Flexible Simulated Moment Estimation of Nonlinear Errors-in-Variables Models

Posted: 26 Jul 2000

See all articles by Whitney K. Newey

Whitney K. Newey

Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: February 1999

Abstract

Nonlinear regression with measurement error is important for estimation from microeconomic data. One approach to identification and estimation is a causal model, where the unobserved true variable is predicted by observable variables. This paper is about 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 results is given. The value of the estimator is demonstrated in a Monte Carlo study and an application to estimating Engle Curves.

Keywords: Nonlinear regression, errors-in-variables, simulated moments

JEL Classification: C15, C21

Suggested Citation

Newey, Whitney K., Flexible Simulated Moment Estimation of Nonlinear Errors-in-Variables Models (February 1999). Available at SSRN: https://ssrn.com/abstract=235790

Whitney K. Newey (Contact Author)

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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National Bureau of Economic Research (NBER) ( email )

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