Many IVs estimation of dynamic panel regression models with measurement error

Nayoung Lee; Hyungsik Roger Moon; Qiankun Zhou

doi:10.1016/j.jeconom.2017.06.009

Many IVs estimation of dynamic panel regression models with measurement error

Nayoung Lee, Hyungsik Roger Moon, Qiankun Zhou

Department of Economics

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

In this paper, we investigate a dynamic linear panel regression model with measurement error. We consider the panel data estimation whose time dimension (T) is not small and comparable to the cross sectional dimension (N). First, we show that the 2SLS estimator suffers from the bias problem due to many instrumental variables. Using the alternative asymptotics where [Formula presented] goes to a constant as N,T→∞, we characterize its asymptotic bias due to many IVs. As a bias reduction method, we investigate the JIVE and derive its limiting distribution under the alternative asymptotics.

Original language	English
Pages (from-to)	251-259
Number of pages	9
Journal	Journal of Econometrics
Volume	200
Issue number	2
DOIs	https://doi.org/10.1016/j.jeconom.2017.06.009
Publication status	Published - 2017 Oct

Bibliographical note

Funding Information:
We thank Tom Wansbeek and two referees for helpful comments. We also appreciate the comments from Xu Cheng and the conference participants of the 2014 ASSA winter meeting in Philadelphia. Moon acknowledges that this work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A5A8012177).

Publisher Copyright:
© 2017 Elsevier B.V.

All Science Journal Classification (ASJC) codes

Economics and Econometrics

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10.1016/j.jeconom.2017.06.009

Cite this

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title = "Many IVs estimation of dynamic panel regression models with measurement error",

abstract = "In this paper, we investigate a dynamic linear panel regression model with measurement error. We consider the panel data estimation whose time dimension (T) is not small and comparable to the cross sectional dimension (N). First, we show that the 2SLS estimator suffers from the bias problem due to many instrumental variables. Using the alternative asymptotics where [Formula presented] goes to a constant as N,T→∞, we characterize its asymptotic bias due to many IVs. As a bias reduction method, we investigate the JIVE and derive its limiting distribution under the alternative asymptotics.",

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AU - Zhou, Qiankun

N1 - Funding Information: We thank Tom Wansbeek and two referees for helpful comments. We also appreciate the comments from Xu Cheng and the conference participants of the 2014 ASSA winter meeting in Philadelphia. Moon acknowledges that this work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A5A8012177). Publisher Copyright: © 2017 Elsevier B.V.

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AB - In this paper, we investigate a dynamic linear panel regression model with measurement error. We consider the panel data estimation whose time dimension (T) is not small and comparable to the cross sectional dimension (N). First, we show that the 2SLS estimator suffers from the bias problem due to many instrumental variables. Using the alternative asymptotics where [Formula presented] goes to a constant as N,T→∞, we characterize its asymptotic bias due to many IVs. As a bias reduction method, we investigate the JIVE and derive its limiting distribution under the alternative asymptotics.

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Many IVs estimation of dynamic panel regression models with measurement error

Abstract

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