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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 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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. 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",[1800,1801,1802],"strong",{},"2026 年 7 月 31 日"," 对期刊、NBER、Brookings 等一手来源的定向检索。它是课程更新，不是穷尽式系统综述。凡是论文报告的经验结论，均明确写成“作者发现”或“论文估计”；网页中的模拟只用于解释机制，不复现论文数据，也不构成现实政策预测。",[1805,1806,1807],"h2",{"id":1807},"学习目标",[1793,1809,1810],{},"完成本章后，你应能够：",[1812,1813,1814,1818,1821,1824,1827],"ol",{},[1815,1816,1817],"li",{},"把疫情后通胀拆成相对价格冲击、部门短缺、劳动力市场紧张、工资和预期等不同渠道；",[1815,1819,1820],{},"解释为什么菲利普斯曲线可能在劳动力市场极度紧张时变陡；",[1815,1822,1823],{},"用任务份额与任务层面的成本节约讨论 AI 对总生产率的数量级；",[1815,1825,1826],{},"区分恒等式、结构模型、估计分解和政策反事实；",[1815,1828,1829],{},"比较彼此并不完全一致的论文，而不是强行选出一个“唯一正确”的故事。",[1805,1831,1833],{"id":1832},"案例一疫情后通胀不能只用一个产出缺口解释","案例一：疫情后通胀不能只用一个“产出缺口”解释",[1835,1836,1838],"h3",{"id":1837},"_1-研究问题","1. 研究问题",[1793,1840,1841],{},"Bernanke 与 Blanchard（2023）追问：美国 2021—2022 年的通胀上升，主要来自过热的总需求和工资—价格循环，还是来自能源、食品、供应链与部门错配？二人在 2024 年又与十个中央银行团队把相近框架应用到 11 个经济体，以检验美国经验是否具有外部有效性。",[1793,1843,1844],{},"这比“通胀是需求拉动还是成本推动”更具体。研究者必须同时解释价格、工资、短期与长期通胀预期，并允许冲击经由不同速度传导。",[1835,1846,1848],{"id":1847},"_2-模型读法","2. 模型读法",[1793,1850,1851],{},"可以把论文的思路简化为以下教学框架：",[1853,1854,1857],"span",{"className":1855},[1856],"katex-display",[1853,1858,1861,1991],{"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",[1871,1872,1873,1986],"semantics",{},[1874,1875,1876,1886,1890,1893,1897,1900,1903,1918,1921,1924,1926,1928,1930,1937,1939,1942,1944,1946,1948,1955,1957,1960,1962,1964,1966,1973,1975,1982],"mrow",{},[1877,1878,1879,1883],"msub",{},[1880,1881,1882],"mi",{},"π",[1880,1884,1885],{},"t",[1887,1888,1889],"mo",{},"=",[1880,1891,1892],{},"a",[1887,1894,1896],{"stretchy":1895},"false","(",[1880,1898,1899],{},"L",[1887,1901,1902],{"stretchy":1895},")",[1877,1904,1905,1907],{},[1880,1906,1882],{},[1874,1908,1909,1911,1914],{},[1880,1910,1885],{},[1887,1912,1913],{},"−",[1915,1916,1917],"mn",{},"1",[1887,1919,1920],{},"+",[1880,1922,1923],{},"b",[1887,1925,1896],{"stretchy":1895},[1880,1927,1899],{},[1887,1929,1902],{"stretchy":1895},[1877,1931,1932,1935],{},[1880,1933,1934],{},"s",[1880,1936,1885],{},[1887,1938,1920],{},[1880,1940,1941],{},"c",[1887,1943,1896],{"stretchy":1895},[1880,1945,1899],{},[1887,1947,1902],{"stretchy":1895},[1877,1949,1950,1953],{},[1880,1951,1952],{},"m",[1880,1954,1885],{},[1887,1956,1920],{},[1880,1958,1959],{},"d",[1887,1961,1896],{"stretchy":1895},[1880,1963,1899],{},[1887,1965,1902],{"stretchy":1895},[1877,1967,1968,1971],{},[1880,1969,1970],{},"w",[1880,1972,1885],{},[1887,1974,1920],{},[1877,1976,1977,1980],{},[1880,1978,1979],{},"ε",[1880,1981,1885],{},[1887,1983,1985],{"separator":1984},"true",",",[1987,1988,1990],"annotation",{"encoding":1989},"application\u002Fx-tex","\\pi_t\n=a(L)\\pi_{t-1}\n+b(L)s_t\n+c(L)m_t\n+d(L)w_t\n+\\varepsilon_t,",[1853,1992,1995,2075,2158,2226,2293,2362],{"className":1993,"ariaHidden":1984},[1994],"katex-html",[1853,1996,1999,2004,2063,2068,2072],{"className":1997},[1998],"base",[1853,2000],{"className":2001,"style":2003},[2002],"strut","height:0.5806em;vertical-align:-0.15em;",[1853,2005,2008,2013],{"className":2006},[2007],"mord",[1853,2009,1882],{"className":2010,"style":2012},[2007,2011],"mathnormal","margin-right:0.0359em;",[1853,2014,2017],{"className":2015},[2016],"msupsub",[1853,2018,2022,2054],{"className":2019},[2020,2021],"vlist-t","vlist-t2",[1853,2023,2026,2049],{"className":2024},[2025],"vlist-r",[1853,2027,2031],{"className":2028,"style":2030},[2029],"vlist","height:0.2806em;",[1853,2032,2034,2039],{"style":2033},"top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;",[1853,2035],{"className":2036,"style":2038},[2037],"pstrut","height:2.7em;",[1853,2040,2046],{"className":2041},[2042,2043,2044,2045],"sizing","reset-size6","size3","mtight",[1853,2047,1885],{"className":2048},[2007,2011,2045],[1853,2050,2053],{"className":2051},[2052],"vlist-s","​",[1853,2055,2057],{"className":2056},[2025],[1853,2058,2061],{"className":2059,"style":2060},[2029],"height:0.15em;",[1853,2062],{},[1853,2064],{"className":2065,"style":2067},[2066],"mspace","margin-right:0.2778em;",[1853,2069,1889],{"className":2070},[2071],"mrel",[1853,2073],{"className":2074,"style":2067},[2066],[1853,2076,2078,2082,2085,2089,2092,2096,2148,2152,2155],{"className":2077},[1998],[1853,2079],{"className":2080,"style":2081},[2002],"height:1em;vertical-align:-0.25em;",[1853,2083,1892],{"className":2084},[2007,2011],[1853,2086,1896],{"className":2087},[2088],"mopen",[1853,2090,1899],{"className":2091},[2007,2011],[1853,2093,1902],{"className":2094},[2095],"mclose",[1853,2097,2099,2102],{"className":2098},[2007],[1853,2100,1882],{"className":2101,"style":2012},[2007,2011],[1853,2103,2105],{"className":2104},[2016],[1853,2106,2108,2139],{"className":2107},[2020,2021],[1853,2109,2111,2136],{"className":2110},[2025],[1853,2112,2115],{"className":2113,"style":2114},[2029],"height:0.3011em;",[1853,2116,2117,2120],{"style":2033},[1853,2118],{"className":2119,"style":2038},[2037],[1853,2121,2123],{"className":2122},[2042,2043,2044,2045],[1853,2124,2126,2129,2133],{"className":2125},[2007,2045],[1853,2127,1885],{"className":2128},[2007,2011,2045],[1853,2130,1913],{"className":2131},[2132,2045],"mbin",[1853,2134,1917],{"className":2135},[2007,2045],[1853,2137,2053],{"className":2138},[2052],[1853,2140,2142],{"className":2141},[2025],[1853,2143,2146],{"className":2144,"style":2145},[2029],"height:0.2083em;",[1853,2147],{},[1853,2149],{"className":2150,"style":2151},[2066],"margin-right:0.2222em;",[1853,2153,1920],{"className":2154},[2132],[1853,2156],{"className":2157,"style":2151},[2066],[1853,2159,2161,2164,2167,2170,2173,2176,2217,2220,2223],{"className":2160},[1998],[1853,2162],{"className":2163,"style":2081},[2002],[1853,2165,1923],{"className":2166},[2007,2011],[1853,2168,1896],{"className":2169},[2088],[1853,2171,1899],{"className":2172},[2007,2011],[1853,2174,1902],{"className":2175},[2095],[1853,2177,2179,2182],{"className":2178},[2007],[18