ec20-lecture1-v6_1

# ec20-lecture1-v6_1 - Econometrics Class#1 Introduction...

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1 Econometrics Class #1: Introduction Rubin Causal Model

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2 What is Econometrics? Statistical tools to estimate and analyze economic relationships. Uses: Economic forecasts Generate inputs for economic policy Test economic theories Assess causality - answer research ?s Today’s ex: does placing people who are unemployed in temp jobs improve their long-run employment and earnings outcomes? Also: developing such tools (not here!)
3 What is Causality? What does it mean that some treatment has a causal (“ceteris paribus”) effect on an outcome? Holding all other factors constant Ex: “Holding other factors constant, getting a temp job improves long-run earnings of unemployed” Nothing else different but getting the temp job The simplest way to assess causality: Random assignment, i.e. experiments Problem: economists rarely do experiments Not always possible / feasible

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4 What is Causality? Instead, economists rely on: Observational data … Data not from an experiment (e.g., a survey) … + econometric models A set of untestable simplifying assumptions about other factors affecting outcome which allow interpretation of estimates as causal To see how, let’s first derive what “causality” means from first principles…
5 What is Causality? First Principles The Rubin Model of Causality Every individual, i, has two (only, for now) potential outcomes, Y i1 and Y i0 : Y i1 = outcome if individual i gets “treatment” Ex: Earnings of i years later if he got a temp job Y i0 = outcome if i does not get the “treatment” Ex: Earnings of i

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ec20-lecture1-v6_1 - Econometrics Class#1 Introduction...

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