":283},"1. Descriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive","en\u002Fbusiness-analytics\u002F01-descriptive\u002Findex",[284,285,289,293,297,301],{"title":280,"path":281,"stem":282},{"title":286,"path":287,"stem":288},"Distributions and Exploratory Data Analysis","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda","en\u002Fbusiness-analytics\u002F01-descriptive\u002F04-distributions-eda",{"title":290,"path":291,"stem":292},"KPIs and Denominators","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators","en\u002Fbusiness-analytics\u002F01-descriptive\u002F05-kpis-denominators",{"title":294,"path":295,"stem":296},"Segments, Cohorts and Funnels","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels","en\u002Fbusiness-analytics\u002F01-descriptive\u002F06-segmentation-cohorts-funnels",{"title":298,"path":299,"stem":300},"Visual Evidence and Data Stories","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story","en\u002Fbusiness-analytics\u002F01-descriptive\u002F07-visualisation-story",{"title":302,"path":303,"stem":304},"Experiments and Causal Boundaries","\u002Fen\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary","en\u002Fbusiness-analytics\u002F01-descriptive\u002F08-experiments-causal-boundary",{"title":306,"path":307,"stem":308,"children":309},"2. Predictive Analytics","\u002Fen\u002Fbusiness-analytics\u002F02-predictive","en\u002Fbusiness-analytics\u002F02-predictive\u002Findex",[310,311,315,319,323,327,331],{"title":306,"path":307,"stem":308},{"title":312,"path":313,"stem":314},"Validation, Baselines and Leakage","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage","en\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage",{"title":316,"path":317,"stem":318},"Regression and Forecasting","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting","en\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting",{"title":320,"path":321,"stem":322},"Classification and Calibration","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration","en\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration",{"title":324,"path":325,"stem":326},"Trees and Ensembles","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles","en\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles",{"title":328,"path":329,"stem":330},"Decision Metrics and Thresholds","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds","en\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds",{"title":332,"path":333,"stem":334},"Explainability, Monitoring and Drift","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift","en\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift",{"title":336,"path":337,"stem":338,"children":339},"3. Prescriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive","en\u002Fbusiness-analytics\u002F03-prescriptive\u002Findex",[340,341,345,349,353,357,361],{"title":336,"path":337,"stem":338},{"title":342,"path":343,"stem":344},"Decision-Making under Uncertainty","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty",{"title":346,"path":347,"stem":348},"Linear Optimisation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization",{"title":350,"path":351,"stem":352},"Inventory and Allocation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation",{"title":354,"path":355,"stem":356},"Queueing and Simulation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation",{"title":358,"path":359,"stem":360},"Pricing and Revenue Management","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation",{"title":362,"path":363,"stem":364},"Causal Targeting and Policy Learning","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting",{"title":366,"path":367,"stem":368,"children":369},"4. Deployment and Governance","\u002Fen\u002Fbusiness-analytics\u002F04-deployment","en\u002Fbusiness-analytics\u002F04-deployment\u002Findex",[370,371,375,379],{"title":366,"path":367,"stem":368},{"title":372,"path":373,"stem":374},"Data Products and Monitoring","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring","en\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring",{"title":376,"path":377,"stem":378},"Governance, Fairness and Privacy","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy","en\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy",{"title":380,"path":381,"stem":382},"Adoption and Business Value","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value","en\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value",{"title":384,"path":385,"stem":386,"children":387},"Appendix and Revision Tools","\u002Fen\u002Fbusiness-analytics\u002Fappendix","en\u002Fbusiness-analytics\u002Fappendix\u002Findex",[388,389,393,397],{"title":384,"path":385,"stem":386},{"title":390,"path":391,"stem":392},"Formula and Decision Map","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map","en\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map",{"title":394,"path":395,"stem":396},"Worked Examples and Pitfalls","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls","en\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls",{"title":84,"path":398,"stem":399},"\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map","en\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map",{"title":401,"path":402,"stem":403,"children":404},"Capstone — The Evening Delivery Promise","\u002Fen\u002Fbusiness-analytics\u002Fcapstone","en\u002Fbusiness-analytics\u002Fcapstone\u002Findex",[405],{"title":401,"path":402,"stem":403},{"title":407,"path":408,"stem":409,"children":410,"page":249},"Financial Economic Time Series","\u002Fen\u002Ffinancial-economic-time-series","en\u002Ffinancial-economic-time-series",[411,417,423,429,435,441,447,453,459,465,471],{"title":412,"path":413,"stem":414,"children":415},"Financial and Economic Time Series — Course Guide","\u002Fen\u002Ffinancial-economic-time-series\u002F00-intro","en\u002Ffinancial-economic-time-series\u002F00-intro\u002Findex",[416],{"title":412,"path":413,"stem":414},{"title":418,"path":419,"stem":420,"children":421},"Three Versions of Time Series","\u002Fen\u002Ffinancial-economic-time-series\u002F01-bridge","en\u002Ffinancial-economic-time-series\u002F01-bridge\u002Findex",[422],{"title":418,"path":419,"stem":420},{"title":424,"path":425,"stem":426,"children":427},"Data, Clocks, and Transformations","\u002Fen\u002Ffinancial-economic-time-series\u002F02-data-transformations","en\u002Ffinancial-economic-time-series\u002F02-data-transformations\u002Findex",[428],{"title":424,"path":425,"stem":426},{"title":430,"path":431,"stem":432,"children":433},"Predictive Regressions and Persistent Predictors","\u002Fen\u002Ffinancial-economic-time-series\u002F03-predictive-regressions","en\u002Ffinancial-economic-time-series\u002F03-predictive-regressions\u002Findex",[434],{"title":430,"path":431,"stem":432},{"title":436,"path":437,"stem":438,"children":439},"Volatility, Tails, and Financial Risk","\u002Fen\u002Ffinancial-economic-time-series\u002F04-volatility-risk","en\u002Ffinancial-economic-time-series\u002F04-volatility-risk\u002Findex",[440],{"title":436,"path":437,"stem":438},{"title":442,"path":443,"stem":444,"children":445},"Unit Roots, Cointegration, and Error Correction","\u002Fen\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration","en\u002Ffinancial-economic-time-series\u002F05-unit-roots-cointegration\u002Findex",[446],{"title":442,"path":443,"stem":444},{"title":448,"path":449,"stem":450,"children":451},"VAR, Structural Identification, and Local Projections","\u002Fen\u002Ffinancial-economic-time-series\u002F06-var-identification","en\u002Ffinancial-economic-time-series\u002F06-var-identification\u002Findex",[452],{"title":448,"path":449,"stem":450},{"title":454,"path":455,"stem":456,"children":457},"State Space, Mixed Frequency, and Nowcasting","\u002Fen\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting","en\u002Ffinancial-economic-time-series\u002F07-state-space-nowcasting\u002Findex",[458],{"title":454,"path":455,"stem":456},{"title":460,"path":461,"stem":462,"children":463},"Forecast Evaluation for Decisions","\u002Fen\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation","en\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation\u002Findex",[464],{"title":460,"path":461,"stem":462},{"title":466,"path":467,"stem":468,"children":469},"Integrated R Laboratory","\u002Fen\u002Ffinancial-economic-time-series\u002F09-r-laboratory","en\u002Ffinancial-economic-time-series\u002F09-r-laboratory\u002Findex",[470],{"title":466,"path":467,"stem":468},{"title":472,"path":473,"stem":474,"children":475},"Capstones, Data, and Reading Ladder","\u002Fen\u002Ffinancial-economic-time-series\u002F10-capstone-readings","en\u002Ffinancial-economic-time-series\u002F10-capstone-readings\u002Findex",[476],{"title":472,"path":473,"stem":474},{"title":478,"path":479,"stem":480,"children":481,"page":249},"Intro To Economics","\u002Fen\u002Fintro-to-economics","en\u002Fintro-to-economics",[482,486,490,494,498,502,506,510,514,518,522,526,530],{"title":483,"path":484,"stem":485},"Introduction to Economics — Decisions, Markets, and the Macroeconomy","\u002Fen\u002Fintro-to-economics\u002F00-intro","en\u002Fintro-to-economics\u002F00-intro",{"title":487,"path":488,"stem":489},"Chapter 1 — Choice, Opportunity Cost, and Trade","\u002Fen\u002Fintro-to-economics\u002F01-foundations","en\u002Fintro-to-economics\u002F01-foundations",{"title":491,"path":492,"stem":493},"Chapter 2 — Demand, Supply, Equilibrium, and Welfare","\u002Fen\u002Fintro-to-economics\u002F02-demand-and-supply","en\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":495,"path":496,"stem":497},"Chapter 3 — Elasticity, Revenue, and Tax Incidence","\u002Fen\u002Fintro-to-economics\u002F03-elasticity","en\u002Fintro-to-economics\u002F03-elasticity",{"title":499,"path":500,"stem":501},"Chapter 4 — Firms, Market Power, and Market Failure","\u002Fen\u002Fintro-to-economics\u002F04-market-structures","en\u002Fintro-to-economics\u002F04-market-structures",{"title":503,"path":504,"stem":505},"Chapter 5 — GDP, Income, Wealth, and Welfare","\u002Fen\u002Fintro-to-economics\u002F05-gdp-and-wealth","en\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":507,"path":508,"stem":509},"Chapter 6 — Inflation, Purchasing Power, and Labour Markets","\u002Fen\u002Fintro-to-economics\u002F06-inflation-and-unemployment","en\u002Fintro-to-economics\u002F06-inflation-and-unemployment",{"title":511,"path":512,"stem":513},"Chapter 7 — Productivity, Technology, and Economic Growth","\u002Fen\u002Fintro-to-economics\u002F07-economic-growth","en\u002Fintro-to-economics\u002F07-economic-growth",{"title":515,"path":516,"stem":517},"Chapter 8 — Money, Credit, and Banking","\u002Fen\u002Fintro-to-economics\u002F08-money-and-banking","en\u002Fintro-to-economics\u002F08-money-and-banking",{"title":519,"path":520,"stem":521},"Chapter 9 — Business Cycles, AD–AS, and Monetary Policy","\u002Fen\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as","en\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as",{"title":523,"path":524,"stem":525},"Chapter 10 — Fiscal Policy, Distribution, and Public Debt","\u002Fen\u002Fintro-to-economics\u002F10-fiscal-policy","en\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":527,"path":528,"stem":529},"Chapter 11 — Trade, Capital Flows, and Exchange Rates","\u002Fen\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates","en\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates",{"title":531,"path":532,"stem":533},"Chapter 12 — Integrated Economic Analysis Studio","\u002Fen\u002Fintro-to-economics\u002F12-review-and-case-studies","en\u002Fintro-to-economics\u002F12-review-and-case-studies",{"title":535,"path":536,"stem":537,"children":538,"page":249},"Microeconometrics","\u002Fen\u002Fmicroeconometrics","en\u002Fmicroeconometrics",[539,557,563,581,603,629,651,673,691,709],{"title":540,"path":541,"stem":542,"children":543},"0. Causal Questions and Designs","\u002Fen\u002Fmicroeconometrics\u002F00-foundations","en\u002Fmicroeconometrics\u002F00-foundations\u002Findex",[544,545,549,553],{"title":540,"path":541,"stem":542},{"title":546,"path":547,"stem":548},"Causal Questions and Estimands","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands","en\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands",{"title":550,"path":551,"stem":552},"Potential Outcomes and Experiments","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments","en\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments",{"title":554,"path":555,"stem":556},"Causal Diagrams and Controls","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls","en\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls",{"title":558,"path":559,"stem":560,"children":561},"Microeconometrics — Designing Credible Counterfactuals","\u002Fen\u002Fmicroeconometrics\u002F00-index","en\u002Fmicroeconometrics\u002F00-index",[562],{"title":558,"path":559,"stem":560},{"title":564,"path":565,"stem":566,"children":567},"1. Regression and Inference","\u002Fen\u002Fmicroeconometrics\u002F01-regression","en\u002Fmicroeconometrics\u002F01-regression\u002Findex",[568,569,573,577],{"title":564,"path":565,"stem":566},{"title":570,"path":571,"stem":572},"OLS as a Projection","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection","en\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection",{"title":574,"path":575,"stem":576},"FWL, Selection and Controls","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls","en\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls",{"title":578,"path":579,"stem":580},"Inference and Clustering","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering","en\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering",{"title":582,"path":583,"stem":584,"children":585},"2. Instruments and Panel Data","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002Findex",[586,587,591,595,599],{"title":582,"path":583,"stem":584},{"title":588,"path":589,"stem":590},"Instrumental Variables","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification",{"title":592,"path":593,"stem":594},"Weak Instruments and LATE","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late",{"title":596,"path":597,"stem":598},"Panel Fixed Effects","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects",{"title":600,"path":601,"stem":602},"Dynamic Panels and Limits","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel",{"title":604,"path":605,"stem":606,"children":607},"3. Policy Evaluation Designs","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs","en\u002Fmicroeconometrics\u002F03-policy-designs\u002Findex",[608,609,613,617,621,625],{"title":604,"path":605,"stem":606},{"title":610,"path":611,"stem":612},"Difference-in-Differences","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core",{"title":614,"path":615,"stem":616},"Staggered DID and Event Studies","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies",{"title":618,"path":619,"stem":620},"Regression Discontinuity","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd",{"title":622,"path":623,"stem":624},"Matching, Weighting and Overlap","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting",{"title":626,"path":627,"stem":628},"Synthetic Control","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control",{"title":630,"path":631,"stem":632,"children":633},"Module 4 — Choice and Limited Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002Findex",[634,635,639,643,647],{"title":630,"path":631,"stem":632},{"title":636,"path":637,"stem":638},"Binary Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice",{"title":640,"path":641,"stem":642},"Multinomial and Ordered Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice",{"title":644,"path":645,"stem":646},"Count Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes",{"title":648,"path":649,"stem":650},"Censoring, Truncation and Selection","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection",{"title":652,"path":653,"stem":654,"children":655},"Module 5 — Modern Causal Analysis","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal","en\u002Fmicroeconometrics\u002F05-modern-causal\u002Findex",[656,657,661,665,669],{"title":652,"path":653,"stem":654},{"title":658,"path":659,"stem":660},"Double Machine Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml",{"title":662,"path":663,"stem":664},"Heterogeneity and Policy Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy",{"title":666,"path":667,"stem":668},"Sensitivity and Partial Identification","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id",{"title":670,"path":671,"stem":672},"External Validity and Transport","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity",{"title":674,"path":675,"stem":676,"children":677},"Module 6 — From Data to Auditable Evidence","\u002Fen\u002Fmicroeconometrics\u002F06-workflow","en\u002Fmicroeconometrics\u002F06-workflow\u002Findex",[678,679,683,687],{"title":674,"path":675,"stem":676},{"title":680,"path":681,"stem":682},"Data Provenance","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance","en\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance",{"title":684,"path":685,"stem":686},"Reproducibility and Reporting","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting","en\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting",{"title":688,"path":689,"stem":690},"Paper and Evidence Audit","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit","en\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit",{"title":692,"path":693,"stem":694,"children":695},"Appendix — Revision and Evidence Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix","en\u002Fmicroeconometrics\u002Fappendix\u002Findex",[696,697,701,705],{"title":692,"path":693,"stem":694},{"title":698,"path":699,"stem":700},"Formula and Design Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map","en\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map",{"title":702,"path":703,"stem":704},"Ten Worked Microeconometric Pitfalls","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls","en\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls",{"title":706,"path":707,"stem":708},"Reading and Software Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map","en\u002Fmicroeconometrics\u002Fappendix\u002F29-reading-software-map",{"title":710,"path":711,"stem":712,"children":713},"Capstone — Should Northbridge Expand Pathways?","\u002Fen\u002Fmicroeconometrics\u002Fcapstone","en\u002Fmicroeconometrics\u002Fcapstone\u002Findex",[714],{"title":710,"path":711,"stem":712},{"title":716,"path":717,"stem":718,"children":719,"page":249},"Microeconomics","\u002Fen\u002Fmicroeconomics","en\u002Fmicroeconomics",[720,726,732,738,744,750,756,762,768,774,780,786,792],{"title":721,"path":722,"stem":723,"children":724},"Advanced Microeconomics — Course Guide","\u002Fen\u002Fmicroeconomics\u002F00-intro","en\u002Fmicroeconomics\u002F00-intro\u002Findex",[725],{"title":721,"path":722,"stem":723},{"title":727,"path":728,"stem":729,"children":730},"Module 1 — Choice, Duality, and Revealed Preference","\u002Fen\u002Fmicroeconomics\u002F01-fundations","en\u002Fmicroeconomics\u002F01-fundations\u002Findex",[731],{"title":727,"path":728,"stem":729},{"title":733,"path":734,"stem":735,"children":736},"Module 2 — Comparative Statics and Welfare Measurement","\u002Fen\u002Fmicroeconomics\u002F02-comparative-statics","en\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[737],{"title":733,"path":734,"stem":735},{"title":739,"path":740,"stem":741,"children":742},"Module 3 — Choice under Risk and Insurance","\u002Fen\u002Fmicroeconomics\u002F03-uncertainty","en\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[743],{"title":739,"path":740,"stem":741},{"title":745,"path":746,"stem":747,"children":748},"Module 4 — General Equilibrium and Welfare","\u002Fen\u002Fmicroeconomics\u002F04-general-equilibrium","en\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[749],{"title":745,"path":746,"stem":747},{"title":751,"path":752,"stem":753,"children":754},"Module 5 — Static, Dynamic, and Repeated Games","\u002Fen\u002Fmicroeconomics\u002F05-game-theory","en\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[755],{"title":751,"path":752,"stem":753},{"title":757,"path":758,"stem":759,"children":760},"Module 6 — Oligopoly, Entry, and Algorithmic Pricing","\u002Fen\u002Fmicroeconomics\u002F06-oligopoly","en\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[761],{"title":757,"path":758,"stem":759},{"title":763,"path":764,"stem":765,"children":766},"Module 7 — Information Economics and Contracts","\u002Fen\u002Fmicroeconomics\u002F07-information-economics","en\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[767],{"title":763,"path":764,"stem":765},{"title":769,"path":770,"stem":771,"children":772},"Module 8 — Mechanism Design and Auctions","\u002Fen\u002Fmicroeconomics\u002F08-mechanism-design","en\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[773],{"title":769,"path":770,"stem":771},{"title":775,"path":776,"stem":777,"children":778},"Module 9 — Behavioural and Experimental Microeconomics","\u002Fen\u002Fmicroeconomics\u002F09-behavioural-economics","en\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[779],{"title":775,"path":776,"stem":777},{"title":781,"path":782,"stem":783,"children":784},"Module 10 — Externalities, Public Goods, and Collective Action","\u002Fen\u002Fmicroeconomics\u002F10-externalities-public-goods","en\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[785],{"title":781,"path":782,"stem":783},{"title":787,"path":788,"stem":789,"children":790},"Module 11 — Matching and Market Design","\u002Fen\u002Fmicroeconomics\u002F11-market-design","en\u002Fmicroeconomics\u002F11-market-design\u002Findex",[791],{"title":787,"path":788,"stem":789},{"title":793,"path":794,"stem":795,"children":796},"Module 12 — Integrated Microeconomic Design Studio","\u002Fen\u002Fmicroeconomics\u002F12-review","en\u002Fmicroeconomics\u002F12-review\u002Findex",[797],{"title":793,"path":794,"stem":795},{"title":799,"path":800,"stem":801,"children":802},"Playground","\u002Fen\u002Fplayground","en\u002Fplayground\u002Findex",[803,804,808,812,816,820],{"title":799,"path":800,"stem":801},{"title":805,"path":806,"stem":807},"Typst Plugin Playground","\u002Fen\u002Fplayground\u002F01-typstex","en\u002Fplayground\u002F01-typstex",{"title":809,"path":810,"stem":811},"Citation Plugin Test","\u002Fen\u002Fplayground\u002F02-citation","en\u002Fplayground\u002F02-citation",{"title":813,"path":814,"stem":815},"Pyodide Playground","\u002Fen\u002Fplayground\u002F03-pyodide","en\u002Fplayground\u002F03-pyodide",{"title":817,"path":818,"stem":819},"WebR Playground","\u002Fen\u002Fplayground\u002F04-webr","en\u002Fplayground\u002F04-webr",{"title":821,"path":822,"stem":823},"Chart.js Visualizations","\u002Fen\u002Fplayground\u002F05-chartjs","en\u002Fplayground\u002F05-chartjs",{"title":825,"path":826,"stem":827,"children":828,"page":249},"Statistics For Insurance","\u002Fen\u002Fstatistics-for-insurance","en\u002Fstatistics-for-insurance",[829,835,857,883,905,927,937],{"title":830,"path":831,"stem":832,"children":833},"Statistics for General Insurance","\u002Fen\u002Fstatistics-for-insurance\u002F01-intro","en\u002Fstatistics-for-insurance\u002F01-intro\u002Findex",[834],{"title":830,"path":831,"stem":832},{"title":836,"path":837,"stem":838,"children":839},"Claims Development and Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002Findex",[840,841,845,849,853],{"title":836,"path":837,"stem":838},{"title":842,"path":843,"stem":844},"Basic Chain Ladder","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain",{"title":846,"path":847,"stem":848},"Frequency–Severity Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim",{"title":850,"path":851,"stem":852},"Bornhuetter–Ferguson Method","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method",{"title":854,"path":855,"stem":856},"Uncertainty and Diagnostics","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics",{"title":858,"path":859,"stem":860,"children":861},"Frequency and Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002Findex",[862,863,867,871,875,879],{"title":858,"path":859,"stem":860},{"title":864,"path":865,"stem":866},"Core Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist",{"title":868,"path":869,"stem":870},"Tail Models and Extreme Values","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist",{"title":872,"path":873,"stem":874},"Claim Count Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist",{"title":876,"path":877,"stem":878},"Fitting and Validating Loss Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist",{"title":880,"path":881,"stem":882},"Mixtures and Heterogeneity","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist",{"title":884,"path":885,"stem":886,"children":887},"Reinsurance as a Loss Transformation","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002Findex",[888,889,893,897,901],{"title":884,"path":885,"stem":886},{"title":890,"path":891,"stem":892},"Proportional Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional",{"title":894,"path":895,"stem":896},"Excess-of-Loss Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess",{"title":898,"path":899,"stem":900},"Inflation and Layer Erosion","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation",{"title":902,"path":903,"stem":904},"Reinsurance Decision Lab","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples",{"title":906,"path":907,"stem":908,"children":909},"Aggregate Risk and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002Findex",[910,911,915,919,923],{"title":906,"path":907,"stem":908},{"title":912,"path":913,"stem":914},"Collective Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective",{"title":916,"path":917,"stem":918},"Individual Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual",{"title":920,"path":921,"stem":922},"Aggregate Risk Computation Lab","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples",{"title":924,"path":925,"stem":926},"Tail Risk, Dependence, and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital",{"title":928,"path":929,"stem":930,"children":931},"Surplus and Ruin Theory","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002Findex",[932,933],{"title":928,"path":929,"stem":930},{"title":934,"path":935,"stem":936},"Finite-Time Ruin Simulation","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation",{"title":938,"path":939,"stem":940,"children":941},"Portfolio Risk Capstone","\u002Fen\u002Fstatistics-for-insurance\u002F07-capstone","en\u002Fstatistics-for-insurance\u002F07-capstone\u002Findex",[942],{"title":938,"path":939,"stem":940},{"title":944,"path":945,"stem":946,"children":947,"page":249},"Time Series","\u002Fen\u002Ftime-series","en\u002Ftime-series",[948,958,964,970,976,982,988,994,1016],{"title":949,"path":950,"stem":951,"children":952},"Classical Time Series — Course Guide","\u002Fen\u002Ftime-series\u002F00-intro","en\u002Ftime-series\u002F00-intro\u002Findex",[953,954],{"title":949,"path":950,"stem":951},{"title":955,"path":956,"stem":957},"Preparation — Stationarity in 30 Minutes","\u002Fen\u002Ftime-series\u002F00-intro\u002F01-stationary","en\u002Ftime-series\u002F00-intro\u002F01-stationary",{"title":959,"path":960,"stem":961,"children":962},"Module 1 — Processes, Dependence, and Stationarity","\u002Fen\u002Ftime-series\u002F01-stochastic-process","en\u002Ftime-series\u002F01-stochastic-process\u002Findex",[963],{"title":959,"path":960,"stem":961},{"title":965,"path":966,"stem":967,"children":968},"Module 2 — ARMA, ARIMA, and Model Identification","\u002Fen\u002Ftime-series\u002F02-arma","en\u002Ftime-series\u002F02-arma\u002Findex",[969],{"title":965,"path":966,"stem":967},{"title":971,"path":972,"stem":973,"children":974},"Module 3 — Linear Prediction and State-Space Recursions","\u002Fen\u002Ftime-series\u002F03-prediction","en\u002Ftime-series\u002F03-prediction\u002Findex",[975],{"title":971,"path":972,"stem":973},{"title":977,"path":978,"stem":979,"children":980},"Module 4 — Estimation, Likelihood, and Inference","\u002Fen\u002Ftime-series\u002F04-estimation","en\u002Ftime-series\u002F04-estimation\u002Findex",[981],{"title":977,"path":978,"stem":979},{"title":983,"path":984,"stem":985,"children":986},"Module 5 — Systems, Seasonality, and Cointegration","\u002Fen\u002Ftime-series\u002F05-multi-ar","en\u002Ftime-series\u002F05-multi-ar\u002Findex",[987],{"title":983,"path":984,"stem":985},{"title":989,"path":990,"stem":991,"children":992},"Module 6 — Spectral Analysis, Cycles, and Filters","\u002Fen\u002Ftime-series\u002F06-spectral-analysis","en\u002Ftime-series\u002F06-spectral-analysis\u002Findex",[993],{"title":989,"path":990,"stem":991},{"title":995,"path":996,"stem":997,"children":998},"R Matrix Laboratory","\u002Fen\u002Ftime-series\u002F07-r-implementation","en\u002Ftime-series\u002F07-r-implementation\u002Findex",[999,1000,1004,1008,1012],{"title":995,"path":996,"stem":997},{"title":1001,"path":1002,"stem":1003},"R Matrix Lab 1 — Covariance Geometry","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices","en\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices",{"title":1005,"path":1006,"stem":1007},"R Matrix Lab 2 — AR Recursions and Yule–Walker Equations","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions","en\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions",{"title":1009,"path":1010,"stem":1011},"R Matrix Lab 3 — Prediction and Gaussian Likelihood","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood","en\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood",{"title":1013,"path":1014,"stem":1015},"R Matrix Lab 4 — State Space and Kalman Filtering","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F04-state-space","en\u002Ftime-series\u002F07-r-implementation\u002F04-state-space",{"title":1017,"path":1018,"stem":1019,"children":1020},"Optional Python Appendix — Empirical Forecasting","\u002Fen\u002Ftime-series\u002F08-python-implementation","en\u002Ftime-series\u002F08-python-implementation\u002Findex",[1021,1022,1026,1030,1034],{"title":1017,"path":1018,"stem":1019},{"title":1023,"path":1024,"stem":1025},"Optional Python Lab 1 — Explore Before Modeling","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F01-exploration","en\u002Ftime-series\u002F08-python-implementation\u002F01-exploration",{"title":1027,"path":1028,"stem":1029},"Optional Python Lab 2 — Diagnose Stationarity","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity","en\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity",{"title":1031,"path":1032,"stem":1033},"Optional Python Lab 3 — Fit and Audit ARMA Errors","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting","en\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting",{"title":1035,"path":1036,"stem":1037},"Optional Python Lab 4 — Forecast, Backtest, and Monitor","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F04-forecasting","en\u002Ftime-series\u002F08-python-implementation\u002F04-forecasting",{"title":1039,"path":1040,"stem":1041,"children":1042},"Zh","\u002Fzh","zh",[1043,1045,1063,1247,1323,1365,1421,1467,1543,1625,1633,1731],{"title":10,"path":1040,"stem":1044},"zh\u002Findex",{"title":1046,"path":1047,"stem":1048,"children":1049},"学术写作与文献综述","\u002Fzh\u002Facademic-writing","zh\u002Facademic-writing\u002Findex",[1050,1051,1055,1059],{"title":1046,"path":1047,"stem":1048},{"title":1052,"path":1053,"stem":1054},"4. 