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",[1853,2417,2419,2437],{"className":2418},[1860],[1853,2420,2422],{"className":2421},[1864],[1866,2423,2424],{"xmlns":1868},[1871,2425,2426,2434],{},[1874,2427,2428],{},[1877,2429,2430,2432],{},[1880,2431,1934],{},[1880,2433,1885],{},[1987,2435,2436],{"encoding":1989},"s_t",[1853,2438,2440],{"className":2439,"ariaHidden":1984},[1994],[1853,2441,2443,2446],{"className":2442},[1998],[1853,2444],{"className":2445,"style":2003},[2002],[1853,2447,2449,2452],{"className":2448},[2007],[1853,2450,1934],{"className":2451},[2007,2011],[1853,2453,2455],{"className":2454},[2016],[1853,2456,2458,2478],{"className":2457},[2020,2021],[1853,2459,2461,2475],{"className":2460},[2025],[1853,2462,2464],{"className":2463,"style":2030},[2029],[1853,2465,2466,2469],{"style":2196},[1853,2467],{"className":2468,"style":2038},[2037],[1853,2470,2472],{"className":2471},[2042,2043,2044,2045],[1853,2473,1885],{"className":2474},[2007,2011,2045],[1853,2476,2053],{"className":2477},[2052],[1853,2479,2481],{"className":2480},[2025],[1853,2482,2484],{"className":2483,"style":2060},[2029],[1853,2485],{}," 表示能源、食品和部门短缺等相对价格冲击，",[1853,2488,2490,2508],{"className":2489},[1860],[1853,2491,2493],{"className":2492},[1864],[1866,2494,2495],{"xmlns":1868},[1871,2496,2497,2505],{},[1874,2498,2499],{},[1877,2500,2501,2503],{},[1880,2502,1952],{},[1880,2504,1885],{},[1987,2506,2507],{"encoding":1989},"m_t",[1853,2509,2511],{"className":2510,"ariaHidden":1984},[1994],[1853,2512,2514,2517],{"className":2513},[1998],[1853,2515],{"className":2516,"style":2003},[2002],[1853,2518,2520,2523],{"className":2519},[2007],[1853,2521,1952],{"className":2522},[2007,2011],[1853,2524,2526],{"className":2525},[2016],[1853,2527,2529,2549],{"className":2528},[2020,2021],[1853,2530,2532,2546],{"className":2531},[2025],[1853,2533,2535],{"className":2534,"style":2030},[2029],[1853,2536,2537,2540],{"style":2196},[1853,2538],{"className":2539,"style":2038},[2037],[1853,2541,2543],{"className":2542},[2042,2043,2044,2045],[1853,2544,1885],{"className":2545},[2007,2011,2045],[1853,2547,2053],{"className":2548},[2052],[1853,2550,2552],{"className":2551},[2025],[1853,2553,2555],{"className":2554,"style":2060},[2029],[1853,2556],{}," 表示劳动力市场紧张，",[1853,2559,2561,2579],{"className":2560},[1860],[1853,2562,2564],{"className":2563},[1864],[1866,2565,2566],{"xmlns":1868},[1871,2567,2568,2576],{},[1874,2569,2570],{},[1877,2571,2572,2574],{},[1880,2573,1970],{},[1880,2575,1885],{},[1987,2577,2578],{"encoding":1989},"w_t",[1853,2580,2582],{"className":2581,"ariaHidden":1984},[1994],[1853,2583,2585,2588],{"className":2584},[1998],[1853,2586],{"className":2587,"style":2003},[2002],[1853,2589,2591,2594],{"className":2590},[2007],[1853,2592,1970],{"className":2593,"style":2317},[2007,2011],[1853,2595,2597],{"className":2596},[2016],[1853,2598,2600,2620],{"className":2599},[2020,2021],[1853,2601,2603,2617],{"className":2602},[2025],[1853,2604,2606],{"className":2605,"style":2030},[2029],[1853,2607,2608,2611],{"style":2332},[1853,2609],{"className":2610,"style":2038},[2037],[1853,2612,2614],{"className":2613},[2042,2043,2044,2045],[1853,2615,1885],{"className":2616},[2007,2011,2045],[1853,2618,2053],{"className":2619},[2052],[1853,2621,2623],{"className":2622},[2025],[1853,2624,2626],{"className":2625,"style":2060},[2029],[1853,2627],{}," 表示工资压力，",[1853,2630,2632,2682],{"className":2631},[1860],[1853,2633,2635],{"className":2634},[1864],[1866,2636,2637],{"xmlns":1868},[1871,2638,2639,2679],{},[1874,2640,2641,2643,2645,2647,2649,2651,2653,2655,2657,2659,2661,2663,2665,2667,2669,2671,2673,2675,2677],{},[1880,2642,1892],{},[1887,2644,1896],{"stretchy":1895},[1880,2646,1899],{},[1887,2648,1902],{"stretchy":1895},[1887,2650,1985],{"separator":1984},[1880,2652,1923],{},[1887,2654,1896],{"stretchy":1895},[1880,2656,1899],{},[1887,2658,1902],{"stretchy":1895},[1887,2660,1985],{"separator":1984},[1880,2662,1941],{},[1887,2664,1896],{"stretchy":1895},[1880,2666,1899],{},[1887,2668,1902],{"stretchy":1895},[1887,2670,1985],{"separator":1984},[1880,2672,1959],{},[1887,2674,1896],{"stretchy":1895},[1880,2676,1899],{},[1887,2678,1902],{"stretchy":1895},[1987,2680,2681],{"encoding":1989},"a(L),b(L),c(L),d(L)",[1853,2683,2685],{"className":2684,"ariaHidden":1984},[1994],[1853,2686,2688,2691,2694,2697,2700,2703,2706,2710,2713,2716,2719,2722,2725,2728,2731,2734,2737,2740,2743,2746,2749,2752,2755],{"className":2687},[1998],[1853,2689],{"className":2690,"style":2081},[2002],[1853,2692,1892],{"className":2693},[2007,2011],[1853,2695,1896],{"className":2696},[2088],[1853,2698,1899],{"className":2699},[2007,2011],[1853,2701,1902],{"className":2702},[2095],[1853,2704,1985],{"className":2705},[2412],[1853,2707],{"className":2708,"style":2709},[2066],"margin-right:0.1667em;",[1853,2711,1923],{"className":2712},[2007,2011],[1853,2714,1896],{"className":2715},[2088],[1853,2717,1899],{"className":2718},[2007,2011],[1853,2720,1902],{"className":2721},[2095],[1853,2723,1985],{"className":2724},[2412],[1853,2726],{"className":2727,"style":2709},[2066],[1853,2729,1941],{"className":2730},[2007,2011],[1853,2732,1896],{"className":2733},[2088],[1853,2735,1899],{"className":2736},[2007,2011],[1853,2738,1902],{"className":2739},[2095],[1853,2741,1985],{"className":2742},[2412],[1853,2744],{"className":2745,"style":2709},[2066],[1853,2747,1959],{"className":2748},[2007,2011],[1853,2750,1896],{"className":2751},[2088],[1853,2753,1899],{"className":2754},[2007,2011],[1853,2756,1902],{"className":2757},[2095]," 表示这些变量可能通过若干滞后进入通胀。模型不是说各项永远可以机械相加，而是要求研究者明确每一项的时间顺序。",[1793,2760,2761],{},"例如，港口拥堵先抬高少数商品的边际成本；商品短缺扩大后，价格指数上升；若家庭和企业仍相信中期通胀会回到目标，工资追赶可能有限。相反，如果劳动力市场持续紧张、工资重新议价且预期脱锚，初始相对价格冲击就更可能转化为持续通胀。",[1835,2763,2765],{"id":2764},"_3-论文报告了什么","3. 论文报告了什么",[1793,2767,2768],{},"Bernanke 与 Blanchard 的美国分析认为，2021—2022 年大部分初始通胀上升与商品价格、能源食品以及部门短缺直接推高价格有关；劳动力市场并非最初来源，但随着相对价格冲击消退，职位空缺相对于失业人数的高水平对工资和价格的持续压力变得更重要。2024 年的 11 个经济体比较得到大体相似的时间顺序，但能源冲击、短缺和工资传导的相对重要性因国家而异。",[1835,2770,2772],{"id":2771},"_4-本科生应掌握的解释","4. 本科生应掌握的解释",[1793,2774,2775],{},"不要把“供给冲击”理解成一条永久左移的短期总供给曲线。