Jive for Panel Dynamic Simultaneous Equations Models
Document Type
Article
Publication Date
12-1-2018
Abstract
We consider the method of moments estimation of a structural equation in a panel dynamic simultaneous equations model under different sample size combinations of cross-sectional dimension, N, and time series dimension, T. Two types of linear transformation to remove the individual-specific effects from the model, first difference and forward orthogonal demeaning, are considered. We show that the Alvarez and Arellano (2003) type GMM estimator under both transformations is consistent only if T/N →0 as(N,T)→ ∞. However, it is asymptotically biased if T3/N → κ 0 < ∞ as(N,T)→∞. Since the validity of statistical inference depends critically on whether an estimator is asymptotically unbiased, we suggest a jackknife bias reduction method and derive its limiting distribution. Monte Carlo studies are conducted to demonstrate the importance of using an asymptotically unbiased estimator to obtain valid statistical inference.
Publication Source (Journal or Book title)
Econometric Theory
First Page
1325
Last Page
1369
Recommended Citation
Hsiao, C., & Zhou, Q. (2018). Jive for Panel Dynamic Simultaneous Equations Models. Econometric Theory, 34 (6), 1325-1369. https://doi.org/10.1017/S0266466617000421