Handling Endogenous Regressors by Joint Estimation Using Copulas

51 Pages Posted: 20 Mar 2012 Last revised: 27 Jun 2012

See all articles by Sungho Park

Sungho Park

Arizona State University (ASU) - W.P. Carey School of Business

Sachin Gupta

Cornell University - Samuel Curtis Johnson Graduate School of Management

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Date Written: January 17, 2012

Abstract

We propose a new statistical instrument-free method to tackle the endogeneity problem. The proposed method models the joint distribution of the endogenous regressor and the error term in the structural equation of interest (the structural error) using a copula method, and makes inferences on the model parameters by maximizing the likelihood derived from the joint distribution. Similar to the “exclusion restriction” in instrumental variable methods, extant instrument-free methods require the assumption that the unobserved instruments are exogenous, a requirement that is difficult to meet. The proposed method does not require such an assumption. Other benefits of the proposed method are that it allows modeling of discrete endogenous regressors and offers a new solution to the slope endogeneity problem. In addition to linear models, the method is applicable to the popular random coefficient logit model with both aggregate data and individual data. We demonstrate the performance of the proposed method via a series of simulation studies and an empirical example.

Keywords: Endogeneity, Copula Method, Instrumental Variables, Two-Stage Least Squares, Linear Regression Model, Logit Model, Random Coefficient

Suggested Citation

Park, Sungho and Gupta, Sachin, Handling Endogenous Regressors by Joint Estimation Using Copulas (January 17, 2012). Marketing Science, Forthcoming; Johnson School Research Paper Series No. 19-2012. Available at SSRN: https://ssrn.com/abstract=2025669

Sungho Park (Contact Author)

Arizona State University (ASU) - W.P. Carey School of Business ( email )

Marketing Department
PO Box 874106
Tempe, AZ 85287-4106
United States

Sachin Gupta

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

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