至少要区分：",[2777,2778,2779,2785,2791,2797],"ul",{},[1815,2780,2781,2784],{},[1800,2782,2783],{},"一次性价格水平冲击","：某类价格上升后稳定，通胀率会先升后降；",[1815,2786,2787,2790],{},[1800,2788,2789],{},"持续成本冲击","：能源或投入价格不断上涨，通胀率持续受压；",[1815,2792,2793,2796],{},[1800,2794,2795],{},"二轮效应","：工资、利润率和预期把初始冲击传播到其他价格；",[1815,2798,2799,2802],{},[1800,2800,2801],{},"需求放大","：财政转移、宽松金融条件或被压抑需求使有限供给面对更强购买力。",[1793,2804,2805],{},"因此，“通胀来自供给”不推出“货币政策毫无作用”；它只说明加息不能生产芯片或天然气，并且政策需要权衡通胀持续性与压低需求的产出成本。",[1835,2807,2809],{"id":2808},"_5-研究生延伸与证据边界","5. 研究生延伸与证据边界",[1793,2811,2812],{},"分解结果依赖模型设定、冲击变量、滞后长度和反事实路径。职位空缺—失业比也是劳动力市场紧张的代理变量，不是完全外生的处理。跨国结果更不能在忽略工资制度、能源结构、财政响应和价格管制的情况下直接平均。高质量研究生报告应至少比较替代紧张度指标、样本期、预期测量和结构突变。",[1805,2814,2816],{"id":2815},"案例二为什么菲利普斯曲线可能是非线性的","案例二：为什么菲利普斯曲线可能是非线性的",[1835,2818,2820],{"id":2819},"_1-从失业率转向匹配紧张度","1. 从失业率转向匹配紧张度",[1793,2822,2823],{},"Benigno 与 Eggertsson（2023）提出一条非线性新凯恩斯菲利普斯曲线，并用职位空缺与失业人数之比",[1853,2825,2827],{"className":2826},[1856],[1853,2828,2830,2868],{"className":2829},[1860],[1853,2831,2833],{"className":2832},[1864],[1866,2834,2835],{"xmlns":1868,"display":1869},[1871,2836,2837,2865],{},[1874,2838,2839,2846,2848],{},[1877,2840,2841,2844],{},[1880,2842,2843],{},"θ",[1880,2845,1885],{},[1887,2847,1889],{},[2849,2850,2851,2858],"mfrac",{},[1877,2852,2853,2856],{},[1880,2854,2855],{},"V",[1880,2857,1885],{},[1877,2859,2860,2863],{},[1880,2861,2862],{},"U",[1880,2864,1885],{},[1987,2866,2867],{"encoding":1989},"\\theta_t=\\frac{V_t}{U_t}",[1853,2869,2871,2929],{"className":2870,"ariaHidden":1984},[1994],[1853,2872,2874,2878,2920,2923,2926],{"className":2873},[1998],[1853,2875],{"className":2876,"style":2877},[2002],"height:0.8444em;vertical-align:-0.15em;",[1853,2879,2881,2885],{"className":2880},[2007],[1853,2882,2843],{"className":2883,"style":2884},[2007,2011],"margin-right:0.0278em;",[1853,2886,2888],{"className":2887},[2016],[1853,2889,2891,2912],{"className":2890},[2020,2021],[1853,2892,2894,2909],{"className":2893},[2025],[1853,2895,2897],{"className":2896,"style":2030},[2029],[1853,2898,2900,2903],{"style":2899},"top:-2.55em;margin-left:-0.0278em;margin-right:0.05em;",[1853,2901],{"className":2902,"style":2038},[2037],[1853,2904,2906],{"className":2905},[2042,2043,2044,2045],[1853,2907,1885],{"className":2908},[2007,2011,2045],[1853,2910,2053],{"className":2911},[2052],[1853,2913,2915],{"className":2914},[2025],[1853,2916,2918],{"className":2917,"style":2060},[2029],[1853,2919],{},[1853,2921],{"className":2922,"style":2067},[2066],[1853,2924,1889],{"className":2925},[2071],[1853,2927],{"className":2928,"style":2067},[2066],[1853,2930,2932,2936],{"className":2931},[1998],[1853,2933],{"className":2934,"style":2935},[2002],"height:2.1963em;vertical-align:-0.836em;",[1853,2937,2939,2943,3081],{"className":2938},[2007],[1853,2940],{"className":2941},[2088,2942],"nulldelimiter",[1853,2944,2946],{"className":2945},[2849],[1853,2947,2949,3072],{"className":2948},[2020,2021],[1853,2950,2952,3069],{"className":2951},[2025],[1853,2953,2956,3008,3019],{"className":2954,"style":2955},[2029],"height:1.3603em;",[1853,2957,2959,2963],{"style":2958},"top:-2.314em;",[1853,2960],{"className":2961,"style":2962},[2037],"height:3em;",[1853,2964,2966],{"className":2965},[2007],[1853,2967,2969,2973],{"className":2968},[2007],[1853,2970,2862],{"className":2971,"style":2972},[2007,2011],"margin-right:0.109em;",[1853,2974,2976],{"className":2975},[2016],[1853,2977,2979,3000],{"className":2978},[2020,2021],[1853,2980,2982,2997],{"className":2981},[2025],[1853,2983,2985],{"className":2984,"style":2030},[2029],[1853,2986,2988,2991],{"style":2987},"top:-2.55em;margin-left:-0.109em;margin-right:0.05em;",[1853,2989],{"className":2990,"style":2038},[2037],[1853,2992,2994],{"className":2993},[2042,2043,2044,2045],[1853,2995,1885],{"className":2996},[2007,2011,2045],[1853,2998,2053],{"className":2999},[2052],[1853,3001,3003],{"className":3002},[2025],[1853,3004,3006],{"className":3005,"style":2060},[2029],[1853,3007],{},[1853,3009,3011,3014],{"style":3010},"top:-3.23em;",[1853,3012],{"className":3013,"style":2962},[2037],[1853,3015],{"className":3016,"style":3018},[3017],"frac-line","border-bottom-width:0.04em;",[1853,3020,3022,3025],{"style":3021},"top:-3.677em;",[1853,3023],{"className":3024,"style":2962},[2037],[1853,3026,3028],{"className":3027},[2007],[1853,3029,3031,3034],{"className":3030},[2007],[1853,3032,2855],{"className":3033,"style":2151},[2007,2011],[1853,3035,3037],{"className":3036},[2016],[1853,3038,3040,3061],{"className":3039},[2020,2021],[1853,3041,3043,3058],{"className":3042},[2025],[1853,3044,3046],{"className":3045,"style":2030},[2029],[1853,3047,3049,3052],{"style":3048},"top:-2.55em;margin-left:-0.2222em;margin-right:0.05em;",[1853,3050],{"className":3051,"style":2038},[2037],[1853,3053,3055],{"className":3054},[2042,2043,2044,2045],[1853,3056,1885],{"className":3057},[2007,2011,2045],[1853,3059,2053],{"className":3060},[2052],[1853,3062,3064],{"className":3063},[2025],[1853,3065,3067],{"className":3066,"style":2060},[2029],[1853,3068],{},[1853,3070,2053],{"className":3071},[2052],[1853,3073,3075],{"className":3074},[2025],[1853,3076,3079],{"className":3077,"style":3078},[2029],"height:0.836em;",[1853,3080],{},[1853,3082],{"className":3083},[2095,2942],[1793,3085,3086],{},"衡量劳动力市场紧张度。