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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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8，比较组同期下降 3，DID 为 ",[1837,2565,2567,2585],{"className":2566},[1844],[1837,2568,2570],{"className":2569},[1848],[1850,2571,2572],{"xmlns":1852},[1855,2573,2574,2582],{},[1858,2575,2576,2578],{},[1872,2577,1923],{},[2579,2580,2581],"mn",{},"5",[2005,2583,2584],{"encoding":2007},"-5",[1837,2586,2588],{"className":2587,"ariaHidden":1866},[2012],[1837,2589,2591,2595,2598],{"className":2590},[2016],[1837,2592],{"className":2593,"style":2594},[2020],"height:0.7278em;vertical-align:-0.0833em;",[1837,2596,1923],{"className":2597},[2025],[1837,2599,2581],{"className":2600},[2025],"。处理组原本污染更高并不自动破坏 DID；关键是没有政策时，两组的",[1799,2603,2604],{},"变化","是否可比。",[1796,2607,2608],{},"回归形式：",[1837,2610,2612],{"className":2611},[1840],[1837,2613,2615,2716],{"className":2614},[1844],[1837,2616,2618],{"className":2617},[1848],[1850,2619,2620],{"xmlns":1852,"display":1853},[1855,2621,2622,2713],{},[1858,2623,2624,2635,2637,2644,2647,2654,2656,2658,2660,2662,2664,2666,2669,2671,2673,2680,2683,2686,2688,2690,2696,2698,2700,2711],{},[1861,2625,2626,2628],{},[1868,2627,1898],{},[1858,2629,2630,2633],{},[1868,2631,2632],{},"i",[1868,2634,1920],{},[1872,2636,1887],{},[1861,2638,2639,2642],{},[1868,2640,2641],{},"α",[1868,2643,2632],{},[1872,2645,2646],{},"+",[1861,2648,2649,2652],{},[1868,2650,2651],{},"λ",[1868,2653,1920],{},[1872,2655,2646],{},[1868,2657,1870],{},[1872,2659,1891],{"stretchy":1890},[1868,2661,1906],{},[1868,2663,1942],{},[1868,2665,1945],{},[1868,2667,2668],{},"a",[1868,2670,1920],{},[1868,2672,1945],{},[1861,2674,2675,2678],{},[1868,2676,2677],{},"d",[1868,2679,2632],{},[1872,2681,2682],{},"×",[1868,2684,2685],{},"P",[1868,2687,1914],{},[1868,2689,1917],{},[1861,2691,2692,2694],{},[1868,2693,1920],{},[1868,2695,1920],{},[1872,2697,1948],{"stretchy":1890},[1872,2699,2646],{},[1861,2701,2702,2705],{},[1868,2703,2704],{},"ε",[1858,2706,2707,2709],{},[1868,2708,2632],{},[1868,2710,1920],{},[1868,2712,2003],{"mathvariant":2002},[2005,2714,2715],{"encoding":2007},"Y_{it}=\\alpha_i+\\lambda_t+\\tau(Treated_i\\times Post_t)+\\varepsilon_{it}.",[1837,2717,2719,2782,2840,2898,2978,3042],{"className":2718,"ariaHidden":1866},[2012],[1837,2720,2722,2726,2773,2776,2779],{"className":2721},[2016],[1837,2723],{"className":2724,"style":2725},[2020],"height:0.8333em;vertical-align:-0.15em;",[1837,2727,2729,2732],{"className":2728},[2025],[1837,2730,1898],{"className":2731,"style":2183},[2025,2054],[1837,2733,2735],{"className":2734},[2082],[1837,2736,2738,2765],{"className":2737},[2033,2086],[1837,2739,2741,2762],{"className":2740},[2037],[1837,2742,2745],{"className":2743,"style":2744},[2041],"height:0.3117em;",[1837,2746,2747,2750],{"style":2212},[1837,2748],{"className":2749,"style":2100},[2049],[1837,2751,2753],{"className":2752},[2104,2105,2106,2107],[1837,2754,2756,2759],{"className":2755},[2025,2107],[1837,2757,2632],{"className":2758},[2025,2054,2107],[1837,2760,1920],{"className":2761},[2025,2054,2107],[1837,2763,2126],{"className":2764},[2125],[1837,2766,2768],{"className":2767},[2037],[1837,2769,2771],{"className":2770,"style":2133},[2041],[1837,2772],{},[1837,2774],{"className":2775,"style":2140},[2139],[1837,2777,1887],{"className":2778},[2144],[1837,2780],{"className":2781,"style":2140},[2139],[1837,2783,2785,2789,2831,2834,2837],{"className":2784},[2016],[1837,2786],{"className":2787,"style":2788},[2020],"height:0.7333em;vertical-align:-0.15em;",[1837,2790,2792,2796],{"className":2791},[2025],[1837,2793,2641],{"className":2794,"style":2795},[2025,2054],"margin-right:0.0037em;",[1837,2797,2799],{"className":2798},[2082],[1837,2800,2802,2823],{"className":2801},[2033,2086],[1837,2803,2805,2820],{"className":2804},[2037],[1837,2806,2808],{"className":2807,"style":2744},[2041],[1837,2809,2811,2814],{"style":2810},"top:-2.55em;margin-left:-0.0037em;margin-right:0.05em;",[1837,2812],{"className":2813,"style":2100},[2049],[1837,2815,2817],{"className":2816},[2104,2105,2106,2107],[1837,2818,2632],{"className":2819},[2025,2054,2107],[1837,2821,2126],{"className":2822},[2125],[1837,2824,2826],{"className":2825},[2037],[1837,2827,2829],{"className":2828,"style":2133},[2041],[1837,2830],{},[1837,2832],{"className":2833,"style":2183},[2139],[1837,2835,2646],{"className":2836},[2258],[1837,2838],{"className":2839,"style":2183},[2139],[1837,2841,2843,2847,2889,2892,2895],{"className":2842},[2016],[1837,2844],{"className":2845,"style":2846},[2020],"height:0.8444em;vertical-align:-0.15em;",[1837,2848,2850,2853],{"className":2849},[2025],[1837,2851,2651],{"className":2852},[2025,2054],[1837,2854,2856],{"className":2855},[2082],[1837,2857,2859,2881],{"className":2858},[2033,2086],[1837,2860,2862,2878],{"className":2861},[2037],[1837,2863,2866],{"className":2864,"style":2865},[2041],"height:0.2806em;",[1837,2867,2869,2872],{"style":2868},"top:-2.55em;margin-left:0em;margin-right:0.05em