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Predictive Analytics","\u002Fen\u002Fbusiness-analytics\u002F02-predictive","en\u002Fbusiness-analytics\u002F02-predictive\u002Findex",[343,344,348,352,356,360,364],{"title":339,"path":340,"stem":341,"sidebar":12},{"title":345,"path":346,"stem":347,"sidebar":12},"Validation, Baselines and Leakage","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage","en\u002Fbusiness-analytics\u002F02-predictive\u002F09-validation-leakage",{"title":349,"path":350,"stem":351,"sidebar":12},"Regression and Forecasting","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting","en\u002Fbusiness-analytics\u002F02-predictive\u002F10-regression-forecasting",{"title":353,"path":354,"stem":355,"sidebar":12},"Classification and Calibration","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration","en\u002Fbusiness-analytics\u002F02-predictive\u002F11-classification-calibration",{"title":357,"path":358,"stem":359,"sidebar":12},"Trees and Ensembles","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles","en\u002Fbusiness-analytics\u002F02-predictive\u002F12-trees-ensembles",{"title":361,"path":362,"stem":363,"sidebar":12},"Decision Metrics and Thresholds","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds","en\u002Fbusiness-analytics\u002F02-predictive\u002F13-decision-metrics-thresholds",{"title":365,"path":366,"stem":367,"sidebar":12},"Explainability, Monitoring and Drift","\u002Fen\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift","en\u002Fbusiness-analytics\u002F02-predictive\u002F14-explainability-drift",{"title":369,"path":370,"stem":371,"children":372,"sidebar":12},"3. Prescriptive Analytics","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive","en\u002Fbusiness-analytics\u002F03-prescriptive\u002Findex",[373,374,378,382,386,390,394],{"title":369,"path":370,"stem":371,"sidebar":12},{"title":375,"path":376,"stem":377,"sidebar":12},"Decision-Making under Uncertainty","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F15-decision-uncertainty",{"title":379,"path":380,"stem":381,"sidebar":12},"Linear Optimisation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F16-linear-optimization",{"title":383,"path":384,"stem":385,"sidebar":12},"Inventory and Allocation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F17-inventory-allocation",{"title":387,"path":388,"stem":389,"sidebar":12},"Queueing and Simulation","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F18-queueing-simulation",{"title":391,"path":392,"stem":393,"sidebar":12},"Pricing and Revenue Management","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F19-pricing-experimentation",{"title":395,"path":396,"stem":397,"sidebar":12},"Causal Targeting and Policy Learning","\u002Fen\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting","en\u002Fbusiness-analytics\u002F03-prescriptive\u002F20-causal-targeting",{"title":399,"path":400,"stem":401,"children":402,"sidebar":12},"4. Deployment and Governance","\u002Fen\u002Fbusiness-analytics\u002F04-deployment","en\u002Fbusiness-analytics\u002F04-deployment\u002Findex",[403,404,408,412],{"title":399,"path":400,"stem":401,"sidebar":12},{"title":405,"path":406,"stem":407,"sidebar":12},"Data Products and Monitoring","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring","en\u002Fbusiness-analytics\u002F04-deployment\u002F21-data-products-monitoring",{"title":409,"path":410,"stem":411,"sidebar":12},"Governance, Fairness and Privacy","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy","en\u002Fbusiness-analytics\u002F04-deployment\u002F22-governance-fairness-privacy",{"title":413,"path":414,"stem":415,"sidebar":12},"Adoption and Business Value","\u002Fen\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value","en\u002Fbusiness-analytics\u002F04-deployment\u002F23-adoption-value",{"title":417,"path":418,"stem":419,"children":420,"sidebar":12},"Appendix and Revision Tools","\u002Fen\u002Fbusiness-analytics\u002Fappendix","en\u002Fbusiness-analytics\u002Fappendix\u002Findex",[421,422,426,430],{"title":417,"path":418,"stem":419,"sidebar":12},{"title":423,"path":424,"stem":425,"sidebar":12},"Formula and Decision Map","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map","en\u002Fbusiness-analytics\u002Fappendix\u002F24-formula-map",{"title":427,"path":428,"stem":429,"sidebar":12},"Worked Examples and Pitfalls","\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls","en\u002Fbusiness-analytics\u002Fappendix\u002F25-worked-examples-pitfalls",{"title":88,"path":431,"stem":432,"sidebar":12},"\u002Fen\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map","en\u002Fbusiness-analytics\u002Fappendix\u002F26-reading-map",{"title":434,"path":435,"stem":436,"children":437,"sidebar":12},"Capstone — The Evening Delivery Promise","\u002Fen\u002Fbusiness-analytics\u002Fcapstone","en\u002Fbusiness-analytics\u002Fcapstone\u002Findex",[438],{"title":434,"path":435,"stem":436,"sidebar":12},{"title":440,"path":441,"stem":442,"children":443,"page":280},"Financial Economic Time Series","\u002Fen\u002Ffinancial-economic-time-series","en\u002Ffinancial-economic-time-series",[444,452,460,468,476,484,493,502,511,520,529],{"title":445,"path":446,"stem":447,"children":448,"sidebar":451},"Financial and Economic Time Series — Course Guide","\u002Fen\u002Ffinancial-economic-time-series\u002F00-intro","en\u002Ffinancial-economic-time-series\u002F00-intro\u002Findex",[449],{"title":445,"path":446,"stem":447,"sidebar":450},{"order":71},{"order":71},{"title":453,"path":454,"stem":455,"children":456,"sidebar":459},"Three Versions of Time Series","\u002Fen\u002Ffinancial-economic-time-series\u002F01-bridge","en\u002Ffinancial-economic-time-series\u002F01-bridge\u002Findex",[457],{"title":453,"path":454,"stem":455,"sidebar":458},{"order":204},{"order":204},{"title":461,"path":462,"stem":463,"children":464,"sidebar":467},"Data, Clocks, and Transformations","\u002Fen\u002Ffinancial-economic-time-series\u002F02-data-transformations","en\u002Ffinancial-economic-time-series\u002F02-data-transformations\u002Findex",[465],{"title":461,"path":462,"stem":463,"sidebar":466},{"order":210},{"order":210},{"title":469,"path":470,"stem":471,"children":472,"sidebar":475},"Predictive Regressions and Persistent Predictors","\u002Fen\u002Ffinancial-economic-time-series\u002F03-predictive-regressions","en\u002Ffinancial-economic-time-series\u002F03-predictive-regressions\u002Findex",[473],{"title":469,"path":470,"stem":471,"sidebar":474},{"order":216},{"order":216},{"title":477,"path":478,"stem":479,"children":480,"sidebar":483},"Volatility, Tails, and Financial