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

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

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

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

Linear GMM in one slide

Linear GMM and 2SLS

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

Difference and system GMM

Problem: Dynamic Panel Bias (Nickell 1981)

Partial solution: OLS in differences

Problem: Other endogeneity

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

Problem: Inefficiency

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

Problem: Autocorrelation

Solution: Restrict to deeper lags

Arellano-Bond AR() test

Problem: Weak instruments

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

Relationship among moments (Tue Gorgens)

Problem: Two-step errors too small

Problem, cont’d

Solution: finite-sample correction (Windmeijer 2005)

Problem: too many instruments

Solution: consider limiting instruments

xtabond2 syntax Z Y X “GMM-style” Classic

Examples

Examples, cont’d

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