文献综述的构建与写作","\u002Fzh\u002Facademic-writing\u002F04-writing-the-literature-review","zh\u002Facademic-writing\u002F04-writing-the-literature-review",{"title":1056,"path":1057,"stem":1058},"8. 文献综述清单与模板","\u002Fzh\u002Facademic-writing\u002F08-literature-review-checklist-and-template","zh\u002Facademic-writing\u002F08-literature-review-checklist-and-template",{"title":1060,"path":1061,"stem":1062},"10. 从分块结构到问题链：文献综述示例","\u002Fzh\u002Facademic-writing\u002F10-从分块结构到问题链-文献综述示例","zh\u002Facademic-writing\u002F10-从分块结构到问题链-文献综述示例",{"title":59,"path":1064,"stem":1065,"children":1066,"page":249},"\u002Fzh\u002Faccounting","zh\u002Faccounting",[1067,1073,1087,1191],{"title":1068,"path":1069,"stem":1070,"children":1071},"会计学学习路线图","\u002Fzh\u002Faccounting\u002F00-index","zh\u002Faccounting\u002F00-index",[1072],{"title":1068,"path":1069,"stem":1070},{"title":1074,"path":1075,"stem":1076,"children":1077},"附录","\u002Fzh\u002Faccounting\u002Fappendix","zh\u002Faccounting\u002Fappendix\u002Findex",[1078,1079,1083],{"title":1074,"path":1075,"stem":1076},{"title":1080,"path":1081,"stem":1082},"综合示例与常见陷阱","\u002Fzh\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls","zh\u002Faccounting\u002Fappendix\u002F24-examples-pitfalls",{"title":1084,"path":1085,"stem":1086},"会计术语速查表","\u002Fzh\u002Faccounting\u002Fappendix\u002F26-glossary","zh\u002Faccounting\u002Fappendix\u002F26-glossary",{"title":1088,"path":1089,"stem":1090,"children":1091},"金融会计","\u002Fzh\u002Faccounting\u002Ffinancial-accounting","zh\u002Faccounting\u002Ffinancial-accounting\u002Findex",[1092,1093,1111,1125,1159,1173],{"title":1088,"path":1089,"stem":1090},{"title":1094,"path":1095,"stem":1096,"children":1097},"1. 基础","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002Findex",[1098,1099,1103,1107],{"title":1094,"path":1095,"stem":1096},{"title":1100,"path":1101,"stem":1102},"会计信息目标与质量特征","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F01-objectives-qualitative-characteristics",{"title":1104,"path":1105,"stem":1106},"会计等式与要素","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F02-equation-elements",{"title":1108,"path":1109,"stem":1110},"记账基础与原则","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles","zh\u002Faccounting\u002Ffinancial-accounting\u002F01-foundations\u002F03-accounting-bases-principles",{"title":1112,"path":1113,"stem":1114,"children":1115},"2. 交易记录","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002Findex",[1116,1117,1121],{"title":1112,"path":1113,"stem":1114},{"title":1118,"path":1119,"stem":1120},"复式记账与借贷规则","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F04-double-entry-dr-cr",{"title":1122,"path":1123,"stem":1124},"会计循环","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle","zh\u002Faccounting\u002Ffinancial-accounting\u002F02-recording-transactions\u002F05-accounting-cycle",{"title":1126,"path":1127,"stem":1128,"children":1129},"3. 计量与调整","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002Findex",[1130,1131,1135,1139,1143,1147,1151,1155],{"title":1126,"path":1127,"stem":1128},{"title":1132,"path":1133,"stem":1134},"收入确认","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F07-revenue-recognition",{"title":1136,"path":1137,"stem":1138},"存货","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F08-inventory",{"title":1140,"path":1141,"stem":1142},"应收账款","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F09-receivables",{"title":1144,"path":1145,"stem":1146},"固定资产","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F10-ppe",{"title":1148,"path":1149,"stem":1150},"无形资产","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F11-intangibles",{"title":1152,"path":1153,"stem":1154},"租赁","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F12-leases",{"title":1156,"path":1157,"stem":1158},"所得税","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax","zh\u002Faccounting\u002Ffinancial-accounting\u002F03-measurement-adjustments\u002F13-income-tax",{"title":1160,"path":1161,"stem":1162,"children":1163},"4. 报表与现金","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002Findex",[1164,1165,1169],{"title":1160,"path":1161,"stem":1162},{"title":1166,"path":1167,"stem":1168},"财务报表","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements",{"title":1170,"path":1171,"stem":1172},"现金控制","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control","zh\u002Faccounting\u002Ffinancial-accounting\u002F04-reporting-cash\u002F14-cash-control",{"title":1174,"path":1175,"stem":1176,"children":1177},"5. 分析与比较","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002Findex",[1178,1179,1183,1187],{"title":1174,"path":1175,"stem":1176},{"title":1180,"path":1181,"stem":1182},"财务比率分析","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis",{"title":1184,"path":1185,"stem":1186},"IFRS 与 US GAAP 对比","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F25-ifrs-gaap",{"title":1188,"path":1189,"stem":1190},"2026 准则更新与报告案例","\u002Fzh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F27-current-standards-2026","zh\u002Faccounting\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F27-current-standards-2026",{"title":1192,"path":1193,"stem":1194,"children":1195},"管理会计","\u002Fzh\u002Faccounting\u002Fmanagement-accounting","zh\u002Faccounting\u002Fmanagement-accounting\u002Findex",[1196,1197,1215,1233],{"title":1192,"path":1193,"stem":1194},{"title":1198,"path":1199,"stem":1200,"children":1201},"1. 成本基础","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002Findex",[1202,1203,1207,1211],{"title":1198,"path":1199,"stem":1200},{"title":1204,"path":1205,"stem":1206},"成本概念","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts",{"title":1208,"path":1209,"stem":1210},"成本核算系统","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F17-costing-systems",{"title":1212,"path":1213,"stem":1214},"变动成本法 vs. 吸收成本法","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption","zh\u002Faccounting\u002Fmanagement-accounting\u002F01-cost-foundations\u002F19-variable-vs-absorption",{"title":1216,"path":1217,"stem":1218,"children":1219},"2. 计划与控制","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002Findex",[1220,1221,1225,1229],{"title":1216,"path":1217,"stem":1218},{"title":1222,"path":1223,"stem":1224},"本量利分析","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F18-cvp-analysis",{"title":1226,"path":1227,"stem":1228},"预算与差异分析","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances",{"title":1230,"path":1231,"stem":1232},"绩效评价","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement","zh\u002Faccounting\u002Fmanagement-accounting\u002F02-planning-control\u002F21-performance-measurement",{"title":1234,"path":1235,"stem":1236,"children":1237},"3. 决策与投资","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002Findex",[1238,1239,1243],{"title":1234,"path":1235,"stem":1236},{"title":1240,"path":1241,"stem":1242},"短期决策","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions",{"title":1244,"path":1245,"stem":1246},"资本预算","\u002Fzh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","zh\u002Faccounting\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting",{"title":1248,"path":1249,"stem":1250,"children":1251},"资产定价理论","\u002Fzh\u002Fasset-pricing","zh\u002Fasset-pricing\u002Findex",[1252,1253,1259,1265,1271,1277,1283,1289,1295,1301,1307,1313,1319],{"title":1248,"path":1249,"stem":1250},{"title":1254,"path":1255,"stem":1256,"children":1257},"第一章：引言与基础","\u002Fzh\u002Fasset-pricing\u002F01-intro","zh\u002Fasset-pricing\u002F01-intro\u002Findex",[1258],{"title":1254,"path":1255,"stem":1256},{"title":1260,"path":1261,"stem":1262,"children":1263},"第二章：效用理论与风险偏好","\u002Fzh\u002Fasset-pricing\u002F02-utility","zh\u002Fasset-pricing\u002F02-utility\u002Findex",[1264],{"title":1260,"path":1261,"stem":1262},{"title":1266,"path":1267,"stem":1268,"children":1269},"第三章：均值-方差分析","\u002Fzh\u002Fasset-pricing\u002F03-mean-variance","zh\u002Fasset-pricing\u002F03-mean-variance\u002Findex",[1270],{"title":1266,"path":1267,"stem":1268},{"title":1272,"path":1273,"stem":1274,"children":1275},"第四章：资本资产定价模型(CAPM)","\u002Fzh\u002Fasset-pricing\u002F04-capm","zh\u002Fasset-pricing\u002F04-capm\u002Findex",[1276],{"title":1272,"path":1273,"stem":1274},{"title":1278,"path":1279,"stem":1280,"children":1281},"第五章：因子模型","\u002Fzh\u002Fasset-pricing\u002F05-factor-models","zh\u002Fasset-pricing\u002F05-factor-models\u002Findex",[1282],{"title":1278,"path":1279,"stem":1280},{"title":1284,"path":1285,"stem":1286,"children":1287},"第六章：跨期资产定价","\u002Fzh\u002Fasset-pricing\u002F06-intertemporal","zh\u002Fasset-pricing\u002F06-intertemporal\u002Findex",[1288],{"title":1284,"path":1285,"stem":1286},{"title":1290,"path":1291,"stem":1292,"children":1293},"第七章：期权定价理论","\u002Fzh\u002Fasset-pricing\u002F07-options","zh\u002Fasset-pricing\u002F07-options\u002Findex",[1294],{"title":1290,"path":1291,"stem":1292},{"title":1296,"path":1297,"stem":1298,"children":1299},"第八章：固定收益证券","\u002Fzh\u002Fasset-pricing\u002F08-fixed-income","zh\u002Fasset-pricing\u002F08-fixed-income\u002Findex",[1300],{"title":1296,"path":1297,"stem":1298},{"title":1302,"path":1303,"stem":1304,"children":1305},"第九章：市场有效性与异象","\u002Fzh\u002Fasset-pricing\u002F09-efficiency","zh\u002Fasset-pricing\u002F09-efficiency\u002Findex",[1306],{"title":1302,"path":1303,"stem":1304},{"title":1308,"path":1309,"stem":1310,"children":1311},"第十章：数值方法与实证应用","\u002Fzh\u002Fasset-pricing\u002F10-empirical","zh\u002Fasset-pricing\u002F10-empirical\u002Findex",[1312],{"title":1308,"path":1309,"stem":1310},{"title":1314,"path":1315,"stem":1316,"children":1317},"第十一章：资产定价浏览器交互实验","\u002Fzh\u002Fasset-pricing\u002F11-interactive-labs","zh\u002Fasset-pricing\u002F11-interactive-labs\u002Findex",[1318],{"title":1314,"path":1315,"stem":1316},{"title":1320,"path":1321,"stem":1322},"第十二章：前沿文献与现代资产定价案例（2023—2026）","\u002Fzh\u002Fasset-pricing\u002F12-frontier-literature-2026","zh\u002Fasset-pricing\u002F12-frontier-literature-2026",{"title":1324,"path":1325,"stem":1326,"children":1327},"计量经济学","\u002Fzh\u002Feconometrics","zh\u002Feconometrics\u002Findex",[1328,1329,1333,1337,1341,1345,1349,1353,1357,1361],{"title":1324,"path":1325,"stem":1326},{"title":1330,"path":1331,"stem":1332},"第一章：数据、概率与回归对象","\u002Fzh\u002Feconometrics\u002F01-data-and-regression","zh\u002Feconometrics\u002F01-data-and-regression",{"title":1334,"path":1335,"stem":1336},"第二章：OLS、矩阵与几何解释","\u002Fzh\u002Feconometrics\u002F02-ols-and-geometry","zh\u002Feconometrics\u002F02-ols-and-geometry",{"title":1338,"path":1339,"stem":1340},"第三章：统计推断与稳健标准误","\u002Fzh\u002Feconometrics\u002F03-inference-and-robustness","zh\u002Feconometrics\u002F03-inference-and-robustness",{"title":1342,"path":1343,"stem":1344},"第四章：内生性、工具变量与两阶段最小二乘","\u002Fzh\u002Feconometrics\u002F04-endogeneity-and-iv","zh\u002Feconometrics\u002F04-endogeneity-and-iv",{"title":1346,"path":1347,"stem":1348},"第五章：面板数据与时间序列","\u002Fzh\u002Feconometrics\u002F05-panel-and-time-series","zh\u002Feconometrics\u002F05-panel-and-time-series",{"title":1350,"path":1351,"stem":1352},"第六章：估计方法与因果设计的共同基础","\u002Fzh\u002Feconometrics\u002F06-estimation-and-causal-design","zh\u002Feconometrics\u002F06-estimation-and-causal-design",{"title":1354,"path":1355,"stem":1356},"第七章：可重复计量实证项目","\u002Fzh\u002Feconometrics\u002F07-reproducible-project","zh\u002Feconometrics\u002F07-reproducible-project",{"title":1358,"path":1359,"stem":1360},"第八章：计量经济学浏览器回归实验","\u002Fzh\u002Feconometrics\u002F08-interactive-regression-labs","zh\u002Feconometrics\u002F08-interactive-regression-labs",{"title":1362,"path":1363,"stem":1364},"第九章：前沿文献与现代计量案例（2023—2026）","\u002Fzh\u002Feconometrics\u002F09-frontier-literature-2026","zh\u002Feconometrics\u002F09-frontier-literature-2026",{"title":478,"path":1366,"stem":1367,"children":1368,"page":249},"\u002Fzh\u002Fintro-to-economics","zh\u002Fintro-to-economics",[1369,1373,1377,1381,1385,1389,1393,1397,1401,1405,1409,1413,1417],{"title":1370,"path":1371,"stem":1372},"经济学导论 (微观与宏观)","\u002Fzh\u002Fintro-to-economics\u002F00-intro","zh\u002Fintro-to-economics\u002F00-intro",{"title":1374,"path":1375,"stem":1376},"第1章：经济学基础原理","\u002Fzh\u002Fintro-to-economics\u002F01-foundations","zh\u002Fintro-to-economics\u002F01-foundations",{"title":1378,"path":1379,"stem":1380},"第2章：需求与供给","\u002Fzh\u002Fintro-to-economics\u002F02-demand-and-supply","zh\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":1382,"path":1383,"stem":1384},"第3章：弹性","\u002Fzh\u002Fintro-to-economics\u002F03-elasticity","zh\u002Fintro-to-economics\u002F03-elasticity",{"title":1386,"path":1387,"stem":1388},"第4章：市场结构","\u002Fzh\u002Fintro-to-economics\u002F04-market-structures","zh\u002Fintro-to-economics\u002F04-market-structures",{"title":1390,"path":1391,"stem":1392},"第5章：GDP 与财富","\u002Fzh\u002Fintro-to-economics\u002F05-gdp-and-wealth","zh\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":1394,"path":1395,"stem":1396},"第6章：通货膨胀与失业","\u002Fzh\u002Fintro-to-economics\u002F06-inflation-and-unemployment","zh\u002Fintro-to-economics\u002F06-inflation-and-unemployment",{"title":1398,"path":1399,"stem":1400},"第7章：经济增长","\u002Fzh\u002Fintro-to-economics\u002F07-economic-growth","zh\u002Fintro-to-economics\u002F07-economic-growth",{"title":1402,"path":1403,"stem":1404},"第8章：货币与银行","\u002Fzh\u002Fintro-to-economics\u002F08-money-and-banking","zh\u002Fintro-to-economics\u002F08-money-and-banking",{"title":1406,"path":1407,"stem":1408},"第9章：货币政策与 AD-AS 模型","\u002Fzh\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as","zh\u002Fintro-to-economics\u002F09-monetary-policy-and-ad-as",{"title":1410,"path":1411,"stem":1412},"第10章：财政政策","\u002Fzh\u002Fintro-to-economics\u002F10-fiscal-policy","zh\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":1414,"path":1415,"stem":1416},"第11章：开放经济与汇率","\u002Fzh\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates","zh\u002Fintro-to-economics\u002F11-open-economy-and-exchange-rates",{"title":1418,"path":1419,"stem":1420},"第12章：综合复习与案例分析","\u002Fzh\u002Fintro-to-economics\u002F12-review-and-case-studies","zh\u002Fintro-to-economics\u002F12-review-and-case-studies",{"title":1422,"path":1423,"stem":1424,"children":1425},"宏观经济学","\u002Fzh\u002Fmacroeconomics","zh\u002Fmacroeconomics\u002Findex",[1426,1427,1431,1435,1439,1443,1447,1451,1455,1459,1463],{"title":1422,"path":1423,"stem":1424},{"title":1428,"path":1429,"stem":1430},"第一章：国民账户与宏观指标","\u002Fzh\u002Fmacroeconomics\u002F01-national-accounts","zh\u002Fmacroeconomics\u002F01-national-accounts",{"title":1432,"path":1433,"stem":1434},"第二章：消费、投资与凯恩斯交叉","\u002Fzh\u002Fmacroeconomics\u002F02-consumption-investment","zh\u002Fmacroeconomics\u002F02-consumption-investment",{"title":1436,"path":1437,"stem":1438},"第三章：货币、银行与货币政策","\u002Fzh\u002Fmacroeconomics\u002F03-money-and-monetary-policy","zh\u002Fmacroeconomics\u002F03-money-and-monetary-policy",{"title":1440,"path":1441,"stem":1442},"第四章：AD–AS、通货膨胀与失业","\u002Fzh\u002Fmacroeconomics\u002F04-ad-as-inflation-unemployment","zh\u002Fmacroeconomics\u002F04-ad-as-inflation-unemployment",{"title":1444,"path":1445,"stem":1446},"第五章：财政政策、债务与稳定化","\u002Fzh\u002Fmacroeconomics\u002F05-fiscal-policy-and-debt","zh\u002Fmacroeconomics\u002F05-fiscal-policy-and-debt",{"title":1448,"path":1449,"stem":1450},"第六章：经济增长、生产率与发展","\u002Fzh\u002Fmacroeconomics\u002F06-growth-productivity","zh\u002Fmacroeconomics\u002F06-growth-productivity",{"title":1452,"path":1453,"stem":1454},"第七章：开放经济、汇率与国际收支","\u002Fzh\u002Fmacroeconomics\u002F07-open-economy","zh\u002Fmacroeconomics\u002F07-open-economy",{"title":1456,"path":1457,"stem":1458},"第八章：宏观研究项目与政策分析","\u002Fzh\u002Fmacroeconomics\u002F08-macro-research-project","zh\u002Fmacroeconomics\u002F08-macro-research-project",{"title":1460,"path":1461,"stem":1462},"第九章：宏观经济学浏览器交互实验","\u002Fzh\u002Fmacroeconomics\u002F09-interactive-policy-labs","zh\u002Fmacroeconomics\u002F09-interactive-policy-labs",{"title":1464,"path":1465,"stem":1466},"第十章：前沿文献与当代宏观案例（2023—2026）","\u002Fzh\u002Fmacroeconomics\u002F10-frontier-literature-2026","zh\u002Fmacroeconomics\u002F10-frontier-literature-2026",{"title":1468,"path":1469,"stem":1470,"children":1471},"微观计量经济学","\u002Fzh\u002Fmicroeconometrics","zh\u002Fmicroeconometrics\u002Findex",[1472,1473,1479,1485,1491,1497,1503,1509,1515,1521,1527,1533,1539],{"title":1468,"path":1469,"stem":1470},{"title":1474,"path":1475,"stem":1476,"children":1477},"第一章：微观计量与因果推断导论","\u002Fzh\u002Fmicroeconometrics\u002F01-intro","zh\u002Fmicroeconometrics\u002F01-intro\u002Findex",[1478],{"title":1474,"path":1475,"stem":1476},{"title":1480,"path":1481,"stem":1482,"children":1483},"第二章：线性回归与 OLS","\u002Fzh\u002Fmicroeconometrics\u002F02-ols","zh\u002Fmicroeconometrics\u002F02-ols\u002Findex",[1484],{"title":1480,"path":1481,"stem":1482},{"title":1486,"path":1487,"stem":1488,"children":1489},"第三章：工具变量法","\u002Fzh\u002Fmicroeconometrics\u002F03-iv","zh\u002Fmicroeconometrics\u002F03-iv\u002Findex",[1490],{"title":1486,"path":1487,"stem":1488},{"title":1492,"path":1493,"stem":1494,"children":1495},"第四章：面板数据方法","\u002Fzh\u002Fmicroeconometrics\u002F04-panel","zh\u002Fmicroeconometrics\u002F04-panel\u002Findex",[1496],{"title":1492,"path":1493,"stem":1494},{"title":1498,"path":1499,"stem":1500,"children":1501},"第五章：双重差分法","\u002Fzh\u002Fmicroeconometrics\u002F05-did","zh\u002Fmicroeconometrics\u002F05-did\u002Findex",[1502],{"title":1498,"path":1499,"stem":1500},{"title":1504,"path":1505,"stem":1506,"children":1507},"第六章：断点回归设计","\u002Fzh\u002Fmicroeconometrics\u002F06-rdd","zh\u002Fmicroeconometrics\u002F06-rdd\u002Findex",[1508],{"title":1504,"path":1505,"stem":1506},{"title":1510,"path":1511,"stem":1512,"children":1513},"第七章：匹配、倾向得分与加权","\u002Fzh\u002Fmicroeconometrics\u002F07-matching","zh\u002Fmicroeconometrics\u002F07-matching\u002Findex",[1514],{"title":1510,"path":1511,"stem":1512},{"title":1516,"path":1517,"stem":1518,"children":1519},"第八章：离散选择模型","\u002Fzh\u002Fmicroeconometrics\u002F08-discrete-choice","zh\u002Fmicroeconometrics\u002F08-discrete-choice\u002Findex",[1520],{"title":1516,"path":1517,"stem":1518},{"title":1522,"path":1523,"stem":1524,"children":1525},"第九章：计数数据与受限因变量","\u002Fzh\u002Fmicroeconometrics\u002F09-count-limited","zh\u002Fmicroeconometrics\u002F09-count-limited\u002Findex",[1526],{"title":1522,"path":1523,"stem":1524},{"title":1528,"path":1529,"stem":1530,"children":1531},"第十章：合成控制法","\u002Fzh\u002Fmicroeconometrics\u002F10-synthetic-control","zh\u002Fmicroeconometrics\u002F10-synthetic-control\u002Findex",[1532],{"title":1528,"path":1529,"stem":1530},{"title":1534,"path":1535,"stem":1536,"children":1537},"第十一章：机器学习与因果推断","\u002Fzh\u002Fmicroeconometrics\u002F11-ml-causal","zh\u002Fmicroeconometrics\u002F11-ml-causal\u002Findex",[1538],{"title":1534,"path":1535,"stem":1536},{"title":1540,"path":1541,"stem":1542},"第十二章：前沿文献与现代微观案例（2024—2026）","\u002Fzh\u002Fmicroeconometrics\u002F12-frontier-literature-2026","zh\u002Fmicroeconometrics\u002F12-frontier-literature-2026",{"title":716,"path":1544,"stem":1545,"children":1546,"page":249},"\u002Fzh\u002Fmicroeconomics","zh\u002Fmicroeconomics",[1547,1553,1559,1565,1571,1577,1583,1589,1595,1601,1607,1613,1619],{"title":1548,"path":1549,"stem":1550,"children":1551},"微观经济学 III","\u002Fzh\u002Fmicroeconomics\u002F00-intro","zh\u002Fmicroeconomics\u002F00-intro\u002Findex",[1552],{"title":1548,"path":1549,"stem":1550},{"title":1554,"path":1555,"stem":1556,"children":1557},"消费者理论与分析基础","\u002Fzh\u002Fmicroeconomics\u002F01-fundations","zh\u002Fmicroeconomics\u002F01-fundations\u002Findex",[1558],{"title":1554,"path":1555,"stem":1556},{"title":1560,"path":1561,"stem":1562,"children":1563},"比较静态分析与福利测度","\u002Fzh\u002Fmicroeconomics\u002F02-comparative-statics","zh\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[1564],{"title":1560,"path":1561,"stem":1562},{"title":1566,"path":1567,"stem":1568,"children":1569},"不确定性下的决策","\u002Fzh\u002Fmicroeconomics\u002F03-uncertainty","zh\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[1570],{"title":1566,"path":1567,"stem":1568},{"title":1572,"path":1573,"stem":1574,"children":1575},"一般均衡与福利经济学","\u002Fzh\u002Fmicroeconomics\u002F04-general-equilibrium","zh\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[1576],{"title":1572,"path":1573,"stem":1574},{"title":1578,"path":1579,"stem":1580,"children":1581},"博弈论：静态与动态博弈","\u002Fzh\u002Fmicroeconomics\u002F05-game-theory","zh\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[1582],{"title":1578,"path":1579,"stem":1580},{"title":1584,"path":1585,"stem":1586,"children":1587},"寡头垄断与策略性市场行为","\u002Fzh\u002Fmicroeconomics\u002F06-oligopoly","zh\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[1588],{"title":1584,"path":1585,"stem":1586},{"title":1590,"path":1591,"stem":1592,"children":1593},"信息经济学：逆向选择与道德风险","\u002Fzh\u002Fmicroeconomics\u002F07-information-economics","zh\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[1594],{"title":1590,"path":1591,"stem":1592},{"title":1596,"path":1597,"stem":1598,"children":1599},"机制设计与拍卖理论","\u002Fzh\u002Fmicroeconomics\u002F08-mechanism-design","zh\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[1600],{"title":1596,"path":1597,"stem":1598},{"title":1602,"path":1603,"stem":1604,"children":1605},"行为与实验微观经济学","\u002Fzh\u002Fmicroeconomics\u002F09-behavioural-economics","zh\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[1606],{"title":1602,"path":1603,"stem":1604},{"title":1608,"path":1609,"stem":1610,"children":1611},"外部性、公共物品与机制","\u002Fzh\u002Fmicroeconomics\u002F10-externalities-public-goods","zh\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[1612],{"title":1608,"path":1609,"stem":1610},{"title":1614,"path":1615,"stem":1616,"children":1617},"市场设计与匹配理论","\u002Fzh\u002Fmicroeconomics\u002F11-market-design","zh\u002Fmicroeconomics\u002F11-market-design\u002Findex",[1618],{"title":1614,"path":1615,"stem":1616},{"title":1620,"path":1621,"stem":1622,"children":1623},"第十二章：微观经济学：回顾与前沿应用","\u002Fzh\u002Fmicroeconomics\u002F12-review","zh\u002Fmicroeconomics\u002F12-review\u002Findex",[1624],{"title":1620,"path":1621,"stem":1622},{"title":799,"path":1626,"stem":1627,"children":1628,"page":249},"\u002Fzh\u002Fplayground","zh\u002Fplayground",[1629],{"title":1630,"path":1631,"stem":1632},"Chart.js 可视化","\u002Fzh\u002Fplayground\u002F05-chartjs","zh\u002Fplayground\u002F05-chartjs",{"title":1634,"path":1635,"stem":1636,"children":1637},"概率论与数理统计","\u002Fzh\u002Fprob-and-stats","zh\u002Fprob-and-stats\u002Findex",[1638,1639,1645,1680,1727],{"title":1634,"path":1635,"stem":1636},{"title":1640,"path":1641,"stem":1642,"children":1643},"第零章：概率统计的对象与学习方法","\u002Fzh\u002Fprob-and-stats\u002F00-intro","zh\u002Fprob-and-stats\u002F00-intro\u002Findex",[1644],{"title":1640,"path":1641,"stem":1642},{"title":1646,"path":1647,"stem":1648,"children":1649,"page":249},"01 Probability","\u002Fzh\u002Fprob-and-stats\u002F01-probability","zh\u002Fprob-and-stats\u002F01-probability",[1650,1656,1662,1668,1674],{"title":1651,"path":1652,"stem":1653,"children":1654},"第一章：概率论基础","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F01-prob-theory","zh\u002Fprob-and-stats\u002F01-probability\u002F01-prob-theory\u002Findex",[1655],{"title":1651,"path":1652,"stem":1653},{"title":1657,"path":1658,"stem":1659,"children":1660},"第二章：随机变量与分布","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F02-random-variables","zh\u002Fprob-and-stats\u002F01-probability\u002F02-random-variables\u002Findex",[1661],{"title":1657,"path":1658,"stem":1659},{"title":1663,"path":1664,"stem":1665,"children":1666},"第三章：期望、方差与条件矩","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F03-moment","zh\u002Fprob-and-stats\u002F01-probability\u002F03-moment\u002Findex",[1667],{"title":1663,"path":1664,"stem":1665},{"title":1669,"path":1670,"stem":1671,"children":1672},"第四章：常见分布族与建模机制","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F04-families","zh\u002Fprob-and-stats\u002F01-probability\u002F04-families\u002Findex",[1673],{"title":1669,"path":1670,"stem":1671},{"title":1675,"path":1676,"stem":1677,"children":1678},"第五章：收敛与渐近理论","\u002Fzh\u002Fprob-and-stats\u002F01-probability\u002F05-asymptotics","zh\u002Fprob-and-stats\u002F01-probability\u002F05-asymptotics\u002Findex",[1679],{"title":1675,"path":1676,"stem":1677},{"title":1681,"path":1682,"stem":1683,"children":1684,"page":249},"02 Statistics","\u002Fzh\u002Fprob-and-stats\u002F02-statistics","zh\u002Fprob-and-stats\u002F02-statistics",[1685,1691,1697,1703,1709,1715,1721],{"title":1686,"path":1687,"stem":1688,"children":1689},"第六章：抽样分布","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling","zh\u002Fprob-and-stats\u002F02-statistics\u002F01-sampling\u002Findex",[1690],{"title":1686,"path":1687,"stem":1688},{"title":1692,"path":1693,"stem":1694,"children":1695},"第七章：区间估计","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F02-interval-estimation\u002Findex",[1696],{"title":1692,"path":1693,"stem":1694},{"title":1698,"path":1699,"stem":1700,"children":1701},"第八章：点估计理论","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation","zh\u002Fprob-and-stats\u002F02-statistics\u002F03-point-estimation\u002Findex",[1702],{"title":1698,"path":1699,"stem":1700},{"title":1704,"path":1705,"stem":1706,"children":1707},"第九章：点估计方法","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F04-pe-method\u002Findex",[1708],{"title":1704,"path":1705,"stem":1706},{"title":1710,"path":1711,"stem":1712,"children":1713},"第十章：假设检验原理","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis","zh\u002Fprob-and-stats\u002F02-statistics\u002F05-hypothesis\u002Findex",[1714],{"title":1710,"path":1711,"stem":1712},{"title":1716,"path":1717,"stem":1718,"children":1719},"第十一章：常用检验方法与选择","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method","zh\u002Fprob-and-stats\u002F02-statistics\u002F06-hypothesis-method\u002Findex",[1720],{"title":1716,"path":1717,"stem":1718},{"title":1722,"path":1723,"stem":1724,"children":1725},"第十二章：Bootstrap 与重抽样","\u002Fzh\u002Fprob-and-stats\u002F02-statistics\u002F07-bootstrap","zh\u002Fprob-and-stats\u002F02-statistics\u002F07-bootstrap\u002Findex",[1726],{"title":1722,"path":1723,"stem":1724},{"title":1728,"path":1729,"stem":1730},"第十三章：前沿文献与现代统计案例（2023—2026）","\u002Fzh\u002Fprob-and-stats\u002F03-frontier-literature-2026","zh\u002Fprob-and-stats\u002F03-frontier-literature-2026",{"title":1732,"path":1733,"stem":1734,"children":1735,"page":249},"Quant","\u002Fzh\u002Fquant","zh\u002Fquant",[1736,1742,1746,1750,1754,1758,1762,1766,1770,1774,1778],{"title":1737,"path":1738,"stem":1739,"children":1740},"量化投资——从可检验信号到可执行组合","\u002Fzh\u002Fquant\u002F00-index","zh\u002Fquant\u002F00-index",[1741],{"title":1737,"path":1738,"stem":1739},{"title":1743,"path":1744,"stem":1745},"数据获取与预处理","\u002Fzh\u002Fquant\u002F01-research-data","zh\u002Fquant\u002F01-research-data",{"title":1747,"path":1748,"stem":1749},"因子与交易信号","\u002Fzh\u002Fquant\u002F02-factor-and-signals","zh\u002Fquant\u002F02-factor-and-signals",{"title":1751,"path":1752,"stem":1753},"策略建模与回测","\u002Fzh\u002Fquant\u002F03-modeling-and-backtest","zh\u002Fquant\u002F03-modeling-and-backtest",{"title":1755,"path":1756,"stem":1757},"组合构建与风险建模（资产定价视角）","\u002Fzh\u002Fquant\u002F04-portfolio-and-risk","zh\u002Fquant\u002F04-portfolio-and-risk",{"title":1759,"path":1760,"stem":1761},"执行策略与市场微结构概览","\u002Fzh\u002Fquant\u002F05-execution-and-microstructure","zh\u002Fquant\u002F05-execution-and-microstructure",{"title":1763,"path":1764,"stem":1765},"策略上线、监控与迭代","\u002Fzh\u002Fquant\u002F06-production-and-monitoring","zh\u002Fquant\u002F06-production-and-monitoring",{"title":1767,"path":1768,"stem":1769},"量化工程与工具链概览","\u002Fzh\u002Fquant\u002F07-engineering-stack","zh\u002Fquant\u002F07-engineering-stack",{"title":1771,"path":1772,"stem":1773},"计量方法与实证检验","\u002Fzh\u002Fquant\u002F08-econometric-methods","zh\u002Fquant\u002F08-econometric-methods",{"title":1775,"path":1776,"stem":1777},"案例研究：多因子股票 Alpha 策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"title":1779,"path":1780,"stem":1781},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",{"path":776},{"id":1784,"title":1602,"body":1785,"description":13030,"extension":13031,"features":13032,"hero":13032,"layout":13032,"locale":13032,"meta":13033,"navigation":13032,"path":1603,"published":13034,"seo":13035,"stem":1604,"__hash__":13036},"docs\u002Fzh\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex.md",{"type":1786,"value":1787,"toc":12969},"minimark",[1788,1793,1797,1801,1804,1820,1823,1842,1846,1849,1852,2054,2057,2060,2063,2141,2144,2148,2156,2177,2188,2214,2220,2224,2238,2242,2246,2256,2261,2281,2285,2291,2296,2299,2305,2314,2437,2441,2448,2452,2460,2464,2467,2473,2487,2491,2494,2499,2507,2511,2517,2660,2666,3053,3194,3199,3207,3211,3215,3220,3225,3233,3238,3246,3385,3391,3395,3408,3460,3949,3954,4267,4319,4597,4602,4883,4916,4920,4926,4931,4950,4956,5008,5013,5024,5028,5033,5064,5070,5074,5082,5086,5094,5098,5102,5107,5152,5157,5218,5223,5243,5247,5263,5267,5273,5314,5318,5332,5340,5344,5348,5966,6121,6416,6421,6429,6434,6445,6449,6455,7412,7416,7989,7994,8100,8103,8588,8683,8686,8877,9090,9333,9481,9484,9490,9494,9498,9504,10041,10122,10128,10746,10803,10808,11471,11475,11483,11489,11493,11502,11506,11517,11522,11527,11531,11537,11551,11556,11648,11652,11656,11662,11688,11692,11773,11777,11781,11785,11796,11802,11808,11818,11822,11826,11837,11842,11846,11861,11865,11875,11879,11883,11893,11897,11947,11951,11956,11970,11975,11983,11987,11992,12003,12008,12016,12021,12029,12033,12037,12090,12094,12112,12116,12120,12126,12131,12151,12157,12168,12172,12177,12188,12193,12204,12208,12212,12293,12296,12360,12363,12368,12379,12385,12399,12405,12409,12414,12440,12445,12460,12465,12480,12485,12499,12504,12518,12521,12539,12552,12555,12558,12564,12570,12821,12913,12916,12930,12933,12950,12953,12956,12959],[1789,1790,1792],"h1",{"id":1791},"第-9-讲行为与实验微观经济学","第 9 讲：行为与实验微观经济学",[1794,1795,1796],"h2",{"id":1796},"本章导学",[1798,1799,1800],"p",{},"标准微观模型非常有力量，但它依赖稳定偏好、完全理性和自利行为等假设。