Risk","\u002Fen\u002Ffinancial-economic-time-series\u002F04-volatility-risk","en\u002Ffinancial-economic-time-series\u002F04-volatility-risk\u002Findex",[481],{"title":477,"path":478,"stem":479,"sidebar":482},{"order":222},{"order":222},{"title":485,"path":486,"stem":487,"children":488,"sidebar":492},"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",[489],{"title":485,"path":486,"stem":487,"sidebar":490},{"order":491},5,{"order":491},{"title":494,"path":495,"stem":496,"children":497,"sidebar":501},"VAR, Structural Identification, and Local Projections","\u002Fen\u002Ffinancial-economic-time-series\u002F06-var-identification","en\u002Ffinancial-economic-time-series\u002F06-var-identification\u002Findex",[498],{"title":494,"path":495,"stem":496,"sidebar":499},{"order":500},6,{"order":500},{"title":503,"path":504,"stem":505,"children":506,"sidebar":510},"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",[507],{"title":503,"path":504,"stem":505,"sidebar":508},{"order":509},7,{"order":509},{"title":512,"path":513,"stem":514,"children":515,"sidebar":519},"Forecast Evaluation for Decisions","\u002Fen\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation","en\u002Ffinancial-economic-time-series\u002F08-forecast-evaluation\u002Findex",[516],{"title":512,"path":513,"stem":514,"sidebar":517},{"order":518},8,{"order":518},{"title":521,"path":522,"stem":523,"children":524,"sidebar":528},"Integrated R Laboratory","\u002Fen\u002Ffinancial-economic-time-series\u002F09-r-laboratory","en\u002Ffinancial-economic-time-series\u002F09-r-laboratory\u002Findex",[525],{"title":521,"path":522,"stem":523,"sidebar":526},{"order":527},9,{"order":527},{"title":530,"path":531,"stem":532,"children":533,"sidebar":537},"Capstones, Data, and Reading Ladder","\u002Fen\u002Ffinancial-economic-time-series\u002F10-capstone-readings","en\u002Ffinancial-economic-time-series\u002F10-capstone-readings\u002Findex",[534],{"title":530,"path":531,"stem":532,"sidebar":535},{"order":536},10,{"order":536},{"title":539,"path":540,"stem":541,"children":542,"page":280},"Intro To Economics","\u002Fen\u002Fintro-to-economics","en\u002Fintro-to-economics",[543,547,551,555,559,563,567,571,575,579,583,587,591],{"title":544,"path":545,"stem":546,"sidebar":12},"Introduction to Economics — Decisions, Markets, and the Macroeconomy","\u002Fen\u002Fintro-to-economics\u002F00-intro","en\u002Fintro-to-economics\u002F00-intro",{"title":548,"path":549,"stem":550,"sidebar":12},"Chapter 1 — Choice, Opportunity Cost, and Trade","\u002Fen\u002Fintro-to-economics\u002F01-foundations","en\u002Fintro-to-economics\u002F01-foundations",{"title":552,"path":553,"stem":554,"sidebar":12},"Chapter 2 — Demand, Supply, Equilibrium, and Welfare","\u002Fen\u002Fintro-to-economics\u002F02-demand-and-supply","en\u002Fintro-to-economics\u002F02-demand-and-supply",{"title":556,"path":557,"stem":558,"sidebar":12},"Chapter 3 — Elasticity, Revenue, and Tax Incidence","\u002Fen\u002Fintro-to-economics\u002F03-elasticity","en\u002Fintro-to-economics\u002F03-elasticity",{"title":560,"path":561,"stem":562,"sidebar":12},"Chapter 4 — Firms, Market Power, and Market Failure","\u002Fen\u002Fintro-to-economics\u002F04-market-structures","en\u002Fintro-to-economics\u002F04-market-structures",{"title":564,"path":565,"stem":566,"sidebar":12},"Chapter 5 — GDP, Income, Wealth, and Welfare","\u002Fen\u002Fintro-to-economics\u002F05-gdp-and-wealth","en\u002Fintro-to-economics\u002F05-gdp-and-wealth",{"title":568,"path":569,"stem":570,"sidebar":12},"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":572,"path":573,"stem":574,"sidebar":12},"Chapter 7 — Productivity, Technology, and Economic Growth","\u002Fen\u002Fintro-to-economics\u002F07-economic-growth","en\u002Fintro-to-economics\u002F07-economic-growth",{"title":576,"path":577,"stem":578,"sidebar":12},"Chapter 8 — Money, Credit, and Banking","\u002Fen\u002Fintro-to-economics\u002F08-money-and-banking","en\u002Fintro-to-economics\u002F08-money-and-banking",{"title":580,"path":581,"stem":582,"sidebar":12},"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":584,"path":585,"stem":586,"sidebar":12},"Chapter 10 — Fiscal Policy, Distribution, and Public Debt","\u002Fen\u002Fintro-to-economics\u002F10-fiscal-policy","en\u002Fintro-to-economics\u002F10-fiscal-policy",{"title":588,"path":589,"stem":590,"sidebar":12},"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":592,"path":593,"stem":594,"sidebar":12},"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":596,"path":597,"stem":598,"children":599,"page":280},"Microeconometrics","\u002Fen\u002Fmicroeconometrics","en\u002Fmicroeconometrics",[600,618,626,644,666,692,716,740,760,780],{"title":601,"path":602,"stem":603,"children":604,"sidebar":12},"0. Causal Questions and Designs","\u002Fen\u002Fmicroeconometrics\u002F00-foundations","en\u002Fmicroeconometrics\u002F00-foundations\u002Findex",[605,606,610,614],{"title":601,"path":602,"stem":603,"sidebar":12},{"title":607,"path":608,"stem":609,"sidebar":12},"Causal Questions and Estimands","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands","en\u002Fmicroeconometrics\u002F00-foundations\u002F01-causal-question-estimands",{"title":611,"path":612,"stem":613,"sidebar":12},"Potential Outcomes and Experiments","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments","en\u002Fmicroeconometrics\u002F00-foundations\u002F02-potential-outcomes-experiments",{"title":615,"path":616,"stem":617,"sidebar":12},"Causal Diagrams and Controls","\u002Fen\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls","en\u002Fmicroeconometrics\u002F00-foundations\u002F03-dags-controls",{"title":619,"path":620,"stem":621,"children":622,"sidebar":625},"Microeconometrics — Designing Credible Counterfactuals","\u002Fen\u002Fmicroeconometrics\u002F00-index","en\u002Fmicroeconometrics\u002F00-index",[623],{"title":619,"path":620,"stem":621,"sidebar":624},{"order":71},{"order":71},{"title":627,"path":628,"stem":629,"children":630,"sidebar":12},"1. Regression and Inference","\u002Fen\u002Fmicroeconometrics\u002F01-regression","en\u002Fmicroeconometrics\u002F01-regression\u002Findex",[631,632,636,640],{"title":627,"path":628,"stem":629,"sidebar":12},{"title":633,"path":634,"stem":635,"sidebar":12},"OLS as a Projection","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection","en\u002Fmicroeconometrics\u002F01-regression\u002F04-ols-projection",{"title":637,"path":638,"stem":639,"sidebar":12},"FWL, Selection and Controls","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls","en\u002Fmicroeconometrics\u002F01-regression\u002F05-fwl-selection-controls",{"title":641,"path":642,"stem":643,"sidebar":12},"Inference and Clustering","\u002Fen\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering","en\u002Fmicroeconometrics\u002F01-regression\u002F06-inference-clustering",{"title":645,"path":646,"stem":647,"children":648,"sidebar":12},"2. Instruments and Panel