直觉是：当失业者很多、岗位很少时，再增加一个岗位未必显著推高工资；当每个失业者对应很多岗位时，企业之间争夺工人，新增需求的工资和价格效应会快速放大。",[1793,3088,3089],{},"教学上可把通胀压力近似写成：",[1853,3091,3093],{"className":3092},[1856],[1853,3094,3096,3161],{"className":3095},[1860],[1853,3097,3099],{"className":3098},[1864],[1866,3100,3101],{"xmlns":1868,"display":1869},[1871,3102,3103,3158],{},[1874,3104,3105,3111,3113,3123,3125,3128,3137,3139,3145,3147,3150,3152,3155],{},[1877,3106,3107,3109],{},[1880,3108,1882],{},[1880,3110,1885],{},[1887,3112,1913],{},[3114,3115,3116,3118,3120],"msubsup",{},[1880,3117,1882],{},[1880,3119,1885],{},[1880,3121,3122],{},"e",[1887,3124,1889],{},[1880,3126,3127],{},"κ",[3114,3129,3130,3132,3134],{},[1880,3131,2843],{},[1880,3133,1885],{},[1880,3135,3136],{},"γ",[1887,3138,1920],{},[1877,3140,3141,3143],{},[1880,3142,1934],{},[1880,3144,1885],{},[1887,3146,1985],{"separator":1984},[2066,3148],{"width":3149},"2em",[1880,3151,3136],{},[1887,3153,3154],{},">",[1915,3156,3157],{},"1.",[1987,3159,3160],{"encoding":1989},"\\pi_t-\\pi_t^e=\\kappa \\theta_t^{\\gamma}+s_t,\n\\qquad \\gamma>1.",[1853,3162,3164,3220,3291,3369,3438],{"className":3163,"ariaHidden":1984},[1994],[1853,3165,3167,3171,3211,3214,3217],{"className":3166},[1998],[1853,3168],{"className":3169,"style":3170},[2002],"height:0.7333em;vertical-align:-0.15em;",[1853,3172,3174,3177],{"className":3173},[2007],[1853,3175,1882],{"className":3176,"style":2012},[2007,2011],[1853,3178,3180],{"className":3179},[2016],[1853,3181,3183,3203],{"className":3182},[2020,2021],[1853,3184,3186,3200],{"className":3185},[2025],[1853,3187,3189],{"className":3188,"style":2030},[2029],[1853,3190,3191,3194],{"style":2033},[1853,3192],{"className":3193,"style":2038},[2037],[1853,3195,3197],{"className":3196},[2042,2043,2044,2045],[1853,3198,1885],{"className":3199},[2007,2011,2045],[1853,3201,2053],{"className":3202},[2052],[1853,3204,3206],{"className":3205},[2025],[1853,3207,3209],{"className":3208,"style":2060},[2029],[1853,3210],{},[1853,3212],{"className":3213,"style":2151},[2066],[1853,3215,1913],{"className":3216},[2132],[1853,3218],{"className":3219,"style":2151},[2066],[1853,3221,3223,3227,3282,3285,3288],{"className":3222},[1998],[1853,3224],{"className":3225,"style":3226},[2002],"height:0.9614em;vertical-align:-0.247em;",[1853,3228,3230,3233],{"className":3229},[2007],[1853,3231,1882],{"className":3232,"style":2012},[2007,2011],[1853,3234,3236],{"className":3235},[2016],[1853,3237,3239,3273],{"className":3238},[2020,2021],[1853,3240,3242,3270],{"className":3241},[2025],[1853,3243,3246,3258],{"className":3244,"style":3245},[2029],"height:0.7144em;",[1853,3247,3249,3252],{"style":3248},"top:-2.453em;margin-left:-0.0359em;margin-right:0.05em;",[1853,3250],{"className":3251,"style":2038},[2037],[1853,3253,3255],{"className":3254},[2042,2043,2044,2045],[1853,3256,1885],{"className":3257},[2007,2011,2045],[1853,3259,3261,3264],{"style":3260},"top:-3.113em;margin-right:0.05em;",[1853,3262],{"className":3263,"style":2038},[2037],[1853,3265,3267],{"className":3266},[2042,2043,2044,2045],[1853,3268,3122],{"className":3269},[2007,2011,2045],[1853,3271,2053],{"className":3272},[2052],[1853,3274,3276],{"className":3275},[2025],[1853,3277,3280],{"className":3278,"style":3279},[2029],"height:0.247em;",[1853,3281],{},[1853,3283],{"className":3284,"style":2067},[2066],[1853,3286,1889],{"className":3287},[2071],[1853,3289],{"className":3290,"style":2067},[2066],[1853,3292,3294,3298,3301,3360,3363,3366],{"className":3293},[1998],[1853,3295],{"className":3296,"style":3297},[2002],"height:1.0281em;vertical-align:-0.2458em;",[1853,3299,3127],{"className":3300},[2007,2011],[1853,3302,3304,3307],{"className":3303},[2007],[1853,3305,2843],{"className":3306,"style":2884},[2007,2011],[1853,3308,3310],{"className":3309},[2016],[1853,3311,3313,3351],{"className":3312},[2020,2021],[1853,3314,3316,3348],{"className":3315},[2025],[1853,3317,3320,3332],{"className":3318,"style":3319},[2029],"height:0.7823em;",[1853,3321,3323,3326],{"style":3322},"top:-2.4542em;margin-left:-0.0278em;margin-right:0.05em;",[1853,3324],{"className":3325,"style":2038},[2037],[1853,3327,3329],{"className":3328},[2042,2043,2044,2045],[1853,3330,1885],{"className":3331},[2007,2011,2045],[1853,3333,3335,3338],{"style":3334},"top:-3.1809em;margin-right:0.05em;",[1853,3336],{"className":3337,"style":2038},[2037],[1853,3339,3341],{"className":3340},[2042,2043,2044,2045],[1853,3342,3344],{"className":3343},[2007,2045],[1853,3345,3136],{"className":3346,"style":3347},[2007,2011,2045],"margin-right:0.0556em;",[1853,3349,2053],{"className":3350},[2052],[1853,3352,3354],{"className":3353},[2025],[1853,3355,3358],{"className":3356,"style":3357},[2029],"height:0.2458em;",[1853,3359],{},[1853,3361],{"className":3362,"style":2151},[2066],[1853,3364,1920],{"className":3365},[2132],[1853,3367],{"className":3368,"style":2151},[2066],[1853,3370,3372,3376,3416,3419,3423,3426,3429,3432,3435],{"className":3371},[1998],[1853,3373],{"className":3374,"style":3375},[2002],"height:0.7335em;vertical-align:-0.1944em;",[1853,3377,3379,3382],{"className":3378},[2007],[1853,3380,1934],{"className":3381},[2007,2011],[1853,3383,3385],{"className":3384},[2016],[1853,3386,3388,3408],{"className":3387},[2020,2021],[1853,3389,3391,3405],{"className":3390},[2025],[1853,3392,3394],{"className":3393,"style":2030},[2029],[1853,3395,3396,3399],{"style":2196},[1853,3397],{"className":3398,"style":2038},[2037],[1853,3400,3402],{"className":3401},[2042,2043,2044,2045],[1853,3403,1885],{"className":3404},[2007,2011,2045],[1853,3406,2053],{"className":3407},[2052],[1853,3409,3411],{"className":3410},[2025],[1853,3412,3414],{"className":3413,"style":2060},[2029],[1853,3415],{},[1853,3417,1985],{"className":3418},[2412],[1853,3420],{"className":3421,"style":3422},[2066],"margin-right:2em;",[1853,3424],{"className":3425,"style":2709},[2066],[1853,3427,3136],{"className":3428,"style":3347},[2007,2011],[1853,3430],{"className":3431,"style":2067},[2066],[1853,3433,3154],{"className":3434},[2071],[1853,3436],{"className":3437,"style":2067},[2066],[1853,3439,3441,3445],{"className":3440},[1998],[1853,3442],{"className":3443,"style":3444},[2002],"height:0.6444em;",[1853,3446,3157],{"className":3447},[2007],[1793,3449,3450,3451,3521,3522,3630,3631,3700],{},"当 ",[1853,3452,3454,3472],{"className":3453},[1860],[1853,3455,3457],{"className":3456},[1864],[1866,3458,3459],{"xmlns":1868},[1871,3460,3461,3469],{},[1874,3462,3463],{},[1877,3464,3465,3467],{},[1880,3466,2843],{},[1880,3468,1885],{},[1987,3470,3471],{"encoding":1989},"\\theta_t",[1853,3473,3475],{"className":3474,"ariaHidden":1984},[1994],[1853,3476,3478,3481],{"className":3477},[1998],[1853,3479],{"className":3480,"style":2877},[2002],[1853,3482,3484,3487],{"className":3483},[2007],[1853,3485,2843],{"className":3486,"style":2884},[2007,2011],[1853,3488,3490],{"className":3489},[2016],[1853,3491,3493,3513],{"className":3492},[2020,2021],[1853,3494,3496,3510],{"className":3495},[2025],[1853,3497,3499],{"className":3498,"style":2030},[2029],[1853,3500,3501,3504],{"style":2899},[1853,3502],{"className":3503,"style":2038},[2037],[1853,3505,3507],{"className":3506},[2042,2043,2044,2045],[1853,3508,1885],{"className":3509},[2007,2011,2045],[1853,3511,2053],{"className":3512},[2052],[1853,3514,3516],{"className":3515},[2025],[1853,3517,3519],{"className":3518,"style":2060},[2029],[1853,3520],{}," 