1. Part 9: GMM Estimation [ 1/57] Econometric Analysis of Panel Data William Greene Department of Economics Stern School of Business

2. Part 9: GMM Estimation [ 2/57] http://people.stern.nyu.edu/wgreene/CumulantInstruments-Racicot-AE(2014)_46(10).pdf

3. Part 9: GMM Estimation [ 3/57]

4. Part 9: GMM Estimation [ 4/57] The NYU No Action Letter

5. Part 9: GMM Estimation [ 5/57]

6. Part 9: GMM Estimation [ 6/57] GMM Estimation for One Equation

7. Part 9: GMM Estimation [ 7/57] GMM for a System of Equations

8. Part 9: GMM Estimation [ 8/57] SUR Model with Endogenous RHS Variables

9. Part 9: GMM Estimation [ 9/57] GMM for the System - Notation

10. Part 9: GMM Estimation [ 10/57] Instruments

11. Part 9: GMM Estimation [ 11/57] Moment Equations

12. Part 9: GMM Estimation [ 12/57] Estimation-1

13. Part 9: GMM Estimation [ 13/57] Estimation-2

14. Part 9: GMM Estimation [ 14/57] Estimation-3

15. Part 9: GMM Estimation [ 15/57] Estimation-4

16. Part 9: GMM Estimation [ 16/57] Estimation-5

17. Part 9: GMM Estimation [ 17/57] The Panel Data Case

18. Part 9: GMM Estimation [ 18/57] Hausman and Taylor FE/RE Model

19. Part 9: GMM Estimation [ 19/57] Useful Result: LSDV is an IV Estimator

20. Part 9: GMM Estimation [ 20/57] Hausman and Taylor

21. Part 9: GMM Estimation [ 21/57] H&T’s FGLS Estimator

22. Part 9: GMM Estimation [ 22/57] H&T’s FGLS Estimator (cont.)

23. Part 9: GMM Estimation [ 23/57] H&T’s 4 STEP IV Estimator

24. Part 9: GMM Estimation [ 24/57]

25. Part 9: GMM Estimation [ 25/57]

26. Part 9: GMM Estimation [ 26/57]

27. Part 9: GMM Estimation [ 27/57]

28. Part 9: GMM Estimation [ 28/57]

29. Part 9: GMM Estimation [ 29/57] Dynamic (Linear) Panel Data (DPD) Models  Application  Bias in Conventional Estimation  Development of Consistent Estimators  Efficient GMM Estimators

30. Part 9: GMM Estimation [ 30/57] Dynamic Linear Model

31. Part 9: GMM Estimation [ 31/57] A General DPD model

32. Part 9: GMM Estimation [ 32/57] OLS and GLS are inconsistent

33. Part 9: GMM Estimation [ 33/57] LSDV is Inconsistent [(Steven) Nickell Bias]

34. Part 9: GMM Estimation [ 34/57] Anderson Hsiao IV Estimator

35. Part 9: GMM Estimation [ 35/57] Arellano and Bond Estimator - 1

36. Part 9: GMM Estimation [ 36/57] Arellano and Bond Estimator - 2

37. Part 9: GMM Estimation [ 37/57] Arellano and Bond Estimator - 3

38. Part 9: GMM Estimation [ 38/57] Instrumental Variables

39. Part 9: GMM Estimation [ 39/57] Simple IV Estimation

40. Part 9: GMM Estimation [ 40/57] Arellano/Bond First Difference Formulation

41. Part 9: GMM Estimation [ 41/57] Arellano/Bond - GLS

42. Part 9: GMM Estimation [ 42/57] Arellano/Bond GLS Estimator

43. Part 9: GMM Estimation [ 43/57] GMM Estimator

44. Part 9: GMM Estimation [ 44/57] Arellano/Bond/Bover’s Formulation Start with H&T

45. Part 9: GMM Estimation [ 45/57] Arellano/Bond/Bover’s Formulation Dynamic Model

46. Part 9: GMM Estimation [ 46/57] Arellano/Bond/Bover’s Formulation

47. Part 9: GMM Estimation [ 47/57] Arellano/Bond/Bover’s Formulation These blocks may contain all previous exogenous variables, or all exogenous variables for all periods. This may contain the all periods of data on x 1 rather than just the group mean. (Amemiya and MaCurdy).

48. Part 9: GMM Estimation [ 48/57] Arellano/Bond/Bover’s Formulation For unbalanced panels the number of columns for Z i varies. Given the form of Z i, the number of columns depends on T i. We need all Z i to have the same number of columns. For matrices with less columns than the largest one, extra columns of zeros are added.

49. Part 9: GMM Estimation [ 49/57] Arellano/Bond/Bover’s Formulation

50. Part 9: GMM Estimation [ 50/57] Arellano/Bond/Bover Estimator

51. Part 9: GMM Estimation [ 51/57] GMM Criterion

52. Part 9: GMM Estimation [ 52/57] Application: Maquiladora

53. Part 9: GMM Estimation [ 53/57] Maquiladora

54. Part 9: GMM Estimation [ 54/57]

55. Part 9: GMM Estimation [ 55/57]

56. Part 9: GMM Estimation [ 56/57] Postscript  There is no theoretical guidance on the instrument set  There is no theoretical guidance on the form of the covariance matrix  There is no theoretical guidance on the number of lags at any level of the model  There is no theoretical guidance on the form of the exogeneity – and it is not testable.  Results vary wildly with small variations in the assumptions.

57. Part 9: GMM Estimation [ 57/57] Ahn and Schmidt