The Review of Economics and Statistics Vol. 83 No. 4 2001
Flexible Simulated Moment Estimation of Nonlinear Errors-in-Variables Models
Abstract
Nonlinear regression with measurement error is important for estimation from microeconomic data. One approach to identification and estimation is a causal model, in which the unobserved true variable is predicted by observable variables. This paper details the estimation of such a model using simulated moments and a flexible disturbance distribution. An estimator of the asymptotic variance is given for parametric models. Also, a semiparametric consistency result is given. The value of the estimator is demonstrated in a Monte Carlo study and an application to estimating Engel Curves.
- DOI
- 10.1162/003465301753237704
- Volume
- 83
- Issue
- 4
- Pages
- 616-627
- Language
- en
- Sources
- openalex crossref