arrow
Return

Simulation error and numerical instability in estimating random coefficient logit demand models

delete2025-01-01
delete0
delete
OA
AI
D
D. Brunner
F
Florian Heiß
A
André Romahn *
C
Constantin Weiser
DOI:10.1016/j.jeconom.2025.105953delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
The nonlinear GMM-IV estimator of Berry, Levinsohn and Pakes (1995) can suffer from numerical instability resulting in a wide range of parameter estimates and economic implications. This has been reported to depend on technical details such as the choice of the optimization algorithm, starting values, and convergence criteria. We show that numerical approximation errors in the estimator's moment function are the main driver of this instability. With accurate approximation, the estimation approach is well-behaved. We provide a simple method to determine the required number of simulation draws.
Keywords:
Structural demand estimation
Numerical integration
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Econometrics cover
Journal of Econometrics
IF:
4
Papers:
5.2K
Citations:
3.0W

Organization

J
johannes gutenberg univ mayence
Scholars:
1
Papers: 1
Citations: 0
H
Heinrich Heine University Dusseldorf
Scholars:
1.8W
Papers: 1.4W
Citations: 126