Data","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002Findex",[649,650,654,658,662],{"title":645,"path":646,"stem":647,"sidebar":12},{"title":651,"path":652,"stem":653,"sidebar":12},"Instrumental Variables","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F07-iv-identification",{"title":655,"path":656,"stem":657,"sidebar":12},"Weak Instruments and LATE","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F08-weak-iv-late",{"title":659,"path":660,"stem":661,"sidebar":12},"Panel Fixed Effects","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F09-panel-fixed-effects",{"title":663,"path":664,"stem":665,"sidebar":12},"Dynamic Panels and Limits","\u002Fen\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel","en\u002Fmicroeconometrics\u002F02-iv-panel\u002F10-dynamic-panel",{"title":667,"path":668,"stem":669,"children":670,"sidebar":12},"3. Policy Evaluation Designs","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs","en\u002Fmicroeconometrics\u002F03-policy-designs\u002Findex",[671,672,676,680,684,688],{"title":667,"path":668,"stem":669,"sidebar":12},{"title":673,"path":674,"stem":675,"sidebar":12},"Difference-in-Differences","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F11-did-core",{"title":677,"path":678,"stem":679,"sidebar":12},"Staggered DID and Event Studies","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F12-staggered-event-studies",{"title":681,"path":682,"stem":683,"sidebar":12},"Regression Discontinuity","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F13-rdd",{"title":685,"path":686,"stem":687,"sidebar":12},"Matching, Weighting and Overlap","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F14-matching-weighting",{"title":689,"path":690,"stem":691,"sidebar":12},"Synthetic Control","\u002Fen\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control","en\u002Fmicroeconometrics\u002F03-policy-designs\u002F15-synthetic-control",{"title":693,"path":694,"stem":695,"children":696,"sidebar":715},"Module 4 — Choice and Limited Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002Findex",[697,699,703,707,711],{"title":693,"path":694,"stem":695,"sidebar":698},{"order":222},{"title":700,"path":701,"stem":702,"sidebar":12},"Binary Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F16-binary-choice",{"title":704,"path":705,"stem":706,"sidebar":12},"Multinomial and Ordered Choice","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F17-multinomial-choice",{"title":708,"path":709,"stem":710,"sidebar":12},"Count Outcomes","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F18-count-outcomes",{"title":712,"path":713,"stem":714,"sidebar":12},"Censoring, Truncation and Selection","\u002Fen\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection","en\u002Fmicroeconometrics\u002F04-outcomes-choice\u002F19-censoring-selection",{"order":222},{"title":717,"path":718,"stem":719,"children":720,"sidebar":739},"Module 5 — Modern Causal Analysis","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal","en\u002Fmicroeconometrics\u002F05-modern-causal\u002Findex",[721,723,727,731,735],{"title":717,"path":718,"stem":719,"sidebar":722},{"order":491},{"title":724,"path":725,"stem":726,"sidebar":12},"Double Machine Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F20-dml",{"title":728,"path":729,"stem":730,"sidebar":12},"Heterogeneity and Policy Learning","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F21-heterogeneity-policy",{"title":732,"path":733,"stem":734,"sidebar":12},"Sensitivity and Partial Identification","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F22-sensitivity-partial-id",{"title":736,"path":737,"stem":738,"sidebar":12},"External Validity and Transport","\u002Fen\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity","en\u002Fmicroeconometrics\u002F05-modern-causal\u002F23-external-validity",{"order":491},{"title":741,"path":742,"stem":743,"children":744,"sidebar":759},"Module 6 — From Data to Auditable Evidence","\u002Fen\u002Fmicroeconometrics\u002F06-workflow","en\u002Fmicroeconometrics\u002F06-workflow\u002Findex",[745,747,751,755],{"title":741,"path":742,"stem":743,"sidebar":746},{"order":500},{"title":748,"path":749,"stem":750,"sidebar":12},"Data Provenance","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance","en\u002Fmicroeconometrics\u002F06-workflow\u002F24-data-provenance",{"title":752,"path":753,"stem":754,"sidebar":12},"Reproducibility and Reporting","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting","en\u002Fmicroeconometrics\u002F06-workflow\u002F25-reproducibility-reporting",{"title":756,"path":757,"stem":758,"sidebar":12},"Paper and Evidence Audit","\u002Fen\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit","en\u002Fmicroeconometrics\u002F06-workflow\u002F26-paper-audit",{"order":500},{"title":761,"path":762,"stem":763,"children":764,"sidebar":779},"Appendix — Revision and Evidence Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix","en\u002Fmicroeconometrics\u002Fappendix\u002Findex",[765,767,771,775],{"title":761,"path":762,"stem":763,"sidebar":766},{"order":518},{"title":768,"path":769,"stem":770,"sidebar":12},"Formula and Design Map","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map","en\u002Fmicroeconometrics\u002Fappendix\u002F27-formula-design-map",{"title":772,"path":773,"stem":774,"sidebar":12},"Ten Worked Microeconometric Pitfalls","\u002Fen\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls","en\u002Fmicroeconometrics\u002Fappendix\u002F28-worked-pitfalls",{"title":776,"path":777,"stem":778,"sidebar":12},"Reading and Software 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Duality, and Revealed Preference","\u002Fen\u002Fmicroeconomics\u002F01-fundations","en\u002Fmicroeconomics\u002F01-fundations\u002Findex",[804],{"title":800,"path":801,"stem":802,"sidebar":12},{"title":806,"path":807,"stem":808,"children":809,"sidebar":12},"Module 2 — Comparative Statics and Welfare Measurement","\u002Fen\u002Fmicroeconomics\u002F02-comparative-statics","en\u002Fmicroeconomics\u002F02-comparative-statics\u002Findex",[810],{"title":806,"path":807,"stem":808,"sidebar":12},{"title":812,"path":813,"stem":814,"children":815,"sidebar":12},"Module 3 — Choice under Risk and Insurance","\u002Fen\u002Fmicroeconomics\u002F03-uncertainty","en\u002Fmicroeconomics\u002F03-uncertainty\u002Findex",[816],{"title":812,"path":813,"stem":814,"sidebar":12},{"title":818,"path":819,"stem":820,"children":821,"sidebar":12},"Module 4 — General Equilibrium and Welfare","\u002Fen\u002Fmicroeconomics\u002F04-general-equilibrium","en\u002Fmicroeconomics\u002F04-general-equilibrium\u002Findex",[822],{"title":818,"path":819,"stem":820,"sidebar":12},{"title":824,"path":825,"stem":826,"children":827,"sidebar":12},"Module 5 — Static, Dynamic, and Repeated