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A1408
Topic: Title: Instrumental variable estimation of panel data models with weakly exogenous variables Authors:  Kazuhiko Hayakawa - Hiroshima University (Japan) [presenting]
Joerg Breitung - University of Cologne (Germany)
Meng Qi - Hiroshima University (Japan)
Abstract: We propose an instrumental variables estimator for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects. The proposed instrumental variable estimator is constructed by removing the fixed effects (and time trends) from both the model and instruments by a variant of GLS transformation. We show that the proposed estimator has the same asymptotic distribution as the bias corrected fixed effects estimator when both $N$ and $T$, the dimensions of cross section and time series, are large. Monte Carlo simulation results reveal that the proposed estimator performs well in finite samples and outperforms the conventional IV/GMM estimators using instruments in levels in many cases.