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INTRODUCTION APPLIED ECONOMETRICS

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13 diapositives · 466 Views · Aug 28, 2014

INTRODUCTION APPLIED ECONOMETRICS. BASICS I. BASIC PROBLEM I. Endogeneity Circularity Egg and chicken Causality and correlation: two very different concepts!!. BASIC PROBLEM I. Interpretation of any graph/table implies many assumptions.

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  1. INTRODUCTIONAPPLIED ECONOMETRICS

  2. BASICS I

  3. BASIC PROBLEM I • Endogeneity • Circularity • Egg and chicken • Causality and correlation: two very different concepts!!

  4. BASIC PROBLEM I • Interpretation of any graph/table implies many assumptions. • However, these assumptions are almost never explicit. • Assumptions for the interpretation of the previous graph? • Direction • Omission

  5. BASICS II • 1936 US presidential election • Sampling list: mail out ballot cards to residential telephone subscribers and owners of cars. • Result of the poll: Landon (republican) will win with 57% of the vote over Roosevelt (democract).

  6. BASICS II • Outcome of the election: Roosevelt won with 62.5% of the votes (523 of the 531 electoral votes!!) • What happened?

  7. BASICS PROBLEM II • Therapy of hormonal replacement for women with menopause. Does it work? • Possible problem. • Solution. • Why did the result with observational data was wrong?

  8. BASICS PROBLEM II • Sample selection problem. • Training courses for employees. • Annual physical: medical review.

  9. SOLUTION if possible • Randomized experiment. Example. • In medical science only randomized experiments are accepted. • Tobacco litigation. • Food and Drug administration. • Many times experiments are NOT AVAILABLE AND ARE VERY EXPENSIVE. • Look for other designs: “clever” regression and proper estimation procedures.

  10. EXOGENEITY • Basic problem: to find an exogenous source of variation. • Impossible (Lucas’ Critique): everything in economics is set simultaneously->DGEM and computable models. “Deep” parameters • Construct experiments or look for natural and pseudo-experiments. Find credible sources of exog. variation.

  11. IMPORTANT!! • Statistical methods are never wrong! • It is their application by clumsy, un- experienced or careless researchers that makes the results wrong. • Remember: if you get the design /assumptions /data right the results will always be right.

  12. The NYT litigation • Last year Morgan Stanley agreed to pay $54 millions for a sexual discrimination demand. Now Walmart. • In the 70’s some women journalist at the NYT claimed that they were discriminated. • Is a simple difference between the salary of men and women a good indicator of discrimination? • Judge decision.

  13. Regressions