Games","\u002Fen\u002Fmicroeconomics\u002F05-game-theory","en\u002Fmicroeconomics\u002F05-game-theory\u002Findex",[828],{"title":824,"path":825,"stem":826,"sidebar":12},{"title":830,"path":831,"stem":832,"children":833,"sidebar":12},"Module 6 — Oligopoly, Entry, and Algorithmic Pricing","\u002Fen\u002Fmicroeconomics\u002F06-oligopoly","en\u002Fmicroeconomics\u002F06-oligopoly\u002Findex",[834],{"title":830,"path":831,"stem":832,"sidebar":12},{"title":836,"path":837,"stem":838,"children":839,"sidebar":12},"Module 7 — Information Economics and Contracts","\u002Fen\u002Fmicroeconomics\u002F07-information-economics","en\u002Fmicroeconomics\u002F07-information-economics\u002Findex",[840],{"title":836,"path":837,"stem":838,"sidebar":12},{"title":842,"path":843,"stem":844,"children":845,"sidebar":12},"Module 8 — Mechanism Design and Auctions","\u002Fen\u002Fmicroeconomics\u002F08-mechanism-design","en\u002Fmicroeconomics\u002F08-mechanism-design\u002Findex",[846],{"title":842,"path":843,"stem":844,"sidebar":12},{"title":848,"path":849,"stem":850,"children":851,"sidebar":12},"Module 9 — Behavioural and Experimental Microeconomics","\u002Fen\u002Fmicroeconomics\u002F09-behavioural-economics","en\u002Fmicroeconomics\u002F09-behavioural-economics\u002Findex",[852],{"title":848,"path":849,"stem":850,"sidebar":12},{"title":854,"path":855,"stem":856,"children":857,"sidebar":12},"Module 10 — Externalities, Public Goods, and Collective Action","\u002Fen\u002Fmicroeconomics\u002F10-externalities-public-goods","en\u002Fmicroeconomics\u002F10-externalities-public-goods\u002Findex",[858],{"title":854,"path":855,"stem":856,"sidebar":12},{"title":860,"path":861,"stem":862,"children":863,"sidebar":12},"Module 11 — Matching and Market Design","\u002Fen\u002Fmicroeconomics\u002F11-market-design","en\u002Fmicroeconomics\u002F11-market-design\u002Findex",[864],{"title":860,"path":861,"stem":862,"sidebar":12},{"title":866,"path":867,"stem":868,"children":869,"sidebar":12},"Module 12 — Integrated Microeconomic Design Studio","\u002Fen\u002Fmicroeconomics\u002F12-review","en\u002Fmicroeconomics\u002F12-review\u002Findex",[870],{"title":866,"path":867,"stem":868,"sidebar":12},{"title":872,"path":873,"stem":874,"children":875,"sidebar":12},"Playground","\u002Fen\u002Fplayground","en\u002Fplayground\u002Findex",[876,877,881,885,889,893],{"title":872,"path":873,"stem":874,"sidebar":12},{"title":878,"path":879,"stem":880,"sidebar":12},"Typst Plugin Playground","\u002Fen\u002Fplayground\u002F01-typstex","en\u002Fplayground\u002F01-typstex",{"title":882,"path":883,"stem":884,"sidebar":12},"Citation Plugin Test","\u002Fen\u002Fplayground\u002F02-citation","en\u002Fplayground\u002F02-citation",{"title":886,"path":887,"stem":888,"sidebar":12},"Pyodide Playground","\u002Fen\u002Fplayground\u002F03-pyodide","en\u002Fplayground\u002F03-pyodide",{"title":890,"path":891,"stem":892,"sidebar":12},"WebR Playground","\u002Fen\u002Fplayground\u002F04-webr","en\u002Fplayground\u002F04-webr",{"title":894,"path":895,"stem":896,"sidebar":12},"Chart.js Visualizations","\u002Fen\u002Fplayground\u002F05-chartjs","en\u002Fplayground\u002F05-chartjs",{"title":898,"path":899,"stem":900,"children":901,"page":280},"Statistics For Insurance","\u002Fen\u002Fstatistics-for-insurance","en\u002Fstatistics-for-insurance",[902,910,938,971,999,1027,1040],{"title":903,"path":904,"stem":905,"children":906,"sidebar":909},"Statistics for General Insurance","\u002Fen\u002Fstatistics-for-insurance\u002F01-intro","en\u002Fstatistics-for-insurance\u002F01-intro\u002Findex",[907],{"title":903,"path":904,"stem":905,"sidebar":908},{"order":71},{"order":71},{"title":911,"path":912,"stem":913,"children":914,"sidebar":937},"Claims Development and Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002Findex",[915,917,922,927,932],{"title":911,"path":912,"stem":913,"sidebar":916},{"order":71},{"title":918,"path":919,"stem":920,"sidebar":921},"Basic Chain Ladder","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F01-basic-chain",{"order":204},{"title":923,"path":924,"stem":925,"sidebar":926},"Frequency–Severity Reserving","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F02-average-per-claim",{"order":210},{"title":928,"path":929,"stem":930,"sidebar":931},"Bornhuetter–Ferguson Method","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F03-b-f-method",{"order":216},{"title":933,"path":934,"stem":935,"sidebar":936},"Uncertainty and Diagnostics","\u002Fen\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics","en\u002Fstatistics-for-insurance\u002F02-chain-ladder\u002F04-uncertainty-diagnostics",{"order":222},{"order":71},{"title":939,"path":940,"stem":941,"children":942,"sidebar":970},"Frequency and Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002Findex",[943,945,950,955,960,965],{"title":939,"path":940,"stem":941,"sidebar":944},{"order":71},{"title":946,"path":947,"stem":948,"sidebar":949},"Core Severity Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F01-loss-dist",{"order":204},{"title":951,"path":952,"stem":953,"sidebar":954},"Tail Models and Extreme Values","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F02-more-dist",{"order":210},{"title":956,"path":957,"stem":958,"sidebar":959},"Claim Count Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F03-case-dist",{"order":216},{"title":961,"path":962,"stem":963,"sidebar":964},"Fitting and Validating Loss Models","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F04-fit-dist",{"order":222},{"title":966,"path":967,"stem":968,"sidebar":969},"Mixtures and Heterogeneity","\u002Fen\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist","en\u002Fstatistics-for-insurance\u002F03-common-dist\u002F05-mix-dist",{"order":491},{"order":71},{"title":972,"path":973,"stem":974,"children":975,"sidebar":998},"Reinsurance as a Loss Transformation","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002Findex",[976,978,983,988,993],{"title":972,"path":973,"stem":974,"sidebar":977},{"order":71},{"title":979,"path":980,"stem":981,"sidebar":982},"Proportional Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F01-proportional",{"order":204},{"title":984,"path":985,"stem":986,"sidebar":987},"Excess-of-Loss Reinsurance","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F02-excess",{"order":210},{"title":989,"path":990,"stem":991,"sidebar":992},"Inflation and Layer Erosion","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F03-inflation",{"order":216},{"title":994,"path":995,"stem":996,"sidebar":997},"Reinsurance Decision Lab","\u002Fen\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples","en\u002Fstatistics-for-insurance\u002F04-reinsurance\u002F04-examples",{"order":222},{"order":71},{"title":1000,"path":1001,"stem":1002,"children":1003,"sidebar":1026},"Aggregate Risk