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ECON742: Empirical microeconomics

ECON742: Empirical microeconomics. Lecture 1 January 2014. correlation ≠causality. In economics, we want to measure the causal impact of X on Y. But crucial distinction between correlation and causality Correlation: relationship between X and Y Causality: X causes Y Maybe X->Y or Y->X

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ECON742: Empirical microeconomics

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  1. ECON742:Empirical microeconomics Lecture 1 January 2014

  2. correlation≠causality • In economics, we want to measure the causal impact of X on Y. • But crucial distinction between correlation and causality • Correlation: relationship between X and Y • Causality: X causes Y • Maybe X->Y or Y->X • Maybe Z->X, Z->Y and so X<->Y

  3. Z->X, Z->Y donc X<->Y • Ice cream sales and shark attacks • Number of decayed teeth and size of vocabulary • Recent article in the British Medical Journal: Brush your teeth 2 times per day, less cardiovascular diseases

  4. X->Y ou Y->X? • Number of doctors and patients

  5. Causal impact of X on Y: OLS? • Lecture 1: OLS • Lecture 2: Limitations • Lecture 3: Panel Data

  6. Lecture 4: Program evaluation • Causal impact of X on Y • Ideal? • Typical problem of evaluation: the counterfactual • Bad control group because of: • Self-selection • Non random program placement

  7. Empirical techniques • Lecture 5: Randomizedexperiments • Lecture 6: Instrumental variables • Lecture 7: Difference-in-differences • Lecture 8: Regression discontinuity design • Lecture 9: Selection models • Lecture 10: Matching • Lecture 12: …

  8. Conclusion • Correlation does not imply causality • The economists have tools (randomized experiments, instrumental variables, DID, discontinuity…) to get the causal impact of programs, reforms, policies on the behaviour of human beings

  9. Evaluation • Final exam: 40% (Date TBA) • Mid-term exam: 20% (03/11) • Exercises (four): 30% • Presentation: 10% (6 papers)

  10. Objectives of the course • correlation≠causality • Master the main microeconometric techniques • Be able to understand a researchpaper (presentation) • Be able to maipulate data (exercises)

  11. Correlation/causality • http://xkcd.com/552/

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