Estimation with overidentifying inequality moment conditions

Hyungsik Roger Moon; Frank Schorfheide

doi:10.1016/j.jeconom.2009.05.003

Estimation with overidentifying inequality moment conditions

Hyungsik Roger Moon, Frank Schorfheide

Department of Economics

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

24 Citations (Scopus)

Abstract

This paper derives limit distributions of empirical likelihood estimators for models in which inequality moment conditions provide overidentifying information. We show that the use of this information leads to a reduction of the asymptotic mean-squared estimation error and propose asymptotically uniformly valid tests and confidence sets for the parameters of interest. While inequality moment conditions arise in many important economic models, we use a dynamic macroeconomic model as a data generating process and illustrate our methods with instrumental variable estimators of monetary policy rules. The results obtained in this paper extend to conventional GMM estimators.

Original language	English
Pages (from-to)	136-154
Number of pages	19
Journal	Journal of Econometrics
Volume	153
Issue number	2
DOIs	https://doi.org/10.1016/j.jeconom.2009.05.003
Publication status	Published - 2009 Dec

Bibliographical note

Funding Information:
An earlier version of this paper was circulated under the title “Empirical Likelihood Estimation with Inequality Moment Constraints”. We thank Ron Gallant (co-editor), two anonymous referees, Sungbae An, Donald Andrews, Jinyong Hahn, Shakeeb Khan, Yuichi Kitamura, Masao Ogaki, Nick Souleles, and seminar participants at the 2003 Econometrics Society Winter Meetings, the 2006 European Econometrics Society Meetings, Columbia University, the Federal Reserve Bank of Atlanta, London School of Economics, Michigan State University, New York University, Penn State University, Princeton University, UC Irvine, UC Riverside, UT Austin, Texas A&M, and the universities of Chicago, Montreal, Pennsylvania, and Virginia for helpful comments. Moon gratefully acknowledges financial support from the USC Faculty Development Award. Schorfheide gratefully acknowledges financial support from the Alfred P. Sloan Foundation. GAUSS programs that implement the Monte Carlo simulation are available at http://www.ssc.upenn.edu/~schorf .

All Science Journal Classification (ASJC) codes

Economics and Econometrics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jeconom.2009.05.003

Cite this

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title = "Estimation with overidentifying inequality moment conditions",

abstract = "This paper derives limit distributions of empirical likelihood estimators for models in which inequality moment conditions provide overidentifying information. We show that the use of this information leads to a reduction of the asymptotic mean-squared estimation error and propose asymptotically uniformly valid tests and confidence sets for the parameters of interest. While inequality moment conditions arise in many important economic models, we use a dynamic macroeconomic model as a data generating process and illustrate our methods with instrumental variable estimators of monetary policy rules. The results obtained in this paper extend to conventional GMM estimators.",

author = "Moon, {Hyungsik Roger} and Frank Schorfheide",

note = "Funding Information: An earlier version of this paper was circulated under the title “Empirical Likelihood Estimation with Inequality Moment Constraints”. We thank Ron Gallant (co-editor), two anonymous referees, Sungbae An, Donald Andrews, Jinyong Hahn, Shakeeb Khan, Yuichi Kitamura, Masao Ogaki, Nick Souleles, and seminar participants at the 2003 Econometrics Society Winter Meetings, the 2006 European Econometrics Society Meetings, Columbia University, the Federal Reserve Bank of Atlanta, London School of Economics, Michigan State University, New York University, Penn State University, Princeton University, UC Irvine, UC Riverside, UT Austin, Texas A&M, and the universities of Chicago, Montreal, Pennsylvania, and Virginia for helpful comments. Moon gratefully acknowledges financial support from the USC Faculty Development Award. Schorfheide gratefully acknowledges financial support from the Alfred P. Sloan Foundation. GAUSS programs that implement the Monte Carlo simulation are available at http://www.ssc.upenn.edu/~schorf . ",

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Estimation with overidentifying inequality moment conditions

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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