and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002Findex",[1004,1006,1011,1016,1021],{"title":1000,"path":1001,"stem":1002,"sidebar":1005},{"order":71},{"title":1007,"path":1008,"stem":1009,"sidebar":1010},"Collective Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F01-collective",{"order":204},{"title":1012,"path":1013,"stem":1014,"sidebar":1015},"Individual Risk Model","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F02-individual",{"order":210},{"title":1017,"path":1018,"stem":1019,"sidebar":1020},"Aggregate Risk Computation Lab","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F03-examples",{"order":216},{"title":1022,"path":1023,"stem":1024,"sidebar":1025},"Tail Risk, Dependence, and Capital","\u002Fen\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital","en\u002Fstatistics-for-insurance\u002F05-risk-theory\u002F04-tail-capital",{"order":222},{"order":71},{"title":1028,"path":1029,"stem":1030,"children":1031,"sidebar":1039},"Surplus and Ruin Theory","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002Findex",[1032,1034],{"title":1028,"path":1029,"stem":1030,"sidebar":1033},{"order":71},{"title":1035,"path":1036,"stem":1037,"sidebar":1038},"Finite-Time Ruin Simulation","\u002Fen\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation","en\u002Fstatistics-for-insurance\u002F06-ruin-theory\u002F01-finite-time-simulation",{"order":204},{"order":71},{"title":1041,"path":1042,"stem":1043,"children":1044,"sidebar":1047},"Portfolio Risk Capstone","\u002Fen\u002Fstatistics-for-insurance\u002F07-capstone","en\u002Fstatistics-for-insurance\u002F07-capstone\u002Findex",[1045],{"title":1041,"path":1042,"stem":1043,"sidebar":1046},{"order":71},{"order":71},{"title":1049,"path":1050,"stem":1051,"children":1052,"page":280},"Time Series","\u002Fen\u002Ftime-series","en\u002Ftime-series",[1053,1066,1074,1082,1090,1098,1106,1114,1142],{"title":1054,"path":1055,"stem":1056,"children":1057,"sidebar":1065},"Classical Time Series — Course Guide","\u002Fen\u002Ftime-series\u002F00-intro","en\u002Ftime-series\u002F00-intro\u002Findex",[1058,1060],{"title":1054,"path":1055,"stem":1056,"sidebar":1059},{"order":71},{"title":1061,"path":1062,"stem":1063,"sidebar":1064},"Preparation — Stationarity in 30 Minutes","\u002Fen\u002Ftime-series\u002F00-intro\u002F01-stationary","en\u002Ftime-series\u002F00-intro\u002F01-stationary",{"order":204},{"order":71},{"title":1067,"path":1068,"stem":1069,"children":1070,"sidebar":1073},"Module 1 — Processes, Dependence, and Stationarity","\u002Fen\u002Ftime-series\u002F01-stochastic-process","en\u002Ftime-series\u002F01-stochastic-process\u002Findex",[1071],{"title":1067,"path":1068,"stem":1069,"sidebar":1072},{"order":204},{"order":204},{"title":1075,"path":1076,"stem":1077,"children":1078,"sidebar":1081},"Module 2 — ARMA, ARIMA, and Model Identification","\u002Fen\u002Ftime-series\u002F02-arma","en\u002Ftime-series\u002F02-arma\u002Findex",[1079],{"title":1075,"path":1076,"stem":1077,"sidebar":1080},{"order":210},{"order":210},{"title":1083,"path":1084,"stem":1085,"children":1086,"sidebar":1089},"Module 3 — Linear Prediction and State-Space Recursions","\u002Fen\u002Ftime-series\u002F03-prediction","en\u002Ftime-series\u002F03-prediction\u002Findex",[1087],{"title":1083,"path":1084,"stem":1085,"sidebar":1088},{"order":216},{"order":216},{"title":1091,"path":1092,"stem":1093,"children":1094,"sidebar":1097},"Module 4 — Estimation, Likelihood, and Inference","\u002Fen\u002Ftime-series\u002F04-estimation","en\u002Ftime-series\u002F04-estimation\u002Findex",[1095],{"title":1091,"path":1092,"stem":1093,"sidebar":1096},{"order":222},{"order":222},{"title":1099,"path":1100,"stem":1101,"children":1102,"sidebar":1105},"Module 5 — Systems, Seasonality, and Cointegration","\u002Fen\u002Ftime-series\u002F05-multi-ar","en\u002Ftime-series\u002F05-multi-ar\u002Findex",[1103],{"title":1099,"path":1100,"stem":1101,"sidebar":1104},{"order":491},{"order":491},{"title":1107,"path":1108,"stem":1109,"children":1110,"sidebar":1113},"Module 6 — Spectral Analysis, Cycles, and Filters","\u002Fen\u002Ftime-series\u002F06-spectral-analysis","en\u002Ftime-series\u002F06-spectral-analysis\u002Findex",[1111],{"title":1107,"path":1108,"stem":1109,"sidebar":1112},{"order":500},{"order":500},{"title":1115,"path":1116,"stem":1117,"children":1118,"sidebar":1141},"R Matrix Laboratory","\u002Fen\u002Ftime-series\u002F07-r-implementation","en\u002Ftime-series\u002F07-r-implementation\u002Findex",[1119,1121,1126,1131,1136],{"title":1115,"path":1116,"stem":1117,"sidebar":1120},{"order":509},{"title":1122,"path":1123,"stem":1124,"sidebar":1125},"R Matrix Lab 1 — Covariance Geometry","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices","en\u002Ftime-series\u002F07-r-implementation\u002F01-covariance-matrices",{"order":204},{"title":1127,"path":1128,"stem":1129,"sidebar":1130},"R Matrix Lab 2 — AR Recursions and Yule–Walker Equations","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions","en\u002Ftime-series\u002F07-r-implementation\u002F02-ar-recursions",{"order":210},{"title":1132,"path":1133,"stem":1134,"sidebar":1135},"R Matrix Lab 3 — Prediction and Gaussian Likelihood","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood","en\u002Ftime-series\u002F07-r-implementation\u002F03-prediction-likelihood",{"order":216},{"title":1137,"path":1138,"stem":1139,"sidebar":1140},"R Matrix Lab 4 — State Space and Kalman Filtering","\u002Fen\u002Ftime-series\u002F07-r-implementation\u002F04-state-space","en\u002Ftime-series\u002F07-r-implementation\u002F04-state-space",{"order":222},{"order":509},{"title":1143,"path":1144,"stem":1145,"children":1146,"sidebar":1169},"Optional Python Appendix — Empirical Forecasting","\u002Fen\u002Ftime-series\u002F08-python-implementation","en\u002Ftime-series\u002F08-python-implementation\u002Findex",[1147,1149,1154,1159,1164],{"title":1143,"path":1144,"stem":1145,"sidebar":1148},{"order":518},{"title":1150,"path":1151,"stem":1152,"sidebar":1153},"Optional Python Lab 1 — Explore Before Modeling","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F01-exploration","en\u002Ftime-series\u002F08-python-implementation\u002F01-exploration",{"order":204},{"title":1155,"path":1156,"stem":1157,"sidebar":1158},"Optional Python Lab 2 — Diagnose Stationarity","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity","en\u002Ftime-series\u002F08-python-implementation\u002F02-stationarity",{"order":210},{"title":1160,"path":1161,"stem":1162,"sidebar":1163},"Optional Python Lab 3 — Fit and Audit ARMA Errors","\u002Fen\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting","en\u002Ftime-series\u002F08-python-implementation\u002F03-arma-fitting",{"order":216},{"title":1165,"path":1166,"stem":1167,"sidebar":1168},"Optional Python Lab 4 — Forecast, Backtest, and 