;",[1837,2870],{"className":2871,"style":2100},[2049],[1837,2873,2875],{"className":2874},[2104,2105,2106,2107],[1837,2876,1920],{"className":2877},[2025,2054,2107],[1837,2879,2126],{"className":2880},[2125],[1837,2882,2884],{"className":2883},[2037],[1837,2885,2887],{"className":2886,"style":2133},[2041],[1837,2888],{},[1837,2890],{"className":2891,"style":2183},[2139],[1837,2893,2646],{"className":2894},[2258],[1837,2896],{"className":2897,"style":2183},[2139],[1837,2899,2901,2905,2908,2911,2914,2917,2920,2923,2926,2929,2969,2972,2975],{"className":2900},[2016],[1837,2902],{"className":2903,"style":2904},[2020],"height:1em;vertical-align:-0.25em;",[1837,2906,1870],{"className":2907,"style":2055},[2025,2054],[1837,2909,1891],{"className":2910},[2158],[1837,2912,1906],{"className":2913,"style":2225},[2025,2054],[1837,2915,1942],{"className":2916,"style":2114},[2025,2054],[1837,2918,1945],{"className":2919},[2025,2054],[1837,2921,2668],{"className":2922},[2025,2054],[1837,2924,1920],{"className":2925},[2025,2054],[1837,2927,1945],{"className":2928},[2025,2054],[1837,2930,2932,2935],{"className":2931},[2025],[1837,2933,2677],{"className":2934},[2025,2054],[1837,2936,2938],{"className":2937},[2082],[1837,2939,2941,2961],{"className":2940},[2033,2086],[1837,2942,2944,2958],{"className":2943},[2037],[1837,2945,2947],{"className":2946,"style":2744},[2041],[1837,2948,2949,2952],{"style":2868},[1837,2950],{"className":2951,"style":2100},[2049],[1837,2953,2955],{"className":2954},[2104,2105,2106,2107],[1837,2956,2632],{"className":2957},[2025,2054,2107],[1837,2959,2126],{"className":2960},[2125],[1837,2962,2964],{"className":2963},[2037],[1837,2965,2967],{"className":2966,"style":2133},[2041],[1837,2968],{},[1837,2970],{"className":2971,"style":2183},[2139],[1837,2973,2682],{"className":2974},[2258],[1837,2976],{"className":2977,"style":2183},[2139],[1837,2979,2981,2984,2987,2990,3030,3033,3036,3039],{"className":2980},[2016],[1837,2982],{"className":2983,"style":2904},[2020],[1837,2985,2685],{"className":2986,"style":2225},[2025,2054],[1837,2988,2236],{"className":2989},[2025,2054],[1837,2991,2993,2996],{"className":2992},[2025],[1837,2994,1920],{"className":2995},[2025,2054],[1837,2997,2999],{"className":2998},[2082],[1837,3000,3002,3022],{"className":3001},[2033,2086],[1837,3003,3005,3019],{"className":3004},[2037],[1837,3006,3008],{"className":3007,"style":2865},[2041],[1837,3009,3010,3013],{"style":2868},[1837,3011],{"className":3012,"style":2100},[2049],[1837,3014,3016],{"className":3015},[2104,2105,2106,2107],[1837,3017,1920],{"className":3018},[2025,2054,2107],[1837,3020,2126],{"className":3021},[2125],[1837,3023,3025],{"className":3024},[2037],[1837,3026,3028],{"className":3027,"style":2133},[2041],[1837,3029],{},[1837,3031,1948],{"className":3032},[2354],[1837,3034],{"className":3035,"style":2183},[2139],[1837,3037,2646],{"className":3038},[2258],[1837,3040],{"className":3041,"style":2183},[2139],[1837,3043,3045,3049,3095],{"className":3044},[2016],[1837,3046],{"className":3047,"style":3048},[2020],"height:0.5806em;vertical-align:-0.15em;",[1837,3050,3052,3055],{"className":3051},[2025],[1837,3053,2704],{"className":3054},[2025,2054],[1837,3056,3058],{"className":3057},[2082],[1837,3059,3061,3087],{"className":3060},[2033,2086],[1837,3062,3064,3084],{"className":3063},[2037],[1837,3065,3067],{"className":3066,"style":2744},[2041],[1837,3068,3069,3072],{"style":2868},[1837,3070],{"className":3071,"style":2100},[2049],[1837,3073,3075],{"className":3074},[2104,2105,2106,2107],[1837,3076,3078,3081],{"className":3077},[2025,2107],[1837,3079,2632],{"className":3080},[2025,2054,2107],[1837,3082,1920],{"className":3083},[2025,2054,2107],[1837,3085,2126],{"className":3086},[2125],[1837,3088,3090],{"className":3089},[2037],[1837,3091,3093],{"className":3092,"style":2133},[2041],[1837,3094],{},[1837,3096,2003],{"className":3097},[2025],[1796,3099,3100],{},"在最简单的二组二期情形，交互项系数等于手算 DID。",[1807,3102,3104],{"id":3103},"_2-平行趋势究竟假设什么","2. 平行趋势究竟假设什么",[1837,3106,3108],{"className":3107},[1840],[1837,3109,3111,3241],{"className":3110},[1844],[1837,3112,3114],{"className":3113},[1848],[1850,3115,3116],{"xmlns":1852,"display":1853},[1855,3117,3118,3238],{},[1858,3119,3120,3123,3126,3140,3142,3145,3147,3149,3161,3163,3165,3167,3170,3173,3175,3177,3180,3182,3184,3186,3200,3202,3204,3206,3208,3220,3222,3224,3226,3228,3230,3232,3234,3236],{},[1868,3121,3122],{},"E",[1872,3124,3125],{"stretchy":1890},"[",[1861,3127,3128,3130],{},[1868,3129,1898],{},[1858,3131,3132,3134,3136,3138],{},[1868,3133,1796],{},[1868,3135,1914],{},[1868,3137,1917],{},[1868,3139,1920],{},[1872,3141,1891],{"stretchy":1890},[2579,3143,3144],{},"0",[1872,3146,1948],{"stretchy":1890},[1872,3148,1923],{},[1861,3150,3151,3153],{},[1868,3152,1898],{},[1858,3154,3155,3157,3159],{},[1868,3156,1796],{},[1868,3158,1942],{},[1868,3160,1945],{},[1872,3162,1891],{"stretchy":1890},[2579,3164,3144],{},[1872,3166,1948],{"stretchy":1890},[1872,3168,3169],{},"∣",[1868,3171