1. How to Do xtabond2 David Roodman Research Fellow
Center for Global Development

2. xtabond2 in a nutshell
First ado version in 11/03, Mata version in 11/05.
Extends built-in xtabond, to do system GMM, Windmeijer correction, revamped syntax
Estimators designed for
Small-T, large-N panels
One dependent variable
Dynamic
Linear
Regressors endogenous and predetermined
Fixed individual effects
Arbitrary autocorrelation and het. within panels
General application

3. Outline of paper Introduction to linear GMM
Motivation and design of difference and system GMM
xtabond2 syntax

4. Black box problem Canned & sophisticated procedure
Dangers in hidden sophistication
finite sample ≠ asymptotic
Users should understand motivation and limits of estimator

5. Linear GMM in one slide

6. Linear GMM and 2SLS

7. Linear GMM in another slide (Holtz-Eakin, Newey, and Rosen 1988)

8. Difference and system GMM

9. Problem: Dynamic Panel Bias (Nickell 1981)

10. Partial solution: OLS in differences

11. Problem: Other endogeneity

12. Solution: Instrument with lags (2SLS) (Anderson and Hsiao 1981)

13. Problem: Inefficiency

14. Solution: GMM & GMM-style instruments (Holtz-Eakin, Newey, and Rosen 1988)

15. Problem: Autocorrelation

16. Solution: Restrict to deeper lags

17. Arellano-Bond AR() test

18. Problem: Weak instruments

19. Solution: Instead of purging fixed effects, find instruments orthogonal to them (Arellano and Bover 1995)

20. Relationship among moments (Tue Gorgens)

21. Problem: Two-step errors too small

22. Problem, cont’d

23. Solution: finite-sample correction (Windmeijer 2005)

25. Problem: too many instruments

26. Solution: consider limiting instruments

27. xtabond2 syntax Z Y X
“GMM-style”
Classic

28. Examples

29. Examples, cont’d

30. Run times for bbest (seconds) 700 MHz PC
xtabond2 ado 57
xtabond2 Mata, favoring space 14
xtabond2 Mata, favoring speed 11
DPD for Ox 3