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Alpha 策略全流程","\u002Fzh\u002Fquant\u002F09-case-study","zh\u002Fquant\u002F09-case-study",{"order":527},{"title":2100,"path":2101,"stem":2102,"sidebar":2103},"量化投资文献与软件图谱","\u002Fzh\u002Fquant\u002F10-reading-software-map","zh\u002Fquant\u002F10-reading-software-map",{"order":536},{"path":1386},{"id":2106,"title":218,"body":2107,"description":3489,"extension":3490,"features":12,"hero":12,"layout":12,"locale":12,"meta":3491,"navigation":12,"path":219,"published":3492,"seo":3493,"sidebar":3494,"stem":220,"__hash__":3495},"docs\u002Fen\u002Faccounting\u002Ffoundation\u002F03-decision-workshop.md",{"type":2108,"value":2109,"toc":3479},"minimark",[2110,2114,2118,2126,2131,2165,2168,2172,2175,2178,2209,2213,2301,2304,2374,2378,2381,2384,2428,2432,2435,2442,2533,2537,2544,2602,2628,3438,3442,3445,3449,3452,3455,3468],[2111,2112],"span",{"id":2113},"accounting-decision-workshop",[2115,2116,2117],"p",{},"Choosing a measure begins with the question you want to answer. A cash balance, a profit margin and an NPV describe different aspects of a business; a favourable result in one does not settle the others. The examples below connect each calculation to its purpose and show where further evidence is needed.",[2115,2119,2120,2121,2125],{},"Each example uses an ",[2122,2123,2124],"strong",{},"independent fictional dataset",", with amounts in pounds. Keep the balances separate from those in other examples and from Northstar. Read the explanations alongside the data, or close the feedback and use the questions for self-checking.",[2127,2128,2130],"h2",{"id":2129},"what-each-tool-contributes","What each tool contributes",[2132,2133,2134,2141,2147,2153,2159],"ul",{},[2135,2136,2137,2140],"li",{},[2122,2138,2139],{},"Cash-flow classification"," explains where a change in cash came from. Borrowing can increase cash without creating revenue.",[2135,2142,2143,2146],{},[2122,2144,2145],{},"Ratios"," relate selected figures to one another. An unchanged ratio may conceal a change in the composition of its inputs.",[2135,2148,2149,2152],{},[2122,2150,2151],{},"Contribution analysis"," shows how sales cover variable and fixed costs under stated assumptions. It does not predict the demand response to a price change.",[2135,2154,2155,2158],{},[2122,2156,2157],{},"Flexible budgets"," compare actual costs with budgeted costs at actual activity. A remaining variance is something to investigate, not a complete explanation of its cause.",[2135,2160,2161,2164],{},[2122,2162,2163],{},"Investment appraisal"," compares future incremental cash flows. NPV measures value at a required return, while payback focuses on recovery time; neither guarantees the forecast.",[2115,2166,2167],{},"Keep those distinctions in mind as you read the examples. The aim is to understand why a calculation is suitable for a question and what it leaves unanswered.",[2127,2169,2171],{"id":2170},"example-1-cash-flow-classification","Example 1: Cash-flow classification",[2115,2173,2174],{},"Opening cash is £4,000. Customers pay £48,000; suppliers receive £25,000 and staff receive £12,000. The business buys equipment for £8,000 cash, receives a £10,000 loan and repays £3,000 of loan principal. These are all the cash movements; there is no interest or tax in this task.",[2115,2176,2177],{},"Classify operating, investing and financing flows, then reconcile closing cash. Explain why neither a new loan nor the equipment payment is revenue or an immediate expense of the same amount.",[2179,2180,2182,2201],"legacy-spoiler",{"title":2181},"Feedback",[2115,2183,2184,2185,2188,2189,2192,2193,2196,2197,2200],{},"Operating cash = £48,000 − £25,000 − £12,000 = ",[2122,2186,2187],{},"£11,000",". Investing cash = ",[2122,2190,2191],{},"−£8,000",". Financing cash = £10,000 − £3,000 = ",[2122,2194,2195],{},"£7,000",". Net increase = £10,000 and closing cash = ",[2122,2198,2199],{},"£14,000",".",[2115,2202,2203,2204,2200],{},"The loan creates a liability; equipment is initially an asset. Depreciation is a later allocation, not a second equipment payment. Profit cannot be calculated without revenue, expense and accrual information. Compare the ",[2205,2206,2208],"a",{"href":2207},"..\u002Ffinancial-accounting\u002F04-reporting-cash\u002F06-financial-statements","cash-flow discussion",[2127,2210,2212],{"id":2211},"example-2-ratios-and-a-defensible-explanation","Example 2: Ratios and a defensible explanation",[2214,2215,2216,2233],"table",{},[2217,2218,2219],"thead",{},[2220,2221,2222,2226,2230],"tr",{},[2223,2224,2225],"th",{},"Item",[2223,2227,2229],{"align":2228},"right","Year 1 £",[2223,2231,2232],{"align":2228},"Year 2 £",[2234,2235,2236,2248,2259,2270,2280,2290],"tbody",{},[2220,2237,2238,2242,2245],{},[2239,2240,2241],"td",{},"Revenue",[2239,2243,2244],{"align":2228},"100,000",[2239,2246,2247],{"align":2228},"120,000",[2220,2249,2250,2253,2256],{},[2239,2251,2252],{},"Gross profit",[2239,2254,2255],{"align":2228},"40,000",[2239,2257,2258],{"align":2228},"42,000",[2220,2260,2261,2264,2267],{},[2239,2262,2263],{},"Net profit",[2239,2265,2266],{"align":2228},"8,000",[2239,2268,2269],{"align":2228},"6,000",[2220,2271,2272,2275,2278],{},[2239,2273,2274],{},"Current assets",[2239,2276,2277],{"align":2228},"30,000",[2239,2279,2255],{"align":2228},[2220,2281,2282,2284,2287],{},[2239,2283,146],{},[2239,2285,2286],{"align":2228},"12,000",[2239,2288,2289],{"align":2228},"25,000",[2220,2291,2292,2295,2298],{},[2239,2293,2294],{},"Current liabilities",[2239,2296,2297],{"align":2228},"15,000",[2239,2299,2300],{"align":2228},"20,000",[2115,2302,2303],{},"Assume current assets consist only of cash, receivables and inventory. Calculate gross and net margins, current ratio and quick ratio for each year. Consider what the comparison tells a supplier who is deciding whether to offer a longer credit period. Identify two items of further evidence; avoid a universal “safe” ratio threshold.",[2179,2305,2306,2366],{"title":2181},[2214,2307,2308,2321],{},[2217,2309,2310],{},[2220,2311,2312,2315,2318],{},[2223,2313,2314],{},"Measure",[2223,2316,2317],{"align":2228},"Year 1",[2223,2319,2320],{"align":2228},"Year 2",[2234,2322,2323,2334,2345,2355],{},[2220,2324,2325,2328,2331],{},[2239,2326,2327],{},"Gross margin: gross profit \u002F revenue",[2239,2329,2330],{"align":2228},"40%",[2239,2332,2333],{"align":2228},"35%",[2220,2335,2336,2339,2342],{},[2239,2337,2338],{},"Net margin: net profit \u002F revenue",[2239,2340,2341],{"align":2228},"8%",[2239,2343,2344],{"align":2228},"5%",[2220,2346,2347,2350,2353],{},[2239,2348,2349],{},"Current ratio: current assets \u002F current liabilities",[2239,2351,2352],{"align":2228},"2.00",[2239,2354,2352],{"align":2228},[2220,2356,2357,2360,2363],{},[2239,2358,2359],{},"Quick ratio: (current assets − inventory) \u002F current liabilities",[2239,2361,2362],{"align":2228},"1.20",[2239,2364,2365],{"align":2228},"0.75",[2115,2367,2368,2369,2373],{},"Revenue rose 20%, but margins fell. Although the current ratio is unchanged, it now relies more heavily on inventory. That warrants a closer look at liquidity, but does not establish that the business will default or that its stock is obsolete. Request receivable ageing and information on inventory sales and obsolescence, then compare payment commitments with the cash forecast. The ratios alone cannot tell you when cash will be collected. See ",[2205,2370,2372],{"href":2371},"..