,3172],{},"G",[1872,3174,1887],{},[1868,3176,1906],{},[1872,3178,3179],{"stretchy":1890},"]",[1872,3181,1887],{},[1868,3183,3122],{},[1872,3185,3125],{"stretchy":1890},[1861,3187,3188,3190],{},[1868,3189,1898],{},[1858,3191,3192,3194,3196,3198],{},[1868,3193,1796],{},[1868,3195,1914],{},[1868,3197,1917],{},[1868,3199,1920],{},[1872,3201,1891],{"stretchy":1890},[2579,3203,3144],{},[1872,3205,1948],{"stretchy":1890},[1872,3207,1923],{},[1861,3209,3210,3212],{},[1868,3211,1898],{},[1858,3213,3214,3216,3218],{},[1868,3215,1796],{},[1868,3217,1942],{},[1868,3219,1945],{},[1872,3221,1891],{"stretchy":1890},[2579,3223,3144],{},[1872,3225,1948],{"stretchy":1890},[1872,3227,3169],{},[1868,3229,3172],{},[1872,3231,1887],{},[1868,3233,1965],{},[1872,3235,3179],{"stretchy":1890},[1868,3237,2003],{"mathvariant":2002},[2005,3239,3240],{"encoding":2007},"E[Y_{post}(0)-Y_{pre}(0)\\mid G=T]\n=\nE[Y_{post}(0)-Y_{pre}(0)\\mid G=C].",[1837,3242,3244,3325,3399,3418,3439,3518,3591,3609],{"className":3243,"ariaHidden":1866},[2012],[1837,3245,3247,3251,3255,3258,3307,3310,3313,3316,3319,3322],{"className":3246},[2016],[1837,3248],{"className":3249,"style":3250},[2020],"height:1.0361em;vertical-align:-0.2861em;",[1837,3252,3122],{"className":3253,"style":3254},[2025,2054],"margin-right:0.0576em;",[1837,3256,3125],{"className":3257},[2158],[1837,3259,3261,3264],{"className":3260},[2025],[1837,3262,1898],{"className":3263,"style":2183},[2025,2054],[1837,3265,3267],{"className":3266},[2082],[1837,3268,3270,3299],{"className":3269},[2033,2086],[1837,3271,3273,3296],{"className":3272},[2037],[1837,3274,3276],{"className":3275,"style":2865},[2041],[1837,3277,3278,3281],{"style":2212},[1837,3279],{"className":3280,"style":2100},[2049],[1837,3282,3284],{"className":3283},[2104,2105,2106,2107],[1837,3285,3287,3290,3293],{"className":3286},[2025,2107],[1837,3288,1796],{"className":3289},[2025,2054,2107],[1837,3291,2236],{"className":3292},[2025,2054,2107],[1837,3294,1920],{"className":3295},[2025,2054,2107],[1837,3297,2126],{"className":3298},[2125],[1837,3300,3302],{"className":3301},[2037],[1837,3303,3305],{"className":3304,"style":2249},[2041],[1837,3306],{},[1837,3308,1891],{"className":3309},[2158],[1837,3311,3144],{"className":3312},[2025],[1837,3314,1948],{"className":3315},[2354],[1837,3317],{"className":3318,"style":2183},[2139],[1837,3320,1923],{"className":3321},[2258],[1837,3323],{"className":3324,"style":2183},[2139],[1837,3326,3328,3331,3381,3384,3387,3390,3393,3396],{"className":3327},[2016],[1837,3329],{"className":3330,"style":3250},[2020],[1837,3332,3334,3337],{"className":3333},[2025],[1837,3335,1898],{"className":3336,"style":2183},[2025,2054],[1837,3338,3340],{"className":3339},[2082],[1837,3341,3343,3373],{"className":3342},[2033,2086],[1837,3344,3346,3370],{"className":3345},[2037],[1837,3347,3350],{"className":3348,"style":3349},[2041],"height:0.1514em;",[1837,3351,3352,3355],{"style":2212},[1837,3353],{"className":3354,"style":2100},[2049],[1837,3356,3358],{"className":3357},[2104,2105,2106,2107],[1837,3359,3361,3364,3367],{"className":3360},[2025,2107],[1837,3362,1796],{"className":3363},[2025,2054,2107],[1837,3365,1942],{"className":3366,"style":2114},[2025,2054,2107],[1837,3368,1945],{"className":3369},[2025,2054,2107],[1837,3371,2126],{"className":3372},[2125],[1837,3374,3376],{"className":3375},[2037],[1837,3377,3379],{"className":3378,"style":2249},[2041],[1837,3380],{},[1837,3382,1891],{"className":3383},[2158],[1837,3385,3144],{"className":3386},[2025],[1837,3388,1948],{"className":3389},[2354],[1837,3391],{"className":3392,"style":2140},[2139],[1837,3394,3169],{"className":3395},[2144],[1837,3397],{"className":3398,"style":2140},[2139],[1837,3400,3402,3406,3409,3412,3415],{"className":3401},[2016],[1837,3403],{"className":3404,"style":3405},[2020],"height:0.6833em;",[1837,3407,3172],{"className":3408},[2025,2054],[1837,3410],{"className":3411,"style":2140},[2139],[1837,3413,1887],{"className":3414},[2144],[1837,3416],{"className":3417,"style":2140},[2139],[1837,3419,3421,3424,3427,3430,3433,3436],{"className":3420},[2016],[1837,3422],{"className":3423,"style":2904},[2020],[1837,3425,1906],{"className":3426,"style":2225},[2025,2054],[1837,3428,3179],{"className":3429},[2354],[1837,3431],{"className":3432,"style":2140},[2139],[1837,3434,1887],{"className":3435},[2144],[1837,3437],{"className":3438,"style":2140},[2139],[1837,3440,3442,3445,3448,3451,3500,3503,3506,3509,3512,3515],{"className":3441},[2016],[1837,3443],{"className":3444,"style":3250},[2020],[1837,3446,3122],{"className":3447,"style":3254},[2025,2054],[1837,3449,3125],{"className":3450},[2158],[1837,3452,3454,3457],{"className":3453},[2025],[1837,3455,1898],{"className":3456,"style":2183},[2025,2054],[1837,3458,3460],{"className":3459},[2082],[1837,3461,3463,3492],{"className":3462},[2033,2086],[1837,3464,3466,3489],{"className":3465},[2037],[1837,3467,3469],{"className":3468,"style":2865},[2041],[1837,3470,3471,3474],{"style":2212},[1837,3472