本章不是简单否定这些假设，而是问：当实验和现实行为系统性偏离标准模型时，我们应当怎样修正模型，并保持经济分析的可检验性？",[1798,1802,1803],{},"学完本章后，你应当能够：",[1805,1806,1807,1811,1814,1817],"ul",{},[1808,1809,1810],"li",{},"说明有限理性、启发式偏差和满意化行为如何改变选择模型。",[1808,1812,1813],{},"用前景理论解释损失规避、参考点依赖和框架效应。",[1808,1815,1816],{},"分析社会偏好、互惠、公平和惩罚行为在博弈中的作用。",[1808,1818,1819],{},"理解实验室实验、田野实验和助推政策的基本设计逻辑。",[1798,1821,1822],{},"常见考查会给出现实行为现象，要求你判断它挑战了标准模型的哪一条假设，并用行为模型重新解释。答题时要避免把所有异常都归因于“非理性”，更好的写法是指出偏好、信念、注意力或决策过程发生了什么变化。",[1798,1824,1825,1826,1831,1832,1836,1837,1841],{},"本章与",[1827,1828,1830],"a",{"href":1829},"..\u002F03-uncertainty\u002F","第 3 章","的风险选择和",[1827,1833,1835],{"href":1834},"..\u002F05-game-theory\u002F","第 5 章","的社会互动有密切关系，也为",[1827,1838,1840],{"href":1839},"..\u002F12-review\u002F","第 12 章","讨论数字平台和算法决策提供更现实的行为基础。",[1794,1843,1845],{"id":1844},"论文精读生成式-ai-作为行为经济学实验场景","论文精读：生成式 AI 作为行为经济学实验场景",[1798,1847,1848],{},"生成式 AI 不是本章的技术新闻，而是一个非常好的行为经济学案例。它同时改变了搜索成本、反馈速度、努力成本、默认选项和错误感知。换句话说，它让我们可以把有限理性、锚定、现时偏好、过度自信和选择架构放到同一个现实场景里分析。",[1798,1850,1851],{},"先用基础模型看。学生是否使用 AI，可以理解成一个跨期选择：",[1853,1854,1857],"span",{"className":1855},[1856],"katex-display",[1853,1858,1861,1920],{"className":1859},[1860],"katex",[1853,1862,1865],{"className":1863},[1864],"katex-mathml",[1866,1867,1870],"math",{"xmlns":1868,"display":1869},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML","block",[1871,1872,1873,1915],"semantics",{},[1874,1875,1876,1880,1884,1888,1891,1894,1897,1900,1903,1906,1908,1911],"mrow",{},[1877,1878,1879],"mi",{},"U",[1881,1882,1883],"mo",{},"=",[1885,1886,1887],"mtext",{},"short-term grade benefit",[1881,1889,1890],{},"+",[1877,1892,1893],{},"δ",[1881,1895,1896],{},"×",[1885,1898,1899],{},"future skill benefit",[1881,1901,1902],{},"−",[1885,1904,1905],{},"effort cost",[1881,1907,1902],{},[1885,1909,1910],{},"integrity risk",[1877,1912,1914],{"mathvariant":1913},"normal",".",[1916,1917,1919],"annotation",{"encoding":1918},"application\u002Fx-tex","U=\\text{short-term grade benefit}+\\delta \\times \\text{future skill benefit}-\\text{effort cost}-\\text{integrity risk}.",[1853,1921,1925,1952,1977,1997,2018,2039],{"className":1922,"ariaHidden":1924},[1923],"katex-html","true",[1853,1926,1929,1934,1940,1945,1949],{"className":1927},[1928],"base",[1853,1930],{"className":1931,"style":1933},[1932],"strut","height:0.6833em;",[1853,1935,1879],{"className":1936,"style":1939},[1937,1938],"mord","mathnormal","margin-right:0.109em;",[1853,1941],{"className":1942,"style":1944},[1943],"mspace","margin-right:0.2778em;",[1853,1946,1883],{"className":1947},[1948],"mrel",[1853,1950],{"className":1951,"style":1944},[1943],[1853,1953,1955,1959,1966,1970,1974],{"className":1954},[1928],[1853,1956],{"className":1957,"style":1958},[1932],"height:0.8889em;vertical-align:-0.1944em;",[1853,1960,1963],{"className":1961},[1937,1962],"text",[1853,1964,1887],{"className":1965},[1937],[1853,1967],{"className":1968,"style":1969},[1943],"margin-right:0.2222em;",[1853,1971,1890],{"className":1972},[1973],"mbin",[1853,1975],{"className":1976,"style":1969},[1943],[1853,1978,1980,1984,1988,1991,1994],{"className":1979},[1928],[1853,1981],{"className":1982,"style":1983},[1932],"height:0.7778em;vertical-align:-0.0833em;",[1853,1985,1893],{"className":1986,"style":1987},[1937,1938],"margin-right:0.0379em;",[1853,1989],{"className":1990,"style":1969},[1943],[1853,1992,1896],{"className":1993},[1973],[1853,1995],{"className":1996,"style":1969},[1943],[1853,1998,2000,2003,2009,2012,2015],{"className":1999},[1928],[1853,2001],{"className":2002,"style":1983},[1932],[1853,2004,2006],{"className":2005},[1937,1962],[1853,2007,1899],{"className":2008},[1937],[1853,2010],{"className":2011,"style":1969},[1943],[1853,2013,1902],{"className":2014},[1973],[1853,2016],{"className":2017,"style":1969},[1943],[1853,2019,2021,2024,2030,2033,2036],{"className":2020},[1928],[1853,2022],{"className":2023,"style":1983},[1932],[1853,2025,2027],{"className":2026},[1937,1962],[1853,2028,1905],{"className":2029},[1937],[1853,2031],{"className":2032,"style":1969},[1943],[1853,2034,1902],{"className":2035},[1973],[1853,2037],{"className":2038,"style":1969},[1943],[1853,2040,2042,2045,2051],{"className":2041},[1928],[1853,2043],{"className":2044,"style":1958},[1932],[1853,2046,2048],{"className":2047},[1937,1962],[1853,2049,1910],{"className":2050},[1937],[1853,2052,1914],{"className":2053},[1937],[1798,2055,2056],{},"当 AI 大幅降低起草和改写成本时，短期收益上升，努力成本下降。如果评价制度只看最终文本，学生就更容易选择“快速生成”；如果评价制度要求过程记录、证据核查和口头解释，长期能力和诚信风险就会重新进入决策。",[1798,2058,2059],{},"Kumar et al. (2026, DOI: 10.3390\u002Finfo17030299) 关于 fluency illusion 的研究，可以放到过度自信部分精读。AI 输出越流畅，学生越容易把“文字读起来顺”误认为“我已经理解”。这对应的是本章的认知偏差：判断依据从真实理解转向表面可得性和语言流畅度。读这类论文时，不要只写“AI 可能有害学习”，而要说明机制：流畅输出降低了学生发现自己不懂的概率。",[1798,2061,2062],{},"Coman et al. (2026, DOI: 10.3389\u002Ffrai.2026.1750978) 和 Ganguly et al. (2025, DOI: 10.1007\u002Fs43681-025-00916-0) 的综述则更适合放到选择架构部分。它们提示我们，AI 是否促进学习，取决于任务如何设计。AI 如果被设计成“直接给答案”，就会强化现时偏好；如果被设计成“提出反问、要求证据、暴露逻辑漏洞”，它反而可能成为一种助推，帮助学生进行更深的自我监控。",[2064,2065,2066,2082],"table",{},[2067,2068,2069],"thead",{},[2070,2071,2072,2076,2079],"tr",{},[2073,2074,2075],"th",{},"行为经济学概念",[2073,2077,2078],{},"AI 场景中的机制",[2073,2080,2081],{},"论文阅读重点",[2083,2084,2085,2097,2108,2119,2130],"tbody",{},[2070,2086,2087,2091,2094],{},[2088,2089,2090],"td",{},"有限理性",[2088,2092,2093],{},"AI 降低搜索成本，但也可能减少独立比较证据",[2088,2095,2096],{},"学生是否仍然检查来源和反例。",[2070,2098,2099,2102,2105],{},[2088,2100,2101],{},"锚定效应",[2088,2103,2104],{},"第一版 AI 答案成为后续写作框架",[2088,2106,2107],{},"学生是否主动生成 alternative outline。",[2070,2109,2110,2113,2116],{},[2088,2111,2112],{},"现时偏好",[2088,2114,2115],{},"快速完成作业压过长期能力积累",[2088,2117,2118],{},"评价制度是否奖励过程而不只是成品。",[2070,2120,2121,2124,2127],{},[2088,2122,2123],{},"过度自信",[2088,2125,2126],{},"流畅文本造成 fluency illusion",[2088,2128,2129],{},"是否用解释、复述和迁移任务检验理解。",[2070,2131,2132,2135,2138],{},[2088,2133,2134],{},"助推",[2088,2136,2137],{},"prompt log、引用核查、反思说明改变默认行为",[2088,2139,2140],{},"规则是否让深度学习变成低摩擦选择。",[1798,2142,2143],{},"所以，如果考试或论文让你分析“生成式 AI 对学生学习的影响”，不要只写工具优缺点。更像行为经济学的写法是：先说明 AI 如何改变选择环境，再说明这些改变通过哪些偏差和激励影响行为，最后讨论制度设计能否纠偏。例如，要求学生提交 prompt log、引用核查表和反思说明，并不是形式主义；它相当于把“直接生成答案”的默认路径，改造成“必须解释证据来源和判断过程”的选择架构。",[1794,2145,2147],{"id":2146},"经济动机-economic-motivation","经济动机 (Economic Motivation)",[1798,2149,2150,2151,2155],{},"传统的微观经济学模型通常假设人是",[2152,2153,2154],"strong",{},"完全理性的、自私的\"经济人\" (Homo Economicus)","：",[2157,2158,2159,2165,2171],"ol",{},[1808,2160,2161,2164],{},[2152,2162,2163],{},"完全理性","：拥有无限的计算能力，总是做出最优决策",[1808,2166,2167,2170],{},[2152,2168,2169],{},"稳定偏好","：偏好不受框架、情绪或环境影响",[1808,2172,2173,2176],{},[2152,2174,2175],{},"完全自利","：只关心自己的物质收益，不关心他人福利或公平",[1798,2178,2179,2180,2183,2184,2187],{},"然而，大量的",[2152,2181,2182],{},"心理学和实验证据","表明，人类的行为",[2152,2185,2186],{},"系统性地","偏离了这些标准假设：",[1805,2189,2190,2197,2202,2208],{},[1808,2191,2192,2193,2196],{},"人们会在损失框架和收益框架下做出不同选择（",[2152,2194,2195],{},"框架效应","）",[1808,2198,2199,2200,2196],{},"人们重视当前消费远超未来消费（",[2152,2201,2112],{},[1808,2203,2204,2205,2196],{},"人们愿意惩罚不公平行为，即使要付出代价（",[2152,2206,2207],{},"公平偏好",[1808,2209,2210,2211,2196],{},"人们过度自信、锚定、遵循从众行为（",[2152,2212,2213],{},"认知偏差",[1798,2215,2216,2219],{},[2152,2217,2218],{},"行为经济学 (Behavioral Economics)"," 将心理学的洞见融入经济学分析，旨在建立更符合现实、更具预测能力的理论模型。",[2221,2222,2223],"h3",{"id":2223},"诺贝尔奖认可",[1805,2225,2226,2232],{},[1808,2227,2228,2231],{},[2152,2229,2230],{},"2002年",": Daniel Kahneman（心理学家）和Vernon Smith（实验经济学家）",[1808,2233,2234,2237],{},[2152,2235,2236],{},"2017年",": Richard Thaler（助推理论、心理账户、禀赋效应）",[1794,2239,2241],{"id":2240},"一有限理性-bounded-rationality","一、有限理性 (Bounded Rationality)",[2221,2243,2245],{"id":2244},"_11-herbert-simon的有限理性理论","1.1 Herbert Simon的有限理性理论",[1798,2247,2248,2251,2252,2255],{},[2152,2249,2250],{},"Simon (1955)"," 提出，由于认知能力、信息处理能力和时间的限制，人们无法做到完全理性。相反，人们采用",[2152,2253,2254],{},"满意化 (satisficing)"," 而非最优化策略。",[1798,2257,2258,2155],{},[2152,2259,2260],{},"核心观点",[1805,2262,2263,2269,2275],{},[1808,2264,2265,2268],{},[2152,2266,2267],{},"程序理性 (Procedural Rationality)","：关注决策过程而非结果",[1808,2270,2271,2274],{},[2152,2272,2273],{},"有限搜索","：不穷尽所有选项，而是搜索到\"足够好\"的选项就停止",[1808,2276,2277,2280],{},[2152,2278,2279],{},"启发式规则 (Heuristics)","：使用简单的经验法则快速决策",[2221,2282,2284],{"id":2283},"_12-启发式与偏差-heuristics-and-biases","1.2 启发式与偏差 (Heuristics and Biases)",[1798,2286,2287,2290],{},[2152,2288,2289],{},"Kahneman & Tversky"," 识别了许多系统性偏差：",[2292,2293,2295],"h4",{"id":2294},"_1-代表性启发式-representativeness-heuristic","(1) 代表性启发式 (Representativeness Heuristic)",[1798,2297,2298],{},"人们根据事物的代表性而非概率做判断。",[1798,2300,2301,2304],{},[2152,2302,2303],{},"例子","（Linda问题）：",[2306,2307,2308,2311],"blockquote",{},[1798,2309,2310],{},"Linda今年31岁，单身，外向且非常聪明。她大学主修哲学，深切关注歧视和社会正义议题，并参加过反核示威。",[1798,2312,2313],{},"以下哪个更可能？\nA. Linda是银行出纳员\nB. Linda是银行出纳员且活跃于女权运动",[1798,2315,2316,2317,2433,2434,2196],{},"理性答案：A（因为 ",[1853,2318,2320,2362],{"className":2319},[1860],[1853,2321,2323],{"className":2322},[1864],[1866,2324,2325],{"xmlns":1868},[1871,2326,2327,2359],{},[1874,2328,2329,2332,2336,2339,2342,2345,2347,2349,2351,2354,2357],{},[1877,2330,2331],{},"P",[1881,2333,2335],{"stretchy":2334},"false","(",[1877,2337,2338],{},"A",[1881,2340,2341],{"stretchy":2334},")",[1881,2343,2344],{},"≥",[1877,2346,2331],{},[1881,2348,2335],{"stretchy":2334},[1877,2350,2338],{},[1881,2352,2353],{},"∩",[1877,2355,2356],{},"B",[1881,2358,2341],{"stretchy":2334},[1916,2360,2361],{"encoding":1918},"P(A) \\geq P(A \\cap B)",[1853,2363,2365,2396,2420],{"className":2364,"ariaHidden":1924},[1923],[1853,2366,2368,2372,2376,2380,2383,2387,2390,2393],{"className":2367},[1928],[1853,2369],{"className":2370,"style":2371},[1932],"height:1em;vertical-align:-0.25em;",[1853,2373,2331],{"className":2374,"style":2375},[1937,1938],"margin-right:0.1389em;",[1853,2377,2335],{"className":2378},[2379],"mopen",[1853,2381,2338],{"className":2382},[1937,1938],[1853,2384,2341],{"className":2385},[2386],"mclose",[1853,2388],{"className":2389,"style":1944},[1943],[1853,2391,2344],{"className":2392},[1948],[1853,2394],{"className":2395,"style":1944},[1943],[1853,2397,2399,2402,2405,2408,2411,2414,2417],{"className":2398},[1928],[1853,2400],{"className":2401,"style":2371},[1932],[1853,2403,2331],{"className":2404,"style":2375},[1937,1938],[1853,2406,2335],{"className":2407},[2379],[1853,2409,2338],{"className":2410},[1937,1938],[1853,2412],{"className":2413,"style":1969},[1943],[1853,2415,2353],{"className":2416},[1973],[1853,2418],{"className":2419,"style":1969},[1943],[1853,2421,2423,2426,2430],{"className":2422},[1928],[1853,2424],{"className":2425,"style":2371},[1932],[1853,2427,2356],{"className":2428,"style":2429},[1937,1938],"margin-right:0.0502em;",[1853,2431,2341],{"className":2432},[2386],"）\n实验结果：85%的人选B（",[2152,2435,2436],{},"合取谬误 conjunction fallacy",[2292,2438,2440],{"id":2439},"_2-可得性启发式-availability-heuristic","(2) 可得性启发式 (Availability Heuristic)",[1798,2442,2443,2444,2447],{},"人们根据信息的",[2152,2445,2446],{},"易得性","而非真实概率判断。",[1798,2449,2450,2155],{},[2152,2451,2303],{},[1805,2453,2454,2457],{},[1808,2455,2456],{},"飞机失事后，人们高估飞行风险",[1808,2458,2459],{},"看到朋友中彩票，高估自己中奖概率",[2292,2461,2463],{"id":2462},"_3-锚定效应-anchoring","(3) 锚定效应 (Anchoring)",[1798,2465,2466],{},"人们的判断受到**初始参考点（锚）**的影响。",[1798,2468,2469,2472],{},[2152,2470,2471],{},"实验","（Tversky & Kahneman 1974）：",[1805,2474,2475,2478,2481,2484],{},[1808,2476,2477],{},"让参与者估计联合国中非洲国家的比例",[1808,2479,2480],{},"先转一个随机数轮盘（例如得到10或65）",[1808,2482,2483],{},"问：\"比例是高于还是低于这个数字？具体是多少？\"",[1808,2485,2486],{},"结果：看到10的人估计25%，看到65的人估计45%",[2292,2488,2490],{"id":2489},"_4-过度自信-overconfidence","(4) 过度自信 (Overconfidence)",[1798,2492,2493],{},"人们系统性地高估自己的能力和知识。",[1798,2495,2496,2155],{},[2152,2497,2498],{},"证据",[1805,2500,2501,2504],{},[1808,2502,2503],{},"80%的司机认为自己的驾驶技术在平均水平之上（明显矛盾）",[1808,2505,2506],{},"创业者高估成功概率（90%的新企业在5年内失败）",[2221,2508,2510],{"id":2509},"_13-simon的满意化模型","1.3 Simon的满意化模型",[1798,2512,2513,2516],{},[2152,2514,2515],{},"形式化","（简化版本）：",[1798,2518,2519,2520,2550,2551,2597,2598,2601,2602,2659],{},"决策者面临选择集 ",[1853,2521,2523,2537],{"className":2522},[1860],[1853,2524,2526],{"className":2525},[1864],[1866,2527,2528],{"xmlns":1868},[1871,2529,2530,2535],{},[1874,2531,2532],{},[1877,2533,2534],{},"X",[1916,2536,2534],{"encoding":1918},[1853,2538,2540],{"className":2539,"ariaHidden":1924},[1923],[1853,2541,2543,2546],{"className":2542},[1928],[1853,2544],{"className":2545,"style":1933},[1932],[1853,2547,2534],{"className":2548,"style":2549},[1937,1938],"margin-right:0.0785em;","，真实效用函数 ",[1853,2552,2554,2576],{"className":2553},[1860],[1853,2555,2557],{"className":2556},[1864],[1866,2558,2559],{"xmlns":1868},[1871,2560,2561,2573],{},[1874,2562,2563,2566,2568,2571],{},[1877,2564,2565],{},"u",[1881,2567,2335],{"stretchy":2334},[1877,2569,2570],{},"x",[1881,2572,2341],{"stretchy":2334},[1916,2574,2575],{"encoding":1918},"u(x)",[1853,2577,2579],{"className":2578,"ariaHidden":1924},[1923],[1853,2580,2582,2585,2588,2591,2594],{"className":2581},[1928],[1853,2583],{"className":2584,"style":2371},[1932],[1853,2586,2565],{"className":2587},[1937,1938],[1853,2589,2335],{"className":2590},[2379],[1853,2592,2570],{"className":2593},[1937,1938],[1853,2595,2341],{"className":2596},[2386],"，但有",[2152,2599,2600],{},"搜索成本"," ",[1853,2603,2605,2627],{"className":2604},[1860],[1853,2606,2608],{"className":2607},[1864],[1866,2609,2610],{"xmlns":1868},[1871,2611,2612,2624],{},[1874,2613,2614,2617,2620],{},[1877,2615,2616],{},"c",[1881,2618,2619],{},">",[2621,2622,2623],"mn",{},"0",[1916,2625,2626],{"encoding":1918},"c > 0",[1853,2628,2630,2649],{"className":2629,"ariaHidden":1924},[1923],[1853,2631,2633,2637,2640,2643,2646],{"className":2632},[1928],[1853,2634],{"className":2635,"style":2636},[1932],"height:0.5782em;vertical-align:-0.0391em;",[1853,2638,2616],{"className":2639},[1937,1938],[1853,2641],{"className":2642,"style":1944},[1943],[1853,2644,2619],{"className":2645},[1948],[1853,2647],{"className":2648,"style":1944},[1943],[1853,2650,2652,2656],{"className":2651},[1928],[1853,2653],{"className":2654,"style":2655},[1932],"height:0.6444em;",[1853,2657,2623],{"className":2658},[1937],"。",[1798,2661,2662,2665],{},[2152,2663,2664],{},"最优停止规则","（满意化）：",[2157,2667,2668,2747,2908],{},[1808,2669,2670,2671,2601,2674],{},"设定一个",[2152,2672,2673],{},"期望水平",[1853,2675,2677,2697],{"className":2676},[1860],[1853,2678,2680],{"className":2679},[1864],[1866,2681,2682],{"xmlns":1868},[1871,2683,2684,2694],{},[1874,2685,2686],{},[2687,2688,2689,2691],"mover",{"accent":1924},[1877,2690,2565],{},[1881,2692,2693],{},"ˉ",[1916,2695,2696],{"encoding":1918},"\\bar{u}",[1853,2698,2700],{"className":2699,"ariaHidden":1924},[1923],[1853,2701,2703,2707],{"className":2702},[1928],[1853,2704],{"className":2705,"style":2706},[1932],"height:0.5678em;",[1853,2708,2711],{"className":2709},[1937,2710],"accent",[1853,2712,2715],{"className":2713},[2714],"vlist-t",[1853,2716,2719],{"className":2717},[2718],"vlist-r",[1853,2720,2723,2734],{"className":2721,"style":2706},[2722],"vlist",[1853,2724,2726,2731],{"style":2725},"top:-3em;",[1853,2727],{"className":2728,"style":2730},[2729],"pstrut","height:3em;",[1853,2732,2565],{"className":2733},[1937,1938],[1853,2735,2736,2739],{"style":2725},[1853,2737],{"className":2738,"style":2730},[2729],[1853,2740,2744],{"className":2741,"style":2743},[2742],"accent-body","left:-0.2222em;",[1853,2745,2693],{"className":2746},[1937],[1808,2748,2749,2750],{},"顺序搜索选项 ",[1853,2751,2753,2788],{"className":2752},[1860],[1853,2754,2756],{"className":2755},[1864],[1866,2757,2758],{"xmlns":1868},[1871,2759,2760,2785],{},[1874,2761,2762,2770,2773,2780,2782],{},[2763,2764,2765,2767],"msub",{},[1877,2766,2570],{},[2621,2768,2769],{},"1",[1881,2771,2772],{"separator":1924},",",[2763,2774,2775,2777],{},[1877,2776,2570],{},[2621,2778,2779],{},"2",[1881,2781,2772],{"separator":1924},[1881,2783,2784],{},"…",[1916,2786,2787],{"encoding":1918},"x_1, x_2, \\ldots",[1853,2789,2791],{"className":2790,"ariaHidden":1924},[1923],[1853,2792,2794,2798,2850,2854,2858,2898,2901,2904],{"className":2793},[1928],[1853,2795],{"className":2796,"style":2797},[1932],"height:0.625em;vertical-align:-0.1944em;",[1853,2799,2801,2804],{"className":2800},[1937],[1853,2802,2570],{"className":2803},[1937,1938],[1853,2805,2808],{"className":2806},[2807],"msupsub",[1853,2809,2812,2841],{"className":2810},[2714,2811],"vlist-t2",[1853,2813,2815,2836],{"className":2814},[2718],[1853,2816,2819],{"className":2817,"style":2818},[2722],"height:0.3011em;",[1853,2820,2822,2826],{"style":2821},"top:-2.55em;margin-left:0em;margin-right:0.05em;",[1853,2823],{"className":2824,"style":2825},[2729],"height:2.7em;",[1853,2827,2833],{"className":2828},[2829,2830,2831,2832],"sizing","reset-size6","size3","mtight",[1853,2834,2769],{"className":2835},[1937,2832],[1853,2837,2840],{"className":2838},[2839],"vlist-s","​",[1853,2842,2844],{"className":2843},[2718],[1853,2845,2848],{"className":2846,"style":2847},[2722],"height:0.15em;",[1853,2849],{},[1853,2851,2772],{"className":2852},[2853],"mpunct",[1853,2855],{"className":2856,"style":2857},[1943],"margin-right:0.1667em;",[1853,2859,2861,2864],{"className":2860},[1937],[1853,2862,2570],{"className":2863},[1937,1938],[1853,2865,2867],{"className":2866},[2807],[1853,2868,2870,2890],{"className":2869},[2714,2811],[1853,2871,2873,2887],{"className":2872},[2718],[1853,2874,2876],{"className":2875,"style":2818},[2722],[1853,2877,2878,2881],{"style":2821},[1853,2879],{"className":2880,"style":2825},[2729],[1853,2882,2884],{"className":2883},[2829,2830,2831,2832],[1853,2885,2779],{"className":2886},[1937,2832],[1853,2888,2840],{"className":2889},[2839],[1853,2891,2893],{"className":2892},[2718],[1853,2894,2896],{"className":2895,"style":2847},[2722],[1853,2897],{},[1853,2899,2772],{"className":2900},[2853],[1853,2902],{"className":2903,"style":2857},[1943],[1853,2905,2784],{"className":2906},[2907],"minner",[1808,2909,2910,2911,3052],{},"选择第一个满足 ",[1853,2912,2914,2947],{"className":2913},[1860],[1853,2915,2917],{"className":2916},[1864],[1866,2918,2919],{"xmlns":1868},[1871,2920,2921,2944],{},[1874,2922,2923,2925,2927,2934,2936,2938],{},[1877,2924,2565],{},[1881,2926,2335],{"stretchy":2334},[2763,2928,2929,2931],{},[1877,2930,2570],{},[1877,2932,2933],{},"i",[1881,2935,2341],{"stretchy":2334},[1881,2937,2344],{},[2687,2939,2940,2942],{"accent":1924},[1877,2941,2565],{},[1881,2943,2693],{},[1916,2945,2946],{"encoding":1918},"u(x_i) \\geq \\bar{u}",[1853,2948,2950,3015],{"className":2949,"ariaHidden":1924},[1923],[1853,2951,2953,2956,2959,2962,3003,3006,3009,3012],{"className":2952},[1928],[1853,2954],{"className":2955,"style":2371},[1932],[1853,2957,2565],{"className":2958},[1937,1938],[1853,2960,2335],{"className":2961},[2379],[1853,2963,2965,2968],{"className":2964},[1937],[1853,2966,2570],{"className":2967},[1937,1938],[1853,2969,2971],{"className":2970},[2807],[1853,2972,2974,2995],{"className":2973},[2714,2811],[1853,2975,2977,2992],{"className":2976},[2718],[1853,2978,2981],{"className":2979,"style":2980},[2722],"height:0.3117em;",[1853,2982,2983,2986],{"style":2821},[1853,2984],{"className":2985,"style":2825},[2729],[1853,2987,2989],{"className":2988},[2829,2830,2831,2832],[1853,2990,2933],{"className":2991},[1937,1938,2832],[1853,2993,2840],{"className":2994},[2839],[1853,2996,2998],{"className":2997},[2718],[1853,2999,3001],{"className":3000,"style":2847},[2722],[1853,3002],{},[1853,3004,2341],{"className":3005},[2386],[1853,3007],{"className":3008,"style":1944},[1943],[1853,3010,2344],{"className":3011},[1948],[1853,3013],{"className":3014,"style":1944},[1943],[1853,3016,3018,3021],{"className":3017},[1928],[1853,3019],{"className":3020,"style":2706},[1932],[1853,3022,3024],{"className":3023},[1937,2710],[1853,3025,3027],{"className":3026},[2714],[1853,3028,3030],{"className":3029},[2718],[1853,3031,3033,3041],{"className":3032,"style":2706},[2722],[1853,3034,3035,3038],{"style":2725},[1853,3036],{"className":3037,"style":2730},[2729],[1853,3039,2565],{"className":3040},[1937,1938],[1853,3042,3043,3046],{"style":2725},[1853,3044],{"className":3045,"style":2730},[2729],[1853,3047,3049],{"className":3048,"style":2743},[2742],[1853,3050,2693],{"className":3051},[1937]," 的选项",[1798,3054,3055,3058,3059],{},[2152,3056,3057],{},"vs. 完全理性","：穷尽搜索并选择 ",[1853,3060,3062,3106],{"className":3061},[1860],[1853,3063,3065],{"className":3064},[1864],[1866,3066,3067],{"xmlns":1868},[1871,3068,3069,3103],{},[1874,3070,3071,3074,3077,3095,3097,3099,3101],{},[1877,3072,3073],{},"arg",[1881,3075,3076],{},"⁡",[2763,3078,3079,3086],{},[1874,3080,3081,3084],{},[1877,3082,3083],{},"max",[1881,3085,3076],{},[1874,3087,3088,3090,3093],{},[1877,3089,2570],{},[1881,3091,3092],{},"∈",[1877,3094,2534],{},[1877,3096,2565],{},[1881,3098,2335],{"stretchy":2334},[1877,3100,2570],{},[1881,3102,2341],{"stretchy":2334},[1916,3104,3105],{"encoding":1918},"\\arg\\max_{x \\in X} u(x)",[1853,3107,3109],{"className":3108,"ariaHidden":1924},[1923],[1853,3110,3112,3115,3124,3127,3179,3182,3185,3188,3191],{"className":3111},[1928],[1853,3113],{"className":3114,"style":2371},[1932],[1853,3116,3119,3120],{"className":3117},[3118],"mop","ar",[1853,3121,3123],{"style":3122},"margin-right:0.0139em;","g",[1853,3125],{"className":3126,"style":2857},[1943],[1853,3128,3130,3133],{"className":3129},[3118],[1853,3131,3083],{"className":3132},[3118],[1853,3134,3136],{"className":3135},[2807],[1853,3137,3139,3170],{"className":3138},[2714,2811],[1853,3140,3142,3167],{"className":3141},[2718],[1853,3143,3146],{"className":3144,"style":3145},[2722],"height:0.3283em;",[1853,3147,3149,3152],{"style":3148},"top:-2.55em;margin-right:0.05em;",[1853,3150],{"className":3151,"style":2825},[2729],[1853,3153,3155],{"className":3154},[2829,2830,2831,2832],[1853,3156,3158,3161,3164],{"className":3157},[1937,2832],[1853,3159,2570],{"className":3160},[1937,1938,2832],[1853,3162,3092],{"className":3163},[1948,2832],[1853,3165,2534],{"className":3166,"style":2549},[1937,1938,2832],[1853,3168,2840],{"className":3169},[2839],[1853,3171,3173],{"className":3172},[2718],[1853,3174,3177],{"className":3175,"style":3176},[2722],"height:0.1774em;",[1853,3178],{},[1853,3180],{"className":3181,"style":2857},[1943],[1853,3183,2565],{"className":3184},[1937,1938],[1853,3186,2335],{"className":3187},[2379],[1853,3189,2570],{"className":3190},[1937,1938],[1853,3192,2341],{"className":3193},[2386],[1798,3195,3196,2155],{},[2152,3197,3198],{},"权衡",[1805,3200,3201,3204],{},[1808,3202,3203],{},"满意化节省搜索成本",[1808,3205,3206],{},"但可能错过全局最优",[1794,3208,3210],{"id":3209},"二前景理论-prospect-theory","二、前景理论 (Prospect Theory)",[2221,3212,3214],{"id":3213},"_21-期望效用理论的反例","2.1 期望效用理论的反例",[1798,3216,3217,2155],{},[2152,3218,3219],{},"Allais悖论 (1953)",[1798,3221,3222,2155],{},[2152,3223,3224],{},"选择1",[1805,3226,3227,3230],{},[1808,3228,3229],{},"A: 100%获得100万",[1808,3231,3232],{},"B: 10%获得500万，89%获得100万，1%获得0",[1798,3234,3235,2155],{},[2152,3236,3237],{},"选择2",[1805,3239,3240,3243],{},[1808,3241,3242],{},"C: 11%获得100万，89%获得0",[1808,3244,3245],{},"D: 10%获得500万，90%获得0",[1798,3247,3248,3251,3252,3384],{},[2152,3249,3250],{},"期望效用理论预测","：\n如果选A（即 ",[1853,3253,3255,3303],{"className":3254},[1860],[1853,3256,3258],{"className":3257},[1864],[1866,3259,3260],{"xmlns":1868},[1871,3261,3262,3300],{},[1874,3263,3264,3266,3268,3271,3273,3275,3278,3280,3282,3285,3287,3289,3292,3294,3296,3298],{},[1877,3265,2565],{},[1881,3267,2335],{"stretchy":2334},[2621,3269,3270],{},"100",[1881,3272,2341],{"stretchy":2334},[1881,3274,2619],{},[2621,3276,3277],{},"0.1",[1877,3279,2565],{},[1881,3281,2335],{"stretchy":2334},[2621,3283,3284],{},"500",[1881,3286,2341],{"stretchy":2334},[1881,3288,1890],{},[2621,3290,3291],{},"0.89",[1877,3293,2565],{},[1881,3295,2335],{"stretchy":2334},[2621,3297,3270],{},[1881,3299,2341],{"stretchy":2334},[1916,3301,3302],{"encoding":1918},"u(100) > 0.1u(500) + 0.89u(100)",[1853,3304,3306,3333,3363],{"className":3305,"ariaHidden":1924},[1923],[1853,3307,3309,3312,3315,3318,3321,3324,3327,3330],{"className":3308},[1928],[1853,3310],{"className":3311,"style":2371},[1932],[1853,3313,2565],{"className":3314},[1937,1938],[1853,3316,2335],{"className":3317},[2379],[1853,3319,3270],{"className":3320},[1937],[1853,3322,2341],{"className":3323},[2386],[1853,3325],{"className":3326,"style":1944},[1943],[1853,3328,2619],{"className":3329},[1948],[1853,3331],{"className":3332,"style":1944},[1943],[1853,3334,3336,3339,3342,3345,3348,3351,3354,3357,3360],{"className":3335},[1928],[1853,3337],{"className":3338,"style":2371},[1932],[1853,3340,3277],{"className":3341},[1937],[1853,3343,2565],{"className":3344},[1937,1938],[1853,3346,2335],{"className":3347},[2379],[1853,3349,3284],{"className":3350},[1937],[1853,3352,2341],{"className":3353},[2386],[1853,3355],{"className":3356,"style":1969},[1943],[1853,3358,1890],{"className":3359},[1973],[1853,3361],{"className":3362,"style":1969},[1943],[1853,3364,3366,3369,3372,3375,3378,3381],{"className":3365},[1928],[1853,3367],{"className":3368,"style":2371},[1932],[1853,3370,3291],{"className":3371},[1937],[1853,3373,2565],{"className":3374},[1937,1938],[1853,3376,2335],{"className":3377},[2379],[1853,3379,3270],{"className":3380},[1937],[1853,3382,2341],{"className":3383},[2386],"），应该选C\n如果选B，应该选D",[1798,3386,3387,3390],{},[2152,3388,3389],{},"实验结果","：大多数人选A和D（违反期望效用理论）",[2221,3392,3394],{"id":3393},"_22-kahneman-tversky的前景理论-1979","2.2 Kahneman & Tversky的前景理论 (1979)",[1798,3396,3397,3400,3401,3404,3405,2659],{},[2152,3398,3399],{},"核心思想","：人们评估的不是绝对财富水平，而是相对于",[2152,3402,3403],{},"参考点","的",[2152,3406,3407],{},"得失",[1798,3409,3410,2601,3413,3459],{},[2152,3411,3412],{},"价值函数",[1853,3414,3416,3437],{"className":3415},[1860],[1853,3417,3419],{"className":3418},[1864],[1866,3420,3421],{"xmlns":1868},[1871,3422,3423,3434],{},[1874,3424,3425,3428,3430,3432],{},[1877,3426,3427],{},"v",[1881,3429,2335],{"stretchy":2334},[1877,3431,2570],{},[1881,3433,2341],{"stretchy":2334},[1916,3435,3436],{"encoding":1918},"v(x)",[1853,3438,3440],{"className":3439,"ariaHidden":1924},[1923],[1853,3441,3443,3446,3450,3453,3456],{"className":3442},[1928],[1853,3444],{"className":3445,"style":2371},[1932],[1853,3447,3427],{"className":3448,"style":3449},[1937,1938],"margin-right:0.0359em;",[1853,3451,2335],{"className":3452},[2379],[1853,3454,2570],{"className":3455},[1937,1938],[1853,3457,2341],{"className":3458},[2386],"（相对于参考点0）：",[1853,3461,3463],{"className":3462},[1856],[1853,3464,3466,3606],{"className":3465},[1860],[1853,3467,3469],{"className":3468},[1864],[1866,3470,3471],{"xmlns":1868,"display":1869},[1871,3472,3473,3603],{},[1874,3474,3475,3477,3479,3481,3483,3485],{},[1877,3476,3427],{},[1881,3478,2335],{"stretchy":2334},[1877,3480,2570],{},[1881,3482,2341],{"stretchy":2334},[1881,3484,1883],{},[1874,3486,3487,3490],{},[1881,3488,3489],{"fence":1924},"{",[3491,3492,3496,3546],"mtable",{"rowspacing":3493,"columnalign":3494,"columnspacing":3495},"0.36em","left left","1em",[3497,3498,3499,3513],"mtr",{},[3500,3501,3502],"mtd",{},[3503,3504,3505],"mstyle",{"scriptlevel":2623,"displaystyle":2334},[3506,3507,3508,3510],"msup",{},[1877,3509,2570],{},[1877,3511,3512],{},"α",[3500,3514,3515],{},[3503,3516,3517],{"scriptlevel":2623,"displaystyle":2334},[1874,3518,3519,3522,3524,3526,3528,3530,3532,3534,3537,3539,3541,3544],{},[1885,3520,3521],{},"if ",[1877,3523,2570],{},[1881,3525,2344],{},[2621,3527,2623],{},[1943,3529],{"width":3495},[1881,3531,2335],{"stretchy":2334},[1877,3533,3512],{},[1881,3535,3536],{},"\u003C",[2621,3538,2769],{},[1881,3540,2772],{"separator":1924},[1885,3542,3543],{},"收益凹性",[1881,3545,2341],{"stretchy":2334},[3497,3547,3548,3572],{},[3500,3549,3550],{},[3503,3551,3552],{"scriptlevel":2623,"displaystyle":2334},[1874,3553,3554,3556,3559,3561,3563,3565],{},[1881,3555,1902],{},[1877,3557,3558],{},"λ",[1881,3560,2335],{"stretchy":2334},[1881,3562,1902],{},[1877,3564,2570],{},[3506,3566,3567,3569],{},[1881,3568,2341],{"stretchy":2334},[1877,3570,3571],{},"β",[3500,3573,3574],{},[3503,3575,3576],{"scriptlevel":2623,"displaystyle":2334},[1874,3577,3578,3580,3582,3584,3586,3588,3590,3592,3594,3596,3598,3601],{},[1885,3579,3521],{},[1877,3581,2570],{},[1881,3583,3536],{},[2621,3585,2623],{},[1943,3587],{"width":3495},[1881,3589,2335],{"stretchy":2334},[1877,3591,3571],{},[1881,3593,3536],{},[2621,3595,2769],{},[1881,3597,2772],{"separator":1924},[1885,3599,3600],{},"损失凸性",[1881,3602,2341],{"stretchy":2334},[1916,3604,3605],{"encoding":1918},"v(x) = \\begin{cases}\nx^\\alpha & \\text{if } x \\geq 0 \\quad (\\alpha \u003C 1, \\text{收益凹性}) \\\\\n-\\lambda (-x)^\\beta & \\text{if } x \u003C 0 \\quad (\\beta \u003C 