\u002Ffinancial-accounting\u002F05-analysis-comparison\u002F15-ratio-analysis","ratio analysis"," for guidance on denominators and comparability.",[2127,2375,2377],{"id":2376},"example-3-contribution-and-a-price-reduction","Example 3: Contribution and a price reduction",[2115,2379,2380],{},"A repair-kit line sells at £25 per kit, has variable cost £15 per kit and monthly fixed cost £12,000. Expected sales are 1,800 kits. Assume production equals sales and the same cost structure applies up to 2,200 kits.",[2115,2382,2383],{},"Calculate contribution, break-even, forecast profit, margin of safety in units and as a percentage of forecast sales, and units for £9,000 target profit. Then reduce price by 10%, holding all other assumptions fixed. Recalculate break-even, profit and safety margin. Does a lower price automatically increase profit?",[2179,2385,2386,2413],{"title":2181},[2115,2387,2388,2389,2392,2393,2396,2397,2400,2401,2404,2405,2408,2409,2412],{},"Base contribution is ",[2122,2390,2391],{},"£10"," per kit. Break-even = £12,000 \u002F £10 = ",[2122,2394,2395],{},"1,200 kits",". Forecast profit = £18,000 − £12,000 = ",[2122,2398,2399],{},"£6,000",". Safety margin = ",[2122,2402,2403],{},"600 kits",", or ",[2122,2406,2407],{},"33.3%"," of forecast sales. The £9,000 target requires ",[2122,2410,2411],{},"2,100 kits",", within the stated range.",[2115,2414,2415,2416,2419,2420,2423,2424,2427],{},"At £22.50, contribution is £7.50; break-even becomes ",[2122,2417,2418],{},"1,600 kits",", profit at 1,800 kits is ",[2122,2421,2422],{},"£1,500",", and safety margin is ",[2122,2425,2426],{},"200 kits \u002F 11.1%",". Maintaining the old £6,000 profit would need 2,400 kits, outside the assumed 2,200-kit range. Obtain a revised capacity\u002Fcost forecast before treating that figure as feasible. A positive safety margin is not evidence that demand risk is low.",[2127,2429,2431],{"id":2430},"example-4-compare-costs-at-the-same-activity","Example 4: Compare costs at the same activity",[2115,2433,2434],{},"The original budget is for 1,000 units. Variable material cost is £8 per unit and variable labour cost £6 per unit. Actual output is 1,200 units, with material cost £10,200 and labour cost £6,900. There are no fixed costs in these two lines.",[2115,2436,2437,2438,2441],{},"Compute the original budget, the flexible budget at actual output, and each cost variance against the flexible budget. Use ",[2122,2439,2440],{},"actual cost minus flexible-budget cost",", so a positive result is unfavourable (U) and a negative result favourable (F). Explain why the total alone cannot identify a price or efficiency cause.",[2179,2443,2444,2526],{"title":2181},[2214,2445,2446,2465],{},[2217,2447,2448],{},[2220,2449,2450,2453,2456,2459,2462],{},[2223,2451,2452],{},"Cost",[2223,2454,2455],{"align":2228},"Original budget £",[2223,2457,2458],{"align":2228},"Flexible budget £",[2223,2460,2461],{"align":2228},"Actual £",[2223,2463,2464],{"align":2228},"Actual minus flexible £",[2234,2466,2467,2483,2499],{},[2220,2468,2469,2472,2474,2477,2480],{},[2239,2470,2471],{},"Materials",[2239,2473,2266],{"align":2228},[2239,2475,2476],{"align":2228},"9,600",[2239,2478,2479],{"align":2228},"10,200",[2239,2481,2482],{"align":2228},"600 U",[2220,2484,2485,2488,2490,2493,2496],{},[2239,2486,2487],{},"Labour",[2239,2489,2269],{"align":2228},[2239,2491,2492],{"align":2228},"7,200",[2239,2494,2495],{"align":2228},"6,900",[2239,2497,2498],{"align":2228},"300 F",[2220,2500,2501,2506,2511,2516,2521],{},[2239,2502,2503],{},[2122,2504,2505],{},"Total",[2239,2507,2508],{"align":2228},[2122,2509,2510],{},"14,000",[2239,2512,2513],{"align":2228},[2122,2514,2515],{},"16,800",[2239,2517,2518],{"align":2228},[2122,2519,2520],{},"17,100",[2239,2522,2523],{"align":2228},[2122,2524,2525],{},"300 U",[2115,2527,2528,2529,2200],{},"Actual costs exceed the original budget by £3,100: £2,800 reflects higher output and £300 remains above the flexible budget. Material prices, waste and specification changes could help explain the difference, but you need quantities and prices to investigate. For labour, you need hours and rates, as well as evidence about quality: a favourable cost total may still conceal quality problems. Continue to ",[2205,2530,2532],{"href":2531},"..\u002Fmanagement-accounting\u002F02-planning-control\u002F20-budgeting-variances","detailed variances",[2127,2534,2536],{"id":2535},"example-5-competing-investments","Example 5: Competing investments",[2115,2538,2539,2540,2543],{},"Two mutually exclusive projects have the same three-year life and assumed risk. Choose at most one. The required return is ",[2122,2541,2542],{},"10%",", an exercise assumption. Cash flows below are complete incremental project cash flows: no additional tax, working capital, residual value or financing flows are to be added. For NPV, all future flows occur at year-end.",[2214,2545,2546,2559],{},[2217,2547,2548],{},[2220,2549,2550,2553,2556],{},[2223,2551,2552],{},"Time",[2223,2554,2555],{"align":2228},"Project A £",[2223,2557,2558],{"align":2228},"Project B £",[2234,2560,2561,2571,2582,2592],{},[2220,2562,2563,2566,2569],{},[2239,2564,2565],{},"0",[2239,2567,2568],{"align":2228},"(24,000)",[2239,2570,2568],{"align":2228},[2220,2572,2573,2576,2579],{},[2239,2574,2575],{},"1",[2239,2577,2578],{"align":2228},"10,000",[2239,2580,2581],{"align":2228},"2,000",[2220,2583,2584,2587,2589],{},[2239,2585,2586],{},"2",[2239,2588,2578],{"align":2228},[2239,2590,2591],{"align":2228},"11,000",[2220,2593,2594,2597,2599],{},[2239,2595,2596],{},"3",[2239,2598,2578],{"align":2228},[2239,2600,2601],{"align":2228},"19,000",[2603,2604,2605,2608,2616,2622,2625],"ol",{},[2135,2606,2607],{},"Calculate each year's present value and total NPV. Choose on the stated value criterion.",[2135,2609,2610,2611,2615],{},"Find the IRR using a spreadsheet or the method in ",[2205,2612,2614],{"href":2613},"..