],{"className":3473,"style":2100},[2049],[1837,3475,3477],{"className":3476},[2104,2105,2106,2107],[1837,3478,3480,3483,3486],{"className":3479},[2025,2107],[1837,3481,1796],{"className":3482},[2025,2054,2107],[1837,3484,2236],{"className":3485},[2025,2054,2107],[1837,3487,1920],{"className":3488},[2025,2054,2107],[1837,3490,2126],{"className":3491},[2125],[1837,3493,3495],{"className":3494},[2037],[1837,3496,3498],{"className":3497,"style":2249},[2041],[1837,3499],{},[1837,3501,1891],{"className":3502},[2158],[1837,3504,3144],{"className":3505},[2025],[1837,3507,1948],{"className":3508},[2354],[1837,3510],{"className":3511,"style":2183},[2139],[1837,3513,1923],{"className":3514},[2258],[1837,3516],{"className":3517,"style":2183},[2139],[1837,3519,3521,3524,3573,3576,3579,3582,3585,3588],{"className":3520},[2016],[1837,3522],{"className":3523,"style":3250},[2020],[1837,3525,3527,3530],{"className":3526},[2025],[1837,3528,1898],{"className":3529,"style":2183},[2025,2054],[1837,3531,3533],{"className":3532},[2082],[1837,3534,3536,3565],{"className":3535},[2033,2086],[1837,3537,3539,3562],{"className":3538},[2037],[1837,3540,3542],{"className":3541,"style":3349},[2041],[1837,3543,3544,3547],{"style":2212},[1837,3545],{"className":3546,"style":2100},[2049],[1837,3548,3550],{"className":3549},[2104,2105,2106,2107],[1837,3551,3553,3556,3559],{"className":3552},[2025,2107],[1837,3554,1796],{"className":3555},[2025,2054,2107],[1837,3557,1942],{"className":3558,"style":2114},[2025,2054,2107],[1837,3560,1945],{"className":3561},[2025,2054,2107],[1837,3563,2126],{"className":3564},[2125],[1837,3566,3568],{"className":3567},[2037],[1837,3569,3571],{"className":3570,"style":2249},[2041],[1837,3572],{},[1837,3574,1891],{"className":3575},[2158],[1837,3577,3144],{"className":3578},[2025],[1837,3580,1948],{"className":3581},[2354],[1837,3583],{"className":3584,"style":2140},[2139],[1837,3586,3169],{"className":3587},[2144],[1837,3589],{"className":3590,"style":2140},[2139],[1837,3592,3594,3597,3600,3603,3606],{"className":3593},[2016],[1837,3595],{"className":3596,"style":3405},[2020],[1837,3598,3172],{"className":3599},[2025,2054],[1837,3601],{"className":3602,"style":2140},[2139],[1837,3604,1887],{"className":3605},[2144],[1837,3607],{"className":3608,"style":2140},[2139],[1837,3610,3612,3615,3618,3621],{"className":3611},[2016],[1837,3613],{"className":3614,"style":2904},[2020],[1837,3616,1965],{"className":3617,"style":2433},[2025,2054],[1837,3619,3179],{"className":3620},[2354],[1837,3622,2003],{"className":3623},[2025],[1796,3625,3626,3627,3630],{},"它关于处理组",[1799,3628,3629],{},"未处理潜在结果","，而这一结果在政策后不可观察。处理前趋势图只能发现明显不一致，不能证明政策后反事实平行。",[1796,3632,3633],{},"支持平行趋势的证据应组合：",[3635,3636,3637,3640,3643,3646,3649],"ul",{},[1817,3638,3639],{},"政策前多期趋势与制度叙述；",[1817,3641,3642],{},"比较组没有受到同一政策或溢出；",[1817,3644,3645],{},"政策时点不是由短期结果冲击触发；",[1817,3647,3648],{},"样本构成和测量规则没有同时改变；",[1817,3650,3651],{},"负向结果、伪政策时点与替代比较组结论一致。",[1807,3653,3655],{"id":3654},"_3-可运行案例相同水平不重要不同趋势很重要","3. 可运行案例：相同水平不重要，不同趋势很重要",[1796,3657,3658],{},"代码构造两种世界。两组起点不同，但第一种世界的未处理趋势平行；第二种世界中处理组本来就改善得更慢。",[3660,3661],"pyodide",{"code64":3662,"layout":3663,"locale":7,"packages":3664,"title":3665},"aW1wb3J0IG51bXB5IGFzIG5wCgpybmcgPSBucC5yYW5kb20uZGVmYXVsdF9ybmcoMjAyNjA1KQpuX3Blcl9ncm91cCwgcGVyaW9kcyA9IDE4MDAsIDYKdGltZSA9IG5wLmFyYW5nZShwZXJpb2RzKQpwb3N0ID0gdGltZSA+PSAzCnRydWVfZWZmZWN0ID0gLTIuMAoKZGVmIG1ha2VfcGFuZWwoZGlmZmVyZW50aWFsX3RyZW5kKToKICAgIGdyb3VwID0gbnAucmVwZWF0KFswLCAxXSwgbl9wZXJfZ3JvdXApCiAgICB1bml0X2xldmVsID0gcm5nLm5vcm1hbChzY2FsZT0yLjUsIHNpemU9Z3JvdXAuc2l6ZSkKICAgIG91dGNvbWVzID0gbnAuZW1wdHkoKGdyb3VwLnNpemUsIHBlcmlvZHMpKQogICAgZm9yIHQgaW4gdGltZToKICAgICAgICB1bnRyZWF0ZWQgPSAoCiAgICAgICAgICAgIDEyCiAgICAgICAgICAgICsgMyAqIGdyb3VwCiAgICAgICAgICAgICsgMC44ICogdAogICAgICAgICAgICArIGRpZmZlcmVudGlhbF90cmVuZCAqIGdyb3VwICogdAogICAgICAgICAgICArIHVuaXRfbGV2ZWwKICAgICAgICAgICAgKyBybmcubm9ybWFsKHNjYWxlPTEuNSwgc2l6ZT1ncm91cC5zaXplKQogICAgICAgICkKICAgICAgICBvdXRjb21lc1s6LCB0XSA9IHVudHJlYXRlZCArIHRydWVfZWZmZWN0ICogZ3JvdXAgKiBwb3N0W3RdCiAgICByZXR1cm4gZ3JvdXAsIG91dGNvbWVzCgpkZWYgZGlkX2Zyb21fdHdvX3BlcmlvZHMoZ3JvdXAsIHksIHByZV90PTIsIHBvc3RfdD01KToKICAgIHRyZWF0ZWRfY2hhbmdlID0geVtncm91cCA9PSAxLCBwb3N0X3RdLm1lYW4oKSAtIHlbZ3JvdXAgPT0gMSwgcHJlX3RdLm1lYW4oKQogICAgY29udHJvbF9jaGFuZ2UgPSB5W2dyb3VwID09IDAsIHBvc3RfdF0ubWVhbigpIC0geVtncm91cCA9PSAwLCBwcmVfdF0ubWVhbigpCiAgICByZXR1cm4gdHJlYXRlZF9jaGFuZ2UgLSBjb250cm9sX2NoYW5nZQoKZzEsIHlfcGFyYWxsZWwgPSBtYWtlX3BhbmVsKGRpZmZlcmVudGlhbF90cmVuZD0wLjApCmcyLCB5X3Zpb2xhdGlvbiA9IG1ha2VfcGFuZWwoZGlmZmVyZW50aWFsX3RyZW5kPTAuNSkKCnByZV9nYXBfY2hhbmdlX3BhcmFsbGVsID0gKAogICAgKHlfcGFyYWxsZWxbZzEgPT0gMSwgMl0ubWVhbigpIC0geV9wYXJhbGxlbFtnMSA9PSAwLCAyXS5tZWFuKCkpCiAgICAtICh5X3BhcmFsbGVsW2cxID09IDEsIDBdLm1lYW4oKSAtIHlfcGFyYWxsZWxbZzEgPT0gMCwgMF0ubWVhbigpKQopCnByZV9nYXBfY2hhbmdlX3Zpb2xhdGlvbiA9ICgKICAgICh5X3Zpb2xhdGlvbltnMiA9PSAxLCAyXS5tZWFuKCkgLSB5X3Zpb2xhdGlvbltnMiA9PSAwLCAyXS5tZWFuKCkpCiAgICAtICh5X3Zpb2xhdGlvbltnMiA9PSAxLCAwXS5tZWFuKCkgLSB5X3Zpb2xhdGlvbltnMiA9PSAwLCAwXS5tZWFuKCkpCikKCnByaW50KGYiVHJ1ZSBwb2xpY3kgZWZmZWN0OiAgICAgICAgICAgICAgICAgICAge3RydWVfZWZmZWN0Oi4zZn0iKQpwcmludChmIkRJRCB3aXRoIHBhcmFsbGVsIHVudHJlYXRlZCB0cmVuZHM6ICAgIHtkaWRfZnJvbV90d29fcGVyaW9kcyhnMSwgeV9wYXJhbGxlbCk6LjNmfSIpCnByaW50KGYiRElEIHdpdGggZGlmZmVyZW50aWFsIHRyZW5kOiAgICAgICAgICAge2RpZF9mcm9tX3R3b19wZXJpb2RzKGcyLCB5X3Zpb2xhdGlvbik6LjNmfSIpCnByaW50KGYiUHJlLXBlcmlvZCBnYXAgY2hhbmdlIChwYXJhbGxlbCk6ICAgICAgIHtwcmVfZ2FwX2NoYW5nZV9wYXJhbGxlbDouM2Z9IikKcHJpbnQoZiJQcmUtcGVyaW9kIGdhcCBjaGFuZ2UgKHZpb2xhdGlvbik6ICAgICAge3ByZV9nYXBfY2hhbmdlX3Zpb2xhdGlvbjouM2Z9Iik=","vertical","numpy","Python：平行趋势与趋势违背",[1796,3667,3668],{},"在违背情形中，DID 同时包含政策效应与原有趋势差。