1, \\text{损失凸性})\n\\end{cases}",[1853,3607,3609,3636],{"className":3608,"ariaHidden":1924},[1923],[1853,3610,3612,3615,3618,3621,3624,3627,3630,3633],{"className":3611},[1928],[1853,3613],{"className":3614,"style":2371},[1932],[1853,3616,3427],{"className":3617,"style":3449},[1937,1938],[1853,3619,2335],{"className":3620},[2379],[1853,3622,2570],{"className":3623},[1937,1938],[1853,3625,2341],{"className":3626},[2386],[1853,3628],{"className":3629,"style":1944},[1943],[1853,3631,1883],{"className":3632},[1948],[1853,3634],{"className":3635,"style":1944},[1943],[1853,3637,3639,3643],{"className":3638},[1928],[1853,3640],{"className":3641,"style":3642},[1932],"height:3em;vertical-align:-1.25em;",[1853,3644,3646,3656,3945],{"className":3645},[2907],[1853,3647,3651],{"className":3648,"style":3650},[2379,3649],"delimcenter","top:0em;",[1853,3652,3489],{"className":3653},[3654,3655],"delimsizing","size4",[1853,3657,3659],{"className":3658},[1937],[1853,3660,3662,3785,3790],{"className":3661},[3491],[1853,3663,3666],{"className":3664},[3665],"col-align-l",[1853,3667,3669,3776],{"className":3668},[2714,2811],[1853,3670,3672,3773],{"className":3671},[2718],[1853,3673,3676,3718],{"className":3674,"style":3675},[2722],"height:1.69em;",[1853,3677,3679,3683],{"style":3678},"top:-3.69em;",[1853,3680],{"className":3681,"style":3682},[2729],"height:3.008em;",[1853,3684,3686],{"className":3685},[1937],[1853,3687,3689,3692],{"className":3688},[1937],[1853,3690,2570],{"className":3691},[1937,1938],[1853,3693,3695],{"className":3694},[2807],[1853,3696,3698],{"className":3697},[2714],[1853,3699,3701],{"className":3700},[2718],[1853,3702,3705],{"className":3703,"style":3704},[2722],"height:0.6644em;",[1853,3706,3708,3711],{"style":3707},"top:-3.063em;margin-right:0.05em;",[1853,3709],{"className":3710,"style":2825},[2729],[1853,3712,3714],{"className":3713},[2829,2830,2831,2832],[1853,3715,3512],{"className":3716,"style":3717},[1937,1938,2832],"margin-right:0.0037em;",[1853,3719,3721,3724],{"style":3720},"top:-2.25em;",[1853,3722],{"className":3723,"style":3682},[2729],[1853,3725,3727,3730,3733,3736,3739,3742],{"className":3726},[1937],[1853,3728,1902],{"className":3729},[1937],[1853,3731,3558],{"className":3732},[1937,1938],[1853,3734,2335],{"className":3735},[2379],[1853,3737,1902],{"className":3738},[1937],[1853,3740,2570],{"className":3741},[1937,1938],[1853,3743,3745,3748],{"className":3744},[2386],[1853,3746,2341],{"className":3747},[2386],[1853,3749,3751],{"className":3750},[2807],[1853,3752,3754],{"className":3753},[2714],[1853,3755,3757],{"className":3756},[2718],[1853,3758,3761],{"className":3759,"style":3760},[2722],"height:0.8491em;",[1853,3762,3763,3766],{"style":3707},[1853,3764],{"className":3765,"style":2825},[2729],[1853,3767,3769],{"className":3768},[2829,2830,2831,2832],[1853,3770,3571],{"className":3771,"style":3772},[1937,1938,2832],"margin-right:0.0528em;",[1853,3774,2840],{"className":3775},[2839],[1853,3777,3779],{"className":3778},[2718],[1853,3780,3783],{"className":3781,"style":3782},[2722],"height:1.19em;",[1853,3784],{},[1853,3786],{"className":3787,"style":3789},[3788],"arraycolsep","width:1em;",[1853,3791,3793],{"className":3792},[3665],[1853,3794,3796,3937],{"className":3795},[2714,2811],[1853,3797,3799,3934],{"className":3798},[2718],[1853,3800,3802,3869],{"className":3801,"style":3675},[2722],[1853,3803,3804,3807],{"style":3678},[1853,3805],{"className":3806,"style":3682},[2729],[1853,3808,3810,3816,3819,3822,3825,3828,3831,3835,3838,3841,3844,3847,3850,3853,3856,3859,3866],{"className":3809},[1937],[1853,3811,3813],{"className":3812},[1937,1962],[1853,3814,3521],{"className":3815},[1937],[1853,3817,2570],{"className":3818},[1937,1938],[1853,3820],{"className":3821,"style":1944},[1943],[1853,3823,2344],{"className":3824},[1948],[1853,3826],{"className":3827,"style":1944},[1943],[1853,3829,2623],{"className":3830},[1937],[1853,3832],{"className":3833,"style":3834},[1943],"margin-right:1em;",[1853,3836,2335],{"className":3837},[2379],[1853,3839,3512],{"className":3840,"style":3717},[1937,1938],[1853,3842],{"className":3843,"style":1944},[1943],[1853,3845,3536],{"className":3846},[1948],[1853,3848],{"className":3849,"style":1944},[1943],[1853,3851,2769],{"className":3852},[1937],[1853,3854,2772],{"className":3855},[2853],[1853,3857],{"className":3858,"style":2857},[1943],[1853,3860,3862],{"className":3861},[1937,1962],[1853,3863,3543],{"className":3864},[1937,3865],"cjk_fallback",[1853,3867,2341],{"className":3868},[2386],[1853,3870,3871,3874],{"style":3720},[1853,3872],{"className":3873,"style":3682},[2729],[1853,3875,3877,3883,3886,3889,3892,3895,3898,3901,3904,3907,3910,3913,3916,3919,3922,3925,3931],{"className":3876},[1937],[1853,3878,3880],{"className":3879},[1937,1962],[1853,3881,3521],{"className":3882},[1937],[1853,3884,2570],{"className":3885},[1937,1938],[1853,3887],{"className":3888,"style":1944},[1943],[1853,3890,3536],{"className":3891},[1948],[1853,3893],{"className":3894,"style":1944},[1943],[1853,3896,2623],{"className":3897},[1937],[1853,3899],{"className":3900,"style":3834},[1943],[1853,3902,2335],{"className":3903},[2379],[1853,3905,3571],{"className":3906,"style":3772},[1937,1938],[1853,3908],{"className":3909,"style":1944},[1943],[1853,3911,3536],{"className":3912},[1948],[1853,3914],{"className":3915,"style":1944},[1943],[1853,3917,2769],{"className":3918},[1937],[1853,3920,2772],{"className":3921},[2853],[1853,3923],{"className":3924,"style":2857},[1943],[1853,3926,3928],{"className":3927},[1937,1962],[1853,3929,3600],{"className":3930},[1937,3865],[1853,3932,2341],{"className":3933},[2386],[1853,3935,2840],{"className":3936},[2839],[1853,3938,3940],{"className":3939},[2718],[1853,3941,3943],{"className":3942,"style":3782},[2722],[1853,3944],{},[1853,3946],{"className":3947},[2386,3948],"nulldelimiter",[1798,3950,3951,2155],{},[2152,3952,3953],{},"关键特征",[2157,3955,3956,3962,4020],{},[1808,3957,3958,3961],{},[2152,3959,3960],{},"参考依赖 (Reference Dependence)","：效用取决于相对变化而非绝对水平",[1808,3963,3964,2155,3967,4019],{},[2152,3965,3966],{},"损失规避 (Loss Aversion)",[1853,3968,3970,3988],{"className":3969},[1860],[1853,3971,3973],{"className":3972},[1864],[1866,3974,3975],{"xmlns":1868},[1871,3976,3977,3985],{},[1874,3978,3979,3981,3983],{},[1877,3980,3558],{},[1881,3982,2619],{},[2621,3984,2769],{},[1916,3986,3987],{"encoding":1918},"\\lambda > 1",[1853,3989,3991,4010],{"className":3990,"ariaHidden":1924},[1923],[1853,3992,3994,3998,4001,4004,4007],{"className":3993},[1928],[1853,3995],{"className":3996,"style":3997},[1932],"height:0.7335em;vertical-align:-0.0391em;",[1853,3999,3558],{"className":4000},[1937,1938],[1853,4002],{"className":4003,"style":1944},[1943],[1853,4005,2619],{"className":4006},[1948],[1853,4008],{"className":4009,"style":1944},[1943],[1853,4011,4013,4016],{"className":4012},[1928],[1853,4014],{"className":4015,"style":2655},[1932],[1853,4017,2769],{"className":4018},[1937],"（典型值2-2.5），损失的痛苦大于等量收益的快乐",[1808,4021,4022,4025,4026],{},[2152,4023,4024],{},"边际敏感性递减","：\n",[1805,4027,4028,4139],{},[1808,4029,4030,4031,4084,4085,4138],{},"收益：",[1853,4032,4034,4054],{"className":4033},[1860],[1853,4035,4037],{"className":4036},[1864],[1866,4038,4039],{"xmlns":1868},[1871,4040,4041,4051],{},[1874,4042,4043,4045,4048],{},[2621,4044,3270],{},[1881,4046,4047],{},"→",[2621,4049,4050],{},"200",[1916,4052,4053],{"encoding":1918},"100 \\to 200",[1853,4055,4057,4075],{"className":4056,"ariaHidden":1924},[1923],[1853,4058,4060,4063,4066,4069,4072],{"className":4059},[1928],[1853,4061],{"className":4062,"style":2655},[1932],[1853,4064,3270],{"className":4065},[1937],[1853,4067],{"className":4068,"style":1944},[1943],[1853,4070,4047],{"className":4071},[1948],[1853,4073],{"className":4074,"style":1944},[1943],[1853,4076,4078,4081],{"className":4077},[1928],[1853,4079],{"className":4080,"style":2655},[1932],[1853,4082,4050],{"className":4083},[1937]," 的快乐 > ",[1853,4086,4088,4108],{"className":4087},[1860],[1853,4089,4091],{"className":4090},[1864],[1866,4092,4093],{"xmlns":1868},[1871,4094,4095,4105],{},[1874,4096,4097,4100,4102],{},[2621,4098,4099],{},"1100",[1881,4101,4047],{},[2621,4103,4104],{},"1200",[1916,4106,4107],{"encoding":1918},"1100 \\to 1200",[1853,4109,4111,4129],{"className":4110,"ariaHidden":1924},[1923],[1853,4112,4114,4117,4120,4123,4126],{"className":4113},[1928],[1853,4115],{"className":4116,"style":2655},[1932],[1853,4118,4099],{"className":4119},[1937],[1853,4121],{"className":4122,"style":1944},[1943],[1853,4124,4047],{"className":4125},[1948],[1853,4127],{"className":4128,"style":1944},[1943],[1853,4130,4132,4135],{"className":4131},[1928],[1853,4133],{"className":4134,"style":2655},[1932],[1853,4136,4104],{"className":4137},[1937]," 的快乐",[1808,4140,4141,4142,4204,4205,4266],{},"损失：",[1853,4143,4145,4167],{"className":4144},[1860],[1853,4146,4148],{"className":4147},[1864],[1866,4149,4150],{"xmlns":1868},[1871,4151,4152,4164],{},[1874,4153,4154,4156,4158,4160,4162],{},[1881,4155,1902],{},[2621,4157,3270],{},[1881,4159,4047],{},[1881,4161,1902],{},[2621,4163,4050],{},[1916,4165,4166],{"encoding":1918},"-100 \\to -200",[1853,4168,4170,4192],{"className":4169,"ariaHidden":1924},[1923],[1853,4171,4173,4177,4180,4183,4186,4189],{"className":4172},[1928],[1853,4174],{"className":4175,"style":4176},[1932],"height:0.7278em;vertical-align:-0.0833em;",[1853,4178,1902],{"className":4179},[1937],[1853,4181,3270],{"className":4182},[1937],[1853,4184],{"className":4185,"style":1944},[1943],[1853,4187,4047],{"className":4188},[1948],[1853,4190],{"className":4191,"style":1944},[1943],[1853,4193,4195,4198,4201],{"className":4194},[1928],[1853,4196],{"className":4197,"style":4176},[1932],[1853,4199,1902],{"className":4200},[1937],[1853,4202,4050],{"className":4203},[1937]," 的痛苦 > ",[1853,4206,4208,4230],{"className":4207},[1860],[1853,4209,4211],{"className":4210},[1864],[1866,4212,4213],{"xmlns":1868},[1871,4214,4215,4227],{},[1874,4216,4217,4219,4221,4223,4225],{},[1881,4218,1902],{},[2621,4220,4099],{},[1881,4222,4047],{},[1881,4224,1902],{},[2621,4226,4104],{},[1916,4228,4229],{"encoding":1918},"-1100 \\to -1200",[1853,4231,4233,4254],{"className":4232,"ariaHidden":1924},[1923],[1853,4234,4236,4239,4242,4245,4248,4251],{"className":4235},[1928],[1853,4237],{"className":4238,"style":4176},[1932],[1853,4240,1902],{"className":4241},[1937],[1853,4243,4099],{"className":4244},[1937],[1853,4246],{"className":4247,"style":1944},[1943],[1853,4249,4047],{"className":4250},[1948],[1853,4252],{"className":4253,"style":1944},[1943],[1853,4255,4257,4260,4263],{"className":4256},[1928],[1853,4258],{"className":4259,"style":4176},[1932],[1853,4261,1902],{"className":4262},[1937],[1853,4264,4104],{"className":4265},[1937]," 的痛苦",[1798,4268,4269,2601,4272,4318],{},[2152,4270,4271],{},"决策权重函数",[1853,4273,4275,4296],{"className":4274},[1860],[1853,4276,4278],{"className":4277},[1864],[1866,4279,4280],{"xmlns":1868},[1871,4281,4282,4293],{},[1874,4283,4284,4287,4289,4291],{},[1877,4285,4286],{},"w",[1881,4288,2335],{"stretchy":2334},[1877,4290,1798],{},[1881,4292,2341],{"stretchy":2334},[1916,4294,4295],{"encoding":1918},"w(p)",[1853,4297,4299],{"className":4298,"ariaHidden":1924},[1923],[1853,4300,4302,4305,4309,4312,4315],{"className":4301},[1928],[1853,4303],{"className":4304,"style":2371},[1932],[1853,4306,4286],{"className":4307,"style":4308},[1937,1938],"margin-right:0.0269em;",[1853,4310,2335],{"className":4311},[2379],[1853,4313,1798],{"className":4314},[1937,1938],[1853,4316,2341],{"className":4317},[2386],"（概率的主观扭曲）：",[1805,4320,4321,4395,4469],{},[1808,4322,4323,4324,2155,4327,4394],{},"小概率被",[2152,4325,4326],{},"高估",[1853,4328,4330,4355],{"className":4329},[1860],[1853,4331,4333],{"className":4332},[1864],[1866,4334,4335],{"xmlns":1868},[1871,4336,4337,4352],{},[1874,4338,4339,4341,4343,4346,4348,4350],{},[1877,4340,4286],{},[1881,4342,2335],{"stretchy":2334},[2621,4344,4345],{},"0.01",[1881,4347,2341],{"stretchy":2334},[1881,4349,2619],{},[2621,4351,4345],{},[1916,4353,4354],{"encoding":1918},"w(0.01) > 0.01",[1853,4356,4358,4385],{"className":4357,"ariaHidden":1924},[1923],[1853,4359,4361,4364,4367,4370,4373,4376,4379,4382],{"className":4360},[1928],[1853,4362],{"className":4363,"style":2371},[1932],[1853,4365,4286],{"className":4366,"style":4308},[1937,1938],[1853,4368,2335],{"className":4369},[2379],[1853,4371,4345],{"className":4372},[1937],[1853,4374,2341],{"className":4375},[2386],[1853,4377],{"className":4378,"style":1944},[1943],[1853,4380,2619],{"className":4381},[1948],[1853,4383],{"className":4384,"style":1944},[1943],[1853,4386,4388,4391],{"className":4387},[1928],[1853,4389],{"className":4390,"style":2655},[1932],[1853,4392,4345],{"className":4393},[1937],"（解释买彩票）",[1808,4396,4397,4398,2155,4401,4468],{},"大概率被",[2152,4399,4400],{},"低估",[1853,4402,4404,4429],{"className":4403},[1860],[1853,4405,4407],{"className":4406},[1864],[1866,4408,4409],{"xmlns":1868},[1871,4410,4411,4426],{},[1874,4412,4413,4415,4417,4420,4422,4424],{},[1877,4414,4286],{},[1881,4416,2335],{"stretchy":2334},[2621,4418,4419],{},"0.99",[1881,4421,2341],{"stretchy":2334},[1881,4423,3536],{},[2621,4425,4419],{},[1916,4427,4428],{"encoding":1918},"w(0.99) \u003C 0.99",[1853,4430,4432,4459],{"className":4431,"ariaHidden":1924},[1923],[1853,4433,4435,4438,4441,4444,4447,4450,4453,4456],{"className":4434},[1928],[1853,4436],{"className":4437,"style":2371},[1932],[1853,4439,4286],{"className":4440,"style":4308},[1937,1938],[1853,4442,2335],{"className":4443},[2379],[1853,4445,4419],{"className":4446},[1937],[1853,4448,2341],{"className":4449},[2386],[1853,4451],{"className":4452,"style":1944},[1943],[1853,4454,3536],{"className":4455},[1948],[1853,4457],{"className":4458,"style":1944},[1943],[1853,4460,4462,4465],{"className":4461},[1928],[1853,4463],{"className":4464,"style":2655},[1932],[1853,4466,4419],{"className":4467},[1937],"（解释买保险）",[1808,4470,4471,4596],{},[1853,4472,4474,4512],{"className":4473},[1860],[1853,4475,4477],{"className":4476},[1864],[1866,4478,4479],{"xmlns":1868},[1871,4480,4481,4509],{},[1874,4482,4483,4485,4487,4489,4491,4493,4495,4497,4499,4501,4503,4505,4507],{},[1877,4484,4286],{},[1881,4486,2335],{"stretchy":2334},[1877,4488,1798],{},[1881,4490,2341],{"stretchy":2334},[1881,4492,1890],{},[1877,4494,4286],{},[1881,4496,2335],{"stretchy":2334},[2621,4498,2769],{},[1881,4500,1902],{},[1877,4502,1798],{},[1881,4504,2341],{"stretchy":2334},[1881,4506,3536],{},[2621,4508,2769],{},[1916,4510,4511],{"encoding":1918},"w(p) + w(1-p) \u003C 1",[1853,4513,4515,4542,4566,4587],{"className":4514,"ariaHidden":1924},[1923],[1853,4516,4518,4521,4524,4527,4530,4533,4536,4539],{"className":4517},[1928],[1853,4519],{"className":4520,"style":2371},[1932],[1853,4522,4286],{"className":4523,"style":4308},[1937,1938],[1853,4525,2335],{"className":4526},[2379],[1853,4528,1798],{"className":4529},[1937,1938],[1853,4531,2341],{"className":4532},[2386],[1853,4534],{"className":4535,"style":1969},[1943],[1853,4537,1890],{"className":4538},[1973],[1853,4540],{"className":4541,"style":1969},[1943],[1853,4543,4545,4548,4551,4554,4557,4560,4563],{"className":4544},[1928],[1853,4546],{"className":4547,"style":2371},[1932],[1853,4549,4286],{"className":4550,"style":4308},[1937,1938],[1853,4552,2335],{"className":4553},[2379],[1853,4555,2769],{"className":4556},[1937],[1853,4558],{"className":4559,"style":1969},[1943],[1853,4561,1902],{"className":4562},[1973],[1853,4564],{"className":4565,"style":1969},[1943],[1853,4567,4569,4572,4575,4578,4581,4584],{"className":4568},[1928],[1853,4570],{"className":4571,"style":2371},[1932],[1853,4573,1798],{"className":4574},[1937,1938],[1853,4576,2341],{"className":4577},[2386],[1853,4579],{"className":4580,"style":1944},[1943],[1853,4582,3536],{"className":4583},[1948],[1853,4585],{"className":4586,"style":1944},[1943],[1853,4588,4590,4593],{"className":4589},[1928],[1853,4591],{"className":4592,"style":2655},[1932],[1853,4594,2769],{"className":4595},[1937],"（次可加性）",[1798,4598,4599,2155],{},[2152,4600,4601],{},"前景理论的预测",[1853,4603,4605],{"className":4604},[1856],[1853,4606,4608,4665],{"className":4607},[1860],[1853,4609,4611],{"className":4610},[1864],[1866,4612,4613],{"xmlns":1868,"display":1869},[1871,4614,4615,4662],{},[1874,4616,4617,4620,4622,4630,4632,4634,4640,4642,4645,4647,4649,4655,4657,4660],{},[1877,4618,4619],{},"V",[1881,4621,1883],{},[4623,4624,4625,4628],"munder",{},[1881,4626,4627],{},"∑",[1877,4629,2933],{},[1877,4631,4286],{},[1881,4633,2335],{"stretchy":2334},[2763,4635,4636,4638],{},[1877,4637,1798],{},[1877,4639,2933],{},[1881,4641,2341],{"stretchy":2334},[1881,4643,4644],{},"⋅",[1877,4646,3427],{},[1881,4648,2335],{"stretchy":2334},[2763,4650,4651,4653],{},[1877,4652,2570],{},[1877,4654,2933],{},[1881,4656,1902],{},[1877,4658,4659],{},"r",[1881,4661,2341],{"stretchy":2334},[1916,4663,4664],{"encoding":1918},"V = \\sum_{i} w(p_i) \\cdot v(x_i - r)",[1853,4666,4668,4686,4809,4870],{"className":4667,"ariaHidden":1924},[1923],[1853,4669,4671,4674,4677,4680,4683],{"className":4670},[1928],[1853,4672],{"className":4673,"style":1933},[1932],[1853,4675,4619],{"className":4676,"style":1969},[1937,1938],[1853,4678],{"className":4679,"style":1944},[1943],[1853,4681,1883],{"className":4682},[1948],[1853,4684],{"className":4685,"style":1944},[1943],[1853,4687,4689,4693,4748,4751,4754,4757,4797,4800,4803,4806],{"className":4688},[1928],[1853,4690],{"className":4691,"style":4692},[1932],"height:2.3277em;vertical-align:-1.2777em;",[1853,4694,4697],{"className":4695},[3118,4696],"op-limits",[1853,4698,4700,4739],{"className":4699},[2714,2811],[1853,4701,4703,4736],{"className":4702},[2718],[1853,4704,4707,4723],{"className":4705,"style":4706},[2722],"height:1.05em;",[1853,4708,4710,4714],{"style":4709},"top:-1.8723em;margin-left:0em;",[1853,4711],{"className":4712,"style":4713},[2729],"height:3.05em;",[1853,4715,4717],{"className":4716},[2829,2830,2831,2832],[1853,4718,4720],{"className":4719},[1937,2832],[1853,4721,2933],{"className":4722},[1937,1938,2832],[1853,4724,4726,4729],{"style":4725},"top:-3.05em;",[1853,4727],{"className":4728,"style":4713},[2729],[1853,4730,4731],{},[1853,4732,4627],{"className":4733},[3118,4734,4735],"op-symbol","large-op",[1853,4737,2840],{"className":4738},[2839],[1853,4740,4742],{"className":4741},[2718],[1853,4743,4746],{"className":4744,"style":4745},[2722],"height:1.2777em;",[1853,4747],{},[1853,4749],{"className":4750,"style":2857},[1943],[1853,4752,4286],{"className":4753,"style":4308},[1937,1938],[1853,4755,2335],{"className":4756},[2379],[1853,4758,4760,4763],{"className":4759},[1937],[1853,4761,1798],{"className":4762},[1937,1938],[1853,4764,4766],{"className":4765},[2807],[1853,4767,4769,4789],{"className":4768},[2714,2811],[1853,4770,4772,4786],{"className":4771},[2718],[1853,4773,4775],{"className":4774,"style":2980},[2722],[1853,4776,4777,4780],{"style":2821},[1853,4778],{"className":4779,"style":2825},[2729],[1853,4781,4783],{"className":4782},[2829,2830,2831,2832],[1853,4784,2933],{"className":4785},[1937,1938,2832],[1853,4787,2840],{"className":4788},[2839],[1853,4790,4792],{"className":4791},[2718],[1853,4793,4795],{"className":4794,"style":2847},[2722],[1853,4796],{},[1853,4798,2341],{"className":4799},[2386],[1853,4801],{"className":4802,"style":1969},[1943],[1853,4804,4644],{"className":4805},[1973],[1853,4807],{"className":4808,"style":1969},[1943],[1853,4810,4812,4815,4818,4821,4861,4864,4867],{"className":4811},[1928],[1853,4813],{"className":4814,"style":2371},[1932],[1853,4816,3427],{"className":4817,"style":3449},[1937,1938],[1853,4819,2335],{"className":4820},[2379],[1853,4822,4824,4827],{"className":4823},[1937],[1853,4825,2570],{"className":4826},[1937,1938],[1853,4828,4830],{"className":4829},[2807],[1853,4831,4833,4853],{"className":4832},[2714,2811],[1853,4834,4836,4850],{"className":4835},[2718],[1853,4837,4839],{"className":4838,"style":2980},[2722],[1853,4840,4841,4844],{"style":2821},[1853,4842],{"className":4843,"style":2825},[2729],[1853,4845,4847],{"className":4846},[2829,2830,2831,2832],[1853,4848,2933],{"className":4849},[1937,1938,2832],[1853,4851,2840],{"className":4852},[2839],[1853,4854,4856],{"className":4855},[2718],[1853,4857,4859],{"className":4858,"style":2847},[2722],[1853,4860],{},[1853,4862],{"className":4863,"style":1969},[1943],[1853,4865,1902],{"className":4866},[1973],[1853,4868],{"className":4869,"style":1969},[1943],[1853,4871,4873,4876,4880],{"className":4872},[1928],[1853,4874],{"className":4875,"style":2371},[1932],[1853,4877,4659],{"className":4878,"style":4879},[1937,1938],"margin-right:0.0278em;",[1853,4881,2341],{"className":4882},[2386],[1798,4884,4885,4886,4915],{},"其中 ",[1853,4887,4889,4902],{"className":4888},[1860],[1853,4890,4892],{"className":4891},[1864],[1866,4893,4894],{"xmlns":1868},[1871,4895,4896,4900],{},[1874,4897,4898],{},[1877,4899,4659],{},[1916,4901,4659],{"encoding":1918},[1853,4903,4905],{"className":4904,"ariaHidden":1924},[1923],[1853,4906,4908,4912],{"className":4907},[1928],[1853,4909],{"className":4910,"style":4911},[1932],"height:0.4306em;",[1853,4913,4659],{"className":4914,"style":4879},[1937,1938]," 是参考点。",[2221,4917,4919],{"id":4918},"_23-应用禀赋效应-endowment-effect","2.3 应用：禀赋效应 (Endowment Effect)",[1798,4921,4922,4925],{},[2152,4923,4924],{},"Thaler (1980)","：人们对拥有的东西估值高于未拥有的东西。",[1798,4927,4928,4930],{},[2152,4929,2471],{},"（Kahneman, Knetsch & Thaler 1990）：",[1805,4932,4933,4936,4943],{},[1808,4934,4935],{},"随机给一半学生发放马克杯",[1808,4937,4938,4939,4942],{},"让拥有者设定",[2152,4940,4941],{},"卖价","（WTA: Willingness to Accept）",[1808,4944,4945,4946,4949],{},"让未拥有者设定",[2152,4947,4948],{},"买价","（WTP: Willingness to Pay）",[1798,4951,4952,4955],{},[2152,4953,4954],{},"理性预测","：WTA = WTP",[1798,4957,4958,4960,4961,5007],{},[2152,4959,3389],{},"：WTA ≈ 2 × WTP（中位数：",[1853,4962,4964,4986],{"className":4963},[1860],[1853,4965,4967],{"className":4966},[1864],[1866,4968,4969],{"xmlns":1868},[1871,4970,4971,4983],{},[1874,4972,4973,4976,4978,4981],{},[2621,4974,4975],{},"7.12",[1877,4977,3427],{},[1877,4979,4980],{},"s",[1877,4982,1914],{"mathvariant":1913},[1916,4984,4985],{"encoding":1918},"7.12 vs. ",[1853,4987,4989],{"className":4988,"ariaHidden":1924},[1923],[1853,4990,4992,4995,4998,5001,5004],{"className":4991},[1928],[1853,4993],{"className":4994,"style":2655},[1932],[1853,4996,4975],{"className":4997},[1937],[1853,4999,3427],{"className":5000,"style":3449},[1937,1938],[1853,5002,4980],{"className":5003},[1937,1938],[1853,5005,1914],{"className":5006},[1937],"2.87）",[1798,5009,5010,2155],{},[2152,5011,5012],{},"解释",[1805,5014,5015,5018,5021],{},[1808,5016,5017],{},"参考点是当前拥有状态",[1808,5019,5020],{},"卖出杯子 = 损失 → 损失规避 → 要求高价",[1808,5022,5023],{},"买入杯子 = 收益 → 较低估值",[2221,5025,5027],{"id":5026},"_24-框架效应-framing-effect","2.4 框架效应 (Framing Effect)",[1798,5029,5030,2155],{},[2152,5031,5032],{},"Tversky & Kahneman (1981) 的亚洲疾病问题",[2306,5034,5035,5038,5043,5051,5056],{},[1798,5036,5037],{},"预计有600人会死于某种疾病。有两种方案：",[1798,5039,5040,2155],{},[2152,5041,5042],{},"收益框架",[1805,5044,5045,5048],{},[1808,5046,5047],{},"方案A：200人确定存活",[1808,5049,5050],{},"方案B：1\u002F3概率600人存活，2\u002F3概率无人存活",[1798,5052,5053,2155],{},[2152,5054,5055],{},"损失框架",[1805,5057,5058,5061],{},[1808,5059,5060],{},"方案C：400人确定死亡",[1808,5062,5063],{},"方案D：1\u002F3概率无人死亡，2\u002F3概率600人死亡",[1798,5065,5066,5069],{},[2152,5067,5068],{},"理性分析","：A ≡ C，B ≡ D（完全相同的结果）",[1798,5071,5072,2155],{},[2152,5073,3389],{},[1805,5075,5076,5079],{},[1808,5077,5078],{},"收益框架：72%选A（风险规避）",[1808,5080,5081],{},"损失框架：78%选D（风险寻求）",[1798,5083,5084,2155],{},[2152,5085,5012],{},[1805,5087,5088,5091],{},[1808,5089,5090],{},"收益域：价值函数凹 → 风险规避 → 选确定性",[1808,5092,5093],{},"损失域：价值函数凸 → 风险寻求 → 选赌博",[1794,5095,5097],{"id":5096},"三社会偏好-social-preferences","三、社会偏好 (Social Preferences)",[2221,5099,5101],{"id":5100},"_31-最后通牒博弈-ultimatum-game","3.1 最后通牒博弈 (Ultimatum Game)",[1798,5103,5104,2155],{},[2152,5105,5106],{},"实验设计",[2157,5108,5109,5149],{},[1808,5110,5111,5112,5148],{},"提议者提出如何分配",[1853,5113,5115,5133],{"className":5114},[1860],[1853,5116,5118],{"className":5117},[1864],[1866,5119,5120],{"xmlns":1868},[1871,5121,5122,5130],{},[1874,5123,5124,5127],{},[2621,5125,5126],{},"10",[1885,5128,5129],{},"（如自己拿",[1916,5131,5132],{"encoding":1918},"10（如自己拿",[1853,5134,5136],{"className":5135,"ariaHidden":1924},[1923],[1853,5137,5139,5142,5145],{"className":5138},[1928],[1853,5140],{"className":5141,"style":1933},[1932],[1853,5143,5126],{"className":5144},[1937],[1853,5146,5129],{"className":5147},[1937,3865],"7，对方拿$3）",[1808,5150,5151],{},"回应者可以接受（双方按提议分配）或拒绝（双方都得$0）",[1798,5153,5154,5156],{},[2152,5155,4954],{},"（完全自利 + 逆向归纳）：",[1805,5158,5159,5162],{},[1808,5160,5161],{},"回应者应接受任何正数（$0.01也接受）",[1808,5163,5164,5165],{},"提议者因此提议",[1853,5166,5168,5191],{"className":5167},[1860],[1853,5169,5171],{"className":5170},[1864],[1866,5172,5173],{"xmlns":1868},[1871,5174,5175,5188],{},[1874,5176,5177,5179,5182,5184,5186],{},[1881,5178,2335],{"stretchy":2334},[2621,5180,5181],{},"9.99",[1881,5183,2772],{"separator":1924},[2621,5185,4345],{},[1881,5187,2341],{"stretchy":2334},[1916,5189,5190],{"encoding":1918},"(9.99, 0.01)",[1853,5192,5194],{"className":5193,"ariaHidden":1924},[1923],[1853,5195,5197,5200,5203,5206,5209,5212,5215],{"className":5196},[1928],[1853,5198],{"className":5199,"style":2371},[1932],[1853,5201,2335],{"className":5202},[2379],[1853,5204,5181],{"className":5205},[1937],[1853,5207,2772],{"className":5208},[2853],[1853,5210],{"className":5211,"style":2857},[1943],[1853,5213,4345],{"className":5214},[1937],[1853,5216,2341],{"className":5217},[2386],[1798,5219,5220,5222],{},[2152,5221,3389],{},"（数百次实验的稳健发现）：",[1805,5224,5225,5231,5237],{},[1808,5226,5227,5230],{},[2152,5228,5229],{},"提议中位数","：40%-50%的总额",[1808,5232,5233,5236],{},[2152,5234,5235],{},"拒绝率","：低于20%的提议常被拒绝（约50%拒绝率）",[1808,5238,5239,5242],{},[2152,5240,5241],{},"跨文化一致性","：虽有差异，但普遍偏离理性预测",[1798,5244,5245,2155],{},[2152,5246,5012],{},[1805,5248,5249,5256],{},[1808,5250,5251,5252,5255],{},"提议者关心",[2152,5253,5254],{},"公平","，避免提议被拒",[1808,5257,5258,5259,5262],{},"回应者愿意付出代价",[2152,5260,5261],{},"惩罚","不公平",[2221,5264,5266],{"id":5265},"_32-独裁者博弈-dictator-game","3.2 独裁者博弈 (Dictator Game)",[1798,5268,5269,5272],{},[2152,5270,5271],{},"设计","：提议者单方面决定分配，回应者无权拒绝",[1798,5274,5275,5277,5278,5313],{},[2152,5276,4954],{},"：提议者拿全部（",[1853,5279,5281,5297],{"className":5280},[1860],[1853,5282,5284],{"className":5283},[1864],[1866,5285,5286],{"xmlns":1868},[1871,5287,5288,5294],{},[1874,5289,5290,5292],{},[2621,5291,5126],{},[1881,5293,2772],{"separator":1924},[1916,5295,5296],{"encoding":1918},"10, ",[1853,5298,5300],{"className":5299,"ariaHidden":1924},[1923],[1853,5301,5303,5307,5310],{"className":5302},[1928],[1853,5304],{"className":5305,"style":5306},[1932],"height:0.8389em;vertical-align:-0.1944em;",[1853,5308,5126],{"className":5309},[1937],[1853,5311,2772],{"className":5312},[2853],"0）",[1798,5315,5316,2155],{},[2152,5317,3389],{},[1805,5319,5320,5326,5329],{},[1808,5321,5322,5325],{},[2152,5323,5324],{},"平均给予","：20%-30%",[1808,5327,5328],{},"约60%的人给正数",[1808,5330,5331],{},"约20%的人平分",[1798,5333,5334,2155,5336,5339],{},[2152,5335,5012],{},[2152,5337,5338],{},"纯粹利他主义","（不是策略性公平）",[2221,5341,5343],{"id":5342},"_33-公共品博弈-public-goods-game","3.3 公共品博弈 (Public Goods Game)",[1798,5345,5346,2155],{},[2152,5347,5271],{},[1805,5349,5350,5411,5534,5590],{},[1808,5351,5352,5381,5382],{},[1853,5353,5355,5369],{"className":5354},[1860],[1853,5356,5358],{"className":5357},[1864],[1866,5359,5360],{"xmlns":1868},[1871,5361,5362,5367],{},[1874,5363,5364],{},[1877,5365,5366],{},"N",[1916,5368,5366],{"encoding":1918},[1853,5370,5372],{"className":5371,"ariaHidden":1924},[1923],[1853,5373,5375,5378],{"className":5374},[1928],[1853,5376],{"className":5377,"style":1933},[1932],[1853,5379,5366],{"className":5380,"style":1939},[1937,1938]," 个参与者，每人初始禀赋 ",[1853,5383,5385,5399],{"className":5384},[1860],[1853,5386,5388],{"className":5387},[1864],[1866,5389,5390],{"xmlns":1868},[1871,5391,5392,5397],{},[1874,5393,5394],{},[1877,5395,5396],{},"e",[1916,5398,5396],{"encoding":1918},[1853,5400,5402],{"className":5401,"ariaHidden":1924},[1923],[1853,5403,5405,5408],{"className":5404},[1928],[1853,5406],{"className":5407,"style":4911},[1932],[1853,5409,5396],{"className":5410},[1937,1938],[1808,5412,5413,5414,5533],{},"每人决定贡献 ",[1853,5415,5417,5449],{"className":5416},[1860],[1853,5418,5420],{"className":5419},[1864],[1866,5421,5422],{"xmlns":1868},[1871,5423,5424,5446],{},[1874,5425,5426,5432,5434,5437,5439,5441,5443],{},[2763,5427,5428,5430],{},[1877,5429,3123],{},[1877,5431,2933],{},[1881,5433,3092],{},[1881,5435,5436],{"stretchy":2334},"[",[2621,5438,2623],{},[1881,5440,2772],{"separator":1924},[1877,5442,5396],{},[1881,5444,5445],{"stretchy":2334},"]",[1916,5447,5448],{"encoding":1918},"g_i \\in [0, e]",[1853,5450,5452,5509],{"className":5451,"ariaHidden":1924},[1923],[1853,5453,5455,5459,5500,5503,5506],{"className":5454},[1928],[1853,5456],{"className":5457,"style":5458},[1932],"height:0.7335em;vertical-align:-0.1944em;",[1853,5460,5462,5465],{"className":5461},[1937],[1853,5463,3123],{"className":5464,"style":3449},[1937,1938],[1853,5466,5468],{"className":5467},[2807],[1853,5469,5471,5492],{"className":5470},[2714,2811],[1853,5472,5474,5489],{"className":5473},[2718],[1853,5475,5477],{"className":5476,"style":2980},[2722],[1853,5478,5480,5483],{"style":5479},"top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;",[1853,5481],{"className":5482,"style":2825},[2729],[1853,5484,5486],{"className":5485},[2829,2830,2831,2832],[1853,5487,2933],{"className":5488},[1937,1938,2832],[1853,5490,2840],{"className":5491},[2839],[1853,5493,5495],{"className":5494},[2718],[1853,5496,5498],{"className":5497,"style":2847},[2722],[1853,5499],{},[1853,5501],{"className":5502,"style":1944},[1943],[1853,5504,3092],{"className":5505},[1948],[1853,5507],{"className":5508,"style":1944},[1943],[1853,5510,5512,5515,5518,5521,5524,5527,5530],{"className":5511},[1928],[1853,5513],{"className":5514,"style":2371},[1932],[1853,5516,5436],{"className":5517},[2379],[1853,5519,2623],{"className":5520},[1937],[1853,5522,2772],{"className":5523},[2853],[1853,5525],{"className":5526,"style":2857},[1943],[1853,5528,5396],{"className":5529},[1937,1938],[1853,5531,5445],{"className":5532},[2386]," 到公共账户",[1808,5535,5536,5537,5589],{},"公共账户乘以 ",[1853,5538,5540,5559],{"className":5539},[1860],[1853,5541,5543],{"className":5542},[1864],[1866,5544,5545],{"xmlns":1868},[1871,5546,5547,5556],{},[1874,5548,5549,5552,5554],{},[1877,5550,5551],{},"m",[1881,5553,2619],{},[2621,5555,2769],{},[1916,5557,5558],{"encoding":1918},"m > 1",[1853,5560,5562,5580],{"className":5561,"ariaHidden":1924},[1923],[1853,5563,5565,5568,5571,5574,5577],{"className":5564},[1928],[1853,5566],{"className":5567,"style":2636},[1932],[1853,5569,5551],{"className":5570},[1937,1938],[1853,5572],{"className":5573,"style":1944},[1943],[1853,5575,2619],{"className":5576},[1948],[1853,5578],{"className":5579,"style":1944},[1943],[1853,5581,5583,5586],{"className":5582},[1928],[1853,5584],{"className":5585,"style":2655},[1932],[1853,5587,2769],{"className":5588},[1937],"（如1.5），然后平均分配",[1808,5591,5592,5593],{},"个人收益：",[1853,5594,5596,5651],{"className":5595},[1860],[1853,5597,5599],{"className":5598},[1864],[1866,5600,5601],{"xmlns":1868},[1871,5602,5603,5648],{},[1874,5604,5605,5612,5614,5616,5618,5624,5626],{},[2763,5606,5607,5610],{},[1877,5608,5609],{},"π",[1877,5611,2933],{},[1881,5613,1883],{},[1877,5615,5396],{},[1881,5617,1902],{},[2763,5619,5620,5622],{},[1877,5621,3123],{},[1877,5623,2933],{},[1881,5625,1890],{},[5627,5628,5629,5646],"mfrac",{},[1874,5630,5631,5633,5640],{},[1877,5632,5551],{},[2763,5634,5635,5637],{},[1881,5636,4627],{},[1877,5638,5639],{},"j",[2763,5641,5642,5644],{},[1877,5643,3123],{},[1877,5645,5639],{},[1877,5647,5366],{},[1916,5649,5650],{"encoding":1918},"\\pi_i = e - g_i + \\frac{m \\sum_j