Testing for Parameter Variation in Non-Linear Regression Models

Abstract

This paper addresses the problem of testing for purely random parameter variation in nonlinear regression models. Based on different approximations to the true density of the data, score-type tests are constructed and their asymptotic distributions are derived. The local power of the tests is investigated both theoretically and via Monte Carlo simulation. An empirical testing example, involving a well-known non-linear aggregate demand for money function, is also given