1. Chapter 12 Instrumental Variables Regression

2. Instrumental Variables Regression (SW Chapter 12)

3. IV Regression with One Regressor and One Instrument (SW Section 12.1)

4. Terminology: endogeneity and exogeneity

5. Two conditions for a valid instrument

6. The IV Estimator, one X and one Z

7. Two Stage Least Squares, ctd.

8. Two Stage Least Squares, ctd.

9. The IV Estimator, one X and one Z, ctd.

10. The IV Estimator, one X and one Z, ctd.

11. Consistency of the TSLS estimator

12. Example #1: Supply and demand for butter

16. TSLS in the supply-demand example:

17. TSLS in the supply-demand example, ctd.

18. Example #2: Test scores and class size

19. Example #2: Test scores and class size, ctd.

20. Inference using TSLS

24. Inference using TSLS, ctd.

25. Example: Cigarette demand, ctd.

26. Cigarette demand, ctd.

27. STATA Example: Cigarette demand, First stage

28. Second stage

29. Combined into a single command

30. Summary of IV Regression with a Single X and Z

31. The General IV Regression Model(SW Section 12.2)

32. Identification

33. Identification, ctd.

34. The general IV regression model: Summary of jargon

35. TSLS with a single endogenous regressor

36. Example: Demand for cigarettes

37. Example: Cigarette demand, one instrument

38. Example: Cigarette demand, two instruments

40. The General Instrument Validity Assumptions

41. The IV Regression Assumptions

42. Checking Instrument Validity (SW Section 12.3)

43. Checking Assumption #1: Instrument Relevance

44. What are the consequences of weak instruments?

45. An example: the sampling distribution of the TSLS t-statistic with weak instruments

46. Why does our trusty normal approximation fail us?

47. Measuring the strength of instruments in practice: The first-stage F-statistic

48. Checking for weak instruments with a single X

49. What to do if you have weak instruments?

50. Confidence intervals with weak instruments