g_j}{N}",[1853,5652,5654,5710,5729,5785],{"className":5653,"ariaHidden":1924},[1923],[1853,5655,5657,5661,5701,5704,5707],{"className":5656},[1928],[1853,5658],{"className":5659,"style":5660},[1932],"height:0.5806em;vertical-align:-0.15em;",[1853,5662,5664,5667],{"className":5663},[1937],[1853,5665,5609],{"className":5666,"style":3449},[1937,1938],[1853,5668,5670],{"className":5669},[2807],[1853,5671,5673,5693],{"className":5672},[2714,2811],[1853,5674,5676,5690],{"className":5675},[2718],[1853,5677,5679],{"className":5678,"style":2980},[2722],[1853,5680,5681,5684],{"style":5479},[1853,5682],{"className":5683,"style":2825},[2729],[1853,5685,5687],{"className":5686},[2829,2830,2831,2832],[1853,5688,2933],{"className":5689},[1937,1938,2832],[1853,5691,2840],{"className":5692},[2839],[1853,5694,5696],{"className":5695},[2718],[1853,5697,5699],{"className":5698,"style":2847},[2722],[1853,5700],{},[1853,5702],{"className":5703,"style":1944},[1943],[1853,5705,1883],{"className":5706},[1948],[1853,5708],{"className":5709,"style":1944},[1943],[1853,5711,5713,5717,5720,5723,5726],{"className":5712},[1928],[1853,5714],{"className":5715,"style":5716},[1932],"height:0.6667em;vertical-align:-0.0833em;",[1853,5718,5396],{"className":5719},[1937,1938],[1853,5721],{"className":5722,"style":1969},[1943],[1853,5724,1902],{"className":5725},[1973],[1853,5727],{"className":5728,"style":1969},[1943],[1853,5730,5732,5736,5776,5779,5782],{"className":5731},[1928],[1853,5733],{"className":5734,"style":5735},[1932],"height:0.7778em;vertical-align:-0.1944em;",[1853,5737,5739,5742],{"className":5738},[1937],[1853,5740,3123],{"className":5741,"style":3449},[1937,1938],[1853,5743,5745],{"className":5744},[2807],[1853,5746,5748,5768],{"className":5747},[2714,2811],[1853,5749,5751,5765],{"className":5750},[2718],[1853,5752,5754],{"className":5753,"style":2980},[2722],[1853,5755,5756,5759],{"style":5479},[1853,5757],{"className":5758,"style":2825},[2729],[1853,5760,5762],{"className":5761},[2829,2830,2831,2832],[1853,5763,2933],{"className":5764},[1937,1938,2832],[1853,5766,2840],{"className":5767},[2839],[1853,5769,5771],{"className":5770},[2718],[1853,5772,5774],{"className":5773,"style":2847},[2722],[1853,5775],{},[1853,5777],{"className":5778,"style":1969},[1943],[1853,5780,1890],{"className":5781},[1973],[1853,5783],{"className":5784,"style":1969},[1943],[1853,5786,5788,5792],{"className":5787},[1928],[1853,5789],{"className":5790,"style":5791},[1932],"height:1.5022em;vertical-align:-0.345em;",[1853,5793,5795,5798,5963],{"className":5794},[1937],[1853,5796],{"className":5797},[2379,3948],[1853,5799,5801],{"className":5800},[5627],[1853,5802,5804,5954],{"className":5803},[2714,2811],[1853,5805,5807,5951],{"className":5806},[2718],[1853,5808,5811,5826,5837],{"className":5809,"style":5810},[2722],"height:1.1572em;",[1853,5812,5814,5817],{"style":5813},"top:-2.655em;",[1853,5815],{"className":5816,"style":2730},[2729],[1853,5818,5820],{"className":5819},[2829,2830,2831,2832],[1853,5821,5823],{"className":5822},[1937,2832],[1853,5824,5366],{"className":5825,"style":1939},[1937,1938,2832],[1853,5827,5829,5832],{"style":5828},"top:-3.23em;",[1853,5830],{"className":5831,"style":2730},[2729],[1853,5833],{"className":5834,"style":5836},[5835],"frac-line","border-bottom-width:0.04em;",[1853,5838,5840,5843],{"style":5839},"top:-3.6322em;",[1853,5841],{"className":5842,"style":2730},[2729],[1853,5844,5846],{"className":5845},[2829,2830,2831,2832],[1853,5847,5849,5852,5856,5905,5908],{"className":5848},[1937,2832],[1853,5850,5551],{"className":5851},[1937,1938,2832],[1853,5853],{"className":5854,"style":5855},[1943,2832],"margin-right:0.1952em;",[1853,5857,5859,5864],{"className":5858},[3118,2832],[1853,5860,4627],{"className":5861,"style":5863},[3118,4734,5862,2832],"small-op","position:relative;top:0em;",[1853,5865,5867],{"className":5866},[2807],[1853,5868,5870,5896],{"className":5869},[2714,2811],[1853,5871,5873,5893],{"className":5872},[2718],[1853,5874,5877],{"className":5875,"style":5876},[2722],"height:0.1496em;",[1853,5878,5880,5884],{"style":5879},"top:-2.1786em;margin-left:0em;margin-right:0.0714em;",[1853,5881],{"className":5882,"style":5883},[2729],"height:2.5em;",[1853,5885,5889],{"className":5886},[2829,5887,5888,2832],"reset-size3","size1",[1853,5890,5639],{"className":5891,"style":5892},[1937,1938,2832],"margin-right:0.0572em;",[1853,5894,2840],{"className":5895},[2839],[1853,5897,5899],{"className":5898},[2718],[1853,5900,5903],{"className":5901,"style":5902},[2722],"height:0.4603em;",[1853,5904],{},[1853,5906],{"className":5907,"style":5855},[1943,2832],[1853,5909,5911,5914],{"className":5910},[1937,2832],[1853,5912,3123],{"className":5913,"style":3449},[1937,1938,2832],[1853,5915,5917],{"className":5916},[2807],[1853,5918,5920,5942],{"className":5919},[2714,2811],[1853,5921,5923,5939],{"className":5922},[2718],[1853,5924,5927],{"className":5925,"style":5926},[2722],"height:0.3281em;",[1853,5928,5930,5933],{"style":5929},"top:-2.357em;margin-left:-0.0359em;margin-right:0.0714em;",[1853,5931],{"className":5932,"style":5883},[2729],[1853,5934,5936],{"className":5935},[2829,5887,5888,2832],[1853,5937,5639],{"className":5938,"style":5892},[1937,1938,2832],[1853,5940,2840],{"className":5941},[2839],[1853,5943,5945],{"className":5944},[2718],[1853,5946,5949],{"className":5947,"style":5948},[2722],"height:0.2819em;",[1853,5950],{},[1853,5952,2840],{"className":5953},[2839],[1853,5955,5957],{"className":5956},[2718],[1853,5958,5961],{"className":5959,"style":5960},[2722],"height:0.345em;",[1853,5962],{},[1853,5964],{"className":5965},[2386,3948],[1798,5967,5968,5971,5972,6064,6065],{},[2152,5969,5970],{},"社会最优","：所有人全部贡献（",[1853,5973,5975,5997],{"className":5974},[1860],[1853,5976,5978],{"className":5977},[1864],[1866,5979,5980],{"xmlns":1868},[1871,5981,5982,5994],{},[1874,5983,5984,5990,5992],{},[2763,5985,5986,5988],{},[1877,5987,3123],{},[1877,5989,2933],{},[1881,5991,1883],{},[1877,5993,5396],{},[1916,5995,5996],{"encoding":1918},"g_i = e",[1853,5998,6000,6055],{"className":5999,"ariaHidden":1924},[1923],[1853,6001,6003,6006,6046,6049,6052],{"className":6002},[1928],[1853,6004],{"className":6005,"style":2797},[1932],[1853,6007,6009,6012],{"className":6008},[1937],[1853,6010,3123],{"className":6011,"style":3449},[1937,1938],[1853,6013,6015],{"className":6014},[2807],[1853,6016,6018,6038],{"className":6017},[2714,2811],[1853,6019,6021,6035],{"className":6020},[2718],[1853,6022,6024],{"className":6023,"style":2980},[2722],[1853,6025,6026,6029],{"style":5479},[1853,6027],{"className":6028,"style":2825},[2729],[1853,6030,6032],{"className":6031},[2829,2830,2831,2832],[1853,6033,2933],{"className":6034},[1937,1938,2832],[1853,6036,2840],{"className":6037},[2839],[1853,6039,6041],{"className":6040},[2718],[1853,6042,6044],{"className":6043,"style":2847},[2722],[1853,6045],{},[1853,6047],{"className":6048,"style":1944},[1943],[1853,6050,1883],{"className":6051},[1948],[1853,6053],{"className":6054,"style":1944},[1943],[1853,6056,6058,6061],{"className":6057},[1928],[1853,6059],{"className":6060,"style":4911},[1932],[1853,6062,5396],{"className":6063},[1937,1938],"），每人得 ",[1853,6066,6068,6088],{"className":6067},[1860],[1853,6069,6071],{"className":6070},[1864],[1866,6072,6073],{"xmlns":1868},[1871,6074,6075,6085],{},[1874,6076,6077,6079,6081,6083],{},[1877,6078,5551],{},[1877,6080,5396],{},[1881,6082,2619],{},[1877,6084,5396],{},[1916,6086,6087],{"encoding":1918},"me > e",[1853,6089,6091,6112],{"className":6090,"ariaHidden":1924},[1923],[1853,6092,6094,6097,6100,6103,6106,6109],{"className":6093},[1928],[1853,6095],{"className":6096,"style":2636},[1932],[1853,6098,5551],{"className":6099},[1937,1938],[1853,6101,5396],{"className":6102},[1937,1938],[1853,6104],{"className":6105,"style":1944},[1943],[1853,6107,2619],{"className":6108},[1948],[1853,6110],{"className":6111,"style":1944},[1943],[1853,6113,6115,6118],{"className":6114},[1928],[1853,6116],{"className":6117,"style":4911},[1932],[1853,6119,5396],{"className":6120},[1937,1938],[1798,6122,6123,6126,6127,6250,6251,6303,6304,6415],{},[2152,6124,6125],{},"纳什均衡","（完全自利）：\n个人边际收益：",[1853,6128,6130,6152],{"className":6129},[1860],[1853,6131,6133],{"className":6132},[1864],[1866,6134,6135],{"xmlns":1868},[1871,6136,6137,6149],{},[1874,6138,6139,6145,6147],{},[5627,6140,6141,6143],{},[1877,6142,5551],{},[1877,6144,5366],{},[1881,6146,3536],{},[2621,6148,2769],{},[1916,6150,6151],{"encoding":1918},"\\frac{m}{N} \u003C 1",[1853,6153,6155,6241],{"className":6154,"ariaHidden":1924},[1923],[1853,6156,6158,6162,6232,6235,6238],{"className":6157},[1928],[1853,6159],{"className":6160,"style":6161},[1932],"height:1.0404em;vertical-align:-0.345em;",[1853,6163,6165,6168,6229],{"className":6164},[1937],[1853,6166],{"className":6167},[2379,3948],[1853,6169,6171],{"className":6170},[5627],[1853,6172,6174,6221],{"className":6173},[2714,2811],[1853,6175,6177,6218],{"className":6176},[2718],[1853,6178,6181,6195,6203],{"className":6179,"style":6180},[2722],"height:0.6954em;",[1853,6182,6183,6186],{"style":5813},[1853,6184],{"className":6185,"style":2730},[2729],[1853,6187,6189],{"className":6188},[2829,2830,2831,2832],[1853,6190,6192],{"className":6191},[1937,2832],[1853,6193,5366],{"className":6194,"style":1939},[1937,1938,2832],[1853,6196,6197,6200],{"style":5828},[1853,6198],{"className":6199,"style":2730},[2729],[1853,6201],{"className":6202,"style":5836},[5835],[1853,6204,6206,6209],{"style":6205},"top:-3.394em;",[1853,6207],{"className":6208,"style":2730},[2729],[1853,6210,6212],{"className":6211},[2829,2830,2831,2832],[1853,6213,6215],{"className":6214},[1937,2832],[1853,6216,5551],{"className":6217},[1937,1938,2832],[1853,6219,2840],{"className":6220},[2839],[1853,6222,6224],{"className":6223},[2718],[1853,6225,6227],{"className":6226,"style":5960},[2722],[1853,6228],{},[1853,6230],{"className":6231},[2386,3948],[1853,6233],{"className":6234,"style":1944},[1943],[1853,6236,3536],{"className":6237},[1948],[1853,6239],{"className":6240,"style":1944},[1943],[1853,6242,6244,6247],{"className":6243},[1928],[1853,6245],{"className":6246,"style":2655},[1932],[1853,6248,2769],{"className":6249},[1937],"（假设 ",[1853,6252,6254,6272],{"className":6253},[1860],[1853,6255,6257],{"className":6256},[1864],[1866,6258,6259],{"xmlns":1868},[1871,6260,6261,6269],{},[1874,6262,6263,6265,6267],{},[1877,6264,5366],{},[1881,6266,2619],{},[1877,6268,5551],{},[1916,6270,6271],{"encoding":1918},"N > m",[1853,6273,6275,6294],{"className":6274,"ariaHidden":1924},[1923],[1853,6276,6278,6282,6285,6288,6291],{"className":6277},[1928],[1853,6279],{"className":6280,"style":6281},[1932],"height:0.7224em;vertical-align:-0.0391em;",[1853,6283,5366],{"className":6284,"style":1939},[1937,1938],[1853,6286],{"className":6287,"style":1944},[1943],[1853,6289,2619],{"className":6290},[1948],[1853,6292],{"className":6293,"style":1944},[1943],[1853,6295,6297,6300],{"className":6296},[1928],[1853,6298],{"className":6299,"style":4911},[1932],[1853,6301,5551],{"className":6302},[1937,1938],"）\n因此 ",[1853,6305,6307,6333],{"className":6306},[1860],[1853,6308,6310],{"className":6309},[1864],[1866,6311,6312],{"xmlns":1868},[1871,6313,6314,6330],{},[1874,6315,6316,6326,6328],{},[6317,6318,6319,6321,6323],"msubsup",{},[1877,6320,3123],{},[1877,6322,2933],{},[1881,6324,6325],{},"∗",[1881,6327,1883],{},[2621,6329,2623],{},[1916,6331,6332],{"encoding":1918},"g_i^* = 0",[1853,6334,6336,6406],{"className":6335,"ariaHidden":1924},[1923],[1853,6337,6339,6343,6397,6400,6403],{"className":6338},[1928],[1853,6340],{"className":6341,"style":6342},[1932],"height:0.9474em;vertical-align:-0.2587em;",[1853,6344,6346,6349],{"className":6345},[1937],[1853,6347,3123],{"className":6348,"style":3449},[1937,1938],[1853,6350,6352],{"className":6351},[2807],[1853,6353,6355,6388],{"className":6354},[2714,2811],[1853,6356,6358,6385],{"className":6357},[2718],[1853,6359,6362,6374],{"className":6360,"style":6361},[2722],"height:0.6887em;",[1853,6363,6365,6368],{"style":6364},"top:-2.4413em;margin-left:-0.0359em;margin-right:0.05em;",[1853,6366],{"className":6367,"style":2825},[2729],[1853,6369,6371],{"className":6370},[2829,2830,2831,2832],[1853,6372,2933],{"className":6373},[1937,1938,2832],[1853,6375,6376,6379],{"style":3707},[1853,6377],{"className":6378,"style":2825},[2729],[1853,6380,6382],{"className":6381},[2829,2830,2831,2832],[1853,6383,6325],{"className":6384},[1973,2832],[1853,6386,2840],{"className":6387},[2839],[1853,6389,6391],{"className":6390},[2718],[1853,6392,6395],{"className":6393,"style":6394},[2722],"height:0.2587em;",[1853,6396],{},[1853,6398],{"className":6399,"style":1944},[1943],[1853,6401,1883],{"className":6402},[1948],[1853,6404],{"className":6405,"style":1944},[1943],[1853,6407,6409,6412],{"className":6408},[1928],[1853,6410],{"className":6411,"style":2655},[1932],[1853,6413,2623],{"className":6414},[1937],"（零贡献）",[1798,6417,6418,6420],{},[2152,6419,3389],{},"（单次博弈）：",[1805,6422,6423,6426],{},[1808,6424,6425],{},"平均贡献：40%-60%",[1808,6427,6428],{},"很少有人完全不贡献或全部贡献",[1798,6430,6431,2155],{},[2152,6432,6433],{},"重复博弈",[1805,6435,6436,6439,6442],{},[1808,6437,6438],{},"初期高贡献",[1808,6440,6441],{},"随轮数增加，贡献逐渐下降（接近理性预测）",[1808,6443,6444],{},"但仍高于零",[2221,6446,6448],{"id":6447},"_34-不公平规避模型-inequity-aversion","3.4 不公平规避模型 (Inequity Aversion)",[1798,6450,6451,6454],{},[2152,6452,6453],{},"Fehr & Schmidt (1999)"," 提出的效用函数：",[1853,6456,6458],{"className":6457},[1856],[1853,6459,6461,6611],{"className":6460},[1860],[1853,6462,6464],{"className":6463},[1864],[1866,6465,6466],{"xmlns":1868,"display":1869},[1871,6467,6468,6608],{},[1874,6469,6470,6476,6478,6480,6482,6484,6490,6492,6498,6510,6523,6525,6527,6529,6535,6537,6543,6545,6547,6550,6552,6558,6570,6582,6584,6586,6588,6594,6596,6602,6604,6606],{},[2763,6471,6472,6474],{},[1877,6473,1879],{},[1877,6475,2933],{},[1881,6477,2335],{"stretchy":2334},[1877,6479,2570],{},[1881,6481,2341],{"stretchy":2334},[1881,6483,1883],{},[2763,6485,6486,6488],{},[1877,6487,2570],{},[1877,6489,2933],{},[1881,6491,1902],{},[2763,6493,6494,6496],{},[1877,6495,3512],{},[1877,6497,2933],{},[5627,6499,6500,6502],{},[2621,6501,2769],{},[1874,6503,6504,6506,6508],{},[1877,6505,5366],{},[1881,6507,1902],{},[2621,6509,2769],{},[4623,6511,6512,6514],{},[1881,6513,4627],{},[1874,6515,6516,6518,6521],{},[1877,6517,5639],{},[1881,6519,6520],{"mathvariant":1913},"≠",[1877,6522,2933],{},[1877,6524,3083],{},[1881,6526,3076],{},[1881,6528,3489],{"stretchy":2334},[2763,6530,6531,6533],{},[1877,6532,2570],{},[1877,6534,5639],{},[1881,6536,1902],{},[2763,6538,6539,6541],{},[1877,6540,2570],{},[1877,6542,2933],{},[1881,6544,2772],{"separator":1924},[2621,6546,2623],{},[1881,6548,6549],{"stretchy":2334},"}",[1881,6551,1902],{},[2763,6553,6554,6556],{},[1877,6555,3571],{},[1877,6557,2933],{},[5627,6559,6560,6562],{},[2621,6561,2769],{},[1874,6563,6564,6566,6568],{},[1877,6565,5366],{},[1881,6567,1902],{},[2621,6569,2769],{},[4623,6571,6572,6574],{},[1881,6573,4627],{},[1874,6575,6576,6578,6580],{},[1877,6577,5639],{},[1881,6579,6520],{"mathvariant":1913},[1877,6581,2933],{},[1877,6583,3083],{},[1881,6585,3076],{},[1881,6587,3489],{"stretchy":2334},[2763,6589,6590,6592],{},[1877,6591,2570],{},[1877,6593,2933],{},[1881,6595,1902],{},[2763,6597,6598,6600],{},[1877,6599,2570],{},[1877,6601,5639],{},[1881,6603,2772],{"separator":1924},[2621,6605,2623],{},[1881,6607,6549],{"stretchy":2334},[1916,6609,6610],{"encoding":1918},"U_i(x) = x_i - \\alpha_i \\frac{1}{N-1} \\sum_{j \\neq i} \\max\\{x_j - x_i, 0\\} - \\beta_i \\frac{1}{N-1} \\sum_{j \\neq i} \\max\\{x_i - x_j, 0\\}",[1853,6612,6614,6679,6735,7018,7085,7353],{"className":6613,"ariaHidden":1924},[1923],[1853,6615,6617,6620,6661,6664,6667,6670,6673,6676],{"className":6616},[1928],[1853,6618],{"className":6619,"style":2371},[1932],[1853,6621,6623,6626],{"className":6622},[1937],[1853,6624,1879],{"className":6625,"style":1939},[1937,1938],[1853,6627,6629],{"className":6628},[2807],[1853,6630,6632,6653],{"className":6631},[2714,2811],[1853,6633,6635,6650],{"className":6634},[2718],[1853,6636,6638],{"className":6637,"style":2980},[2722],[1853,6639,6641,6644],{"style":6640},"top:-2.55em;margin-left:-0.109em;margin-right:0.05em;",[1853,6642],{"className":6643,"style":2825},[2729],[1853,6645,6647],{"className":6646},[2829,2830,2831,2832],[1853,6648,2933],{"className":6649},[1937,1938,2832],[1853,6651,2840],{"className":6652},[2839],[1853,6654,6656],{"className":6655},[2718],[1853,6657,6659],{"className":6658,"style":2847},[2722],[1853,6660],{},[1853,6662,2335],{"className":6663},[2379],[1853,6665,2570],{"className":6666},[1937,1938],[1853,6668,2341],{"className":6669},[2386],[1853,6671],{"className":6672,"style":1944},[1943],[1853,6674,1883],{"className":6675},[1948],[1853,6677],{"className":6678,"style":1944},[1943],[1853,6680,6682,6686,6726,6729,6732],{"className":6681},[1928],[1853,6683],{"className":6684,"style":6685},[1932],"height:0.7333em;vertical-align:-0.15em;",[1853,6687,6689,6692],{"className":6688},[1937],[1853,6690,2570],{"className":6691},[1937,1938],[1853,6693,6695],{"className":6694},[2807],[1853,6696,6698,6718],{"className":6697},[2714,2811],[1853,6699,6701,6715],{"className":6700},[2718],[1853,6702,6704],{"className":6703,"style":2980},[2722],[1853,6705,6706,6709],{"style":2821},[1853,6707],{"className":6708,"style":2825},[2729],[1853,6710,6712],{"className":6711},[2829,2830,2831,2832],[1853,6713,2933],{"className":6714},[1937,1938,2832],[1853,6716,2840],{"className":6717},[2839],[1853,6719,6721],{"className":6720},[2718],[1853,6722,6724],{"className":6723,"style":2847},[2722],[1853,6725],{},[1853,6727],{"className":6728,"style":1969},[1943],[1853,6730,1902],{"className":6731},[1973],[1853,6733],{"className":6734,"style":1969},[1943],[1853,6736,6738,6742,6783,6861,6864,6959,6962,6965,6968,7009,7012,7015],{"className":6737},[1928],[1853,6739],{"className":6740,"style":6741},[1932],"height:2.7597em;vertical-align:-1.4382em;",[1853,6743,6745,6748],{"className":6744},[1937],[1853,6746,3512],{"className":6747,"style":3717},[1937,1938],[1853,6749,6751],{"className":6750},[2807],[1853,6752,6754,6775],{"className":6753},[2714,2811],[1853,6755,6757,6772],{"className":6756},[2718],[1853,6758,6760],{"className":6759,"style":2980},[2722],[1853,6761,6763,6766],{"style":6762},"top:-2.55em;margin-left:-0.0037em;margin-right:0.05em;",[1853,6764],{"className":6765,"style":2825},[2729],[1853,6767,6769],{"className":6768},[2829,2830,2831,2832],[1853,6770,2933],{"className":6771},[1937,1938,2832],[1853,6773,2840],{"className":6774},[2839],[1853,6776,6778],{"className":6777},[2718],[1853,6779,6781],{"className":6780,"style":2847},[2722],[1853,6782],{},[1853,6784,6786,6789,6858],{"className":6785},[1937],[1853,6787],{"className":6788},[2379,3948],[1853,6790,6792],{"className":6791},[5627],[1853,6793,6795,6849],{"className":6794},[2714,2811],[1853,6796,6798,6846],{"className":6797},[2718],[1853,6799,6802,6826,6834],{"className":6800,"style":6801},[2722],"height:1.3214em;",[1853,6803,6805,6808],{"style":6804},"top:-2.314em;",[1853,6806],{"className":6807,"style":2730},[2729],[1853,6809,6811,6814,6817,6820,6823],{"className":6810},[1937],[1853,6812,5366],{"className":6813,"style":1939},[1937,1938],[1853,6815],{"className":6816,"style":1969},[1943],[1853,6818,1902],{"className":6819},[1973],[1853,6821],{"className":6822,"style":1969},[1943],[1853,6824,2769],{"className":6825},[1937],[1853,6827,6828,6831],{"style":5828},[1853,6829],{"className":6830,"style":2730},[2729],[1853,6832],{"className":6833,"style":5836},[5835],[1853,6835,6837,6840],{"style":6836},"top:-3.677em;",[1853,6838],{"className":6839,"style":2730},[2729],[1853,6841,6843],{"className":6842},[1937],[1853,6844,2769],{"className":6845},[1937],[1853,6847,2840],{"className":6848},[2839],[1853,6850,6852],{"className":6851},[2718],[1853,6853,6856],{"className":6854,"style":6855},[2722],"height:0.7693em;",[1853,6857],{},[1853,6859],{"className":6860},[2386,3948],[1853,6862],{"className":6863,"style":2857},[1943],[1853,6865,6867],{"className":6866},[3118,4696],[1853,6868,6870,6950],{"className":6869},[2714,2811],[1853,6871,6873,6947],{"className":6872},[2718],[1853,6874,6876,6937],{"className":6875,"style":4706},[2722],[1853,6877,6879,6882],{"style":6878},"top:-1.8479em;margin-left:0em;",[1853,6880],{"className":6881,"style":4713},[2729],[1853,6883,6885],{"className":6884},[2829,2830,2831,2832],[1853,6886,6888,6891,6934],{"className":6887},[1937,2832],[1853,6889,5639],{"className":6890,"style":5892},[1937,1938,2832],[1853,6892,6894,6927,6931],{"className":6893},[1948,2832],[1853,6895,6897],{"className":6896},[1948,2832],[1853,6898,6901],{"className":6899},[1937,6900,2832],"vbox",[1853,6902,6905],{"className":6903},[6904,2832],"thinbox",[1853,6906,6909,6912,6923],{"className":6907},[6908,2832],"rlap",[1853,6910],{"className":6911,"style":1958},[1932],[1853,6913,6916],{"className":6914},[6915],"inner",[1853,6917,6919],{"className":6918},[1937,2832],[1853,6920,6922],{"className":6921},[1948,2832],"",[1853,6924],{"className":6925},[6926],"fix",[1853,6928],{"className":6929},[1943,6930,2832],"nobreak",[1853,6932,1883],{"className":6933},[1948,2832],[1853,6935,2933],{"className":6936},[1937,1938,2832],[1853,6938,6939,6942],{"style":4725},[1853,6940],{"className":6941,"style":4713},[2729],[1853,6943,6944],{},[1853,6945,4627],{"className":6946},[3118,4734,4735],[1853,6948,2840],{"className":6949},[2839],[1853,6951,6953],{"className":6952},[2718],[1853,6954,6957],{"className":6955,"style":6956},[2722],"height:1.4382em;",[1853,6958],{},[1853,6960],{"className":6961,"style":2857},[1943],[1853,6963,3083],{"className":6964},[3118],[1853,6966,3489],{"className":6967},[2379],[1853,6969,6971,6974],{"className":6970},[1937],[1853,6972,2570],{"className":6973},[1937,1938],[1853,6975,6977],{"className":6976},[2807],[1853,6978,6980,7000],{"className":6979},[2714,2811],[1853,6981,6983,6997],{"className":6982},[2718],[1853,6984,6986],{"className":6985,"style":2980},[2722],[1853,6987,6988,6991],{"style":2821},[1853,6989],{"className":6990,"style":2825},[2729],[1853,6992,6994],{"className":6993},[2829,2830,2831,2832],[1853,6995,5639],{"className":6996,"style":5892},[1937,1938,2832],[1853,6998,2840],{"className":6999},[2839],[1853,7001,7003],{"className":7002},[2718],[1853,7004,7007],{"className":7005,"style":7006},[2722],"height:0.2861em;",[1853,7008],{},[1853,7010],{"className":7011,"style":1969},[1943],[1853,7013,1902],{"className":7014},[1973],[1853,7016],{"className":7017,"style":1969},[1943],[1853,7019,7021,7024,7064,7067,7070,7073,7076,7079,7082],{"className":7020},[1928],[1853,7022],{"className":7023,"style":2371},[1932],[1853,7025,7027,7030],{"className":7026},[1937],[1853,7028,2570],{"className":7029},[1937,1938],[1853,7031,7033],{"className":7032},[2807],[1853,7034,7036,7056],{"className":7035},[2714,2811],[1853,7037,7039,7053],{"className":7038},[2718],[1853,7040,7042],{"className":7041,"style":2980},[2722],[1853,7043,7044,7047],{"style":2821},[1853,7045],{"className":7046,"style":2825},[2729],[1853,7048,7050],{"className":7049},[2829,2830,2831,2832],[1853,7051,2933],{"className":7052},[1937,1938,2832],[1853,7054,2840],{"className":7055},[2839],[1853,7057,7059],{"className":7058},[2718],[1853,7060,7062],{"className":7061,"style":2847},[2722],[1853,7063],{},[1853,7065,2772],{"className":7066},[2853],[1853,7068],{"className":7069,"style":2857},[1943],[1853,7071,2623],{"className":7072},[1937],[1853,7074,6549],{"className":7075},[2386],[1853,7077],{"className":7078,"style":1969},[1943],[1853,7080,1902],{"className":7081},[1973],[1853,7083],{"className":7084,"style":1969},[1943],[1853,7086,7088,7091,7132,7206,7209,7295,7298,7301,7304,7344,7347,7350],{"className":7087},[1928],[1853,7089],{"className":7090,"style":6741},[1932],[1853,7092,7094,7097],{"className":7093},[1937],[1853,7095,3571],{"className":7096,"style":3772},[1937,1938],[1853,7098,7100],{"className":7099},[2807],[1853,7101,7103,7124],{"className":7102},[2714,2811],[1853,7104,7106,7121],{"className":7105},[2718],[1853,7107,7109],{"className":7108,"style":2980},[2722],[1853,7110,7112,7115],{"style":7111},"top:-2.55em;margin-left:-0.0528em;margin-right:0.05em;",[1853,7113],{"className":7114,"style":2825},[2729],[1853,7116,7118],{"className":7117},[2829,2830,2831,2832],[1853,7119,2933],{"className":7120},[1937,1938,2832],[1853,7122,2840],{"className":7123},[2839],[1853,7125,7127],{"className":7126},[2718],[1853,7128,7130],{"className":7129,"style":2847},[2722],[1853,7131],{},[1853,7133,7135,7138,7203],{"className":7134},[1937],[1853,7136],{"className":7137},[2379,3948],[1853,7139,7141],{"className":7140},[5627],[1853,7142,7144,7195],{"className":7143},[2714,2811],[1853,7145,7147,7192],{"className":7146},[2718],[1853,7148,7150,7173,7181],{"className":7149,"style":6801},[2722],[1853,7151,7152,7155],{"style":6804},[1853,7153],{"className":7154,"style":2730},[2729],[1853,7156,7158,7161,7164,7167,7170],{"className":7157},[1937],[1853,7159,5366],{"className":7160,"style":1939},[1937,1938],[1853,7162],{"className":7163,"style":1969},[1943],[1853,7165,1902],{"className":7166},[1973],[1853,7168],{"className":7169,"style":1969},[1943],[1853,7171,2769],{"className":7172},[1937],[1853,7174,7175,7178],{"style":5828},[1853,7176],{"className":7177,"style":2730},[2729],[1853,7179],{"className":7180,"style":5836},[5835],[1853,7182,7183,7186],{"style":6836},[1853,7184],{"className":7185,"style":2730},[2729],[1853,7187,7189],{"className":7188},[1937],[1853,7190,2769],{"className":7191},[1937],[1853,7193,2840],{"className":7194},[2839],[1853,7196,7198],{"className":7197},[2718],[1853,7199,7201],{"className":7200,"style":6855},[2722],[1853,7202],{},[1853,7204],{"className":7205},[2386,3948],[1853,7207],{"className":7208,"style":2857},[1943],[1853,7210,7212],{"className":7211},[3118,4696],[1853,7213,7215,7287],{"className":7214},[2714,2811],[1853,7216,7218,7284],{"className":7217},[2718],[1853,7219,7221,7274],{"className":7220,"style":4706},[2722],[1853,7222,7223,7226],{"style":6878},[1853,7224],{"className":7225,"style":4713},[2729],[1853,7227,7229],{"className":7228},[2829,2830,2831,2832],[1853,7230,7232,7235,7271],{"className":7231},[1937,2832],[1853,7233,5639],{"className":7234,"style":5892},[1937,1938,2832],[1853,7236,7238,7265,7268],{"className":7237},[1948,2832],[1853,7239,7241],{"className":7240},[1948,2832],[1853,7242,7244],{"className":7243},[1937,6900,2832],[1853,7245,7247],{"className":7246},[6904,2832],[1853,7248,7250,7253,7262],{"className":7249},[6908,2832],[1853,7251],{"className":7252,"style":1958},[1932],[1853,7254,7256],{"className":7255},[6915],[1853,7257,7259],{"className":7258},[1937,2832],[1853,7260,6922],{"className":7261},[1948,2832],[1853,7263],{"className":7264},[6926],[1853,7266],{"className":7267},[1943,6930,2832],[1853,7269,1883],{"className":7270},[1948,2832],[1853,7272,2933],{"className":7273},[1937,1938,2832],[1853,7275,7276,7279],{"style":4725},[1853,7277],{"className":7278,"style":4713},[2729],[1853,7280,7281],{},[1853,7282,4627],{"className":7283},[3118,4734,4735],[1853,7285,2840],{"className":7286},[2839],[1853,7288,7290],{"className":7289},[2718],[1853,7291,7293],{"className":7292,"style":6956},[2722],[1853,7294],{},[1853,7296],{"className":7297,"style":2857},[1943],[1853,7299,3083],{"className":7300},[3118],[1853,7302,3489],{"className":7303},[2379],[1853,7305,7307,7310],{"className":7306},[1937],[1853,7308,2570],{"className":7309},[1937,1938],[1853,7311,7313],{"className":7312},[2807],[1853,7314,7316,7336],{"className":7315},[2714,2811],[1853,7317,7319,7333],{"className":7318},[2718],[1853,7320,7322],{"className":7321,"style":2980},[2722],[1853,7323,7324,7327],{"style":2821},[1853,7325],{"className":7326,"style":2825},[2729],[1853,7328,7330],{"className":7329},[2829,2830,2831,2832],[1853,7331,2933],{"className":7332},[1937,1938,2832],[1853,7334,2840],{"className":7335},[2839],[1853,7337,7339],{"className":7338},[2718],[1853,7340,7342],{"className":7341,"style":2847},[2722],[1853,7343],{},[1853,7345],{"className":7346,"style":1969},[1943],[1853,7348,1902],{"className":7349},[1973],[1853,7351],{"className":7352,"style":1969},[1943],[1853,7354,7356,7360,7400,7403,7406,7409],{"className":7355},[1928],[1853,7357],{"className":7358,"style":7359},[1932],"height:1.0361em;vertical-align:-0.2861em;",[1853,7361,7363,7366],{"className":7362},[1937],[1853,7364,2570],{"className":7365},[1937,1938],[1853,7367,7369],{"className":7368},[2807],[1853,7370,7372,7392],{"className":7371},[2714,2811],[1853,7373,7375,7389],{"className":7374},[2718],[1853,7376,7378],{"className":7377,"style":2980},[2722],[1853,7379,7380,7383],{"style":2821},[1853,7381],{"className":7382,"style":2825},[2729],[1853,7384,7386],{"className":7385},[2829,2830,2831,2832],[1853,7387,5639],{"className":7388,"style":5892},[1937,1938,2832],[1853,7390,2840],{"className":7391},[2839],[1853,7393,7395],{"className":7394},[2718],[1853,7396,7398],{"className":7397,"style":7006},[2722],[1853,7399],{},[1853,7401,2772],{"className":7402},[2853],[1853,7404],{"className":7405,"style":2857},[1943],[1853,7407,2623],{"className":7408},[1937],[1853,7410,6549],{"className":7411},[2386],[1798,7413,7414,2155],{},[2152,7415,5012],{},[1805,7417,7418,7491,7660,7852],{},[1808,7419,7420,7490],{},[1853,7421,7423,7441],{"className":7422},[1860],[1853,7424,7426],{"className":7425},[1864],[1866,7427,7428],{"xmlns":1868},[1871,7429,7430,7438],{},[1874,7431,7432],{},[2763,7433,7434,7436],{},[1877,7435,2570],{},[1877,7437,2933],{},[1916,7439,7440],{"encoding":1918},"x_i",[1853,7442,7444],{"className":7443,"ariaHidden":1924},[1923],[1853,7445,7447,7450],{"className":7446},[1928],[1853,7448],{"className":7449,"style":5660},[1932],[1853,7451,7453,7456],{"className":7452},[1937],[1853,7454,2570],{"className":7455},[1937,1938],[1853,7457,7459],{"className":7458},[2807],[1853,7460,7462,7482],{"className":7461},[2714,2811],[1853,7463,7465,7479],{"className":7464},[2718],[1853,7466,7468],{"className":7467,"style":2980},[2722],[1853,7469,7470,7473],{"style":2821},[1853,7471],{"className":7472,"style":2825},[2729],[1853,7474,7476],{"className":7475},[2829,2830,2831,2832],[1853,7477,2933],{"className":7478},[1937,1938,2832],[1853,7480,2840],{"className":7481},[2839],[1853,7483,7485],{"className":7484},[2718],[1853,7486,7488],{"className":7487,"style":2847},[2722],[1853,7489],{},"：个人收益",[1808,7492,7493,2155,7563,7566,7567,2196],{},[1853,7494,7496,7514],{"className":7495},[1860],[1853,7497,7499],{"className":7498},[1864],[1866,7500,7501],{"xmlns":1868},[1871,7502,7503,7511],{},[1874,7504,7505],{},[2763,7506,7507,7509],{},[1877,7508,3512],{},[1877,7510,2933],{},[1916,7512,7513],{"encoding":1918},"\\alpha_i",[1853,7515,7517],{"className":7516,"ariaHidden":1924},[1923],[1853,7518,7520,7523],{"className":7519},[1928],[1853,7521],{"className":7522,"style":5660},[1932],[1853,7524,7526,7529],{"className":7525},[1937],[1853,7527,3512],{"className":7528,"style":3717},[1937,1938],[1853,7530,7532],{"className":7531},[2807],[1853,7533,7535,7555],{"className":7534},[2714,2811],[1853,7536,7538,7552],{"className":7537},[2718],[1853,7539,7541],{"className":7540,"style":2980},[2722],[1853,7542,7543,7546],{"style":6762},[1853,7544],{"className":7545,"style":2825},[2729],[1853,7547,7549],{"className":7548},[2829,2830,2831,2832],[1853,7550,2933],{"className":7551},[1937,1938,2832],[1853,7553,2840],{"className":7554},[2839],[1853,7556,7558],{"className":7557},[2718],[1853,7559,7561],{"className":7560,"style":2847},[2722],[1853,7562],{},[2152,7564,7565],{},"嫉妒 (envy)","，他人比我多时的负效用（",[1853,7568,7570,7592],{"className":7569},[1860],[1853,7571,7573],{"className":7572},[1864],[1866,7574,7575],{"xmlns":1868},[1871,7576,7577,7589],{},[1874,7578,7579,7585,7587],{},[2763,7580,7581,7583],{},[1877,7582,3512],{},[1877,7584,2933],{},[1881,7586,2344],{},[2621,7588,2623],{},[1916,7590,7591],{"encoding":1918},"\\alpha_i \\geq 0",[1853,7593,7595,7651],{"className":7594,"ariaHidden":1924},[1923],[1853,7596,7598,7602,7642,7645,7648],{"className":7597},[1928],[1853,7599],{"className":7600,"style":7601},[1932],"height:0.786em;vertical-align:-0.15em;",[1853,7603,7605,7608],{"className":7604},[1937],[1853,7606,3512],{"className":7607,"style":3717},[1937,1938],[1853,7609,7611],{"className":7610},[2807],[1853,7612,7614,7634],{"className":7613},[2714,2811],[1853,7615,7617,7631],{"className":7616},[2718],[1853,7618,7620],{"className":7619,"style":2980},[2722],[1853,7621,7622,7625],{"style":6762},[1853,7623],{"className":7624,"style":2825},[2729],[1853,7626,7628],{"className":7627},[2829,2830,2831,2832],[1853,7629,2933],{"className":7630},[1937,1938,2832],[1853,7632,2840],{"className":7633},[2839],[1853,7635,7637],{"className":7636},[2718],[1853,7638,7640],{"className":7639,"style":2847},[2722],[1853,7641],{},[1853,7643],{"className":7644,"style":1944},[1943],[1853,7646,2344],{"className":7647},[1948],[1853,7649],{"className":7650,"style":1944},[1943],[1853,7652,7654,7657],{"className":7653},[1928],[1853,7655],{"className":7656,"style":2655},[1932],[1853,7658,2623],{"className":7659},[1937],[1808,7661,7662,2155,7732,7735,7736,2196],{},[1853,7663,7665,7683],{"className":7664},[1860],[1853,7666,7668],{"className":7667},[1864],[1866,7669,7670],{"xmlns":1868},[1871,7671,7672,7680],{},[1874,7673,7674],{},[2763,7675,7676,7678],{},[1877,7677,3571],{},[1877,7679,2933],{},[1916,7681,7682],{"encoding":1918},"\\beta_i",[1853,7684,7686],{"className":7685,"ariaHidden":1924},[1923],[1853,7687,7689,7692],{"className":7688},[1928],[1853,7690],{"className":7691,"style":1958},[1932],[1853,7693,7695,7698],{"className":7694},[1937],[1853,7696,3571],{"className":7697,"style":3772},[1937,1938],[1853,7699,7701],{"className":7700},[2807],[1853,7702,7704,7724],{"className":7703},[2714,2811],[1853,7705,7707,7721],{"className":7706},[2718],[1853,7708,7710],{"className":7709,"style":2980},[2722],[1853,7711,7712,7715],{"style":7111},[1853,7713],{"className":7714,"style":2825},[2729],[1853,7716,7718],{"className":7717},[2829,2830,2831,2832],[1853,7719,2933],{"className":7720},[1937,1938,2832],[1853,7722,2840],{"className":7723},[2839],[1853,7725,7727],{"className":7726},[2718],[1853,7728,7730],{"className":7729,"style":2847},[2722],[1853,7731],{},[2152,7733,7734],{},"内疚 (guilt)","，我比他人多时的负效用（",[1853,7737,7739,7766],{"className":7738},[1860],[1853,7740,7742],{"className":7741},[1864],[1866,7743,7744],{"xmlns":1868},[1871,7745,7746,7763],{},[1874,7747,7748,7750,7753,7759,7761],{},[2621,7749,2623],{},[1881,7751,7752],{},"≤",[2763,7754,7755,7757],{},[1877,7756,3571],{},[1877,7758,2933],{},[1881,7760,3536],{},[2621,7762,2769],{},[1916,7764,7765],{"encoding":1918},"0 \\leq \\beta_i \u003C 1",[1853,7767,7769,7788,7843],{"className":7768,"ariaHidden":1924},[1923],[1853,7770,7772,7776,7779,7782,7785],{"className":7771},[1928],[1853,7773],{"className":7774,"style":7775},[1932],"height:0.7804em;vertical-align:-0.136em;",[1853,7777,2623],{"className":7778},[1937],[1853,7780],{"className":7781,"style":1944},[1943],[1853,7783,7752],{"className":7784},[1948],[1853,7786],{"className":7787,"style":1944},[1943],[1853,7789,7791,7794,7834,7837,7840],{"className":7790},[1928],[1853,7792],{"className":7793,"style":1958},[1932],[1853,7795,7797,7800],{"className":7796},[1937],[1853,7798,3571],{"className":7799,"style":3772},[1937,1938],[1853,7801,7803],{"className":7802},[2807],[1853,7804,7806,7826],{"className":7805},[2714,2811],[1853,7807,7809,7823],{"className":7808},[2718],[1853,7810,7812],{"className":7811,"style":2980},[2722],[1853,7813,7814,7817],{"style":7111},[1853,7815],{"className":7816,"style":2825},[2729],[1853,7818,7820],{"className":7819},[2829,2830,2831,2832],[1853,7821,2933],{"className":7822},[1937,1938,2832],[1853,7824,2840],{"className":7825},[2839],[1853,7827,7829],{"className":7828},[2718],[1853,7830,7832],{"className":7831,"style":2847},[2722],[1853,7833],{},[1853,7835],{"className":7836,"style":1944},[1943],[1853,7838,3536],{"className":7839},[1948],[1853,7841],{"className":7842,"style":1944},[1943],[1853,7844,7846,7849],{"className":7845},[1928],[1853,7847],{"className":7848,"style":2655},[1932],[1853,7850,2769],{"className":7851},[1937],[1808,7853,7854,7855,7988],{},"假设：",[1853,7856,7858,7884],{"className":7857},[1860],[1853,7859,7861],{"className":7860},[1864],[1866,7862,7863],{"xmlns":1868},[1871,7864,7865,7881],{},[1874,7866,7867,7873,7875],{},[2763,7868,7869,7871],{},[1877,7870,3512],{},[1877,7872,2933],{},[1881,7874,2344],{},[2763,7876,7877,7879],{},[1877,7878,3571],{},[1877,7880,2933],{},[1916,7882,7883],{"encoding":1918},"\\alpha_i \\geq \\beta_i",[1853,7885,7887,7942],{"className":7886,"ariaHidden":1924},[1923],[1853,7888,7890,7893,7933,7936,7939],{"className":7889},[1928],[1853,7891],{"className":7892,"style":7601},[1932],[1853,7894,7896,7899],{"className":7895},[1937],[1853,7897,3512],{"className":7898,"style":3717},[1937,1938],[1853,7900,7902],{"className":7901},[2807],[1853,7903,7905,7925],{"className":7904},[2714,2811],[1853,7906,7908,7922],{"className":7907},[2718],[1853,7909,7911],{"className":7910,"style":2980},[2722],[1853,7912,7913,7916],{"style":6762},[1853,7914],{"className":7915,"style":2825},[2729],[1853,7917,7919],{"className":7918},[2829,2830,2831,2832],[1853,7920,2933],{"className":7921},[1937,1938,2832],[1853,7923,2840],{"className":7924},[2839],[1853,7926,7928],{"className":7927},[2718],[1853,7929,7931],{"className":7930,"style":2847},[2722],[1853,7932],{},[1853,7934],{"className":7935,"style":1944},[1943],[1853,7937,2344],{"className":7938},[1948],[1853,7940],{"className":7941,"style":1944},[1943],[1853,7943,7945,7948],{"className":7944},[1928],[1853,7946],{"className":7947,"style":1958},[1932],[1853,7949,7951,7954],{"className":7950},[1937],[1853,7952,3571],{"className":7953,"style":3772},[1937,1938],[1853,7955,7957],{"className":7956},[2807],[1853,7958,7960,7980],{"className":7959},[2714,2811],[1853,7961,7963,7977],{"className":7962},[2718],[1853,7964,7966],{"className":7965,"style":2980},[2722],[1853,7967,7968,7971],{"style":7111},[1853,7969],{"className":7970,"style":2825},[2729],[1853,7972,7974],{"className":7973},[2829,2830,2831,2832],[1853,7975,2933],{"className":7976},[1937,1938,2832],[1853,7978,2840],{"className":7979},[2839],[1853,7981,7983],{"className":7982},[2718],[1853,7984,7986],{"className":7985,"style":2847},[2722],[1853,7987],{},"（嫉妒 > 内疚）",[1798,7990,7991,2155],{},[2152,7992,7993],{},"应用于最后通牒博弈",[1798,7995,7996,7997,8071,8072,2659],{},"提议者提议 ",[1853,7998,8000,8026],{"className":7999},[1860],[1853,8001,8003],{"className":8002},[1864],[1866,8004,8005],{"xmlns":1868},[1871,8006,8007,8023],{},[1874,8008,8009,8011,8013,8015,8017,8019,8021],{},[1881,8010,2335],{"stretchy":2334},[1877,8012,4980],{},[1881,8014,2772],{"separator":1924},[2621,8016,2769],{},[1881,8018,1902],{},[1877,8020,4980],{},[1881,8022,2341],{"stretchy":2334},[1916,8024,8025],{"encoding":1918},"(s, 1-s)",[1853,8027,8029,8059],{"className":8028,"ariaHidden":1924},[1923],[1853,8030,8032,8035,8038,8041,8044,8047,8050,8053,8056],{"className":8031},[1928],[1853,8033],{"className":8034,"style":2371},[1932],[1853,8036,2335],{"className":8037},[2379],[1853,8039,4980],{"className":8040},[1937,1938],[1853,8042,2772],{"className":8043},[2853],[1853,8045],{"className":8046,"style":2857},[1943],[1853,8048,2769],{"className":8049},[1937],[1853,8051],{"className":8052,"style":1969},[1943],[1853,8054,1902],{"className":8055},[1973],[1853,8057],{"className":8058,"style":1969},[1943],[1853,8060,8062,8065,8068],{"className":8061},[1928],[1853,8063],{"className":8064,"style":2371},[1932],[1853,8066,4980],{"className":8067},[1937,1938],[1853,8069,2341],{"className":8070},[2386],"，自己拿 ",[1853,8073,8075,8088],{"className":8074},[1860],[1853,8076,8078],{"className":8077},[1864],[1866,8079,8080],{"xmlns":1868},[1871,8081,8082,8086],{},[1874,8083,8084],{},[1877,8085,4980],{},[1916,8087,4980],{"encoding":1918},[1853,8089,8091],{"className":8090,"ariaHidden":1924},[1923],[1853,8092,8094,8097],{"className":8093},[1928],[1853,8095],{"className":8096,"style":4911},[1932],[1853,8098,4980],{"className":8099},[1937,1938],[1798,8101,8102],{},"回应者效用（如果接受）：",[1853,8104,8106],{"className":8105},[1856],[1853,8107,8109,8217],{"className":8108},[1860],[1853,8110,8112],{"className":8111},[1864],[1866,8113,8114],{"xmlns":1868,"display":1869},[1871,8115,8116,8214],{},[1874,8117,8118,8125,8127,8129,8131,8133,8135,8137,8139,8145,8147,8149,8151,8153,8155,8157,8159,8161,8163,8165,8167,8169,8171,8173,8175,8177,8179,8181,8183,8185,8191,8193,8195,8197,8199,8201,8203,8205,8207,8209,8211],{},[2763,8119,8120,8122],{},[1877,8121,1879],{},[1877,8123,8124],{},"R",[1881,8126,1883],{},[1881,8128,2335],{"stretchy":2334},[2621,8130,2769],{},[1881,8132,1902],{},[1877,8134,4980],{},[1881,8136,2341],{"stretchy":2334},[1881,8138,1902],{},[2763,8140,8141,8143],{},[1877,8142,3512],{},[1877,8144,8124],{},[1877,8146,3083],{},[1881,8148,3076],{},[1881,8150,3489],{"stretchy":2334},[1877,8152,4980],{},[1881,8154,1902],{},[1881,8156,2335],{"stretchy":2334},[2621,8158,2769],{},[1881,8160,1902],{},[1877,8162,4980],{},[1881,8164,2341],{"stretchy":2334},[1881,8166,2772],{"separator":1924},[2621,8168,2623],{},[1881,8170,6549],{"stretchy":2334},[1881,8172,1883],{},[1881,8174,2335],{"stretchy":2334},[2621,8176,2769],{},[1881,8178,1902],{},[1877,8180,4980],{},[1881,8182,2341],{"stretchy":2334},[1881,8184,1902],{},[2763,8186,8187,8189],{},[1877,8188,3512],{},[1877,8190,8124],{},[1881,8192,2335],{"stretchy":2334},[2621,8194,2779],{},[1877,8196,4980],{},[1881,8198,1902],{},[2621,8200,2769],{},[1881,8202,2341],{"stretchy":2334},[1943,8204],{"width":3495},[1885,8206,3521],{},[1877,8208,4980],{},[1881,8210,2619],{},[2621,8212,8213],{},"0.5",[1916,8215,8216],{"encoding":1918},"U_R = (1-s) - \\alpha_R \\max\\{s - (1-s), 0\\} = (1-s) - \\alpha_R(2s-1) \\quad \\text{if } s > 0.5",[1853,8218,8220,8277,8298,8319,8386,8407,8440,8461,8482,8546,8579],{"className":8219,"ariaHidden":1924},[1923],[1853,8221,8223,8227,8268,8271,8274],{"className":8222},[1928],[1853,8224],{"className":8225,"style":8226},[1932],"height:0.8333em;vertical-align:-0.15em;",[1853,8228,8230,8233],{"className":8229},[1937],[1853,8231,1879],{"className":8232,"style":1939},[1937,1938],[1853,8234,8236],{"className":8235},[2807],[1853,8237,8239,8260],{"className":8238},[2714,2811],[1853,8240,8242,8257],{"className":8241},[2718],[1853,8243,8245],{"className":8244,"style":3145},[2722],[1853,8246,8247,8250],{"style":6640},[1853,8248],{"className":8249,"style":2825},[2729],[1853,8251,8253],{"className":8252},[2829,2830,2831,2832],[1853,8254,8124],{"className":8255,"style":8256},[1937,1938,2832],"margin-right:0.0077em;",[1853,8258,2840],{"className":8259},[2839],[1853,8261,8263],{"className":8262},[2718],[1853,8264,8266],{"className":8265,"style":2847},[2722],[1853,8267],{},[1853,8269],{"className":8270,"style":1944},[1943],[1853,8272,1883],{"className":8273},[1948],[1853,8275],{"className":8276,"style":1944},[1943],[1853,8278,8280,8283,8286,8289,8292,8295],{"className":8279},[1928],[1853,8281],{"className":8282,"style":2371},[1932],[1853,8284,2335],{"className":8285},[2379],[1853,8287,2769],{"className":8288},[1937],[1853,8290],{"className":8291,"style":1969},[1943],[1853,8293,1902],{"className":8294},[1973],[1853,8296],{"className":8297,"style":1969},[1943],[1853,8299,8301,8304,8307,8310,8313,8316],{"className":8300},[1928],[1853,8302],{"className":8303,"style":2371},[1932],[1853,8305,4980],{"className":8306},[1937,1938],[1853,8308,2341],{"className":8309},[2386],[1853,8311],{"className":8312,"style":1969},[1943],[1853,8314,1902],{"className":8315},[1973],[1853,8317],{"className":8318,"style":1969},[1943],[1853,8320,8322,8325,8365,8368,8371,8374,8377,8380,8383],{"className":8321},[1928],[1853,8323],{"className":8324,"style":2371},[1932],[1853,8326,8328,8331],{"className":8327},[1937],[1853,8329,3512],{"className":8330,"style":3717},[1937,1938],[1853,8332,8334],{"className":8333},[2807],[1853,8335,8337,8357],{"className":8336},[2714,2811],[1853,8338,8340,8354],{"className":8339},[2718],[1853,8341,8343],{"className":8342,"style":3145},[2722],[1853,8344,8345,8348],{"style":6762},[1853,8346],{"className":8347,"style":2825},[2729],[1853,8349,8351],{"className":8350},[2829,2830,2831,2832],[1853,8352,8124],{"className":8353,"style":8256},[1937,1938,2832],[1853,8355,2840],{"className":8356},[2839],[1853,8358,8360],{"className":8359},[2718],[1853,8361,8363],{"className":8362,"style":2847},[2722],[1853,8364],{},[1853,8366],{"className":8367,"style":2857},[1943],[1853,8369,3083],{"className":8370},[3118],[1853,8372,3489],{"className":8373},[2379],[1853,8375,4980],{"className":8376},[1937,1938],[1853,8378],{"className":8379,"style":1969},[1943],[1853,8381,1902],{"className":8382},[1973],[1853,8384],{"className":8385,"style":1969},[1943],[1853,8387,8389,8392,8395,8398,8401,8404],{"className":8388},[1928],[1853,8390],{"className":8391,"style":2371},[1932],[1853,8393,2335],{"className":8394},[2379],[1853,8396,2769],{"className":8397},[1937],[1853,8399],{"className":8400,"style":1969},[1943],[1853,8402,1902],{"className":8403},[1973],[1853,8405],{"className":8406,"style":1969},[1943],[1853,8408,8410,8413,8416,8419,8422,8425,8428,8431,8434,8437],{"className":8409},[1928],[1853,8411],{"className":8412,"style":2371},[1932],[1853,8414,4980],{"className":8415},[1937,1938],[1853,8417,2341],{"className":8418},[2386],[1853,8420,2772],{"className":8421},[2853],[1853,8423],{"className":8424,"style":2857},[1943],[1853,8426,2623],{"className":8427},[1937],[1853,8429,6549],{"className":8430},[2386],[1853,8432],{"className":8433,"style":1944},[1943],[1853,8435,1883],{"className":8436},[1948],[1853,8438],{"className":8439,"style":1944},[1943],[1853,8441,8443,8446,8449,8452,8455,8458],{"className":8442},[1928],[1853,8444],{"className":8445,"style":2371},[1932],[1853,8447,2335],{"className":8448},[2379],[1853,8450,2769],{"className":8451},[1937],[1853,8453],{"className":8454,"style":1969},[1943],[1853,8456,1902],{"className":8457},[1973],[1853,8459],{"className":8460,"style":1969},[1943],[1853,8462,8464,8467,8470,8473,8476,8479],{"className":8463},[1928],[1853,8465],{"className":8466,"style":2371},[1932],[1853,8468,4980],{"className":8469},[1937,1938],[1853,8471,2341],{"className":8472},[2386],[1853,8474],{"className":8475,"style":1969},[1943],[1853,8477,1902],{"className":8478},[1973],[1853,8480],{"className":8481,"style":1969},[1943],[1853,8483,8485,8488,8528,8531,8534,8537,8540,8543],{"className":8484},[1928],[1853,8486],{"className":8487,"style":2371},[1932],[1853,8489,8491,8494],{"className":8490},[1937],[1853,8492,3512],{"className":8493,"style":3717},[1937,1938],[1853,8495,8497],{"className":8496},[2807],[1853,8498,8500,8520],{"className":8499},[2714,2811],[1853,8501,8503,8517],{"className":8502},[2718],[1853,8504,8506],{"className":8505,"style":3145},[2722],[1853,8507,8508,8511],{"style":6762},[1853,8509],{"className":8510,"style":2825},[2729],[1853,8512,8514],{"className":8513},[2829,2830,2831,2832],[1853,8515,8124],{"className":8516,"style":8256},[1937,1938,2832],[1853,8518,2840],{"className":8519},[2839],[1853,8521,8523],{"className":8522},[2718],[1853,8524,8526],{"className":8525,"style":2847},[2722],[1853,8527],{},[1853,8529,2335],{"className":8530},[2379],[1853,8532,2779],{"className":8533},[1937],[1853,8535,4980],{"className":8536},[1937,1938],[1853,8538],{"className":8539,"style":1969},[1943],[1853,8541,1902],{"className":8542},[1973],[1853,8544],{"className":8545,"style":1969},[1943],[1853,8547,8549,8552,8555,8558,8561,8567,8570,8573,8576],{"className":8548},[1928],[1853,8550],{"className":8551,"style":2371},[1932],[1853,8553,2769],{"className":8554},[1937],[1853,8556,2341],{"className":8557},[2386],[1853,8559],{"className":8560,"style":3834},[1943],[1853,8562,8564],{"className":8563},[1937,1962],[1853,8565,3521],{"className":8566},[1937],[1853,8568,4980],{"className":8569},[1937,1938],[1853,8571],{"className":8572,"style":1944},[1943],[1853,8574,2619],{"className":8575},[1948],[1853,8577],{"className":8578,"style":1944},[1943],[1853,8580,8582,8585],{"className":8581},[1928],[1853,8583],{"className":8584,"style":2655},[1932],[1853,8586,8213],{"className":8587},[1937],[1798,8589,8590,8591,2659],{},"拒绝则 ",[1853,8592,8594,8616],{"className":8593},[1860],[1853,8595,8597],{"className":8596},[1864],[1866,8598,8599],{"xmlns":1868},[1871,8600,8601,8613],{},[1874,8602,8603,8609,8611],{},[2763,8604,8605,8607],{},[1877,8606,1879],{},[1877,8608,8124],{},[1881,8610,1883],{},[2621,8612,2623],{},[1916,8614,8615],{"encoding":1918},"U_R = 0",[1853,8617,8619,8674],{"className":8618,"ariaHidden":1924},[1923],[1853,8620,8622,8625,8665,8668,8671],{"className":8621},[1928],[1853,8623],{"className":8624,"style":8226},[1932],[1853,8626,8628,8631],{"className":8627},[1937],[1853,8629,1879],{"className":8630,"style":1939},[1937,1938],[1853,8632,8634],{"className":8633},[2807],[1853,8635,8637,8657],{"className":8636},[2714,2811],[1853,8638,8640,8654],{"className":8639},[2718],[1853,8641,8643],{"className":8642,"style":3145},[2722],[1853,8644,8645,8648],{"style":6640},[1853,8646],{"className":8647,"style":2825},[2729],[1853,8649,8651],{"className":8650},[2829,2830,2831,2832],[1853,8652,8124],{"className":8653,"style":8256},[1937,1938,2832],[1853,8655,2840],{"className":8656},[2839],[1853,8658,8660],{"className":8659},[2718],[1853,8661,8663],{"className":8662,"style":2847},[2722],[1853,8664],{},[1853,8666],{"className":8667,"style":1944},[1943],[1853,8669,1883],{"className":8670},[1948],[1853,8672],{"className":8673,"style":1944},[1943],[1853,8675,8677,8680],{"className":8676},[1928],[1853,8678],{"className":8679,"style":2655},[1932],[1853,8681,2623],{"className":8682},[1937],[1798,8684,8685],{},"接受条件：",[1853,8687,8689],{"className":8688},[1856],[1853,8690,8692,8738],{"className":8691},[1860],[1853,8693,8695],{"className":8694},[1864],[1866,8696,8697],{"xmlns":1868,"display":1869},[1871,8698,8699,8735],{},[1874,8700,8701,8703,8705,8707,8709,8711,8713,8719,8721,8723,8725,8727,8729,8731,8733],{},[1881,8702,2335],{"stretchy":2334},[2621,8704,2769],{},[1881,8706,1902],{},[1877,8708,4980],{},[1881,8710,2341],{"stretchy":2334},[1881,8712,1902],{},[2763,8714,8715,8717],{},[1877,8716,3512],{},[1877,8718,8124],{},[1881,8720,2335],{"stretchy":2334},[2621,8722,2779],{},[1877,8724,4980],{},[1881,8726,1902],{},[2621,8728,2769],{},[1881,8730,2341],{"stretchy":2334},[1881,8732,2344],{},[2621,8734,2623],{},[1916,8736,8737],{"encoding":1918},"(1-s) - \\alpha_R(2s-1) \\geq 0",[1853,8739,8741,8762,8783,8847,8868],{"className":8740,"ariaHidden":1924},[1923],[1853,8742,8744,8747,8750,8753,8756,8759],{"className":8743},[1928],[1853,8745],{"className":8746,"style":2371},[1932],[1853,8748,2335],{"className":8749},[2379],[1853,8751,2769],{"className":8752},[1937],[1853,8754],{"className":8755,"style":1969},[1943],[1853,8757,1902],{"className":8758},[1973],[1853,8760],{"className":8761,"style":1969},[1943],[1853,8763,8765,8768,8771,8774,8777,8780],{"className":8764},[1928],[1853,8766],{"className":8767,"style":2371},[1932],[1853,8769,4980],{"className":8770},[1937,1938],[1853,8772,2341],{"className":8773},[2386],[1853,8775],{"className":8776,"style":1969},[1943],[1853,8778,1902],{"className":8779},[1973],[1853,8781],{"className":8782,"style":1969},[1943],[1853,8784,8786,8789,8829,8832,8835,8838,8841,8844],{"className":8785},[1928],[1853,8787],{"className":8788,"style":2371},[1932],[1853,8790,8792,8795],{"className":8791},[1937],[1853,8793,3512],{"className":8794,"style":3717},[1937,1938],[1853,8796,8798],{"className":8797},[2807],[1853,8799,8801,8821],{"className":8800},[2714,2811],[1853,8802,8804,8818],{"className":8803},[2718],[1853,8805,8807],{"className":8806,"style":3145},[2722],[1853,8808,8809,8812],{"style":6762},[1853,8810],{"className":8811,"style":2825},[2729],[1853,8813,8815],{"className":8814},[2829,2830,2831,2832],[1853,8816,8124],{"className":8817,"style":8256},[1937,1938,2832],[1853,8819,2840],{"className":8820},[2839],[1853,8822,8824],{"className":8823},[2718],[1853,8825,8827],{"className":8826,"style":2847},[2722],[1853,8828],{},[1853,8830,2335],{"className":8831},[2379],[1853,8833,2779],{"className":8834},[1937],[1853,8836,4980],{"className":8837},[1937,1938],[1853,8839],{"className":8840,"style":1969},[1943],[1853,8842,1902],{"className":8843},[1973],[1853,8845],{"className":8846,"style":1969},[1943],[1853,8848,8850,8853,8856,8859,8862,8865],{"className":8849},[1928],[1853,8851],{"className":8852,"style":2371},[1932],[1853,8854,2769],{"className":8855},[1937],[1853,8857,2341],{"className":8858},[2386],[1853,8860],{"className":8861,"style":1944},[1943],[1853,8863,2344],{"className":8864},[1948],[1853,8866],{"className":8867,"style":1944},[1943],[1853,8869,8871,8874],{"className":8870},[1928],[1853,8872],{"className":8873,"style":2655},[1932],[1853,8875,2623],{"className":8876},[1937],[1853,8878,8880],{"className":8879},[1856],[1853,8881,8883,8925],{"className":8882},[1860],[1853,8884,8886],{"className":8885},[1864],[1866,8887,8888],{"xmlns":1868,"display":1869},[1871,8889,8890,8922],{},[1874,8891,8892,8894,8896,8898,8900,8902,8908,8910,8912,8918,8920],{},[2621,8893,2769],{},[1881,8895,1902],{},[1877,8897,4980],{},[1881,8899,1902],{},[2621,8901,2779],{},[2763,8903,8904,8906],{},[1877,8905,3512],{},[1877,8907,8124],{},[1877,8909,4980],{},[1881,8911,1890],{},[2763,8913,8914,8916],{},[1877,8915,3512],{},[1877,8917,8124],{},[1881,8919,2344],{},[2621,8921,2623],{},[1916,8923,8924],{"encoding":1918},"1 - s - 2\\alpha_R s + \\alpha_R \\geq 0",[1853,8926,8928,8946,8964,9026,9081],{"className":8927,"ariaHidden":1924},[1923],[1853,8929,8931,8934,8937,8940,8943],{"className":8930},[1928],[1853,8932],{"className":8933,"style":4176},[1932],[1853,8935,2769],{"className":8936},[1937],[1853,8938],{"className":8939,"style":1969},[1943],[1853,8941,1902],{"className":8942},[1973],[1853,8944],{"className":8945,"style":1969},[1943],[1853,8947,8949,8952,8955,8958,8961],{"className":8948},[1928],[1853,8950],{"className":8951,"style":5716},[1932],[1853,8953,4980],{"className":8954},[1937,1938],[1853,8956],{"className":8957,"style":1969},[1943],[1853,8959,1902],{"className":8960},[1973],[1853,8962],{"className":8963,"style":1969},[1943],[1853,8965,8967,8971,8974,9014,9017,9020,9023],{"className":8966},[1928],[1853,8968],{"className":8969,"style":8970},[1932],"height:0.7944em;vertical-align:-0.15em;",[1853,8972,2779],{"className":8973},[1937],[1853,8975,8977,8980],{"className":8976},[1937],[1853,8978,3512],{"className":8979,"style":3717},[1937,1938],[1853,8981,8983],{"className":8982},[2807],[1853,8984,8986,9006],{"className":8985},[2714,2811],[1853,8987,8989,9003],{"className":8988},[2718],[1853,8990,8992],{"className":8991,"style":3145},[2722],[1853,8993,8994,8997],{"style":6762},[1853,8995],{"className":8996,"style":2825},[2729],[1853,8998,9000],{"className":8999},[2829,2830,2831,2832],[1853,9001,8124],{"className":9002,"style":8256},[1937,1938,2832],[1853,9004,2840],{"className":9005},[2839],[1853,9007,9009],{"className":9008},[2718],[1853,9010,9012],{"className":9011,"style":2847},[2722],[1853,9013],{},[1853,9015,4980],{"className":9016},[1937,1938],[1853,9018],{"className":9019,"style":1969},[1943],[1853,9021,1890],{"className":9022},[1973],[1853,9024],{"className":9025,"style":1969},[1943],[1853,9027,9029,9032,9072,9075,9078],{"className":9028},[1928],[1853,9030],{"className":9031,"style":7601},[1932],[1853,9033,9035,9038],{"className":9034},[1937],[1853,9036,3512],{"className":9037,"style":3717},[1937,1938],[1853,9039,9041],{"className":9040},[2807],[1853,9042,9044,9064],{"className":9043},[2714,2811],[1853,9045,9047,9061],{"className":9046},[2718],[1853,9048,9050],{"className":9049,"style":3145},[2722],[1853,9051,9052,9055],{"style":6762},[1853,9053],{"className":9054,"style":2825},[2729],[1853,9056,9058],{"className":9057},[2829,2830,2831,2832],[1853,9059,8124],{"className":9060,"style":8256},[1937,1938,2832],[1853,9062,2840],{"className":9063},[2839],[1853,9065,9067],{"className":9066},[2718],[1853,9068,9070],{"className":9069,"style":2847},[2722],[1853,9071],{},[1853,9073],{"className":9074,"style":1944},[1943],[1853,9076,2344],{"className":9077},[1948],[1853,9079],{"className":9080,"style":1944},[1943],[1853,9082,9084,9087],{"className":9083},[1928],[1853,9085],{"className":9086,"style":2655},[1932],[1853,9088,2623],{"className":9089},[1937],[1853,9091,9093],{"className":9092},[1856],[1853,9094,9096,9140],{"className":9095},[1860],[1853,9097,9099],{"className":9098},[1864],[1866,9100,9101],{"xmlns":1868,"display":1869},[1871,9102,9103,9137],{},[1874,9104,9105,9107,9109],{},[1877,9106,4980],{},[1881,9108,7752],{},[5627,9110,9111,9123],{},[1874,9112,9113,9115,9117],{},[2621,9114,2769],{},[1881,9116,1890],{},[2763,9118,9119,9121],{},[1877,9120,3512],{},[1877,9122,8124],{},[1874,9124,9125,9127,9129,9131],{},[2621,9126,2769],{},[1881,9128,1890],{},[2621,9130,2779],{},[2763,9132,9133,9135],{},[1877,9134,3512],{},[1877,9136,8124],{},[1916,9138,9139],{"encoding":1918},"s \\leq \\frac{1 + \\alpha_R}{1 + 2\\alpha_R}",[1853,9141,9143,9162],{"className":9142,"ariaHidden":1924},[1923],[1853,9144,9146,9150,9153,9156,9159],{"className":9145},[1928],[1853,9147],{"className":9148,"style":9149},[1932],"height:0.7719em;vertical-align:-0.136em;",[1853,9151,4980],{"className":9152},[1937,1938],[1853,9154],{"className":9155,"style":1944},[1943],[1853,9157,7752],{"className":9158},[1948],[1853,9160],{"className":9161,"style":1944},[1943],[1853,9163,9165,9169],{"className":9164},[1928],[1853,9166],{"className":9167,"style":9168},[1932],"height:2.1574em;vertical-align:-0.836em;",[1853,9170,9172,9175,9330],{"className":9171},[1937],[1853,9173],{"className":9174},[2379,3948],[1853,9176,9178],{"className":9177},[5627],[1853,9179,9181,9321],{"className":9180},[2714,2811],[1853,9182,9184,9318],{"className":9183},[2718],[1853,9185,9187,9250,9258],{"className":9186,"style":6801},[2722],[1853,9188,9189,9192],{"style":6804},[1853,9190],{"className":9191,"style":2730},[2729],[1853,9193,9195,9198,9201,9204,9207,9210],{"className":9194},[1937],[1853,9196,2769],{"className":9197},[1937],[1853,9199],{"className":9200,"style":1969},[1943],[1853,9202,1890],{"className":9203},[1973],[1853,9205],{"className":9206,"style":1969},[1943],[1853,9208,2779],{"className":9209},[1937],[1853,9211,9213,9216],{"className":9212},[1937],[1853,9214,3512],{"className":9215,"style":3717},[1937,1938],[1853,9217,9219],{"className":9218},[2807],[1853,9220,9222,9242],{"className":9221},[2714,2811],[1853,9223,9225,9239],{"className":9224},[2718],[1853,9226,9228],{"className":9227,"style":3145},[2722],[1853,9229,9230,9233],{"style":6762},[1853,9231],{"className":9232,"style":2825},[2729],[1853,9234,9236],{"className":9235},[2829,2830,2831,2832],[1853,9237,8124],{"className":9238,"style":8256},[1937,1938,2832],[1853,9240,2840],{"className":9241},[2839],[1853,9243,9245],{"className":9244},[2718],[1853,9246,9248],{"className":9247,"style":2847},[2722],[1853,9249],{},[1853,9251,9252,9255],{"style":5828},[1853,9253],{"className":9254,"style":2730},[2729],[1853,9256],{"className":9257,"style":5836},[5835],[1853,9259,9260,9263],{"style":6836},[1853,9261],{"className":9262,"style":2730},[2729],[1853,9264,9266,9269,9272,9275,9278],{"className":9265},[1937],[1853,9267,2769],{"className":9268},[1937],[1853,9270],{"className":9271,"style":1969},[1943],[1853,9273,1890],{"className":9274},[1973],[1853,9276],{"className":9277,"style":1969},[1943],[1853,9279,9281,9284],{"className":9280},[1937],[1853,9282,3512],{"className":9283,"style":3717},[1937,1938],[1853,9285,9287],{"className":9286},[2807],[1853,9288,9290,9310],{"className":9289},[2714,2811],[1853,9291,9293,9307],{"className":9292},[2718],[1853,9294,9296],{"className":9295,"style":3145},[2722],[1853,9297,9298,9301],{"style":6762},[1853,9299],{"className":9300,"style":2825},[2729],[1853,9302,9304],{"className":9303},[2829,2830,2831,2832],[1853,9305,8124],{"className":9306,"style":8256},[1937,1938,2832],[1853,9308,2840],{"className":9309},[2839],[1853,9311,9313],{"className":9312},[2718],[1853,9314,9316],{"className":9315,"style":2847},[2722],[1853,9317],{},[1853,9319,2840],{"className":9320},[2839],[1853,9322,9324],{"className":9323},[2718],[1853,9325,9328],{"className":9326,"style":9327},[2722],"height:0.836em;",[1853,9329],{},[1853,9331],{"className":9332},[2386,3948],[1798,9334,9335,9336,9428,9429,2659],{},"如果 ",[1853,9337,9339,9361],{"className":9338},[1860],[1853,9340,9342],{"className":9341},[1864],[1866,9343,9344],{"xmlns":1868},[1871,9345,9346,9358],{},[1874,9347,9348,9354,9356],{},[2763,9349,9350,9352],{},[1877,9351,3512],{},[1877,9353,8124],{},[1881,9355,1883],{},[2621,9357,2779],{},[1916,9359,9360],{"encoding":1918},"\\alpha_R = 2",[1853,9362,9364,9419],{"className":9363,"ariaHidden":1924},[1923],[1853,9365,9367,9370,9410,9413,9416],{"className":9366},[1928],[1853,9368],{"className":9369,"style":5660},[1932],[1853,9371,9373,9376],{"className":9372},[1937],[1853,9374,3512],{"className":9375,"style":3717},[1937,1938],[1853,9377,9379],{"className":9378},[2807],[1853,9380,9382,9402],{"className":9381},[2714,2811],[1853,9383,9385,9399],{"className":9384},[2718],[1853,9386,9388],{"className":9387,"style":3145},[2722],[1853,9389,9390,9393],{"style":6762},[1853,9391],{"className":9392,"style":2825},[2729],[1853,9394,9396],{"className":9395},[2829,2830,2831,2832],[1853,9397,8124],{"className":9398,"style":8256},[1937,1938,2832],[1853,9400,2840],{"className":9401},[2839],[1853,9403,9405],{"className":9404},[2718],[1853,9406,9408],{"className":9407,"style":2847},[2722],[1853,9409],{},[1853,9411],{"className":9412,"style":1944},[1943],[1853,9414,1883],{"className":9415},[1948],[1853,9417],{"className":9418,"style":1944},[1943],[1853,9420,9422,9425],{"className":9421},[1928],[1853,9423],{"className":9424,"style":2655},[1932],[1853,9426,2779],{"className":9427},[1937],"（嫉妒系数），接受当且仅当 ",[1853,9430,9432,9451],{"className":9431},[1860],[1853,9433,9435],{"className":9434},[1864],[1866,9436,9437],{"xmlns":1868},[1871,9438,9439,9448],{},[1874,9440,9441,9443,9445],{},[1877,9442,4980],{},[1881,9444,7752],{},[2621,9446,9447],{},"0.6",[1916,9449,9450],{"encoding":1918},"s \\leq 0.6",[1853,9452,9454,9472],{"className":9453,"ariaHidden":1924},[1923],[1853,9455,9457,9460,9463,9466,9469],{"className":9456},[1928],[1853,9458],{"className":9459,"style":9149},[1932],[1853,9461,4980],{"className":9462},[1937,1938],[1853,9464],{"className":9465,"style":1944},[1943],[1853,9467,7752],{"className":9468},[1948],[1853,9470],{"className":9471,"style":1944},[1943],[1853,9473,9475,9478],{"className":9474},[1928],[1853,9476],{"className":9477,"style":2655},[1932],[1853,9479,9447],{"className":9480},[1937],[1798,9482,9483],{},"提议者（预期回应者会拒绝不公平提议）的最优策略：提议接近临界值（如50%-60%给自己）。",[1798,9485,9486,9489],{},[2152,9487,9488],{},"Bolton & Ockenfels (2000)"," 的ERC模型（平等规避）类似，但关注相对份额而非绝对差距。",[1794,9491,9493],{"id":9492},"四跨期选择-intertemporal-choice","四、跨期选择 (Intertemporal Choice)",[2221,9495,9497],{"id":9496},"_41-指数贴现-vs-双曲贴现","4.1 指数贴现 vs. 