In this paper, we develop a Bayesian analysis of a semi-parametric binary choice model. The prior specification of the functional parameter, namely the distribution function of a latent variable, is of the Dirichlet process type and the prior specification of the Euclidean parameter, namely the...

This paper develops new Bayesian methods for semiparametric inference in the partial linear Normal regression model. These methodes draw solely on teh Normal linear regression model with natural conjugate prior. Hence, analytical finite sample results are available which do not suffer form...

This paper, prepared for the Invited Symposium "Financial Econometrics" at the 7th WCES, Tokyo, August 1995, surveys the subject of Econometrics of option pricing, and more precisely try to offer versatile tools to model the source of the prediction errors in option pricing.

The expectations hypothesis of the term structure of interest rates implies that the spread between short and long bond yields should forecast next period's change in the long yield. Regression based tests have systematically rejected the expectations hypothesis, with estimated coefficients far...

This paper proposes a semiparametric proportional hazard model for bivariate duration data in the analysis of two-component systems. Examples include the two infection times of the left and the right kidneys of patients and the two retirement times of married couples. As a generalization of the...

The correlated gamma-frailty model is a generalization of Cox' proportional hazard model, which allows for correlation between individuals within the same group. The nonparametric maximum likelihood estimator in this model has previously been studied by Murphy (1994, 1995) and Parner (1998)....

This paper shows how the dynamic linear model with fixed regressors can be efficiently estimated. This dynamic model can be used to distinguish spurious correlation from state dependence and we show that the integrated likelihood estimator is adaptive for any asymptotics with T increasing where...