加入更多观测不会消除这种设计偏误。",[1807,3670,3672],{"id":3671},"_4-事件研究怎样读","4. 事件研究怎样读",[1796,3674,3675,3676,3746,3747,3865],{},"设首次处理时间为 ",[1837,3677,3679,3697],{"className":3678},[1844],[1837,3680,3682],{"className":3681},[1848],[1850,3683,3684],{"xmlns":1852},[1855,3685,3686,3694],{},[1858,3687,3688],{},[1861,3689,3690,3692],{},[1868,3691,3172],{},[1868,3693,2632],{},[2005,3695,3696],{"encoding":2007},"G_i",[1837,3698,3700],{"className":3699,"ariaHidden":1866},[2012],[1837,3701,3703,3706],{"className":3702},[2016],[1837,3704],{"className":3705,"style":2725},[2020],[1837,3707,3709,3712],{"className":3708},[2025],[1837,3710,3172],{"className":3711},[2025,2054],[1837,3713,3715],{"className":3714},[2082],[1837,3716,3718,3738],{"className":3717},[2033,2086],[1837,3719,3721,3735],{"className":3720},[2037],[1837,3722,3724],{"className":3723,"style":2744},[2041],[1837,3725,3726,3729],{"style":2868},[1837,3727],{"className":3728,"style":2100},[2049],[1837,3730,3732],{"className":3731},[2104,2105,2106,2107],[1837,3733,2632],{"className":3734},[2025,2054,2107],[1837,3736,2126],{"className":3737},[2125],[1837,3739,3741],{"className":3740},[2037],[1837,3742,3744],{"className":3743,"style":2133},[2041],[1837,3745],{},"，事件时间 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-1}\\beta_k\n\\mathbf 1\\{t-G_i=k\\}+\\varepsilon_{it}.",[1837,3975,3977,4038,4093,4148,4327,4382,4403],{"className":3976,"ariaHidden":1866},[2012],[1837,3978,3980,3983,4029,4032,4035],{"className":3979},[2016],[1837,3981],{"className":3982,"style":2725},[2020],[1837,3984,3986,3989],{"className":3985},[2025],[1837,3987,1898],{"className":3988,"style":2183},[2025,2054],[1837,3990,3992],{"className":3991},[2082],[1837,3993,3995,4021],{"className":3994},[2033,2086],[1837,3996,3998,4018],{"className":3997},[2037],[1837,3999,4001],{"className":4000,"style":2744},[2041],[1837,4002,4003,4006],{"style":2212},[1837,4004],{"className":4005,"style":2100},[2049],[1837,4007,4009],{"className":4008},[2104,2105,2106,2107],[1837,4010,4012,4015],{"className":4011},[2025,2107],[1837,4013,2632],{"className":4014},[2025,2054,2107],[1837,4016,1920],{"className":4017},[2025,2054,2107],[1837,4019,2126],{"className":4020},[2125],[1837,4022,4024],{"className":4023},[2037],[1837,4025,4027],{"className":4026,"style":2133},[2041],[1837,4028],{},[1837,4030],{"className":4031,"style":2140},[2139],[1837,4033,1887],{"className":4034},[2144],[1837,4036],{"className":4037,"style":2140},[2139],[1837,4039,4041,4044,4084,4087,4090],{"className":4040},[2016],[1837,4042],{"className":4043,"style":2788},[2020],[1837,4045,4047,4050],{"className":4046},[2025],[1837,4048,2641],{"className":4049,"style":2795},[2025,2054],[1837,4051,4053],{"className":4052},[2082],[1837,4054,4056,4076],{"className":4055},[2033,2086],[1837,4057,4059,4073],{"className":4058},[2037],[1837,4060,4062],{"className":4061,"style":2744},[2041],[1837,4063,4064,4067],{"style":2810},[1837,4065],{"className":4066,"style":2100},[2049],[1837,4068,4070],{"className":4069},[2104,2105,2106,2107],[1837,4071,2632],{"className":4072},[2025,2054,2107],[1837,4074,2126],{"className":4075},[2125],[1837,4077,4079],{"className":4078},[2037],[1837,4080,4082],{"className":4081,"style":2133},[2041],[1837,4083],{},[1837,4085],{"className":4086,"style":2183},[2139],[1837,4088,2646],{"className":4089},[2258],[1837,4091],{"className":4092,"style":2183},[2139],[1837,4094,4096,4099,4139,4142,4145],{"className":4095},[2016],[1837,4097],{"className":4098,"style":2846},[2020],[1837,4100,4102,4105],{"className":4101},[2025],[1837,4103,2651],{"className":4104},[2025,2054],[1837,4106,4108],{"className":4107},[2082],[1837,4109,4111,4131],{"className":4110},[2033,2086],[1837,4112,4114,4128],{"className":4113},[2037],[1837,4115,4117],{"className":4116,"style":2865},[2041],[1837,4118,4119,4122],{"style":2868},[1837,4120],{"className":4121,"style":2100},[2049],[1837,4123,4125],{"className":4124},[2104,2105,2106,2107],[1837,4126,1920],{"className":4127},[2025,2054,2107],[1837,4129,2126],{"className":4130},[2125],[1837,4132,4134],{"className":4133},[2037],[1837,4135,4137],{"className":4136,"style":2133},[2041],[1837,4138],{},[1837,4140],{"className":4141,"style":2183},[2139],[1837,4143,2646],{"className":4144},[2258],[1837,4146],{"className":4147,"style":2183},[2139],[1837,4149,4151,4155,4261,4265,4308,4312,4315