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Articles 1 - 3 of 3
Full-Text Articles in Social and Behavioral Sciences
Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou
Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou
Center for Policy Research
We develop averaged instrumental variables estimators as a way to deal with many weak instruments. We propose a weighted average of the preliminary k-class estimators, where each estimator is obtained using different subsets of the available instrumental variables. The averaged estimators are shown to be consistent and to satisfy asymptotic normality. Furthermore, its approximate mean squared error reveals that using a small number of instruments for each preliminary k-class estimator reduces the finite sample bias, while averaging prevents the variance from inflating. Monte Carlo simulations find that the averaged estimators compare favorably with alternative instrumental-variable-selection approaches when the strength levels …
Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi
Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi
Center for Policy Research
This paper extends Pesaran's (2006) work on common correlated effects (CCE) estimators for large heterogeneous panels with a general multifactor error structure by allowing for unknown common structural breaks. Structural breaks due to new policy implementation or major technological shocks, are more likely to occur over a longer time span. Consequently, ignoring structural breaks may lead to inconsistent estimation and invalid inference. We propose a general framework that includes heterogeneous panel data models and structural break models as special cases. The least squares method proposed by Bai (1997a, 2010) is applied to estimate the common change points, and the consistency …
Estimation And Identification Of Change Points In Panel Models With Nonstationary Or Stationary Regressors And Error Term, Badi H. Baltagi, Chihwa Kao, Long Liu
Estimation And Identification Of Change Points In Panel Models With Nonstationary Or Stationary Regressors And Error Term, Badi H. Baltagi, Chihwa Kao, Long Liu
Center for Policy Research
This paper studies the estimation of change point in panel models. We extend Bai (2010) and Feng, Kao and Lazarová (2009) to the case of stationary or nonstationary regressors and error term, and whether the change point is present or not. We prove consistency and derive the asymptotic distributions of the Ordinary Least Squares (OLS) and First Difference (FD) estimators. We find that the FD estimator is robust for all cases considered.