\u002Fmanagement-accounting\u002F03-decisions-investment\u002F23-capital-budgeting","capital budgeting",". Check that NPV is close to zero at that rate.",[2135,2617,2618,2619,2200],{},"State the payback and discounted-payback dates under the ",[2122,2620,2621],{},"literal year-end receipt assumption",[2135,2623,2624],{},"As a separate approximation, interpolate within the recovery year. For simple payback this assumes cash arrives evenly during that year; discounted-payback interpolation spreads that year's discounted amount evenly. Label these approximations rather than silently changing the timing convention.",[2135,2626,2627],{},"Give a recommendation, one forecast risk and one reason shorter payback may be valuable even when NPV is lower.",[2179,2629,2631,3302,3419,3422,3428],{"title":2630},"Calculations and recommendation",[2111,2632,2635],{"className":2633},[2634],"katex-display",[2111,2636,2639,2784],{"className":2637},[2638],"katex",[2111,2640,2643],{"className":2641},[2642],"katex-mathml",[2644,2645,2648],"math",{"xmlns":2646,"display":2647},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML","block",[2649,2650,2651,2779],"semantics",{},[2652,2653,2657,2722],"mtable",{"rowspacing":2654,"columnalign":2655,"columnspacing":2656},"0.25em","right 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],{"className":3299,"style":2907},[2820],[2111,3301],{},[2214,3303,3304,3316],{},[2217,3305,3306],{},[2220,3307,3308,3310,3313],{},[2223,3309,2314],{},[2223,3311,3312],{"align":2228},"Project A",[2223,3314,3315],{"align":2228},"Project B",[2234,3317,3318,3329,3339,3350,3367,3378,3388,3397,3408],{},[2220,3319,3320,3323,3326],{},[2239,3321,3322],{},"Year 1 present value £",[2239,3324,3325],{"align":2228},"9,090.91",[2239,3327,3328],{"align":2228},"1,818.18",[2220,3330,3331,3334,3337],{},[2239,3332,3333],{},"Year 2 present value £",[2239,3335,3336],{"align":2228},"8,264.46",[2239,3338,3325],{"align":2228},[2220,3340,3341,3344,3347],{},[2239,3342,3343],{},"Year 3 present value £",[2239,3345,3346],{"align":2228},"7,513.15",[2239,3348,3349],{"align":2228},"14,274.98",[2220,3351,3352,3357,3362],{},[2239,3353,3354],{},[2122,3355,3356],{},"NPV £",[2239,3358,3359],{"align":2228},[2122,3360,3361],{},"868.52",[2239,3363,3364],{"align":2228},[2122,3365,3366],{},"1,184.07",[2220,3368,3369,3372,3375],{},[2239,3370,3371],{},"IRR, approximately",[2239,3373,3374],{"align":2228},"12.044%",[2239,3376,3377],{"align":2228},"12.147%",[2220,3379,3380,3383,3386],{},[2239,3381,3382],{},"Payback with year-end receipts",[2239,3384,3385],{"align":2228},"End of year 3",[2239,3387,3385],{"align":2228},[2220,3389,3390,3393,3395],{},[2239,3391,3392],{},"Discounted payback with year-end receipts",[2239,3394,3385],{"align":2228},[2239,3396,3385],{"align":2228},[2220,3398,3399,3402,3405],{},[2239,3400,3401],{},"Interpolated simple payback, years",[2239,3403,3404],{"align":2228},"2.400",[2239,3406,3407],{"align":2228},"2.579",[2220,3409,3410,3413,3416],{},[2239,3411,3412],{},"Interpolated discounted payback, years",[2239,3414,3415],{"align":2228},"2.884",[2239,3417,3418],{"align":2228},"2.917",[2115,3420,3421],{},"For A, simple interpolation is 2 + £4,000 \u002F £10,000 = 2.4 years. Discounted interpolation is 2 + (£24,000 − £9,090.91 − £8,264.46) \u002F £7,513.15 ≈ 2.884 years. Use unrounded present values internally, then round the result.",[2115,3423,3424,3427],{},[2122,3425,3426],{},"B has the higher NPV by £315.55"," under the supplied assumptions. The result is sensitive to its £19,000 final receipt: a £1,000 shortfall reduces B's NPV by £751.31 to £432.76, reversing the base-case ranking if A is unchanged. A returns more cash earlier, which may matter when liquidity is constrained. Neither a positive NPV nor an IRR above 10% guarantees that the forecast will be achieved.",[2115,3429,3430,3431,3437],{},"For relevant project cash flows and timing, see ",[2205,3432,3436],{"href":3433,"rel":3434},"https:\u002F\u002Fwww.accaglobal.com\u002Fuk\u002Fen\u002Fstudent\u002Fexam-support-resources\u002Fprodipsust-study-resources\u002Ftechnical-articles\u002Finvestment-appraisal.html",[3435],"nofollow","ACCA's investment-appraisal guidance",". The cases and numbers here are original teaching examples.",[2127,3439,3441],{"id":3440},"review-your-reasoning","Review your reasoning",[2115,3443,3444],{},"For any example, separate the calculation from the conclusion you draw. If your answer differs, identify the business event, benchmark or timing assumption you interpreted differently. Reconstructing that link helps you apply the method to another business with different numbers.",[2127,3446,3448],{"id":3447},"extension-investigate-the-comparison-itself","Extension: investigate the comparison itself",[2115,3450,3451],{},"The ratio example compares two years, the flexible budget compares costs at the same activity, and the investment example compares mutually exclusive future projects. Each comparison needs a different baseline. Before interpreting a difference, ask what has been held constant and what has changed.",[2115,3453,3454],{},"The remaining flexible-budget variance does not identify its own cause: different prices, hours or quantities could produce the same total. Likewise, a higher NPV is a conclusion under the supplied cash-flow and risk assumptions. The forecast variation in Example 5 shows how that ranking can reverse. A useful summary therefore records the result, its assumptions and the evidence that would make you reconsider it.",[2115,3456,3457,3458,3462,3463,3467],{},"To extend these ideas, use ",[2205,3459,3461],{"href":3460},"..\u002Fmanagement-accounting\u002F01-cost-foundations\u002F16-cost-concepts","cost concepts"," to distinguish cost behaviour from decision relevance, then read ",[2205,3464,3466],{"href":3465},"..\u002Fmanagement-accounting\u002F03-decisions-investment\u002F22-short-term-decisions","short-term decisions"," to see how capacity and opportunity cost affect a choice.",[2115,3469,3470,3474,3475],{},[2205,3471,3473],{"href":3472},".\u002F","Return to the foundation route"," · ",[2205,3476,3478],{"href":3477},"..\u002F00-index","Continue the full accounting course",{"title":10,"searchDepth":210,"depth":210,"links":3480},[3481,3482,3483,3484,3485,3486,3487,3488],{"id":2129,"depth":210,"text":2130},{"id":2170,"depth":210,"text":2171},{"id":2211,"depth":210,"text":2212},{"id":2376,"depth":210,"text":2377},{"id":2430,"depth":210,"text":2431},{"id":2535,"depth":210,"text":2536},{"id":3440,"depth":210,"text":3441},{"id":3447,"depth":210,"text":3448},"Summarise what accounting measures can tell us, then compare their use in worked decisions","md",{},true,{"title":218,"description":3489},{"order":222},"vO-rw1_OcQ0GKEq3N18UNl01TA1aurcQIeRlv_1XNQo",[3497,3499],{"title":212,"path":213,"stem":214,"description":3498,"children":-1},"Build monthly receipts, payments and funding schedules before interpreting cash balances",{"title":225,"path":226,"stem":227,"description":3500,"children":-1},"Purpose-built information for planning, control and decisions",1791046343457]