We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior...

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, "diffuse'' priors on model-specific parameters can lead to quite unexpected...

We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior...

This paper provides a Bayesian analysis of Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. We discuss in detail inference on impulse responses, and show how Bayesian methods can be used to (i) test ARFIMA models against ARIMA alternatives, and (ii) take model uncertainty...

We present a simple model of management teams where the time it takes to make decisions is related to the size of the committee. We characterize the situations where larger or smaller sizes of the management team are desirable depending on the covariance structure of the signals that the...

We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. We examine the effect of a variety of prior...

We present a simple model of management teams where the time it takes to make decisions is related to the size of the committee. We characterize the situations where larger or smaller sizes of the management team are desirable depending on the covariance structure of the signals that the...

This paper deals with the issue of modeling daily catches of fishing boats in the Grand Bank fishing grounds. We have data on catches per species for a number of vessels collected by the European Union in the context of the North Atlantic Fisheries Organization. Many variables can be thought to...

We consider a Bayesian implementation of a new approach to estimating Demand Systems. This approach, suggested by Varian (1990), is based on a generalization of Afriat's (1967) efficiency index. The model we propose leads to a very tractable posterior and predictive analysis, yet allows for...