,4318,4321,4324],{"className":4150},[2016],[1837,4152],{"className":4153,"style":4154},[2020],"height:2.4882em;vertical-align:-1.4382em;",[1837,4156,4160],{"className":4157},[4158,4159],"mop","op-limits",[1837,4161,4163,4252],{"className":4162},[2033,2086],[1837,4164,4166,4249],{"className":4165},[2037],[1837,4167,4170,4236],{"className":4168,"style":4169},[2041],"height:1.05em;",[1837,4171,4173,4177],{"style":4172},"top:-1.8479em;margin-left:0em;",[1837,4174],{"className":4175,"style":4176},[2049],"height:3.05em;",[1837,4178,4180],{"className":4179},[2104,2105,2106,2107],[1837,4181,4183,4186,4230,4233],{"className":4182},[2025,2107],[1837,4184,3761],{"className":4185,"style":3790},[2025,2054,2107],[1837,4187,4189,4223,4227],{"className":4188},[2144,2107],[1837,4190,4192],{"className":4191},[2144,2107],[1837,4193,4196],{"className":4194},[2025,4195,2107],"vbox",[1837,4197,4200],{"className":4198},[4199,2107],"thinbox",[1837,4201,4204,4208,4219],{"className":4202},[4203,2107],"rlap",[1837,4205],{"className":4206,"style":4207},[2020],"height:0.8889em;vertical-align:-0.1944em;",[1837,4209,4212],{"className":4210},[4211],"inner",[1837,4213,4215],{"className":4214},[2025,2107],[1837,4216,4218],{"className":4217},[2144,2107],"",[1837,4220],{"className":4221},[4222],"fix",[1837,4224],{"className":4225},[2139,4226,2107],"nobreak",[1837,4228,1887],{"className":4229},[2144,2107],[1837,4231,1923],{"className":4232},[2025,2107],[1837,4234,3926],{"className":4235},[2025,2107],[1837,4237,4239,4242],{"style":4238},"top:-3.05em;",[1837,4240],{"className":4241,"style":4176},[2049],[1837,4243,4244],{},[1837,4245,3914],{"className":4246},[4158,4247,4248],"op-symbol","large-op",[1837,4250,2126],{"className":4251},[2125],[1837,4253,4255],{"className":4254},[2037],[1837,4256,4259],{"className":4257,"style":4258},[2041],"height:1.4382em;",[1837,4260],{},[1837,4262],{"className":4263,"style":4264},[2139],"margin-right:0.1667em;",[1837,4266,4268,4272],{"className":4267},[2025],[1837,4269,3931],{"className":4270,"style":4271},[2025,2054],"margin-right:0.0528em;",[1837,4273,4275],{"className":4274},[2082],[1837,4276,4278,4300],{"className":4277},[2033,2086],[1837,4279,4281,4297],{"className":4280},[2037],[1837,4282,4285],{"className":4283,"style":4284},[2041],"height:0.3361em;",[1837,4286,4288,4291],{"style":4287},"top:-2.55em;margin-left:-0.0528em;margin-right:0.05em;",[1837,4289],{"className":4290,"style":2100},[2049],[1837,4292,4294],{"className":4293},[2104,2105,2106,2107],[1837,4295,3761],{"className":4296,"style":3790},[2025,2054,2107],[1837,4298,2126],{"className":4299},[2125],[1837,4301,4303],{"className":4302},[2037],[1837,4304,4306],{"className":4305,"style":2133},[2041],[1837,4307],{},[1837,4309,3926],{"className":4310},[2025,4311],"mathbf",[1837,4313,3939],{"className":4314},[2158],[1837,4316,1920],{"className":4317},[2025,2054],[1837,4319],{"className":4320,"style":2183},[2139],[1837,4322,1923],{"className":4323},[2258],[1837,4325],{"className":4326,"style":2183},[2139],[1837,4328,4330,4333,4373,4376,4379],{"className":4329},[2016],[1837,4331],{"className":4332,"style":2725},[2020],[1837,4334,4336,4339],{"className":4335},[2025],[1837,4337,3172],{"className":4338},[2025,2054],[1837,4340,4342],{"className":4341},[2082],[1837,4343,4345,4365],{"className":4344},[2033,2086],[1837,4346,4348,4362],{"className":4347},[2037],[1837,4349,4351],{"className":4350,"style":2744},[2041],[1837,4352,4353,4356],{"style":2868},[1837,4354],{"className":4355,"style":2100},[2049],[1837,4357,4359],{"className":4358},[2104,2105,2106,2107],[1837,4360,2632],{"className":4361},[2025,2054,2107],[1837,4363,2126],{"className":4364},[2125],[1837,4366,4368],{"className":4367},[2037],[1837,4369,4371],{"className":4370,"style":2133},[2041],[1837,4372],{},[1837,4374],{"className":4375,"style":2140},[2139],[1837,4377,1887],{"className":4378},[2144],[1837,4380],{"className":4381,"style":2140},[2139],[1837,4383,4385,4388,4391,4394,4397,4400],{"className":4384},[2016],[1837,4386],{"className":4387,"style":2904},[2020],[1837,4389,3761],{"className":4390,"style":3790},[2025,2054],[1837,4392,3956],{"className":4393},[2354],[1837,4395],{"className":4396,"style":2183},[2139],[1837,4398,2646],{"className":4399},[2258],[1837,4401],{"className":4402,"style":2183},[2139],[1837,4404,4406,4409,4455],{"className":4405},[2016],[1837,4407],{"className":4408,"style":3048},[2020],[1837,4410,4412,4415],{"className":4411},[2025],[1837,4413,2704],{"className":4414},[2025,2054],[1837,4416,4418],{"className":4417},[2082],[1837,4419,4421,4447],{"className":4420},[2033,2086],[1837,4422,4424,4444],{"className":4423},[2037],[1837,4425,4427],{"className":4426,"style":2744},[2041],[1837,4428,4429,4432],{"style":2868},[1837,4430],{"className":4431,"style":2100},[2049],[1837,4433,4435],{"className":4434},[2104,2105,2106,2107],[1837,4436,4438,4441],{"className":4437},[2025,2107],[1837,4439,2632],{"className":4440},[2025,2054,2107],[1837,4442,1920],{"className":4443},[2025,2054,2107],