较低时，导数 ",[1853,3523,3525,3555],{"className":3524},[1860],[1853,3526,3528],{"className":3527},[1864],[1866,3529,3530],{"xmlns":1868},[1871,3531,3532,3552],{},[1874,3533,3534,3536,3538],{},[1880,3535,3127],{},[1880,3537,3136],{},[3114,3539,3540,3542,3544],{},[1880,3541,2843],{},[1880,3543,1885],{},[1874,3545,3546,3548,3550],{},[1880,3547,3136],{},[1887,3549,1913],{},[1915,3551,1917],{},[1987,3553,3554],{"encoding":1989},"\\kappa\\gamma\\theta_t^{\\gamma-1}",[1853,3556,3558],{"className":3557,"ariaHidden":1984},[1994],[1853,3559,3561,3565,3569],{"className":3560},[1998],[1853,3562],{"className":3563,"style":3564},[2002],"height:1.1778em;vertical-align:-0.2458em;",[1853,3566,3568],{"className":3567,"style":3347},[2007,2011],"κγ",[1853,3570,3572,3575],{"className":3571},[2007],[1853,3573,2843],{"className":3574,"style":2884},[2007,2011],[1853,3576,3578],{"className":3577},[2016],[1853,3579,3581,3622],{"className":3580},[2020,2021],[1853,3582,3584,3619],{"className":3583},[2025],[1853,3585,3588,3599],{"className":3586,"style":3587},[2029],"height:0.932em;",[1853,3589,3590,3593],{"style":3322},[1853,3591],{"className":3592,"style":2038},[2037],[1853,3594,3596],{"className":3595},[2042,2043,2044,2045],[1853,3597,1885],{"className":3598},[2007,2011,2045],[1853,3600,3601,3604],{"style":3334},[1853,3602],{"className":3603,"style":2038},[2037],[1853,3605,3607],{"className":3606},[2042,2043,2044,2045],[1853,3608,3610,3613,3616],{"className":3609},[2007,2045],[1853,3611,3136],{"className":3612,"style":3347},[2007,2011,2045],[1853,3614,1913],{"className":3615},[2132,2045],[1853,3617,1917],{"className":3618},[2007,2045],[1853,3620,2053],{"className":3621},[2052],[1853,3623,3625],{"className":3624},[2025],[1853,3626,3628],{"className":3627,"style":3357},[2029],[1853,3629],{}," 较小；当 ",[1853,3632,3634,3651],{"className":3633},[1860],[1853,3635,3637],{"className":3636},[1864],[1866,3638,3639],{"xmlns":1868},[1871,3640,3641,3649],{},[1874,3642,3643],{},[1877,3644,3645,3647],{},[1880,3646,2843],{},[1880,3648,1885],{},[1987,3650,3471],{"encoding":1989},[1853,3652,3654],{"className":3653,"ariaHidden":1984},[1994],[1853,3655,3657,3660],{"className":3656},[1998],[1853,3658],{"className":3659,"style":2877},[2002],[1853,3661,3663,3666],{"className":3662},[2007],[1853,3664,2843],{"className":3665,"style":2884},[2007,2011],[1853,3667,3669],{"className":3668},[2016],[1853,3670,3672,3692],{"className":3671},[2020,2021],[1853,3673,3675,3689],{"className":3674},[2025],[1853,3676,3678],{"className":3677,"style":2030},[2029],[1853,3679,3680,3683],{"style":2899},[1853,3681],{"className":3682,"style":2038},[2037],[1853,3684,3686],{"className":3685},[2042,2043,2044,2045],[1853,3687,1885],{"className":3688},[2007,2011,2045],[1853,3690,2053],{"className":3691},[2052],[1853,3693,3695],{"className":3694},[2025],[1853,3696,3698],{"className":3697,"style":2060},[2029],[1853,3699],{}," 很高时，同样的紧张度变化带来更大的通胀变化。这就是“曲线在极端紧张区间变陡”的含义。",[1835,3702,3704],{"id":3703},"_2-这对政策有什么改变","2. 这对政策有什么改变",[1793,3706,3707],{},"在线性模型里，从紧张度 0.8 降到 0.6 与从 1.8 降到 1.6 的边际通胀效果相同。非线性模型则允许后者更大。因此，如果政策能主要减少职位空缺而不是大量增加失业，通胀可能明显下降而失业上升有限。",[1793,3709,3710,3711,3714],{},"但这是一项模型条件下的政策含义，不是保证。岗位空缺能否平稳下降，取决于匹配效率、企业招聘行为、劳动供给和政策可信度。论文把 2020 年代通胀更多归因于劳动力短缺，而 Bernanke—Blanchard 更强调初期相对价格冲击；两者并非简单互斥，它们对",[1800,3712,3713],{},"冲击起点与后期持续机制","赋予了不同权重。",[1835,3716,3718],{"id":3717},"_3-阅读争论的方法","3. 阅读争论的方法",[1793,3720,3721],{},"面对两篇结论不同的论文，按四步比较：",[1812,3723,3724,3727,3730,3733],{},[1815,3725,3726],{},"两篇论文解释的是通胀峰值、累计通胀，还是回落的“最后一公里”？",[1815,3728,3729],{},"劳动力紧张、短缺和预期分别怎样测量？",[1815,3731,3732],{},"哪些关系由数据识别，哪些来自模型函数形式？",[1815,3734,3735],{},"更换国家、时期或政策制度后，关键参数是否可能变化？",[1805,3737,3739],{"id":3738},"案例三ai-会让宏观生产率提高多少","案例三：AI 会让宏观生产率提高多少",[1835,3741,3743],{"id":3742},"_1-从技术很强到可计算的宏观对象","1. 从“技术很强”到可计算的宏观对象",[1793,3745,3746],{},"Acemoglu（2025，2024 年在线发表）用任务模型与 Hulten 定理讨论 AI。核心提醒是：某项技术在个别任务上提高效率，不等于整个经济以同样比例提高生产率。",[1793,3748,3749,3750,3779,3780,3809,3810,3841],{},"设 AI 可影响的任务份额为 ",[1853,3751,3753,3767],{"className":3752},[1860],[1853,3754,3756],{"className":3755},[1864],[1866,3757,3758],{"xmlns":1868},[1871,3759,3760,3765],{},[1874,3761,3762],{},[1880,3763,3764],{},"q",[1987,3766,3764],{"encoding":1989},[1853,3768,3770],{"className":3769,"ariaHidden":1984},[1994],[1853,3771,3773,3776],{"className":3772},[1998],[1853,3774],{"className":3775,"style":2368},[2002],[1853,3777,3764],{"className":3778,"style":2012},[2007,2011],"，这些任务的平均成本节约为 ",[1853,3781,3783,3797],{"className":3782},[1860],[1853,3784,3786],{"className":3785},[1864],[1866,3787,3788],{"xmlns":1868},[1871,3789,3790,3795],{},[1874,3791,3792],{},[1880,3793,3794],{},"g",[1987,3796,3794],{"encoding":1989},[1853,3798,3800],{"className":3799,"ariaHidden":1984},[1994],[1853,3801,3803,3806],{"className":3802},[1998],[1853,3804],{"className":3805,"style":2368},[2002],[1853,3807,3794],{"className":3808,"style":2012},[2007,2011],"，能被企业真正吸收并转化为生产率的比例为 ",[1853,3811,3813,3828],{"className":3812},[1860],[1853,3814,3816],{"className":3815},[1864],[1866,3817,3818],{"xmlns":1868},[1871,3819,3820,3825],{},[1874,3821,3822],{},[1880,3823,3824],{},"λ",[1987,3826,3827],{"encoding":1989},"\\lambda",[1853,3829,3831],{"className":3830,"ariaHidden":1984},[1994],[1853,3832,3834,3838],{"className":3833},[1998],[1853,3835],{"className":3836,"style":3837},[2002],"height:0.6944em;",[1853,3839,3824],{"className":3840},[2007,2011],"。