In this paper we consider bayesian semiparametric regression within the generalized linear model framework. Specifically, we study a class of autoregressive time series where the time trend is incorporated in a nonparametrically way. Estimation and inference where performed through Markov Chain...

I use numerical methods to test for the presence of one-time structural breaks in the conditional variance of nominal interest rate spreads in four European countries over a period of eleven years (Jan 1988 to Dec 1998). I start with an intuitive approach consisting of a sequence of breakpoint...

A welfare analysis of a risky policy is impossible within a linear or linearized model and its certainty equivalence property. The presented algorithms are designed as a toolbox for a general model class. The computational challenges are considerable and I concentrate on the numerics and...

An exciting development in modeling has been the ability to estimate reliable individual-level parameters for choice models. Individual partworths derived from these parameters have been very useful in segmentation, identifying extreme individuals, and in creating appropriate choice simulators....

We propose a Bayesian methodology that enables banks to improve their credit scoring models by imposing prior information. As prior information, we use coefficients from credit scoring models estimated on other data sets. Through simulations, we explore the default prediction power of three...

This paper extends the analogy previously established by Leamer (1978a), between a Bayesian inference problem and an economics allocation problem, and shows that posterior modes can be interpreted as optimal outcomes of a bargaining game. This bargaining game, over a parameter value, is played...

This paper considers bidding automata programmed by experienced subjects in sequential first price sealed bid auction experiments. These automata play against each other in computer tournaments. The risk neutral subgame perfect Nash equilibrium strategy of the independent private value model...

In this paper, we develop methods of the determination of the rank of random matrix. Using the matrix perturbation theory to construct or find a suitable bases of the kernel (null space) of the matrix and to determine the limiting distribution of the estimator of the smallest singular values. We...

The standard confidence regions based on the first-order approximation of quantile regression estimators can be inaccurate in small samples. We show that confidence regions based on the smoothed empirical likelihood ratio have coverage errors of order n^{-1} and may be Bartlett-corrected to...

The Carbon Kuznets hypothesis conjectures an inverse U{shape relation between GDP and carbon dioxide emissions. We investigate a number of empirical problems with this hypothesis by way of both econometric analysis and CGE modelling. The econometric analysis takes into account the possibility of...