TESTING FOR PARAMETER VARIATION IN NONLINEAR-REGRESSION MODELS

This paper addresses the problem of testing for purely random parameter variation in non-linear 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.