一个非常粗略的课堂近似是：",[1853,3843,3845],{"className":3844},[1856],[1853,3846,3848,3896],{"className":3847},[1860],[1853,3849,3851],{"className":3850},[1864],[1866,3852,3853],{"xmlns":1868,"display":1869},[1871,3854,3855,3893],{},[1874,3856,3857,3861,3864,3867,3870,3873,3876,3879,3881,3884,3886,3888,3890],{},[1880,3858,3860],{"mathvariant":3859},"normal","Δ",[1880,3862,3863],{},"log",[1887,3865,3866],{},"⁡",[1880,3868,3869],{},"T",[1880,3871,3872],{},"F",[1880,3874,3875],{},"P",[1887,3877,3878],{},"≈",[1880,3880,3764],{},[1887,3882,3883],{},"×",[1880,3885,3794],{},[1887,3887,3883],{},[1880,3889,3824],{},[1880,3891,3892],{"mathvariant":3859},".",[1987,3894,3895],{"encoding":1989},"\\Delta \\log TFP\\approx q\\times g\\times \\lambda.",[1853,3897,3899,3942,3961,3979],{"className":3898,"ariaHidden":1984},[1994],[1853,3900,3902,3906,3909,3912,3920,3923,3927,3930,3933,3936,3939],{"className":3901},[1998],[1853,3903],{"className":3904,"style":3905},[2002],"height:0.8889em;vertical-align:-0.1944em;",[1853,3907,3860],{"className":3908},[2007],[1853,3910],{"className":3911,"style":2709},[2066],[1853,3913,3916,3917],{"className":3914},[3915],"mop","lo",[1853,3918,3794],{"style":3919},"margin-right:0.0139em;",[1853,3921],{"className":3922,"style":2709},[2066],[1853,3924,3869],{"className":3925,"style":3926},[2007,2011],"margin-right:0.1389em;",[1853,3928,3872],{"className":3929,"style":3926},[2007,2011],[1853,3931,3875],{"className":3932,"style":3926},[2007,2011],[1853,3934],{"className":3935,"style":2067},[2066],[1853,3937,3878],{"className":3938},[2071],[1853,3940],{"className":3941,"style":2067},[2066],[1853,3943,3945,3949,3952,3955,3958],{"className":3944},[1998],[1853,3946],{"className":3947,"style":3948},[2002],"height:0.7778em;vertical-align:-0.1944em;",[1853,3950,3764],{"className":3951,"style":2012},[2007,2011],[1853,3953],{"className":3954,"style":2151},[2066],[1853,3956,3883],{"className":3957},[2132],[1853,3959],{"className":3960,"style":2151},[2066],[1853,3962,3964,3967,3970,3973,3976],{"className":3963},[1998],[1853,3965],{"className":3966,"style":3948},[2002],[1853,3968,3794],{"className":3969,"style":2012},[2007,2011],[1853,3971],{"className":3972,"style":2151},[2066],[1853,3974,3883],{"className":3975},[2132],[1853,3977],{"className":3978,"style":2151},[2066],[1853,3980,3982,3985,3988],{"className":3981},[1998],[1853,3983],{"className":3984,"style":3837},[2002],[1853,3986,3824],{"className":3987},[2007,2011],[1853,3989,3892],{"className":3990},[2007],[1793,3992,3993,3994,4099],{},"若只有 20% 的任务在研究期内可被有效辅助，任务成本平均下降 25%，其中 60% 转化为净生产率增益，则十年累计 TFP 增益的机械估算为 ",[1853,3995,3997,4030],{"className":3996},[1860],[1853,3998,4000],{"className":3999},[1864],[1866,4001,4002],{"xmlns":1868},[1871,4003,4004,4027],{},[1874,4005,4006,4009,4011,4014,4016,4019,4021,4024],{},[1915,4007,4008],{},"0.20",[1887,4010,3883],{},[1915,4012,4013],{},"0.25",[1887,4015,3883],{},[1915,4017,4018],{},"0.60",[1887,4020,1889],{},[1915,4022,4023],{},"3",[1880,4025,4026],{"mathvariant":3859},"%",[1987,4028,4029],{"encoding":1989},"0.20\\times0.25\\times0.60=3\\%",[1853,4031,4033,4052,4070,4088],{"className":4032,"ariaHidden":1984},[1994],[1853,4034,4036,4040,4043,4046,4049],{"className":4035},[1998],[1853,4037],{"className":4038,"style":4039},[2002],"height:0.7278em;vertical-align:-0.0833em;",[1853,4041,4008],{"className":4042},[2007],[1853,4044],{"className":4045,"style":2151},[2066],[1853,4047,3883],{"className":4048},[2132],[1853,4050],{"className":4051,"style":2151},[2066],[1853,4053,4055,4058,4061,4064,4067],{"className":4054},[1998],[1853,4056],{"className":4057,"style":4039},[2002],[1853,4059,4013],{"className":4060},[2007],[1853,4062],{"className":4063,"style":2151},[2066],[1853,4065,3883],{"className":4066},[2132],[1853,4068],{"className":4069,"style":2151},[2066],[1853,4071,4073,4076,4079,4082,4085],{"className":4072},[1998],[1853,4074],{"className":4075,"style":3444},[2002],[1853,4077,4018],{"className":4078},[2007],[1853,4080],{"className":4081,"style":2067},[2066],[1853,4083,1889],{"className":4084},[2071],[1853,4086],{"className":4087,"style":2067},[2066],[1853,4089,4091,4095],{"className":4090},[1998],[1853,4092],{"className":4093,"style":4094},[2002],"height:0.8056em;vertical-align:-0.0556em;",[1853,4096,4098],{"className":4097},[2007],"3%","。这个数字是课堂情景，不是论文估计；它的作用是迫使我们写出假设。",[1835,4101,4103],{"id":4102},"_2-论文结论的准确读法","2. 论文结论的准确读法",[1793,4105,4106],{},"Acemoglu 汇总任务暴露和任务层生产率证据后，估计未来十年 AI 带来的 TFP 增益上限约为 0.66%，较偏好的估计低于约 0.53%。论文同时提醒，早期实验往往集中在较容易学习、结果容易评价的任务；复杂、依赖情境且缺乏明确反馈的任务可能更难自动化。",[1793,4108,4109],{},"这里的“较小”是相对于一些宏大预测而言，并不等于 AI 对所有行业或劳动者都无关紧要。即使总量效应有限，行业、职业和收入分配效应仍可能很大；提高低技能劳动者在部分任务上的效率，也不必然缩小资本收入与劳动收入之间的差距。",[1835,4111,4113],{"id":4112},"_3-研究生扩展","3. 研究生扩展",[1793,4115,4116],{},"研究生应把公式扩展为任务异质性：",[1853,4118,4120],{"className":4119},[1856],[1853,4121,4123,4188],{"className":4122},[1860],[1853,4124,4126],{"className":4125},[1864],[1866,4127,4128],{"xmlns":1868,"display":1869},[1871,4129,4130,4185],{},[1874,4131,4132,4134,4136,4138,4140,4142,4144,4146,4164,4171,4177,4183],{},[1880,4133,3860],{"mathvariant":3859},[1880,4135,3863],{},[1887,4137,3866],{},[1880,4139,3869],{},[1880,4141,3872],{},[1880,4143,3875],{},[1887,4145,3878],{},[4147,4148,4149,4152,4161],"munderover",{},[1887,4150,4151],{},"∑",[1874,4153,4154,4157,4159],{},[1880,4155,4156],{},"j",[1887,4158,1889],{},[1915,4160,1917],{},[1880,4162,4163],{},"J",[1877,4165,4166,4169],{},[1880,4167,4168],{},"ω",[1880,4170,4156],{},[1877,4172,4173,4175],{},[1880,4174,3122],{},[1880,4176,4156],{},[1877,4178,4179,4181],{},[1880,4180,3794],{},[1880,4182,4156],{},[1887,4184,1985],{"separator":1984},[1987,4186,4187],{"encoding":1989},"\\Delta \\log TFP\n\\approx \\sum_{j=1}^{J}\\omega_j e_j