双曲贴现",[1798,9499,9500,9503],{},[2152,9501,9502],{},"标准模型","（指数贴现）：",[1853,9505,9507],{"className":9506},[1856],[1853,9508,9510,9616],{"className":9509},[1860],[1853,9511,9513],{"className":9512},[1864],[1866,9514,9515],{"xmlns":1868,"display":1869},[1871,9516,9517,9613],{},[1874,9518,9519,9521,9523,9525,9527,9533,9535,9537,9539,9541,9543,9549,9551,9553,9559,9561,9563,9569,9571,9573,9576,9578,9595,9601,9603,9605,9611],{},[1877,9520,1879],{},[1881,9522,1883],{},[1877,9524,2565],{},[1881,9526,2335],{"stretchy":2334},[2763,9528,9529,9531],{},[1877,9530,2616],{},[2621,9532,2623],{},[1881,9534,2341],{"stretchy":2334},[1881,9536,1890],{},[1877,9538,1893],{},[1877,9540,2565],{},[1881,9542,2335],{"stretchy":2334},[2763,9544,9545,9547],{},[1877,9546,2616],{},[2621,9548,2769],{},[1881,9550,2341],{"stretchy":2334},[1881,9552,1890],{},[3506,9554,9555,9557],{},[1877,9556,1893],{},[2621,9558,2779],{},[1877,9560,2565],{},[1881,9562,2335],{"stretchy":2334},[2763,9564,9565,9567],{},[1877,9566,2616],{},[2621,9568,2779],{},[1881,9570,2341],{"stretchy":2334},[1881,9572,1890],{},[1881,9574,9575],{},"⋯",[1881,9577,1883],{},[9579,9580,9581,9583,9592],"munderover",{},[1881,9582,4627],{},[1874,9584,9585,9588,9590],{},[1877,9586,9587],{},"t",[1881,9589,1883],{},[2621,9591,2623],{},[1877,9593,9594],{"mathvariant":1913},"∞",[3506,9596,9597,9599],{},[1877,9598,1893],{},[1877,9600,9587],{},[1877,9602,2565],{},[1881,9604,2335],{"stretchy":2334},[2763,9606,9607,9609],{},[1877,9608,2616],{},[1877,9610,9587],{},[1881,9612,2341],{"stretchy":2334},[1916,9614,9615],{"encoding":1918},"U = u(c_0) + \\delta u(c_1) + \\delta^2 u(c_2) + \\cdots = \\sum_{t=0}^\\infty \\delta^t u(c_t)",[1853,9617,9619,9637,9701,9768,9864,9883],{"className":9618,"ariaHidden":1924},[1923],[1853,9620,9622,9625,9628,9631,9634],{"className":9621},[1928],[1853,9623],{"className":9624,"style":1933},[1932],[1853,9626,1879],{"className":9627,"style":1939},[1937,1938],[1853,9629],{"className":9630,"style":1944},[1943],[1853,9632,1883],{"className":9633},[1948],[1853,9635],{"className":9636,"style":1944},[1943],[1853,9638,9640,9643,9646,9649,9689,9692,9695,9698],{"className":9639},[1928],[1853,9641],{"className":9642,"style":2371},[1932],[1853,9644,2565],{"className":9645},[1937,1938],[1853,9647,2335],{"className":9648},[2379],[1853,9650,9652,9655],{"className":9651},[1937],[1853,9653,2616],{"className":9654},[1937,1938],[1853,9656,9658],{"className":9657},[2807],[1853,9659,9661,9681],{"className":9660},[2714,2811],[1853,9662,9664,9678],{"className":9663},[2718],[1853,9665,9667],{"className":9666,"style":2818},[2722],[1853,9668,9669,9672],{"style":2821},[1853,9670],{"className":9671,"style":2825},[2729],[1853,9673,9675],{"className":9674},[2829,2830,2831,2832],[1853,9676,2623],{"className":9677},[1937,2832],[1853,9679,2840],{"className":9680},[2839],[1853,9682,9684],{"className":9683},[2718],[1853,9685,9687],{"className":9686,"style":2847},[2722],[1853,9688],{},[1853,9690,2341],{"className":9691},[2386],[1853,9693],{"className":9694,"style":1969},[1943],[1853,9696,1890],{"className":9697},[1973],[1853,9699],{"className":9700,"style":1969},[1943],[1853,9702,9704,9707,9710,9713,9716,9756,9759,9762,9765],{"className":9703},[1928],[1853,9705],{"className":9706,"style":2371},[1932],[1853,9708,1893],{"className":9709,"style":1987},[1937,1938],[1853,9711,2565],{"className":9712},[1937,1938],[1853,9714,2335],{"className":9715},[2379],[1853,9717,9719,9722],{"className":9718},[1937],[1853,9720,2616],{"className":9721},[1937,1938],[1853,9723,9725],{"className":9724},[2807],[1853,9726,9728,9748],{"className":9727},[2714,2811],[1853,9729,9731,9745],{"className":9730},[2718],[1853,9732,9734],{"className":9733,"style":2818},[2722],[1853,9735,9736,9739],{"style":2821},[1853,9737],{"className":9738,"style":2825},[2729],[1853,9740,9742],{"className":9741},[2829,2830,2831,2832],[1853,9743,2769],{"className":9744},[1937,2832],[1853,9746,2840],{"className":9747},[2839],[1853,9749,9751],{"className":9750},[2718],[1853,9752,9754],{"className":9753,"style":2847},[2722],[1853,9755],{},[1853,9757,2341],{"className":9758},[2386],[1853,9760],{"className":9761,"style":1969},[1943],[1853,9763,1890],{"className":9764},[1973],[1853,9766],{"className":9767,"style":1969},[1943],[1853,9769,9771,9775,9806,9809,9812,9852,9855,9858,9861],{"className":9770},[1928],[1853,9772],{"className":9773,"style":9774},[1932],"height:1.1141em;vertical-align:-0.25em;",[1853,9776,9778,9781],{"className":9777},[1937],[1853,9779,1893],{"className":9780,"style":1987},[1937,1938],[1853,9782,9784],{"className":9783},[2807],[1853,9785,9787],{"className":9786},[2714],[1853,9788,9790],{"className":9789},[2718],[1853,9791,9794],{"className":9792,"style":9793},[2722],"height:0.8641em;",[1853,9795,9797,9800],{"style":9796},"top:-3.113em;margin-right:0.05em;",[1853,9798],{"className":9799,"style":2825},[2729],[1853,9801,9803],{"className":9802},[2829,2830,2831,2832],[1853,9804,2779],{"className":9805},[1937,2832],[1853,9807,2565],{"className":9808},[1937,1938],[1853,9810,2335],{"className":9811},[2379],[1853,9813,9815,9818],{"className":9814},[1937],[1853,9816,2616],{"className":9817},[1937,1938],[1853,9819,9821],{"className":9820},[2807],[1853,9822,9824,9844],{"className":9823},[2714,2811],[1853,9825,9827,9841],{"className":9826},[2718],[1853,9828,9830],{"className":9829,"style":2818},[2722],[1853,9831,9832,9835],{"style":2821},[1853,9833],{"className":9834,"style":2825},[2729],[1853,9836,9838],{"className":9837},[2829,2830,2831,2832],[1853,9839,2779],{"className":9840},[1937,2832],[1853,9842,2840],{"className":9843},[2839],[1853,9845,9847],{"className":9846},[2718],[1853,9848,9850],{"className":9849,"style":2847},[2722],[1853,9851],{},[1853,9853,2341],{"className":9854},[2386],[1853,9856],{"className":9857,"style":1969},[1943],[1853,9859,1890],{"className":9860},[1973],[1853,9862],{"className":9863,"style":1969},[1943],[1853,9865,9867,9871,9874,9877,9880],{"className":9866},[1928],[1853,9868],{"className":9869,"style":9870},[1932],"height:0.3669em;",[1853,9872,9575],{"className":9873},[2907],[1853,9875],{"className":9876,"style":1944},[1943],[1853,9878,1883],{"className":9879},[1948],[1853,9881],{"className":9882,"style":1944},[1943],[1853,9884,9886,9890,9958,9961,9991,9994,9997,10038],{"className":9885},[1928],[1853,9887],{"className":9888,"style":9889},[1932],"height:2.9185em;vertical-align:-1.2671em;",[1853,9891,9893],{"className":9892},[3118,4696],[1853,9894,9896,9949],{"className":9895},[2714,2811],[1853,9897,9899,9946],{"className":9898},[2718],[1853,9900,9903,9924,9934],{"className":9901,"style":9902},[2722],"height:1.6514em;",[1853,9904,9906,9909],{"style":9905},"top:-1.8829em;margin-left:0em;",[1853,9907],{"className":9908,"style":4713},[2729],[1853,9910,9912],{"className":9911},[2829,2830,2831,2832],[1853,9913,9915,9918,9921],{"className":9914},[1937,2832],[1853,9916,9587],{"className":9917},[1937,1938,2832],[1853,9919,1883],{"className":9920},[1948,2832],[1853,9922,2623],{"className":9923},[1937,2832],[1853,9925,9926,9929],{"style":4725},[1853,9927],{"className":9928,"style":4713},[2729],[1853,9930,9931],{},[1853,9932,4627],{"className":9933},[3118,4734,4735],[1853,9935,9937,9940],{"style":9936},"top:-4.3em;margin-left:0em;",[1853,9938],{"className":9939,"style":4713},[2729],[1853,9941,9943],{"className":9942},[2829,2830,2831,2832],[1853,9944,9594],{"className":9945},[1937,2832],[1853,9947,2840],{"className":9948},[2839],[1853,9950,9952],{"className":9951},[2718],[1853,9953,9956],{"className":9954,"style":9955},[2722],"height:1.2671em;",[1853,9957],{},[1853,9959],{"className":9960,"style":2857},[1943],[1853,9962,9964,9967],{"className":9963},[1937],[1853,9965,1893],{"className":9966,"style":1987},[1937,1938],[1853,9968,9970],{"className":9969},[2807],[1853,9971,9973],{"className":9972},[2714],[1853,9974,9976],{"className":9975},[2718],[1853,9977,9980],{"className":9978,"style":9979},[2722],"height:0.8436em;",[1853,9981,9982,9985],{"style":9796},[1853,9983],{"className":9984,"style":2825},[2729],[1853,9986,9988],{"className":9987},[2829,2830,2831,2832],[1853,9989,9587],{"className":9990},[1937,1938,2832],[1853,9992,2565],{"className":9993},[1937,1938],[1853,9995,2335],{"className":9996},[2379],[1853,9998,10000,10003],{"className":9999},[1937],[1853,10001,2616],{"className":10002},[1937,1938],[1853,10004,10006],{"className":10005},[2807],[1853,10007,10009,10030],{"className":10008},[2714,2811],[1853,10010,10012,10027],{"className":10011},[2718],[1853,10013,10016],{"className":10014,"style":10015},[2722],"height:0.2806em;",[1853,10017,10018,10021],{"style":2821},[1853,10019],{"className":10020,"style":2825},[2729],[1853,10022,10024],{"className":10023},[2829,2830,2831,2832],[1853,10025,9587],{"className":10026},[1937,1938,2832],[1853,10028,2840],{"className":10029},[2839],[1853,10031,10033],{"className":10032},[2718],[1853,10034,10036],{"className":10035,"style":2847},[2722],[1853,10037],{},[1853,10039,2341],{"className":10040},[2386],[1798,10042,4885,10043,10117,10118,10121],{},[1853,10044,10046,10072],{"className":10045},[1860],[1853,10047,10049],{"className":10048},[1864],[1866,10050,10051],{"xmlns":1868},[1871,10052,10053,10069],{},[1874,10054,10055,10057,10059,10061,10063,10065,10067],{},[1877,10056,1893],{},[1881,10058,3092],{},[1881,10060,2335],{"stretchy":2334},[2621,10062,2623],{},[1881,10064,2772],{"separator":1924},[2621,10066,2769],{},[1881,10068,2341],{"stretchy":2334},[1916,10070,10071],{"encoding":1918},"\\delta \\in (0,1)",[1853,10073,10075,10093],{"className":10074,"ariaHidden":1924},[1923],[1853,10076,10078,10081,10084,10087,10090],{"className":10077},[1928],[1853,10079],{"className":10080,"style":3997},[1932],[1853,10082,1893],{"className":10083,"style":1987},[1937,1938],[1853,10085],{"className":10086,"style":1944},[1943],[1853,10088,3092],{"className":10089},[1948],[1853,10091],{"className":10092,"style":1944},[1943],[1853,10094,10096,10099,10102,10105,10108,10111,10114],{"className":10095},[1928],[1853,10097],{"className":10098,"style":2371},[1932],[1853,10100,2335],{"className":10101},[2379],[1853,10103,2623],{"className":10104},[1937],[1853,10106,2772],{"className":10107},[2853],[1853,10109],{"className":10110,"style":2857},[1943],[1853,10112,2769],{"className":10113},[1937],[1853,10115,2341],{"className":10116},[2386]," 是贴现因子，",[2152,10119,10120],{},"时间一致性","成立。",[1798,10123,10124,10127],{},[2152,10125,10126],{},"双曲贴现 (Hyperbolic Discounting)","（Laibson 1997）：",[1853,10129,10131],{"className":10130},[1856],[1853,10132,10134,10256],{"className":10133},[1860],[1853,10135,10137],{"className":10136},[1864],[1866,10138,10139],{"xmlns":1868,"display":1869},[1871,10140,10141,10253],{},[1874,10142,10143,10145,10147,10149,10151,10157,10159,10161,10163,10165,10167,10169,10175,10177,10179,10181,10187,10189,10191,10197,10199,10201,10203,10205,10207,10209,10215,10217,10219,10221,10235,10241,10243,10245,10251],{},[1877,10144,1879],{},[1881,10146,1883],{},[1877,10148,2565],{},[1881,10150,2335],{"stretchy":2334},[2763,10152,10153,10155],{},[1877,10154,2616],{},[2621,10156,2623],{},[1881,10158,2341],{"stretchy":2334},[1881,10160,1890],{},[1877,10162,3571],{},[1877,10164,1893],{},[1877,10166,2565],{},[1881,10168,2335],{"stretchy":2334},[2763,10170,10171,10173],{},[1877,10172,2616],{},[2621,10174,2769],{},[1881,10176,2341],{"stretchy":2334},[1881,10178,1890],{},[1877,10180,3571],{},[3506,10182,10183,10185],{},[1877,10184,1893],{},[2621,10186,2779],{},[1877,10188,2565],{},[1881,10190,2335],{"stretchy":2334},[2763,10192,10193,10195],{},[1877,10194,2616],{},[2621,10196,2779],{},[1881,10198,2341],{"stretchy":2334},[1881,10200,1890],{},[1881,10202,9575],{},[1881,10204,1883],{},[1877,10206,2565],{},[1881,10208,2335],{"stretchy":2334},[2763,10210,10211,10213],{},[1877,10212,2616],{},[2621,10214,2623],{},[1881,10216,2341],{"stretchy":2334},[1881,10218,1890],{},[1877,10220,3571],{},[9579,10222,10223,10225,10233],{},[1881,10224,4627],{},[1874,10226,10227,10229,10231],{},[1877,10228,9587],{},[1881,10230,1883],{},[2621,10232,2769],{},[1877,10234,9594],{"mathvariant":1913},[3506,10236,10237,10239],{},[1877,10238,1893],{},[1877,10240,9587],{},[1877,10242,2565],{},[1881,10244,2335],{"stretchy":2334},[2763,10246,10247,10249],{},[1877,10248,2616],{},[1877,10250,9587],{},[1881,10252,2341],{"stretchy":2334},[1916,10254,10255],{"encoding":1918},"U = u(c_0) + \\beta \\delta u(c_1) + \\beta \\delta^2 u(c_2) + \\cdots = u(c_0) + \\beta \\sum_{t=1}^\\infty \\delta^t u(c_t)",[1853,10257,10259,10277,10341,10411,10507,10525,10589],{"className":10258,"ariaHidden":1924},[1923],[1853,10260,10262,10265,10268,10271,10274],{"className":10261},[1928],[1853,10263],{"className":10264,"style":1933},[1932],[1853,10266,1879],{"className":10267,"style":1939},[1937,1938],[1853,10269],{"className":10270,"style":1944},[1943],[1853,10272,1883],{"className":10273},[1948],[1853,10275],{"className":10276,"style":1944},[1943],[1853,10278,10280,10283,10286,10289,10329,10332,10335,10338],{"className":10279},[1928],[1853,10281],{"className":10282,"style":2371},[1932],[1853,10284,2565],{"className":10285},[1937,1938],[1853,10287,2335],{"className":10288},[2379],[1853,10290,10292,10295],{"className":10291},[1937],[1853,10293,2616],{"className":10294},[1937,1938],[1853,10296,10298],{"className":10297},[2807],[1853,10299,10301,10321],{"className":10300},[2714,2811],[1853,10302,10304,10318],{"className":10303},[2718],[1853,10305,10307],{"className":10306,"style":2818},[2722],[1853,10308,10309,10312],{"style":2821},[1853,10310],{"className":10311,"style":2825},[2729],[1853,10313,10315],{"className":10314},[2829,2830,2831,2832],[1853,10316,2623],{"className":10317},[1937,2832],[1853,10319,2840],{"className":10320},[2839],[1853,10322,10324],{"className":10323},[2718],[1853,10325,10327],{"className":10326,"style":2847},[2722],[1853,10328],{},[1853,10330,2341],{"className":10331},[2386],[1853,10333],{"className":10334,"style":1969},[1943],[1853,10336,1890],{"className":10337},[1973],[1853,10339],{"className":10340,"style":1969},[1943],[1853,10342,10344,10347,10350,10353,10356,10359,10399,10402,10405,10408],{"className":10343},[1928],[1853,10345],{"className":10346,"style":2371},[1932],[1853,10348,3571],{"className":10349,"style":3772},[1937,1938],[1853,10351,1893],{"className":10352,"style":1987},[1937,1938],[1853,10354,2565],{"className":10355},[1937,1938],[1853,10357,2335],{"className":10358},[2379],[1853,10360,10362,10365],{"className":10361},[1937],[1853,10363,2616],{"className":10364},[1937,1938],[1853,10366,10368],{"className":10367},[2807],[1853,10369,10371,10391],{"className":10370},[2714,2811],[1853,10372,10374,10388],{"className":10373},[2718],[1853,10375,10377],{"className":10376,"style":2818},[2722],[1853,10378,10379,10382],{"style":2821},[1853,10380],{"className":10381,"style":2825},[2729],[1853,10383,10385],{"className":10384},[2829,2830,2831,2832],[1853,10386,2769],{"className":10387},[1937,2832],[1853,10389,2840],{"className":10390},[2839],[1853,10392,10394],{"className":10393},[2718],[1853,10395,10397],{"className":10396,"style":2847},[2722],[1853,10398],{},[1853,10400,2341],{"className":10401},[2386],[1853,10403],{"className":10404,"style":1969},[1943],[1853,10406,1890],{"className":10407},[1973],[1853,10409],{"className":10410,"style":1969},[1943],[1853,10412,10414,10417,10420,10449,10452,10455,10495,10498,10501,10504],{"className":10413},[1928],[1853,10415],{"className":10416,"style":9774},[1932],[1853,10418,3571],{"className":10419,"style":3772},[1937,1938],[1853,10421,10423,10426],{"className":10422},[1937],[1853,10424,1893],{"className":10425,"style":1987},[1937,1938],[1853,10427,10429],{"className":10428},[2807],[1853,10430,10432],{"className":10431},[2714],[1853,10433,10435],{"className":10434},[2718],[1853,10436,10438],{"className":10437,"style":9793},[2722],[1853,10439,10440,10443],{"style":9796},[1853,10441],{"className":10442,"style":2825},[2729],[1853,10444,10446],{"className":10445},[2829,2830,2831,2832],[1853,10447,2779],{"className":10448},[1937,2832],[1853,10450,2565],{"className":10451},[1937,1938],[1853,10453,2335],{"className":10454},[2379],[1853,10456,10458,10461],{"className":10457},[1937],[1853,10459,2616],{"className":10460},[1937,1938],[1853,10462,10464],{"className":10463},[2807],[1853,10465,10467,10487],{"className":10466},[2714,2811],[1853,10468,10470,10484],{"className":10469},[2718],[1853,10471,10473],{"className":10472,"style":2818},[2722],[1853,10474,10475,10478],{"style":2821},[1853,10476],{"className":10477,"style":2825},[2729],[1853,10479,10481],{"className":10480},[2829,2830,2831,2832],[1853,10482,2779],{"className":10483},[1937,2832],[1853,10485,2840],{"className":10486},[2839],[1853,10488,10490],{"className":10489},[2718],[1853,10491,10493],{"className":10492,"style":2847},[2722],[1853,10494],{},[1853,10496,2341],{"className":10497},[2386],[1853,10499],{"className":10500,"style":1969},[1943],[1853,10502,1890],{"className":10503},[1973],[1853,10505],{"className":10506,"style":1969},[1943],[1853,10508,10510,10513,10516,10519,10522],{"className":10509},[1928],[1853,10511],{"className":10512,"style":9870},[1932],[1853,10514,9575],{"className":10515},[2907],[1853,10517],{"className":10518,"style":1944},[1943],[1853,10520,1883],{"className":10521},[1948],[1853,10523],{"className":10524,"style":1944},[1943],[1853,10526,10528,10531,10534,10537,10577,10580,10583,10586],{"className":10527},[1928],[1853,10529],{"className":10530,"style":2371},[1932],[1853,10532,2565],{"className":10533},[1937,1938],[1853,10535,2335],{"className":10536},[2379],[1853,10538,10540,10543],{"className":10539},[1937],[1853,10541,2616],{"className":10542},[1937,1938],[1853,10544,10546],{"className":10545},[2807],[1853,10547,10549,10569],{"className":10548},[2714,2811],[1853,10550,10552,10566],{"className":10551},[2718],[1853,10553,10555],{"className":10554,"style":2818},[2722],[1853,10556,10557,10560],{"style":2821},[1853,10558],{"className":10559,"style":2825},[2729],[1853,10561,10563],{"className":10562},[2829,2830,2831,2832],[1853,10564,2623],{"className":10565},[1937,2832],[1853,10567,2840],{"className":10568},[2839],[1853,10570,10572],{"className":10571},[2718],[1853,10573,10575],{"className":10574,"style":2847},[2722],[1853,10576],{},[1853,10578,2341],{"className":10579},[2386],[1853,10581],{"className":10582,"style":1969},[1943],[1853,10584,1890],{"className":10585},[1973],[1853,10587],{"className":10588,"style":1969},[1943],[1853,10590,10592,10595,10598,10601,10665,10668,10697,10700,10703,10743],{"className":10591},[1928],[1853,10593],{"className":10594,"style":9889},[1932],[1853,10596,3571],{"className":10597,"style":3772},[1937,1938],[1853,10599],{"className":10600,"style":2857},[1943],[1853,10602,10604],{"className":10603},[3118,4696],[1853,10605,10607,10657],{"className":10606},[2714,2811],[1853,10608,10610,10654],{"className":10609},[2718],[1853,10611,10613,10633,10643],{"className":10612,"style":9902},[2722],[1853,10614,10615,10618],{"style":9905},[1853,10616],{"className":10617,"style":4713},[2729],[1853,10619,10621],{"className":10620},[2829,2830,2831,2832],[1853,10622,10624,10627,10630],{"className":10623},[1937,2832],[1853,10625,9587],{"className":10626},[1937,1938,2832],[1853,10628,1883],{"className":10629},[1948,2832],[1853,10631,2769],{"className":10632},[1937,2832],[1853,10634,10635,10638],{"style":4725},[1853,10636],{"className":10637,"style":4713},[2729],[1853,10639,10640],{},[1853,10641,4627],{"className":10642},[3118,4734,4735],[1853,10644,10645,10648],{"style":9936},[1853,10646],{"className":10647,"style":4713},[2729],[1853,10649,10651],{"className":10650},[2829,2830,2831,2832],[1853,10652,9594],{"className":10653},[1937,2832],[1853,10655,2840],{"className":10656},[2839],[1853,10658,10660],{"className":10659},[2718],[1853,10661,10663],{"className":10662,"style":9955},[2722],[1853,10664],{},[1853,10666],{"className":10667,"style":2857},[1943],[1853,10669,10671,10674],{"className":10670},[1937],[1853,10672,1893],{"className":10673,"style":1987},[1937,1938],[1853,10675,10677],{"className":10676},[2807],[1853,10678,10680],{"className":10679},[2714],[1853,10681,10683],{"className":10682},[2718],[1853,10684,10686],{"className":10685,"style":9979},[2722],[1853,10687,10688,10691],{"style":9796},[1853,10689],{"className":10690,"style":2825},[2729],[1853,10692,10694],{"className":10693},[2829,2830,2831,2832],[1853,10695,9587],{"className":10696},[1937,1938,2832],[1853,10698,2565],{"className":10699},[1937,1938],[1853,10701,2335],{"className":10702},[2379],[1853,10704,10706,10709],{"className":10705},[1937],[1853,10707,2616],{"className":10708},[1937,1938],[1853,10710,10712],{"className":10711},[2807],[1853,10713,10715,10735],{"className":10714},[2714,2811],[1853,10716,10718,10732],{"className":10717},[2718],[1853,10719,10721],{"className":10720,"style":10015},[2722],[1853,10722,10723,10726],{"style":2821},[1853,10724],{"className":10725,"style":2825},[2729],[1853,10727,10729],{"className":10728},[2829,2830,2831,2832],[1853,10730,9587],{"className":10731},[1937,1938,2832],[1853,10733,2840],{"className":10734},[2839],[1853,10736,10738],{"className":10737},[2718],[1853,10739,10741],{"className":10740,"style":2847},[2722],[1853,10742],{},[1853,10744,2341],{"className":10745},[2386],[1798,10747,4885,10748,10799,10800,2659],{},[1853,10749,10751,10769],{"className":10750},[1860],[1853,10752,10754],{"className":10753},[1864],[1866,10755,10756],{"xmlns":1868},[1871,10757,10758,10766],{},[1874,10759,10760,10762,10764],{},[1877,10761,3571],{},[1881,10763,3536],{},[2621,10765,2769],{},[1916,10767,10768],{"encoding":1918},"\\beta \u003C 1",[1853,10770,10772,10790],{"className":10771,"ariaHidden":1924},[1923],[1853,10773,10775,10778,10781,10784,10787],{"className":10774},[1928],[1853,10776],{"className":10777,"style":1958},[1932],[1853,10779,3571],{"className":10780,"style":3772},[1937,1938],[1853,10782],{"className":10783,"style":1944},[1943],[1853,10785,3536],{"className":10786},[1948],[1853,10788],{"className":10789,"style":1944},[1943],[1853,10791,10793,10796],{"className":10792},[1928],[1853,10794],{"className":10795,"style":2655},[1932],[1853,10797,2769],{"className":10798},[1937]," 是",[2152,10801,10802],{},"现时偏好参数",[1798,10804,10805,2155],{},[2152,10806,10807],{},"关键区别",[1805,10809,10810,11211],{},[1808,10811,10812,10813,10865,10866,10917,10918,10969,10970],{},"从 ",[1853,10814,10816,10834],{"className":10815},[1860],[1853,10817,10819],{"className":10818},[1864],[1866,10820,10821],{"xmlns":1868},[1871,10822,10823,10831],{},[1874,10824,10825,10827,10829],{},[1877,10826,9587],{},[1881,10828,1883],{},[2621,10830,2623],{},[1916,10832,10833],{"encoding":1918},"t=0",[1853,10835,10837,10856],{"className":10836,"ariaHidden":1924},[1923],[1853,10838,10840,10844,10847,10850,10853],{"className":10839},[1928],[1853,10841],{"className":10842,"style":10843},[1932],"height:0.6151em;",[1853,10845,9587],{"className":10846},[1937,1938],[1853,10848],{"className":10849,"style":1944},[1943],[1853,10851,1883],{"className":10852},[1948],[1853,10854],{"className":10855,"style":1944},[1943],[1853,10857,10859,10862],{"className":10858},[1928],[1853,10860],{"className":10861,"style":2655},[1932],[1853,10863,2623],{"className":10864},[1937]," 看，",[1853,10867,10869,10887],{"className":10868},[1860],[1853,10870,10872],{"className":10871},[1864],[1866,10873,10874],{"xmlns":1868},[1871,10875,10876,10884],{},[1874,10877,10878,10880,10882],{},[1877,10879,9587],{},[1881,10881,1883],{},[2621,10883,2769],{},[1916,10885,10886],{"encoding":1918},"t=1",[1853,10888,10890,10908],{"className":10889,"ariaHidden":1924},[1923],[1853,10891,10893,10896,10899,10902,10905],{"className":10892},[1928],[1853,10894],{"className":10895,"style":10843},[1932],[1853,10897,9587],{"className":10898},[1937,1938],[1853,10900],{"className":10901,"style":1944},[1943],[1853,10903,1883],{"className":10904},[1948],[1853,10906],{"className":10907,"style":1944},[1943],[1853,10909,10911,10914],{"className":10910},[1928],[1853,10912],{"className":10913,"style":2655},[1932],[1853,10915,2769],{"className":10916},[1937]," 和 ",[1853,10919,10921,10939],{"className":10920},[1860],[1853,10922,10924],{"className":10923},[1864],[1866,10925,10926],{"xmlns":1868},[1871,10927,10928,10936],{},[1874,10929,10930,10932,10934],{},[1877,10931,9587],{},[1881,10933,1883],{},[2621,10935,2779],{},[1916,10937,10938],{"encoding":1918},"t=2",[1853,10940,10942,10960],{"className":10941,"ariaHidden":1924},[1923],[1853,10943,10945,10948,10951,10954,10957],{"className":10944},[1928],[1853,10946],{"className":10947,"style":10843},[1932],[1853,10949,9587],{"className":10950},[1937,1938],[1853,10952],{"className":10953,"style":1944},[1943],[1853,10955,1883],{"className":10956},[1948],[1853,10958],{"className":10959,"style":1944},[1943],[1853,10961,10963,10966],{"className":10962},[1928],[1853,10964],{"className":10965,"style":2655},[1932],[1853,10967,2779],{"className":10968},[1937]," 的效用比：",[1853,10971,10973,11011],{"className":10972},[1860],[1853,10974,10976],{"className":10975},[1864],[1866,10977,10978],{"xmlns":1868},[1871,10979,10980,11008],{},[1874,10981,10982,11000,11002],{},[5627,10983,10984,10990],{},[1874,10985,10986,10988],{},[1877,10987,3571],{},[1877,10989,1893],{},[1874,10991,10992,10994],{},[1877,10993,3571],{},[3506,10995,10996,10998],{},[1877,10997,1893],{},[2621,10999,2779],{},[1881,11001,1883],{},[5627,11003,11004,11006],{},[2621,11005,2769],{},[1877,11007,1893],{},[1916,11009,11010],{"encoding":1918},"\\frac{\\beta\\delta}{\\beta\\delta^2} = \\frac{1}{\\delta}",[1853,11012,11014,11135],{"className":11013,"ariaHidden":1924},[1923],[1853,11015,11017,11021,11126,11129,11132],{"className":11016},[1928],[1853,11018],{"className":11019,"style":11020},[1932],"height:1.4133em;vertical-align:-0.4811em;",[1853,11022,11024,11027,11123],{"className":11023},[1937],[1853,11025],{"className":11026},[2379,3948],[1853,11028,11030],{"className":11029},[5627],[1853,11031,11033,11114],{"className":11032},[2714,2811],[1853,11034,11036,11111],{"className":11035},[2718],[1853,11037,11040,11085,11093],{"className":11038,"style":11039},[2722],"height:0.9322em;",[1853,11041,11042,11045],{"style":5813},[1853,11043],{"className":11044,"style":2730},[2729],[1853,11046,11048],{"className":11047},[2829,2830,2831,2832],[1853,11049,11051,11054],{"className":11050},[1937,2832],[1853,11052,3571],{"className":11053,"style":3772},[1937,1938,2832],[1853,11055,11057,11060],{"className":11056},[1937,2832],[1853,11058,1893],{"className":11059,"style":1987},[1937,1938,2832],[1853,11061,11063],{"className":11062},[2807],[1853,11064,11066],{"className":11065},[2714],[1853,11067,11069],{"className":11068},[2718],[1853,11070,11073],{"className":11071,"style":11072},[2722],"height:0.7463em;",[1853,11074,11076,11079],{"style":11075},"top:-2.786em;margin-right:0.0714em;",[1853,11077],{"className":11078,"style":5883},[2729],[1853,11080,11082],{"className":11081},[2829,5887,5888,2832],[1853,11083,2779],{"className":11084},[1937,2832],[1853,11086,11087,11090],{"style":5828},[1853,11088],{"className":11089,"style":2730},[2729],[1853,11091],{"className":11092,"style":5836},[5835],[1853,11094,11096,11099],{"style":11095},"top:-3.4461em;",[1853,11097],{"className":11098,"style":2730},[2729],[1853,11100,11102],{"className":11101},[2829,2830,2831,2832],[1853,11103,11105,11108],{"className":11104},[1937,2832],[1853,11106,3571],{"className":11107,"style":3772},[1937,1938,2832],[1853,11109,1893],{"className":11110,"style":1987},[1937,1938,2832],[1853,11112,2840],{"className":11113},[2839],[1853,11115,11117],{"className":11116},[2718],[1853,11118,11121],{"className":11119,"style":11120},[2722],"height:0.4811em;",[1853,11122],{},[1853,11124],{"className":11125},[2386,3948],[1853,11127],{"className":11128,"style":1944},[1943],[1853,11130,1883],{"className":11131},[1948],[1853,11133],{"className":11134,"style":1944},[1943],[1853,11136,11138,11142],{"className":11137},[1928],[1853,11139],{"className":11140,"style":11141},[1932],"height:1.1901em;vertical-align:-0.345em;",[1853,11143,11145,11148,11208],{"className":11144},[1937],[1853,11146],{"className":11147},[2379,3948],[1853,11149,11151],{"className":11150},[5627],[1853,11152,11154,11200],{"className":11153},[2714,2811],[1853,11155,11157,11197],{"className":11156},[2718],[1853,11158,11161,11175,11183],{"className":11159,"style":11160},[2722],"height:0.8451em;",[1853,11162,11163,11166],{"style":5813},[1853,11164],{"className":11165,"style":2730},[2729],[1853,11167,11169],{"className":11168},[2829,2830,2831,2832],[1853,11170,11172],{"className":11171},[1937,2832],[1853,11173,1893],{"className":11174,"style":1987},[1937,1938,2832],[1853,11176,11177,11180],{"style":5828},[1853,11178],{"className":11179,"style":2730},[2729],[1853,11181],{"className":11182,"style":5836},[5835],[1853,11184,11185,11188],{"style":6205},[1853,11186],{"className":11187,"style":2730},[2729],[1853,11189,11191],{"className":11190},[2829,2830,2831,2832],[1853,11192,11194],{"className":11193},[1937,2832],[1853,11195,2769],{"className":11196},[1937,2832],[1853,11198,2840],{"className":11199},[2839],[1853,11201,11203],{"className":11202},[2718],[1853,11204,11206],{"className":11205,"style":5960},[2722],[1853,11207],{},[1853,11209],{"className":11210},[2386,3948],[1808,11212,10812,11213,11263,11264,10917,11314,10969,11364,11470],{},[1853,11214,11216,11233],{"className":11215},[1860],[1853,11217,11219],{"className":11218},[1864],[1866,11220,11221],{"xmlns":1868},[1871,11222,11223,11231],{},[1874,11224,11225,11227,11229],{},[1877,11226,9587],{},[1881,11228,1883],{},[2621,11230,2769],{},[1916,11232,10886],{"encoding":1918},[1853,11234,11236,11254],{"className":11235,"ariaHidden":1924},[1923],[1853,11237,11239,11242,11245,11248,11251],{"className":11238},[1928],[1853,11240],{"className":11241,"style":10843},[1932],[1853,11243,9587],{"className":11244},[1937,1938],[1853,11246],{"className":11247,"style":1944},[1943],[1853,11249,1883],{"className":11250},[1948],[1853,11252],{"className":11253,"style":1944},[1943],[1853,11255,11257,11260],{"className":11256},[1928],[1853,11258],{"className":11259,"style":2655},[1932],[1853,11261,2769],{"className":11262},[1937]," 