Universität zu Köln

Hayakawa, Kazuhiko ORCID: 0000-0002-8321-8448, Qi, Meng and Breitung, Joerg (2019). Double filter instrumental variable estimation of panel data models with weakly exogenous variables. Econom. Rev., 38 (9). S. 1055 - 1089. PHILADELPHIA: TAYLOR & FRANCIS INC. ISSN 1532-4168

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Abstract

In this article, we propose instrumental variables (IV) and generalized method of moments (GMM) estimators for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects (FE). The proposed IV and GMM estimators are obtained by applying a forward filter to the model and a backward filter to the instruments in order to remove FE, thereby called the double filter IV and GMM estimators. We derive the asymptotic properties of the proposed estimators under fixed T and large N, and large T and large N asymptotics where N and T denote the dimensions of cross section and time series, respectively. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias corrected FE estimator when both N and T 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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Hayakawa, Kazuhiko UNSPECIFIED orcid.org/0000-0002-8321-8448 UNSPECIFIED Qi, Meng UNSPECIFIED UNSPECIFIED UNSPECIFIED Breitung, Joerg UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-137852
DOI:	10.1080/07474938.2018.1514024
Journal or Publication Title:	Econom. Rev.
Volume:	38
Number:	9
Page Range:	S. 1055 - 1089
Date:	2019
Publisher:	TAYLOR & FRANCIS INC
Place of Publication:	PHILADELPHIA
ISSN:	1532-4168
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language TIME-SERIES; EFFICIENT ESTIMATION; DYNAMIC-MODELS; DISTRIBUTIONS; BIAS Multiple languages Economics; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; Statistics & Probability Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/13785