g_j,",[1853,4189,4191,4229],{"className":4190,"ariaHidden":1984},[1994],[1853,4192,4194,4197,4200,4203,4208,4211,4214,4217,4220,4223,4226],{"className":4193},[1998],[1853,4195],{"className":4196,"style":3905},[2002],[1853,4198,3860],{"className":4199},[2007],[1853,4201],{"className":4202,"style":2709},[2066],[1853,4204,3916,4206],{"className":4205},[3915],[1853,4207,3794],{"style":3919},[1853,4209],{"className":4210,"style":2709},[2066],[1853,4212,3869],{"className":4213,"style":3926},[2007,2011],[1853,4215,3872],{"className":4216,"style":3926},[2007,2011],[1853,4218,3875],{"className":4219,"style":3926},[2007,2011],[1853,4221],{"className":4222,"style":2067},[2066],[1853,4224,3878],{"className":4225},[2071],[1853,4227],{"className":4228,"style":2067},[2066],[1853,4230,4232,4236,4314,4317,4359,4399,4439],{"className":4231},[1998],[1853,4233],{"className":4234,"style":4235},[2002],"height:3.2421em;vertical-align:-1.4138em;",[1853,4237,4240],{"className":4238},[3915,4239],"op-limits",[1853,4241,4243,4305],{"className":4242},[2020,2021],[1853,4244,4246,4302],{"className":4245},[2025],[1853,4247,4250,4273,4286],{"className":4248,"style":4249},[2029],"height:1.8283em;",[1853,4251,4253,4257],{"style":4252},"top:-1.8723em;margin-left:0em;",[1853,4254],{"className":4255,"style":4256},[2037],"height:3.05em;",[1853,4258,4260],{"className":4259},[2042,2043,2044,2045],[1853,4261,4263,4267,4270],{"className":4262},[2007,2045],[1853,4264,4156],{"className":4265,"style":4266},[2007,2011,2045],"margin-right:0.0572em;",[1853,4268,1889],{"className":4269},[2071,2045],[1853,4271,1917],{"className":4272},[2007,2045],[1853,4274,4276,4279],{"style":4275},"top:-3.05em;",[1853,4277],{"className":4278,"style":4256},[2037],[1853,4280,4281],{},[1853,4282,4151],{"className":4283},[3915,4284,4285],"op-symbol","large-op",[1853,4287,4289,4292],{"style":4288},"top:-4.3em;margin-left:0em;",[1853,4290],{"className":4291,"style":4256},[2037],[1853,4293,4295],{"className":4294},[2042,2043,2044,2045],[1853,4296,4298],{"className":4297},[2007,2045],[1853,4299,4163],{"className":4300,"style":4301},[2007,2011,2045],"margin-right:0.0962em;",[1853,4303,2053],{"className":4304},[2052],[1853,4306,4308],{"className":4307},[2025],[1853,4309,4312],{"className":4310,"style":4311},[2029],"height:1.4138em;",[1853,4313],{},[1853,4315],{"className":4316,"style":2709},[2066],[1853,4318,4320,4323],{"className":4319},[2007],[1853,4321,4168],{"className":4322,"style":2012},[2007,2011],[1853,4324,4326],{"className":4325},[2016],[1853,4327,4329,4350],{"className":4328},[2020,2021],[1853,4330,4332,4347],{"className":4331},[2025],[1853,4333,4336],{"className":4334,"style":4335},[2029],"height:0.3117em;",[1853,4337,4338,4341],{"style":2033},[1853,4339],{"className":4340,"style":2038},[2037],[1853,4342,4344],{"className":4343},[2042,2043,2044,2045],[1853,4345,4156],{"className":4346,"style":4266},[2007,2011,2045],[1853,4348,2053],{"className":4349},[2052],[1853,4351,4353],{"className":4352},[2025],[1853,4354,4357],{"className":4355,"style":4356},[2029],"height:0.2861em;",[1853,4358],{},[1853,4360,4362,4365],{"className":4361},[2007],[1853,4363,3122],{"className":4364},[2007,2011],[1853,4366,4368],{"className":4367},[2016],[1853,4369,4371,4391],{"className":4370},[2020,2021],[1853,4372,4374,4388],{"className":4373},[2025],[1853,4375,4377],{"className":4376,"style":4335},[2029],[1853,4378,4379,4382],{"style":2196},[1853,4380],{"className":4381,"style":2038},[2037],[1853,4383,4385],{"className":4384},[2042,2043,2044,2045],[1853,4386,4156],{"className":4387,"style":4266},[2007,2011,2045],[1853,4389,2053],{"className":4390},[2052],[1853,4392,4394],{"className":4393},[2025],[1853,4395,4397],{"className":4396,"style":4356},[2029],[1853,4398],{},[1853,4400,4402,4405],{"className":4401},[2007],[1853,4403,3794],{"className":4404,"style":2012},[2007,2011],[1853,4406,4408],{"className":4407},[2016],[1853,4409,4411,4431],{"className":4410},[2020,2021],[1853,4412,4414,4428],{"className":4413},[2025],[1853,4415,4417],{"className":4416,"style":4335},[2029],[1853,4418,4419,4422],{"style":2033},[1853,4420],{"className":4421,"style":2038},[2037],[1853,4423,4425],{"className":4424},[2042,2043,2044,2045],[1853,4426,4156],{"className":4427,"style":4266},[2007,2011,2045],[1853,4429,2053],{"className":4430},[2052],[1853,4432,4434],{"className":4433},[2025],[1853,4435,4437],{"className":4436,"style":4356},[2029],[1853,4438],{},[1853,4440,1985],{"className":4441},[2412],[1793,4443,2415,4444,4515,4516,4586,4587,4657],{},[1853,4445,4447,4465],{"className":4446},[1860],[1853,4448,4450],{"className":4449},[1864],[1866,4451,4452],{"xmlns":1868},[1871,4453,4454,4462],{},[1874,4455,4456],{},[1877,4457,4458,4460],{},[1880,4459,4168],{},[1880,4461,4156],{},[1987,4463,4464],{"encoding":1989},"\\omega_j",[1853,4466,4468],{"className":4467,"ariaHidden":1984},[1994],[1853,4469,4471,4475],{"className":4470},[1998],[1853,4472],{"className":4473,"style":4474},[2002],"height:0.7167em;vertical-align:-0.2861em;",[1853,4476,4478,4481],{"className":4477},[2007],[1853,4479,4168],{"className":4480,"style":2012},[2007,2011],[1853,4482,4484],{"className":4483},[2016],[1853,4485,4487,4507],{"className":4486},[2020,2021],[1853,4488,4490,4504],{"className":4489},[2025],[1853,4491,4493],{"className":4492,"style":4335},[2029],[1853,4494,4495,4498],{"style":2033},[1853,4496],{"className":4497,"style":2038},[2037],[1853,4499,4501],{"className":4500},[2042,2043,2044,2045],[1853,4502,4156],{"className":4503,"style":4266},[2007,2011,2045],[1853,4505,2053],{"className":4506},[2052],[1853,4508,4510],{"className":4509},[2025],[1853,4511,4513],{"className":4512,"style":4356},[2029],[1853,4514],{}," 是任务在成本中的权重，",[1853,4517,4519,4537],{"className":4518},[1860],[1853,4520,4522],{"className":4521},[1864],[1866,4523,4524],{"xmlns":1868},[1871,4525,4526,4534],{},[1874,4527,4528],{},[1877,4529,4530,4532],{},[1880,4531,3122],{},[1880,4533,4156],{},[1987,4535,4536],{"encoding":1989},"e_j",[1853,4538,4540],{"className":4539,"ariaHidden":1984},[1994],[1853,4541,4543,4546],{"className":4542},[1998],[1853,4544],{"className":4545,"style":4474},[2002],[1853,4547,4549,4552],{"className":4548},[2007],[1853,4550,3122],{"className":4551},[2007,2011],[1853,4553,4555],{"className":4554},[2016],[1853,4556,4558,4578],{"className":4557},[2020,2021],[1853,4559,4561,4575],{"className":4560},[2025],[1853,4562,4564],{"className":4563,"style":4335},[2029],[1853,4565,4566,4569],{"style":2196},[1853,4567],{"className":4568,"style":2038},[2037],[1853,4570,4572],{"className":4571},[2042,2043,2044,2045],[1853,4573,4156],{"className":4574,"style":4266},[2007,2011,2045],[1853,4576,2053],{"className":4577},[2052],[1853,4579,4581],{"className":4580},[2025],[1853,4582,4584],{"className":4583,"style":4356},[2029],[1853,4585],{}," 是可被 AI 