看（重新优化），",[1853,11265,11267,11284],{"className":11266},[1860],[1853,11268,11270],{"className":11269},[1864],[1866,11271,11272],{"xmlns":1868},[1871,11273,11274,11282],{},[1874,11275,11276,11278,11280],{},[1877,11277,9587],{},[1881,11279,1883],{},[2621,11281,2769],{},[1916,11283,10886],{"encoding":1918},[1853,11285,11287,11305],{"className":11286,"ariaHidden":1924},[1923],[1853,11288,11290,11293,11296,11299,11302],{"className":11289},[1928],[1853,11291],{"className":11292,"style":10843},[1932],[1853,11294,9587],{"className":11295},[1937,1938],[1853,11297],{"className":11298,"style":1944},[1943],[1853,11300,1883],{"className":11301},[1948],[1853,11303],{"className":11304,"style":1944},[1943],[1853,11306,11308,11311],{"className":11307},[1928],[1853,11309],{"className":11310,"style":2655},[1932],[1853,11312,2769],{"className":11313},[1937],[1853,11315,11317,11334],{"className":11316},[1860],[1853,11318,11320],{"className":11319},[1864],[1866,11321,11322],{"xmlns":1868},[1871,11323,11324,11332],{},[1874,11325,11326,11328,11330],{},[1877,11327,9587],{},[1881,11329,1883],{},[2621,11331,2779],{},[1916,11333,10938],{"encoding":1918},[1853,11335,11337,11355],{"className":11336,"ariaHidden":1924},[1923],[1853,11338,11340,11343,11346,11349,11352],{"className":11339},[1928],[1853,11341],{"className":11342,"style":10843},[1932],[1853,11344,9587],{"className":11345},[1937,1938],[1853,11347],{"className":11348,"style":1944},[1943],[1853,11350,1883],{"className":11351},[1948],[1853,11353],{"className":11354,"style":1944},[1943],[1853,11356,11358,11361],{"className":11357},[1928],[1853,11359],{"className":11360,"style":2655},[1932],[1853,11362,2779],{"className":11363},[1937],[1853,11365,11367,11389],{"className":11366},[1860],[1853,11368,11370],{"className":11369},[1864],[1866,11371,11372],{"xmlns":1868},[1871,11373,11374,11386],{},[1874,11375,11376],{},[5627,11377,11378,11380],{},[2621,11379,2769],{},[1874,11381,11382,11384],{},[1877,11383,3571],{},[1877,11385,1893],{},[1916,11387,11388],{"encoding":1918},"\\frac{1}{\\beta\\delta}",[1853,11390,11392],{"className":11391,"ariaHidden":1924},[1923],[1853,11393,11395,11399],{"className":11394},[1928],[1853,11396],{"className":11397,"style":11398},[1932],"height:1.3262em;vertical-align:-0.4811em;",[1853,11400,11402,11405,11467],{"className":11401},[1937],[1853,11403],{"className":11404},[2379,3948],[1853,11406,11408],{"className":11407},[5627],[1853,11409,11411,11459],{"className":11410},[2714,2811],[1853,11412,11414,11456],{"className":11413},[2718],[1853,11415,11417,11434,11442],{"className":11416,"style":11160},[2722],[1853,11418,11419,11422],{"style":5813},[1853,11420],{"className":11421,"style":2730},[2729],[1853,11423,11425],{"className":11424},[2829,2830,2831,2832],[1853,11426,11428,11431],{"className":11427},[1937,2832],[1853,11429,3571],{"className":11430,"style":3772},[1937,1938,2832],[1853,11432,1893],{"className":11433,"style":1987},[1937,1938,2832],[1853,11435,11436,11439],{"style":5828},[1853,11437],{"className":11438,"style":2730},[2729],[1853,11440],{"className":11441,"style":5836},[5835],[1853,11443,11444,11447],{"style":6205},[1853,11445],{"className":11446,"style":2730},[2729],[1853,11448,11450],{"className":11449},[2829,2830,2831,2832],[1853,11451,11453],{"className":11452},[1937,2832],[1853,11454,2769],{"className":11455},[1937,2832],[1853,11457,2840],{"className":11458},[2839],[1853,11460,11462],{"className":11461},[2718],[1853,11463,11465],{"className":11464,"style":11120},[2722],[1853,11466],{},[1853,11468],{"className":11469},[2386,3948],"（不一致！）",[1798,11472,11473,2155],{},[2152,11474,2303],{},[1805,11476,11477,11480],{},[1808,11478,11479],{},"今天：选择\"明天吃苹果\"vs.\"后天吃两个苹果\" → 选后者（有耐心）",[1808,11481,11482],{},"明天重新选择：选\"今天吃一个\"vs.\"明天吃两个\" → 选前者（没耐心）",[1798,11484,11485,11486,2659],{},"这是",[2152,11487,11488],{},"动态不一致 (Time Inconsistency)",[2221,11490,11492],{"id":11491},"_42-承诺机制-commitment-devices","4.2 承诺机制 (Commitment Devices)",[1798,11494,11495,11498,11499,2155],{},[2152,11496,11497],{},"理性的双曲贴现者","（sophisticated）知道自己未来会缺乏自制力，因此寻求",[2152,11500,11501],{},"承诺",[1798,11503,11504,2155],{},[2152,11505,2303],{},[1805,11507,11508,11511,11514],{},[1808,11509,11510],{},"自动储蓄计划（锁定资金）",[1808,11512,11513],{},"戒烟承诺（公开宣告、赌约）",[1808,11515,11516],{},"Odysseus绑在桅杆上（抵御海妖歌声）",[1798,11518,11519,2155],{},[2152,11520,11521],{},"实证证据",[1805,11523,11524],{},[1808,11525,11526],{},"Ashraf, Karlan & Yin (2006)：菲律宾银行提供\"承诺储蓄账户\"（锁定到目标日期或金额），增加了储蓄28%",[2221,11528,11530],{"id":11529},"_43-拖延症-procrastination","4.3 拖延症 (Procrastination)",[1798,11532,11533,11536],{},[2152,11534,11535],{},"O'Donoghue & Rabin (1999)","：区分两类双曲贴现者",[2157,11538,11539,11545],{},[1808,11540,11541,11544],{},[2152,11542,11543],{},"Sophisticated","：知道自己未来会拖延，提前采取对策",[1808,11546,11547,11550],{},[2152,11548,11549],{},"Naive","：以为自己未来会有自制力，结果一再拖延",[1798,11552,11553,11555],{},[2152,11554,2303],{},"（健身房会员）：",[1805,11557,11558,11561,11645],{},[1808,11559,11560],{},"Naive认为\"我会经常去\"，购买年卡",[1808,11562,11563,11564,11644],{},"实际很少去，年卡单次成本高达",[1853,11565,11567,11599],{"className":11566},[1860],[1853,11568,11570],{"className":11569},[1864],[1866,11571,11572],{"xmlns":1868},[1871,11573,11574,11596],{},[1874,11575,11576,11579,11581,11584,11587,11589,11591,11593],{},[2621,11577,11578],{},"15",[1881,11580,1902],{},[2621,11582,11583],{},"20",[1885,11585,11586],{},"（",[1877,11588,3427],{},[1877,11590,4980],{},[1877,11592,1914],{"mathvariant":1913},[1885,11594,11595],{},"单次",[1916,11597,11598],{"encoding":1918},"15-20（vs. 单次",[1853,11600,11602,11620],{"className":11601,"ariaHidden":1924},[1923],[1853,11603,11605,11608,11611,11614,11617],{"className":11604},[1928],[1853,11606],{"className":11607,"style":4176},[1932],[1853,11609,11578],{"className":11610},[1937],[1853,11612],{"className":11613,"style":1969},[1943],[1853,11615,1902],{"className":11616},[1973],[1853,11618],{"className":11619,"style":1969},[1943],[1853,11621,11623,11626,11629,11632,11635,11638,11641],{"className":11622},[1928],[1853,11624],{"className":11625,"style":1933},[1932],[1853,11627,11583],{"className":11628},[1937],[1853,11630,11586],{"className":11631},[1937,3865],[1853,11633,3427],{"className":11634,"style":3449},[1937,1938],[1853,11636,4980],{"className":11637},[1937,1938],[1853,11639,1914],{"className":11640},[1937],[1853,11642,11595],{"className":11643},[1937,3865],"10）",[1808,11646,11647],{},"健身房利用这种偏差定价",[1794,11649,11651],{"id":11650},"五实验经济学方法-experimental-methods","五、实验经济学方法 (Experimental Methods)",[2221,11653,11655],{"id":11654},"_51-实验设计原则","5.1 实验设计原则",[1798,11657,11658,11661],{},[2152,11659,11660],{},"Vernon Smith (1982)"," 提出实验经济学的核心原则：",[2157,11663,11664,11670,11676,11682],{},[1808,11665,11666,11669],{},[2152,11667,11668],{},"显著性 (Salience)","：奖励与表现挂钩",[1808,11671,11672,11675],{},[2152,11673,11674],{},"支配性 (Dominance)","：奖励足够大，使其他动机（如无聊、助人）不重要",[1808,11677,11678,11681],{},[2152,11679,11680],{},"隐私性 (Privacy)","：个人决策不被他人观察（避免羞耻、炫耀）",[1808,11683,11684,11687],{},[2152,11685,11686],{},"去欺骗 (No Deception)","：不误导参与者（建立信任）",[2221,11689,11691],{"id":11690},"_52-实验室实验-vs-田野实验","5.2 实验室实验 vs. 田野实验",[2064,11693,11694,11707],{},[2067,11695,11696],{},[2070,11697,11698,11701,11704],{},[2073,11699,11700],{},"维度",[2073,11702,11703],{},"实验室实验",[2073,11705,11706],{},"田野实验",[2083,11708,11709,11722,11735,11748,11761],{},[2070,11710,11711,11716,11719],{},[2088,11712,11713],{},[2152,11714,11715],{},"控制",[2088,11717,11718],{},"高（控制变量）",[2088,11720,11721],{},"低（真实环境复杂）",[2070,11723,11724,11729,11732],{},[2088,11725,11726],{},[2152,11727,11728],{},"内部效度",[2088,11730,11731],{},"高（因果推断清晰）",[2088,11733,11734],{},"中",[2070,11736,11737,11742,11745],{},[2088,11738,11739],{},[2152,11740,11741],{},"外部效度",[2088,11743,11744],{},"低（人工环境）",[2088,11746,11747],{},"高（真实决策）",[2070,11749,11750,11755,11758],{},[2088,11751,11752],{},[2152,11753,11754],{},"成本",[2088,11756,11757],{},"低",[2088,11759,11760],{},"高",[2070,11762,11763,11767,11770],{},[2088,11764,11765],{},[2152,11766,2303],{},[2088,11768,11769],{},"最后通牒博弈",[2088,11771,11772],{},"eBay拍卖、Uber定价实验",[2221,11774,11776],{"id":11775},"_53-经典实验案例","5.3 经典实验案例",[2292,11778,11780],{"id":11779},"_1-双盲拍卖市场smith-1962","(1) 双盲拍卖市场（Smith 1962）",[1798,11782,11783,2155],{},[2152,11784,5271],{},[1805,11786,11787,11790,11793],{},[1808,11788,11789],{},"买家有私人估值，卖家有私人成本",[1808,11791,11792],{},"双向喊价，直到无交易",[1808,11794,11795],{},"记录成交价格和数量",[1798,11797,11798,11801],{},[2152,11799,11800],{},"理论预测","：竞争均衡价格",[1798,11803,11804,11807],{},[2152,11805,11806],{},"结果","：即使只有少数参与者（5买家 + 5卖家），几轮后价格收敛到均衡",[1798,11809,11810,11813,11814,11817],{},[2152,11811,11812],{},"意义","：市场机制的",[2152,11815,11816],{},"鲁棒性","，即使参与者非完全理性",[2292,11819,11821],{"id":11820},"_2-理性泡沫实验smith-suchanek-williams-1988","(2) 理性泡沫实验（Smith, Suchanek & Williams 1988）",[1798,11823,11824,2155],{},[2152,11825,5271],{},[1805,11827,11828,11831,11834],{},[1808,11829,11830],{},"交易一种资产，存续15期",[1808,11832,11833],{},"每期以确定概率支付红利（期望值已知）",[1808,11835,11836],{},"理性价值随时间递减（因为剩余红利减少）",[1798,11838,11839,11841],{},[2152,11840,11800],{},"：价格沿基本价值递减",[1798,11843,11844,2155],{},[2152,11845,11806],{},[1805,11847,11848,11855,11858],{},[1808,11849,11850,11851,11854],{},"价格先",[2152,11852,11853],{},"高于","基本价值（泡沫）",[1808,11856,11857],{},"然后崩溃",[1808,11859,11860],{},"即使参与者是MBA学生、重复实验，泡沫仍出现",[1798,11862,11863,2155],{},[2152,11864,5012],{},[1805,11866,11867,11870,11872],{},[1808,11868,11869],{},"投机动机（\"博傻理论\"）",[1808,11871,2123],{},[1808,11873,11874],{},"羊群效应",[1794,11876,11878],{"id":11877},"六助推与政策应用-nudge-and-policy","六、助推与政策应用 (Nudge and Policy)",[2221,11880,11882],{"id":11881},"_61-thaler-sunstein的助推理论","6.1 Thaler & Sunstein的助推理论",[1798,11884,11885,11888,11889,11892],{},[2152,11886,11887],{},"助推 (Nudge)","：通过改变",[2152,11890,11891],{},"选择架构 (Choice Architecture)"," 而非限制选择或改变激励，来引导人们做出更好的决策。",[1798,11894,11895,2155],{},[2152,11896,2303],{},[2157,11898,11899,11915,11931],{},[1808,11900,11901,11904],{},[2152,11902,11903],{},"默认选项 (Default Options)",[1805,11905,11906,11909,11912],{},[1808,11907,11908],{},"器官捐赠：opt-in（需主动登记）vs. opt-out（自动登记除非退出）",[1808,11910,11911],{},"数据：opt-out国家捐赠率接近100%，opt-in约15%",[1808,11913,11914],{},"原因：惯性、拖延、默认=建议",[1808,11916,11917,11920],{},[2152,11918,11919],{},"储蓄计划",[1805,11921,11922,11925,11928],{},[1808,11923,11924],{},"\"Save More Tomorrow\" (Thaler & Benartzi 2004)",[1808,11926,11927],{},"自动增加储蓄率（与加薪挂钩）",[1808,11929,11930],{},"储蓄率从3.5%增加到13.6%",[1808,11932,11933,11936],{},[2152,11934,11935],{},"食堂设计",[1805,11937,11938,11941,11944],{},[1808,11939,11940],{},"将健康食品放在视线高度、收银台附近",[1808,11942,11943],{},"不健康食品放在不显眼处",[1808,11945,11946],{},"增加健康食品消费",[2221,11948,11950],{"id":11949},"_62-自由主义的父爱主义-libertarian-paternalism","6.2 自由主义的父爱主义 (Libertarian Paternalism)",[1798,11952,11953,2155],{},[2152,11954,11955],{},"理念",[1805,11957,11958,11964],{},[1808,11959,11960,11963],{},[2152,11961,11962],{},"父爱主义","：政策制定者帮助人们做出更好选择",[1808,11965,11966,11969],{},[2152,11967,11968],{},"自由主义","：保留选择自由，不强制",[1798,11971,11972,2155],{},[2152,11973,11974],{},"争议",[1805,11976,11977,11980],{},[1808,11978,11979],{},"支持者：纠正认知偏差，提高福利",[1808,11981,11982],{},"反对者：谁定义\"更好\"？可能被滥用（操纵）",[2221,11984,11986],{"id":11985},"_63-政策案例","6.3 政策案例",[1798,11988,11989,2155],{},[2152,11990,11991],{},"退休储蓄（美国401k计划）",[1805,11993,11994,11997,12000],{},[1808,11995,11996],{},"问题：很多人不参加（惯性、拖延）",[1808,11998,11999],{},"改革：自动注册（automatic enrollment）",[1808,12001,12002],{},"效果：参与率从38%增加到86%",[1798,12004,12005,2155],{},[2152,12006,12007],{},"能源使用",[1805,12009,12010,12013],{},[1808,12011,12012],{},"寄账单时附上邻居平均用电量（社会比较）",[1808,12014,12015],{},"高于平均者减少用电2%",[1798,12017,12018,2155],{},[2152,12019,12020],{},"税收征缴",[1805,12022,12023,12026],{},[1808,12024,12025],{},"信中提到\"90%的人已按时缴税\"（社会规范）",[1808,12027,12028],{},"增加按时缴税率",[1794,12030,12032],{"id":12031},"七批评与局限-criticisms-and-limitations","七、批评与局限 (Criticisms and Limitations)",[2221,12034,12036],{"id":12035},"_71-对行为经济学的批评","7.1 对行为经济学的批评",[2157,12038,12039,12052,12065,12077],{},[1808,12040,12041,12044],{},[2152,12042,12043],{},"缺乏统一理论",[1805,12045,12046,12049],{},[1808,12047,12048],{},"许多\"ad hoc\"模型，针对特定偏差",[1808,12050,12051],{},"不像理性模型那样有统一框架",[1808,12053,12054,12057],{},[2152,12055,12056],{},"市场会纠正偏差？",[1805,12058,12059,12062],{},[1808,12060,12061],{},"芝加哥学派（Friedman）：竞争市场惩罚非理性者",[1808,12063,12064],{},"反驳：很多偏差即使在市场中也持续（如泡沫）",[1808,12066,12067,12069],{},[2152,12068,11741],{},[1805,12070,12071,12074],{},[1808,12072,12073],{},"实验室发现能推广到真实世界吗？",[1808,12075,12076],{},"例：小金额实验 vs. 大额真实决策",[1808,12078,12079,12082],{},[2152,12080,12081],{},"可操纵性",[1805,12083,12084,12087],{},[1808,12085,12086],{},"助推可能被用于操纵而非帮助",[1808,12088,12089],{},"企业利用偏差（如默认自动续费）",[2221,12091,12093],{"id":12092},"_72-行为模型的演进","7.2 行为模型的演进",[1798,12095,12096,12099,12100,12103,12104,12107,12108,12111],{},[2152,12097,12098],{},"第一代","：记录偏差（Kahneman & Tversky）\n",[2152,12101,12102],{},"第二代","：建立形式模型（前景理论、双曲贴现）\n",[2152,12105,12106],{},"第三代","：神经经济学（fMRI研究大脑决策机制）\n",[2152,12109,12110],{},"第四代","：大数据与AI（识别和预测行为模式）",[1794,12113,12115],{"id":12114},"八神经经济学与未来方向-neuroeconomics","八、神经经济学与未来方向 (Neuroeconomics)",[2221,12117,12119],{"id":12118},"_81-神经经济学","8.1 神经经济学",[1798,12121,12122,12125],{},[2152,12123,12124],{},"方法","：使用fMRI、EEG等技术研究大脑在经济决策中的活动",[1798,12127,12128,2155],{},[2152,12129,12130],{},"发现",[1805,12132,12133,12139,12145],{},[1808,12134,12135,12138],{},[2152,12136,12137],{},"奖励系统","：多巴胺与预期收益",[1808,12140,12141,12144],{},[2152,12142,12143],{},"损失规避","：杏仁核对损失的强烈反应",[1808,12146,12147,12150],{},[2152,12148,12149],{},"自我控制","：前额叶皮层抑制冲动",[1798,12152,12153,12156],{},[2152,12154,12155],{},"例","（McClure et al. 2004）：",[1805,12158,12159,12162,12165],{},[1808,12160,12161],{},"即时奖励激活边缘系统（情绪、冲动）",[1808,12163,12164],{},"延迟奖励激活前额叶（理性规划）",[1808,12166,12167],{},"双曲贴现的神经基础",[2221,12169,12171],{"id":12170},"_82-大数据时代的行为经济学","8.2 大数据时代的行为经济学",[1798,12173,12174,2155],{},[2152,12175,12176],{},"机会",[1805,12178,12179,12182,12185],{},[1808,12180,12181],{},"海量真实决策数据（在线购物、社交媒体）",[1808,12183,12184],{},"更精确的行为模式识别",[1808,12186,12187],{},"个性化助推",[1798,12189,12190,2155],{},[2152,12191,12192],{},"挑战",[1805,12194,12195,12198,12201],{},[1808,12196,12197],{},"隐私与伦理",[1808,12199,12200],{},"算法歧视",[1808,12202,12203],{},"\"黑箱\"问题（深度学习不可解释）",[1794,12205,12207],{"id":12206},"直觉总结-intuitive-summary","直觉总结 (Intuitive Summary)",[2221,12209,12211],{"id":12210},"标准模型-vs-行为模型","标准模型 vs. 行为模型",[2064,12213,12214,12226],{},[2067,12215,12216],{},[2070,12217,12218,12220,12223],{},[2073,12219,11700],{},[2073,12221,12222],{},"标准经济学",[2073,12224,12225],{},"行为经济学",[2083,12227,12228,12241,12254,12267,12280],{},[2070,12229,12230,12235,12238],{},[2088,12231,12232],{},[2152,12233,12234],{},"理性",[2088,12236,12237],{},"完全理性、无限计算能力",[2088,12239,12240],{},"有限理性、启发式",[2070,12242,12243,12248,12251],{},[2088,12244,12245],{},[2152,12246,12247],{},"偏好",[2088,12249,12250],{},"稳定、不受框架影响",[2088,12252,12253],{},"参考依赖、框架效应",[2070,12255,12256,12261,12264],{},[2088,12257,12258],{},[2152,12259,12260],{},"自利",[2088,12262,12263],{},"完全自私",[2088,12265,12266],{},"公平、互惠、利他",[2070,12268,12269,12274,12277],{},[2088,12270,12271],{},[2152,12272,12273],{},"时间",[2088,12275,12276],{},"指数贴现、时间一致",[2088,12278,12279],{},"双曲贴现、现时偏好",[2070,12281,12282,12287,12290],{},[2088,12283,12284],{},[2152,12285,12286],{},"风险",[2088,12288,12289],{},"期望效用理论",[2088,12291,12292],{},"前景理论、损失规避",[2221,12294,12295],{"id":12295},"核心洞见",[2157,12297,12298,12311,12334,12347],{},[1808,12299,12300,12303],{},[2152,12301,12302],{},"系统性偏差",[1805,12304,12305,12308],{},[1808,12306,12307],{},"人类偏差不是随机的，而是可预测的",[1808,12309,12310],{},"因此可以建模、可以利用（商业）或纠正（政策）",[1808,12312,12313,12316,12317],{},[2152,12314,12315],{},"双系统理论"," (Kahneman)",[1805,12318,12319,12325,12331],{},[1808,12320,12321,12324],{},[2152,12322,12323],{},"系统1","：快速、直觉、情绪化、自动",[1808,12326,12327,12330],{},[2152,12328,12329],{},"系统2","：慢速、理性、费力、控制",[1808,12332,12333],{},"很多偏差源于过度依赖系统1",[1808,12335,12336,12339],{},[2152,12337,12338],{},"环境的重要性",[1805,12340,12341,12344],{},[1808,12342,12343],{},"同样的人在不同环境下表现不同",[1808,12345,12346],{},"选择架构影响决策",[1808,12348,12349,12352],{},[2152,12350,12351],{},"实验的价值",[1805,12353,12354,12357],{},[1808,12355,12356],{},"经济学从\"黑板经济学\"走向实证科学",[1808,12358,12359],{},"实验既检验理论，也发现新现象",[2221,12361,12362],{"id":12362},"政策含义",[1798,12364,12365,2155],{},[2152,12366,12367],{},"传统政策工具",[1805,12369,12370,12373,12376],{},[1808,12371,12372],{},"价格（税收、补贴）",[1808,12374,12375],{},"数量（配额、禁令）",[1808,12377,12378],{},"信息（披露要求）",[1798,12380,12381,12384],{},[2152,12382,12383],{},"行为工具","（助推）：",[1805,12386,12387,12390,12393,12396],{},[1808,12388,12389],{},"默认选项",[1808,12391,12392],{},"简化流程",[1808,12394,12395],{},"社会规范",[1808,12397,12398],{},"及时反馈",[1798,12400,12401,12404],{},[2152,12402,12403],{},"组合使用","：最有效的政策往往结合传统工具和行为洞见。",[1794,12406,12408],{"id":12407},"文献导读-literature-guide","文献导读 (Literature Guide)",[1798,12410,12411,2155],{},[2152,12412,12413],{},"奠基性论文",[1805,12415,12416,12423,12429,12435],{},[1808,12417,12418,12419,1914],{},"Simon, H. (1955). \"A Behavioral Model of Rational Choice.\" ",[12420,12421,12422],"em",{},"QJE",[1808,12424,12425,12426,1914],{},"Kahneman, D., & Tversky, A. (1979). \"Prospect Theory: An Analysis of Decision under Risk.\" ",[12420,12427,12428],{},"Econometrica",[1808,12430,12431,12432,1914],{},"Thaler, R. (1980). \"Toward a Positive Theory of Consumer Choice.\" ",[12420,12433,12434],{},"Journal of Economic Behavior & Organization",[1808,12436,12437,12438,1914],{},"Fehr, E., & Schmidt, K. (1999). \"A Theory of Fairness, Competition, and Cooperation.\" ",[12420,12439,12422],{},[1798,12441,12442,2155],{},[2152,12443,12444],{},"综述",[1805,12446,12447,12453],{},[1808,12448,12449,12450,1914],{},"DellaVigna, S. (2009). \"Psychology and Economics: Evidence from the Field.\" ",[12420,12451,12452],{},"JEL",[1808,12454,12455,12456,12459],{},"Camerer, C., Loewenstein, G., & Rabin, M. (2004). ",[12420,12457,12458],{},"Advances in Behavioral Economics",". Princeton.",[1798,12461,12462,2155],{},[2152,12463,12464],{},"教科书",[1805,12466,12467,12473],{},[1808,12468,12469,12470,1914],{},"Thaler, R., & Sunstein, C. (2008). ",[12420,12471,12472],{},"Nudge: Improving Decisions about Health, Wealth, and Happiness",[1808,12474,12475,12476,12479],{},"Kahneman, D. (2011). ",[12420,12477,12478],{},"Thinking, Fast and Slow",". (畅销书，系统1和系统2)",[1798,12481,12482,2155],{},[2152,12483,12484],{},"实验方法",[1805,12486,12487,12493],{},[1808,12488,12489,12490,1914],{},"Smith, V. (1982). \"Microeconomic Systems as an Experimental Science.\" ",[12420,12491,12492],{},"AER",[1808,12494,12495,12496,1914],{},"Roth, A. (1995). \"Introduction to Experimental Economics.\" In ",[12420,12497,12498],{},"Handbook of Experimental Economics",[1798,12500,12501,2155],{},[2152,12502,12503],{},"应用",[1805,12505,12506,12512],{},[1808,12507,12508,12509,1914],{},"Benartzi, S., & Thaler, R. (2007). \"Heuristics and Biases in Retirement Savings Behavior.\" ",[12420,12510,12511],{},"JEP",[1808,12513,12514,12515,1914],{},"Allcott, H. (2011). \"Social Norms and Energy Conservation.\" ",[12420,12516,12517],{},"Journal of Public Economics",[1794,12519,12520],{"id":12520},"本章小结",[1798,12522,12523,12524,12526,12527,12530,12531,12534,12535,12538],{},"行为经济学挑战了传统经济学的\"完全理性\"假设，引入了心理学的洞见来解释人类决策中的系统性偏差。从",[2152,12525,2090],{},"（启发式与偏差）到",[2152,12528,12529],{},"前景理论","（损失规避、框架效应），从",[2152,12532,12533],{},"社会偏好","（公平、互惠）到",[2152,12536,12537],{},"跨期选择","（双曲贴现、现时偏好），行为经济学揭示了人类决策的真实机制。",[1798,12540,12541,12544,12545,12548,12549,12551],{},[2152,12542,12543],{},"实验经济学","提供了检验这些理论的方法，从最后通牒博弈到资产泡沫实验，实验结果一再显示标准模型的预测失败。这些发现不仅具有学术价值，更有重要的",[2152,12546,12547],{},"政策应用","：通过",[2152,12550,2134],{},"（改变选择架构）等行为工具，可以帮助人们做出更好的决策，提高社会福利。",[1798,12553,12554],{},"然而，行为经济学也面临批评：缺乏统一理论框架、外部效度的疑问、以及助推可能被滥用的担忧。未来的发展方向包括神经经济学（探索大脑机制）和大数据应用（个性化干预），但也必须警惕隐私和伦理问题。",[1794,12556,12557],{"id":12557},"自学检查",[1798,12559,12560,12563],{},[2152,12561,12562],{},"核心直觉回看","：行为经济学不是否定模型，而是把标准模型当作基准，再解释哪些偏差是稳定、可预测、可被制度影响的。好的行为模型仍然要给出清楚的心理机制和可检验预测。",[1798,12565,12566,12569],{},[2152,12567,12568],{},"关键模型提醒","：前景理论把结果写成相对参照点的收益和损失：",[1853,12571,12573],{"className":12572},[1856],[1853,12574,12576,12628],{"className":12575},[1860],[1853,12577,12579],{"className":12578},[1864],[1866,12580,12581],{"xmlns":1868,"display":1869},[1871,12582,12583,12625],{},[1874,12584,12585,12587,12589,12595,12597,12599,12605,12607,12609,12611,12617,12619,12621,12623],{},[1877,12586,4619],{},[1881,12588,1883],{},[4623,12590,12591,12593],{},[1881,12592,4627],{},[1877,12594,2933],{},[1877,12596,5609],{},[1881,12598,2335],{"stretchy":2334},[2763,12600,12601,12603],{},[1877,12602,1798],{},[1877,12604,2933],{},[1881,12606,2341],{"stretchy":2334},[1877,12608,3427],{},[1881,12610,2335],{"stretchy":2334},[2763,12612,12613,12615],{},[1877,12614,2570],{},[1877,12616,2933],{},[1881,12618,1902],{},[1877,12620,4659],{},[1881,12622,2341],{"stretchy":2334},[1881,12624,2772],{"separator":1924},[1916,12626,12627],{"encoding":1918},"V=\\sum_i \\pi(p_i)v(x_i-r),",[1853,12629,12631,12649,12806],{"className":12630,"ariaHidden":1924},[1923],[1853,12632,12634,12637,12640,12643,12646],{"className":12633},[1928],[1853,12635],{"className":12636,"style":1933},[1932],[1853,12638,4619],{"className":12639,"style":1969},[1937,1938],[1853,12641],{"className":12642,"style":1944},[1943],[1853,12644,1883],{"className":12645},[1948],[1853,12647],{"className":12648,"style":1944},[1943],[1853,12650,12652,12655,12699,12702,12705,12708,12748,12751,12754,12757,12797,12800,12803],{"className":12651},[1928],[1853,12653],{"className":12654,"style":4692},[1932],[1853,12656,12658],{"className":12657},[3118,4696],[1853,12659,12661,12691],{"className":12660},[2714,2811],[1853,12662,12664,12688],{"className":12663},[2718],[1853,12665,12667,12678],{"className":12666,"style":4706},[2722],[1853,12668,12669,12672],{"style":4709},[1853,12670],{"className":12671,"style":4713},[2729],[1853,12673,12675],{"className":12674},[2829,2830,2831,2832],[1853,12676,2933],{"className":12677},[1937,1938,2832],[1853,12679,12680,12683],{"style":4725},[1853,12681],{"className":12682,"style":4713},[2729],[1853,12684,12685],{},[1853,12686,4627],{"className":12687},[3118,4734,4735],[1853,12689,2840],{"className":12690},[2839],[1853,12692,12694],{"className":12693},[2718],[1853,12695,12697],{"className":12696,"style":4745},[2722],[1853,12698],{},[1853,12700],{"className":12701,"style":2857},[1943],[1853,12703,5609],{"className":12704,"style":3449},[1937,1938],[1853,12706,2335],{"className":12707},[2379],[1853,12709,12711,12714],{"className":12710},[1937],[1853,12712,1798],{"className":12713},[1937,1938],[1853,12715,12717],{"className":12716},[2807],[1853,12718,12720,12740],{"className":12719},[2714,2811],[1853,12721,12723,12737],{"className":12722},[2718],[1853,12724,12726],{"className":12725,"style":2980},[2722],[1853,12727,12728,12731],{"style":2821},[1853,12729],{"className":12730,"style":2825},[2729],[1853,12732,12734],{"className":12733},[2829,2830,2831,2832],[1853,12735,2933],{"className":12736},[1937,1938,2832],[1853,12738,2840],{"className":12739},[2839],[1853,12741,12743],{"className":12742},[2718],[1853,12744,12746],{"className":12745,"style":2847},[2722],[1853,12747],{},[1853,12749,2341],{"className":12750},[2386],[1853,12752,3427],{"className":12753,"style":3449},[1937,1938],[1853,12755,2335],{"className":12756},[2379],[1853,12758,12760,12763],{"className":12759},[1937],[1853,12761,2570],{"className":12762},[1937,1938],[1853,12764,12766],{"className":12765},[2807],[1853,12767,12769,12789],{"className":12768},[2714,2811],[1853,12770,12772,12786],{"className":12771},[2718],[1853,12773,12775],{"className":12774,"style":2980},[2722],[1853,12776,12777,12780],{"style":2821},[1853,12778],{"className":12779,"style":2825},[2729],[1853,12781,12783],{"className":12782},[2829,2830,2831,2832],[1853,12784,2933],{"className":12785},[1937,1938,2832],[1853,12787,2840],{"className":12788},[2839],[1853,12790,12792],{"className":12791},[2718],[1853,12793,12795],{"className":12794,"style":2847},[2722],[1853,12796],{},[1853,12798],{"className":12799,"style":1969},[1943],[1853,12801,1902],{"className":12802},[1973],[1853,12804],{"className":12805,"style":1969},[1943],[1853,12807,12809,12812,12815,12818],{"className":12808},[1928],[1853,12810],{"className":12811,"style":2371},[1932],[1853,12813,4659],{"className":12814,"style":4879},[1937,1938],[1853,12816,2341],{"className":12817},[2386],[1853,12819,2772],{"className":12820},[2853],[1798,12822,4885,12823,12867,12868,12912],{},[1853,12824,12826,12846],{"className":12825},[1860],[1853,12827,12829],{"className":12828},[1864],[1866,12830,12831],{"xmlns":1868},[1871,12832,12833,12843],{},[1874,12834,12835,12837,12839,12841],{},[1877,12836,3427],{},[1881,12838,2335],{"stretchy":2334},[1881,12840,4644],{},[1881,12842,2341],{"stretchy":2334},[1916,12844,12845],{"encoding":1918},"v(\\cdot)",[1853,12847,12849],{"className":12848,"ariaHidden":1924},[1923],[1853,12850,12852,12855,12858,12861,12864],{"className":12851},[1928],[1853,12853],{"className":12854,"style":2371},[1932],[1853,12856,3427],{"className":12857,"style":3449},[1937,1938],[1853,12859,2335],{"className":12860},[2379],[1853,12862,4644],{"className":12863},[1937],[1853,12865,2341],{"className":12866},[2386]," 通常在损失区更陡，",[1853,12869,12871,12891],{"className":12870},[1860],[1853,12872,12874],{"className":12873},[1864],[1866,12875,12876],{"xmlns":1868},[1871,12877,12878,12888],{},[1874,12879,12880,12882,12884,12886],{},[1877,12881,5609],{},[1881,12883,2335],{"stretchy":2334},[1881,12885,4644],{},[1881,12887,2341],{"stretchy":2334},[1916,12889,12890],{"encoding":1918},"\\pi(\\cdot)",[1853,12892,12894],{"className":12893,"ariaHidden":1924},[1923],[1853,12895,12897,12900,12903,12906,12909],{"className":12896},[1928],[1853,12898],{"className":12899,"style":2371},[1932],[1853,12901,5609],{"className":12902,"style":3449},[1937,1938],[1853,12904,2335],{"className":12905},[2379],[1853,12907,4644],{"className":12908},[1937],[1853,12910,2341],{"className":12911},[2386]," 表示概率权重。社会偏好模型则把他人的收益也放进自己的效用函数。",[2221,12914,12915],{"id":12915},"常见误区",[1805,12917,12918,12921,12924,12927],{},[1808,12919,12920],{},"把“有限理性”理解成“什么行为都可以解释”。行为模型必须能预测，而不是事后讲故事。",[1808,12922,12923],{},"只记住损失规避，却忘记参照点、概率权重和框架效应共同作用。",[1808,12925,12926],{},"认为实验室结果可以无条件推广到现实市场。外部效度需要额外证据。",[1808,12928,12929],{},"把助推看成没有成本的政策工具。选择架构也可能被操纵，并涉及伦理边界。",[2221,12931,12932],{"id":12932},"自测题",[2157,12934,12935,12938,12941,12944,12947],{},[1808,12936,12937],{},"代表性启发式和可得性启发式分别会导致什么判断偏差？",[1808,12939,12940],{},"前景理论如何解释“收益区间风险厌恶、损失区间风险追求”？",[1808,12942,12943],{},"最后通牒博弈为什么挑战了纯自利模型？",[1808,12945,12946],{},"双曲贴现如何解释拖延和提前承诺？",[1808,12948,12949],{},"设计一个助推政策时，为什么要同时考虑福利和自主选择？",[2221,12951,12952],{"id":12952},"下一步学习提示",[1798,12954,12955],{},"下一章回到市场失灵。请比较两种政策思路：传统微观强调价格矫正和机制设计，行为经济学则强调选择架构。现实政策常常需要二者结合。",[12957,12958],"hr",{},[1798,12960,12961,12964,12965,12968],{},[2152,12962,12963],{},"下一章","我们将学习",[2152,12966,12967],{},"外部性与公共物品","，分析市场失灵的另一个重要来源，并探讨庇古税、科斯定理、VCG机制等解决方案。",{"title":10,"searchDepth":12970,"depth":12970,"links":12971},2,[12972,12973,12974,12978,12983,12989,12995,13000,13005,13010,13014,13018,13023,13024,13025],{"id":1796,"depth":12970,"text":1796},{"id":1844,"depth":12970,"text":1845},{"id":2146,"depth":12970,"text":2147,"children":12975},[12976],{"id":2223,"depth":12977,"text":2223},3,{"id":2240,"depth":12970,"text":2241,"children":12979},[12980,12981,12982],{"id":2244,"depth":12977,"text":2245},{"id":2283,"depth":12977,"text":2284},{"id":2509,"depth":12977,"text":2510},{"id":3209,"depth":12970,"text":3210,"children":12984},[12985,12986,12987,12988],{"id":3213,"depth":12977,"text":3214},{"id":3393,"depth":12977,"text":3394},{"id":4918,"depth":12977,"text":4919},{"id":5026,"depth":12977,"text":5027},{"id":5096,"depth":12970,"text":5097,"children":12990},[12991,12992,12993,12994],{"id":5100,"depth":12977,"text":5101},{"id":5265,"depth":12977,"text":5266},{"id":5342,"depth":12977,"text":5343},{"id":6447,"depth":12977,"text":6448},{"id":9492,"depth":12970,"text":9493,"children":12996},[12997,12998,12999],{"id":9496,"depth":12977,"text":9497},{"id":11491,"depth":12977,"text":11492},{"id":11529,"depth":12977,"text":11530},{"id":11650,"depth":12970,"text":11651,"children":13001},[13002,13003,13004],{"id":11654,"depth":12977,"text":11655},{"id":11690,"depth":12977,"text":11691},{"id":11775,"depth":12977,"text":11776},{"id":11877,"depth":12970,"text":11878,"children":13006},[13007,13008,13009],{"id":11881,"depth":12977,"text":11882},{"id":11949,"depth":12977,"text":11950},{"id":11985,"depth":12977,"text":11986},{"id":12031,"depth":12970,"text":12032,"children":13011},[13012,13013],{"id":12035,"depth":12977,"text":12036},{"id":12092,"depth":12977,"text":12093},{"id":12114,"depth":12970,"text":12115,"children":13015},[13016,13017],{"id":12118,"depth":12977,"text":12119},{"id":12170,"depth":12977,"text":12171},{"id":12206,"depth":12970,"text":12207,"children":13019},[13020,13021,13022],{"id":12210,"depth":12977,"text":12211},{"id":12295,"depth":12977,"text":12295},{"id":12362,"depth":12977,"text":12362},{"id":12407,"depth":12970,"text":12408},{"id":12520,"depth":12970,"text":12520},{"id":12557,"depth":12970,"text":12557,"children":13026},[13027,13028,13029],{"id":12915,"depth":12977,"text":12915},{"id":12932,"depth":12977,"text":12932},{"id":12952,"depth":12977,"text":12952},"有限理性、前景理论、社会偏好、跨期选择与实验方法","md",null,{},true,{"title":1602,"description":13030},"B0Oxu4EFkCdekMsEQAkT1N_bX82yGT1YdljCxW7DPpk",[13038,13040],{"title":1596,"path":1597,"stem":1598,"description":13039,"children":-1},"显示原理、激励相容、VCG机制、收入等价与最优拍卖",{"title":1608,"path":1609,"stem":1610,"description":13041,"children":-1},"外部性、庇古税、科斯定理、公共物品供给与VCG机制",1785754755376]