Pretest Estimation in the Random Parameters Logit Model

Advances in Econometrics, Volume 26, 107-136, 2010

31 Pages Posted: 19 Jun 2015

See all articles by Tong Zeng

Tong Zeng

University of La Verne-Department of Applied Business Sciences and Economics

Carter Hill

Louisiana State University, Baton Rouge - Department of Economics

Date Written: September 18, 2010

Abstract

In this paper we use Monte Carlo sampling experiments to examine the properties of pretest estimators in the random parameters logit (RPL) model. The pretests are for the presence of random parameters. We study the Lagrange multiplier (LM), likelihood ratio (LR), and Wald tests, using conditional logit as the restricted model. The LM test is the fastest test to implement among these three test procedures since it only uses restricted, conditional logit, estimates. However, the LM-based pretest estimator has poor risk properties. The ratio of LM-based pretest estimator root mean squared error (RMSE) to the random parameters logit model estimator RMSE diverges from one with increases in the standard deviation of the parameter distribution. The LR and Wald tests exhibit properties of consistent tests, with the power approaching one as the specification error increases, so that the pretest estimator is consistent. We explore the power of these three tests for the random parameters by calculating the empirical percentile values, size, and rejection rates of the test statistics. We find the power of LR and Wald tests decreases with increases in the mean of the coefficient distribution.

Keywords: pretest estimator, Lagrange Multiplier test, Likelihood Ratio test, Wald test

JEL Classification: C12, C13, C35

Suggested Citation

Zeng, Tong and Hill, R. Carter, Pretest Estimation in the Random Parameters Logit Model (September 18, 2010). Advances in Econometrics, Volume 26, 107-136, 2010, Available at SSRN: https://ssrn.com/abstract=2620049

Tong Zeng (Contact Author)

University of La Verne-Department of Applied Business Sciences and Economics ( email )

1950 Third Street
La Verne, CA 91750
United States

R. Carter Hill

Louisiana State University, Baton Rouge - Department of Economics ( email )

Department of economics
Baton Rouge, LA 70803-6308
United States

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