有效影响的程度，",[1853,4588,4590,4608],{"className":4589},[1860],[1853,4591,4593],{"className":4592},[1864],[1866,4594,4595],{"xmlns":1868},[1871,4596,4597,4605],{},[1874,4598,4599],{},[1877,4600,4601,4603],{},[1880,4602,3794],{},[1880,4604,4156],{},[1987,4606,4607],{"encoding":1989},"g_j",[1853,4609,4611],{"className":4610,"ariaHidden":1984},[1994],[1853,4612,4614,4617],{"className":4613},[1998],[1853,4615],{"className":4616,"style":4474},[2002],[1853,4618,4620,4623],{"className":4619},[2007],[1853,4621,3794],{"className":4622,"style":2012},[2007,2011],[1853,4624,4626],{"className":4625},[2016],[1853,4627,4629,4649],{"className":4628},[2020,2021],[1853,4630,4632,4646],{"className":4631},[2025],[1853,4633,4635],{"className":4634,"style":4335},[2029],[1853,4636,4637,4640],{"style":2033},[1853,4638],{"className":4639,"style":2038},[2037],[1853,4641,4643],{"className":4642},[2042,2043,2044,2045],[1853,4644,4156],{"className":4645,"style":4266},[2007,2011,2045],[1853,4647,2053],{"className":4648},[2052],[1853,4650,4652],{"className":4651},[2025],[1853,4653,4655],{"className":4654,"style":4356},[2029],[1853,4656],{}," 是任务层成本节约。随后讨论新任务创造、质量变化、调整成本、市场势力、劳动再配置和社会价值未被简单成本节约公式覆盖的部分。",[1805,4659,4661],{"id":4660},"浏览器实验非线性通胀与-ai-任务聚合","浏览器实验：非线性通胀与 AI 任务聚合",[1793,4663,4664],{},"下面的模拟把两个机制放在同一页。第一部分比较线性与非线性菲利普斯曲线；第二部分计算不同任务暴露情景下的 TFP 数量级。参数是教学设定，不拟合任何国家，也不复现上述论文。",[4666,4667],"pyodide",{"code64":4668,"layout":4669,"locale":7,"packages":4670,"title":4671},"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","vertical","numpy","Python：非线性菲利普斯曲线与任务聚合",[4673,4674],"web-r",{"code64":4675,"layout":4669,"locale":7,"title":4676},"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","R：非线性菲利普斯曲线与任务聚合",[1835,4678,4679],{"id":4679},"实验审计",[2777,4681,4682,4685,4688,4691],{},[1815,4683,4684],{},"把供给冲击从 0.8 改为 0，观察它只改变曲线水平还是也改变斜率。",[1815,4686,4687],{},"把非线性指数从 2.2 改为 1，解释模型退化成什么形式。",[1815,4689,4690],{},"让三个 AI 情景保持相同任务份额，只改变转化比例，说明组织调整为何是宏观参数的一部分。",[1815,4692,4693],{},"不要把模拟输出与论文的 0.66% 直接比较；两者使用的任务定义、证据和校准完全不同。",[1805,4695,4696],{"id":4696},"分层教学任务",[1835,4698,4699],{"id":4699},"本科生任务",[1793,4701,4702],{},"选择一个国家 2021—2024 年的通胀经历，制作四列时间线：总体通胀、能源\u002F食品通胀、职位空缺—失业比、工资增长。写 800 字说明哪个渠道先变化、哪个渠道更持久，以及图形相关性为什么还不是因果识别。",[1835,4704,4705],{"id":4705},"研究生任务",[1793,4707,4708],{},"在 Bernanke—Blanchard 分解与非线性菲利普斯曲线之间设计一个可区分的经验检验。必须写出目标参数、数据频率、结构突变、内生性来源和至少两个替代紧张度指标。若使用局部投影或 VAR，要说明冲击如何识别，而不是只报告脉冲响应图。",[1835,4710,4711],{"id":4711},"课堂讨论",[4713,4714,4715],"blockquote",{},[1793,4716,4717],{},"如果初始通胀主要来自相对价格冲击，而后期持续性主要来自劳动力紧张，中央银行应在何时收紧？答案必须同时讨论政策时滞、预期、分配后果和误判成本。",[1805,4719,4720],{"id":4720},"一手文献与延伸阅读",[1812,4722,4723,4733,4742,4756],{},[1815,4724,4725,4726,4732],{},"Bernanke, B. S., & Blanchard, O. (2023). ",[1892,4727,4731],{"href":4728,"rel":4729},"https:\u002F\u002Fwww.brookings.edu\u002Farticles\u002Fwhat-caused-the-u-s-pandemic-era-inflation\u002F",[4730],"nofollow","What Caused the U.S. Pandemic-Era Inflation?"," Brookings Papers \u002F Hutchins Center Working Paper. 页面提供全文与复现材料。",[1815,4734,4735,4736,4741],{},"Bernanke, B. S., & Blanchard, O. (2024). ",[1892,4737,4740],{"href":4738,"rel":4739},"https:\u002F\u002Fwww.brookings.edu\u002Farticles\u002Fan-analysis-of-pandemic-era-inflation-in-11-economies\u002F",[4730],"An Analysis of Pandemic-Era Inflation in 11 Economies",". Hutchins Center Working Paper 91.",[1815,4743,4744,4745,4750,4751,3892],{},"Benigno, P., & Eggertsson, G. B. (2023). ",[1892,4746,4749],{"href":4747,"rel":4748},"https:\u002F\u002Fwww.nber.org\u002Fpapers\u002Fw31197",[4730],"It’s Baaack: The Surge in Inflation in the 2020s and the Return of the Non-Linear Phillips Curve",". NBER Working Paper 31197. DOI: ",[1892,4752,4755],{"href":4753,"rel":4754},"https:\u002F\u002Fdoi.org\u002F10.3386\u002Fw31197",[4730],"10.3386\u002Fw31197",[1815,4757,4758,4759,4764,4765,4769,4770,3892],{},"Acemoglu, D. (2025). ",[1892,4760,4763],{"href":4761,"rel":4762},"https:\u002F\u002Facademic.oup.com\u002Feconomicpolicy\u002Farticle-abstract\u002F40\u002F121\u002F13\u002F7728473",[4730],"The Simple Macroeconomics of AI",". ",[4766,4767,4768],"em",{},"Economic Policy",", 40(121), 13–58. DOI: ",[1892,4771,4774],{"href":4772,"rel":4773},"https:\u002F\u002Fdoi.org\u002F10.1093\u002Fepolic\u002Feiae042",[4730],"10.1093\u002Fepolic\u002Feiae042",[1793,4776,4777,4778,4782,4783,4787,4788,4792],{},"继续学习时，可将本章与",[1892,4779,4781],{"href":4780},".\u002F04-ad-as-inflation-unemployment","通胀与失业","、",[1892,4784,4786],{"href":4785},".\u002F06-growth-productivity","增长与生产率","和",[1892,4789,4791],{"href":4790},".\u002F09-interactive-policy-labs","浏览器政策实验","配套阅读。",{"title":10,"searchDepth":4794,"depth":4794,"links":4795},2,[4796,4797,4805,4810,4815,4818,4823],{"id":1807,"depth":4794,"text":1807},{"id":1832,"depth":4794,"text":1833,"children":4798},[4799,4801,4802,4803,4804],{"id":1837,"depth":4800,"text":1838},3,{"id":1847,"depth":4800,"text":1848},{"id":2764,"depth":4800,"text":2765},{"id":2771,"depth":4800,"text":2772},{"id":2808,"depth":4800,"text":2809},{"id":2815,"depth":4794,"text":2816,"children":4806},[4807,4808,4809],{"id":2819,"depth":4800,"text":2820},{"id":3703,"depth":4800,"text":3704},{"id":3717,"depth":4800,"text":3718},{"id":3738,"depth":4794,"text":3739,"children":4811},[4812,4813,4814],{"id":3742,"depth":4800,"text":3743},{"id":4102,"depth":4800,"text":4103},{"id":4112,"depth":4800,"text":4113},{"id":4660,"depth":4794,"text":4661,"children":4816},[4817],{"id":4679,"depth":4800,"text":4679},{"id":4696,"depth":4794,"text":4696,"children":4819},[4820,4821,4822],{"id":4699,"depth":4800,"text":4699},{"id":4705,"depth":4800,"text":4705},{"id":4711,"depth":4800,"text":4711},{"id":4720,"depth":4794,"text":4720},"用近期一手研究深入理解疫情后通胀、非线性菲利普斯曲线与人工智能的宏观生产率效应。","md",{"sidebar":4827},{"order":4828},10,true,{"title":1464,"description":4824},"kyWJ_ozBcTbVSbJtIlqBXQrhGY2_MLUvNez4EeP8esY",[4833,4835],{"title":1460,"path":1461,"stem":1462,"description":4834,"children":-1},"使用可点击运行的 Python 与 R 单元理解财政乘数、Taylor 规则、债务动态、Solow 增长和局部投影。",{"title":1468,"path":1469,"stem":1470,"description":4836,"children":-1},"面向本科生与研究生的微观数据因果推断课程，覆盖 OLS、IV、面板、DID、RDD、匹配、离散选择和机器学习。",1785754750987]