In this paper, we consider binary response correlated random coefficient (CRC) panel data models which are frequently used in the analysis of treatment effects and demand of products. We focus on the nonparametric identification and estimation of panel data models under unobserved heterogeneity which is captured by random coefficients and when these random coefficients are correlated with regre...

The consistency of the quasi maximum likelihood estimator for random coefficient autoregressive models requires that the coefficient be a non-degenerate random variable. In this paper we propose empirical likelihood methods based on weighted score equations to construct a confidence interval for the coefficient. We do not need to distinguish whether the coefficient is random or deterministic an...

In this paper, we extend the minimum distance method of Beran (1993) to random coefficient autoregressive (RCA) models. After stating the necessary assumptions the asymptotic properties of the minimum distance estimator are derived. A M S classification: 62M05

This paper considers partially linear varying coefficient models when the response variable is missing at random. The paper uses imputation techniques to develop an omnibus specification test. The test is based on a simple modification of a Cramer von Mises functional that overcomes the curse of dimensionality often associated with the standard Cramer von Mises functional. The paper also consid...

We develop a hierarchical Bayesian approach for inference in random coefficient dynamic panel data models. Our approach allows for the initial values of each unit’s process to be correlated with the unit-specific coefficients. We impose a stationarity assumption for each unit’s process by assuming that the unit-specific autoregressive coefficient is drawn from a logitnormal distribution. Our me...

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...

We give conditions for first and second order stationarity of mixture autoregressive processes and discuss related, sometimes confusing, results for such models. We obtain a simple condition for positive definiteness of the solution of a generalisation of the Stein’s equation with semidefinite right-hand side and apply it to second order stationarity. The said condition may be of independent in...

Random coe cient regression models have been applied in di erent elds and they constitute a unifying setup for many statistical problems. The nonparametric study of this model started with Beran and Hall (1992) and it has become a fruitful framework. In this paper we propose and study statistics for testing a basic hypothesis concerning this model: the constancy of coe cients. The asymptotic be...