This paper presents a general, nonlinear model for term structure interest rate. The approach is the same of Stanton (1997) but it has been extended to a multifactor model. The novel aspect is that rather than choosing the functional specification of the model, the process is generated from the...

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...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

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...

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral- t family of conditionally conjugate priors for hierarchical standard deviation parameters, and then consider noninformative and weakly informative...

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...