[1837,4445,2126],{"className":4446},[2125],[1837,4448,4450],{"className":4449},[2037],[1837,4451,4453],{"className":4452,"style":2133},[2041],[1837,4454],{},[1837,4456,2003],{"className":4457},[2025],[3635,4459,4460,4517,4573],{},[1817,4461,4462,4516],{},[1837,4463,4465,4484],{"className":4464},[1844],[1837,4466,4468],{"className":4467},[1848],[1850,4469,4470],{"xmlns":1852},[1855,4471,4472,4481],{},[1858,4473,4474,4476,4479],{},[1868,4475,3761],{},[1872,4477,4478],{},"\u003C",[2579,4480,3144],{},[2005,4482,4483],{"encoding":2007},"k\u003C0",[1837,4485,4487,4506],{"className":4486,"ariaHidden":1866},[2012],[1837,4488,4490,4494,4497,4500,4503],{"className":4489},[2016],[1837,4491],{"className":4492,"style":4493},[2020],"height:0.7335em;vertical-align:-0.0391em;",[1837,4495,3761],{"className":4496,"style":3790},[2025,2054],[1837,4498],{"className":4499,"style":2140},[2139],[1837,4501,4478],{"className":4502},[2144],[1837,4504],{"className":4505,"style":2140},[2139],[1837,4507,4509,4513],{"className":4508},[2016],[1837,4510],{"className":4511,"style":4512},[2020],"height:0.6444em;",[1837,4514,3144],{"className":4515},[2025],"：处理前系数，用于暴露预趋势、预期效应或时点错误；",[1817,4518,4519,4572],{},[1837,4520,4522,4541],{"className":4521},[1844],[1837,4523,4525],{"className":4524},[1848],[1850,4526,4527],{"xmlns":1852},[1855,4528,4529,4538],{},[1858,4530,4531,4533,4536],{},[1868,4532,3761],{},[1872,4534,4535],{},"≥",[2579,4537,3144],{},[2005,4539,4540],{"encoding":2007},"k\\ge 0",[1837,4542,4544,4563],{"className":4543,"ariaHidden":1866},[2012],[1837,4545,4547,4551,4554,4557,4560],{"className":4546},[2016],[1837,4548],{"className":4549,"style":4550},[2020],"height:0.8304em;vertical-align:-0.136em;",[1837,4552,3761],{"className":4553,"style":3790},[2025,2054],[1837,4555],{"className":4556,"style":2140},[2139],[1837,4558,4535],{"className":4559},[2144],[1837,4561],{"className":4562,"style":2140},[2139],[1837,4564,4566,4569],{"className":4565},[2016],[1837,4567],{"className":4568,"style":4512},[2020],[1837,4570,3144],{"className":4571},[2025],"：相对基准期的动态效应；",[1817,4574,4575,4576,4632],{},"省略期通常为 ",[1837,4577,4579,4599],{"className":4578},[1844],[1837,4580,4582],{"className":4581},[1848],[1850,4583,4584],{"xmlns":1852},[1855,4585,4586,4596],{},[1858,4587,4588,4590,4592,4594],{},[1868,4589,3761],{},[1872,4591,1887],{},[1872,4593,1923],{},[2579,4595,3926],{},[2005,4597,4598],{"encoding":2007},"k=-1",[1837,4600,4602,4620],{"className":4601,"ariaHidden":1866},[2012],[1837,4603,4605,4608,4611,4614,4617],{"className":4604},[2016],[1837,4606],{"className":4607,"style":3786},[2020],[1837,4609,3761],{"className":4610,"style":3790},[2025,2054],[1837,4612],{"className":4613,"style":2140},[2139],[1837,4615,1887],{"className":4616},[2144],[1837,4618],{"className":4619,"style":2140},[2139],[1837,4621,4623,4626,4629],{"className":4622},[2016],[1837,4624],{"className":4625,"style":2594},[2020],[1837,4627,1923],{"className":4628},[2025],[1837,4630,3926],{"className":4631},[2025],"，所有系数都相对它解释。",[1796,4634,4635],{},"“处理前系数不显著”不等于平行趋势成立：检验可能低功效，且研究者可能在看图后调整窗口。",[1807,4637,4639],{"id":4638},"_5-交错实施为何需要现代估计","5. 交错实施为何需要现代估计",[1796,4641,4642],{},"若不同组在不同时间接受永久处理，传统 TWFE 可能让已处理组充当后来处理组的比较组。在处理效应随组别或时间异质时，系数可能是难解释甚至带负权重的组合。",[1796,4644,4645],{},"更清楚的流程是：",[1814,4647,4648,4722,4725,4795],{},[1817,4649,4650,4651,4721],{},"定义组别—时间效应 ",[1837,4652,4654,4684],{"className":4653},[1844],[1837,4655,4657],{"className":4656},[1848],[1850,4658,4659],{"xmlns":1852},[1855,4660,4661,4681],{},[1858,4662,4663,4666,4668,4670,4672,4675,4677,4679],{},[1868,4664,4665],{},"A",[1868,4667,1906],{},[1868,4669,1906],{},[1872,4671,1891],{"stretchy":1890},[1868,4673,4674],{},"g",[1872,4676,1909],{"separator":1866},[1868,4678,1920],{},[1872,4680,1948],{"stretchy":1890},[2005,4682,4683],{"encoding":2007},"ATT(g,t)",[1837,4685,4687],{"className":4686,"ariaHidden":1866},[2012],[1837,4688,4690,4693,4696,4699,4702,4705,4709,4712,4715,4718],{"className":4689},[2016],[1837,4691],{"className":4692,"style":2904},[2020],[1837,4694,4665],{"className":4695},[2025,2054],[1837,4697,1906],{"className":4698,"style":2225},[2025,2054],[1837,4700,1906],{"className":4701,"style":2225},[2025,2054],[1837,4703,1891],{"className":4704},[2158],[1837,4706,4674],{"className":4707,"style":4708},[2025,2054],"margin-right:0.0359em;",[1837,4710,1909],{"className":4711},[2229],[1837,4713],{"className":4714,"style":4264},[2139],[1837,4716,1920],{"className":4717},[2025,2054],[1837,4719,1948],{"className":4720},[2354],"；",[1817,4723,4724],{},"只使用尚未处理或从未处理的有效比较组；",[1817,4726,4727,4728,4794],{},"先估计各 ",[1837,4729,4731,4758],{"className":4730},[1844],[1837,4732,4734],{"className":4733},[1848],[1850,4735,4736],{"xmlns":1852},[1855,4737,4738,4756],{},[1858,4739,4740,4742,4744,4746,4748,4750,4752,4754],{},[1868,4741,4665],{},[1868,4743,1906],{},[1868,4745,1906],{},[1872,4747,1891],{"stretchy":1890},[1868,4749,4674],{},[1872,4751,1909],{"separator":1866},[1868,4753,1920],{},[1872,4755,1948],{"stretchy":1890},[2005,4757,4683],{"encoding":2007},[1837,4759,4761],{"className":4760,"ariaHidden":1866},[2012],[1837,4762,4764,4767,4770,4773,4776,4779,4782,4785,4788,4791],{"className":4763},[2016],[1837,4765],{"className":4766,"style":2904},[2020],[1837,4768,4665],{"className":4769},[2025,2054],[1837,4771,1906],{"className":4772,"style":2225},[2025,2054],[1837,4774,1906],{"className":4775,"style":2225},[2025,2054],[1837,4777,1891],{"className":4778},[2158],[1837,4780,4674],{"className":4781,"style":4708},[2025,2054],[1837,4783,1909],{"className":4784},[2229],[1837,4786],{"className":4787,"style":4264},[2139],[1837,4789,1920],{"className":4790},[2025,2054],[1837,4792,1948],{"className":4793},[2354],"，再按明确权重聚合；",[1817,4796,4797],{},"分别展示日历时间、事件时间和组别异质性。",[1796,4799,4800,4801,4805,4806,4812],{},"2024 年 ",[4802,4803,4804],"em",{},"Review of Economic Studies"," 的 ",[2668,4807,4811],{"href":4808,"rel":4809},"https:\u002F\u002Facademic.oup.com\u002Frestud\u002Farticle\u002F91\u002F6\u002F3253\u002F7601390",[4810],"nofollow","Borusyak、Jaravel 与 Spiess"," 进一步系统化了交错事件研究的稳健且高效估计。",[1807,4814,4816],{"id":4815},"_6-诊断与报告","6. 诊断与报告",[3635,4818,4819,4822,4825,4828,4831,4834,4837],{},[1817,4820,4821],{},"处理何时宣布、何时开始、何时真正执行？",[1817,4823,4824],{},"比较组在每一期是谁？是否已受处理？",[1817,4826,4827],{},"政策是否引发迁移、提前反应或跨地区溢出？",[1817,4829,4830],{},"结果定义、采样频率和样本构成是否同期变化？",[1817,4832,4833],{},"标准误是否按政策分配层级聚类？",[1817,4835,4836],{},"事件研究是否给出同时置信带或多重检验说明？",[1817,4838,4839],{},"聚合权重是否对应政策问题？",[1807,4841,4842],{"id":4842},"常见误区",[3635,4844,4845,4848,4851,4854,4857],{},[1817,4846,4847],{},"把水平不相等误判为 DID 不可用；",[1817,4849,4850],{},"用一个不显著的处理前联合检验“证明”平行趋势；",[1817,4852,4853],{},"控制政策影响的中介变量；",[1817,4855,4856],{},"交错实施仍只报告一个 TWFE 系数；",[1817,4858,4859],{},"把处理前趋势校正当作无假设修复。",[1807,4861,4862],{"id":4862},"课堂任务",[1796,4864,4865],{},"为最低工资政策设计 DID：",[1814,4867,4868,4871,4874,4877,4880],{},[1817,4869,4870],{},"定义处理组、比较组、宣布期与执行期；",[1817,4872,4873],{},"写出未处理潜在结果下的平行趋势；",[1817,4875,4876],{},"指出一个可能的跨地区溢出；",[1817,4878,4879],{},"设计一个不应受最低工资影响的负向结果；",[1817,4881,4882,4883,4949],{},"说明分期上调时如何构造 ",[1837,4884,4886,4913],{"className":4885},[1844],[1837,4887,4889],{"className":4888},[1848],[1850,4890,4891],{"xmlns":1852},[1855,4892,4893,4911],{},[1858,4894,4895,4897,4899,4901,4903,4905,4907,4909],{},[1868,4896,4665],{},[1868,4898,1906],{},[1868,4900,1906],{},[1872,4902,1891],{"stretchy":1890},[1868,4904,4674],{},[1872,4906,1909],{"separator":1866},[1868,4908,1920],{},[1872,4910,1948],{"stretchy":1890},[2005,4912,4683],{"encoding":2007},[1837,4914,4916],{"className":4915,"ariaHidden":1866},[2012],[1837,4917,4919,4922,4925,4928,4931,4934,4937,4940,4943,4946],{"className":4918},[2016],[1837,4920],{"className":4921,"style":2904},[2020],[1837,4923,4665],{"className":4924},[2025,2054],[1837,4926,1906],{"className":4927,"style":2225},[2025,2054],[1837,4929,1906],{"className":4930,"style":2225},[2025,2054],[1837,4932,1891],{"className":4933},[2158],[1837,4935,4674],{"className":4936,"style":4708},[2025,2054],[1837,4938,1909],{"className":4939},[2229],[1837,4941],{"className":4942,"style":4264},[2139],[1837,4944,1920],{"className":4945},[2025,2054],[1837,4947,1948],{"className":4948},[2354],"。",[1807,4951,4952],{"id":4952},"核心阅读",[3635,4954,4955,4963,4971],{},[1817,4956,4957,4958,4949],{},"Callaway & Sant’Anna (2021), ",[2668,4959,4962],{"href":4960,"rel":4961},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jeconom.2020.12.001",[4810],"“Difference-in-Differences with Multiple Time Periods”",[1817,4964,4965,4966,4949],{},"Sun & Abraham (2021), ",[2668,4967,4970],{"href":4968,"rel":4969},"https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jeconom.2020.09.006",[4810],"“Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects”",[1817,4972,4973,4974,4949],{},"Borusyak, Jaravel & Spiess (2024), ",[2668,4975,4978],{"href":4976,"rel":4977},"https:\u002F\u002Fdoi.org\u002F10.1093\u002Frestud\u002Frdae007",[4810],"“Revisiting Event-Study Designs”",[1796,4980,4981,4982,4986,4987,4949],{},"上一章：",[2668,4983,4985],{"href":4984},"..\u002F04-panel\u002F","面板数据方法","｜下一章：",[2668,4988,4990],{"href":4989},"..\u002F06-rdd\u002F","断点回归设计",{"title":10,"searchDepth":4992,"depth":4992,"links":4993},2,[4994,4995,4996,4997,4998,4999,5000,5001,5002,5003],{"id":1809,"depth":4992,"text":1809},{"id":1834,"depth":4992,"text":1835},{"id":3103,"depth":4992,"text":3104},{"id":3654,"depth":4992,"text":3655},{"id":3671,"depth":4992,"text":3672},{"id":4638,"depth":4992,"text":4639},{"id":4815,"depth":4992,"text":4816},{"id":4842,"depth":4992,"text":4842},{"id":4862,"depth":4992,"text":4862},{"id":4952,"depth":4992,"text":4952},"从二乘二设计进入事件研究与交错实施，聚焦平行趋势、动态效应和有效比较组。","md",{"sidebar":5007},{"order":5008},5,true,{"title":1498,"description":5004},"acRdxS16HQ-KZg-HUzWJQj-utVRpy52NDptM7gXH68s",[5013,5015],{"title":1492,"path":1493,"stem":1494,"description":5014,"children":-1},"用同一单位的时间变化理解固定效应、双向固定效应、聚类推断与动态偏误。",{"title":1504,"path":1505,"stem":1506,"description":5016,"children":-1},"用阈值附近的局部比较理解连续性、带宽、操纵检验、局部多项式与模糊断点。",1785754751641]