We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a...

A growing body of literature shows that geographic location plays an important role in influencing economic phenomena. Despite the renewed interest in economic geography, the existing literature on the firm size distribution (FSD) has ignored the impact of geographic location. A wave of recent...

In this study I apply a simple DSGE model to forecast the quarterly Romanian GDP. The forecast is based on the posterior distribution of the model parameters resulted from the Bayesian estimation. The forecast for the 2006-2007 period shows that the realized GDP is within the confidence interval...

The two main influences leading to adoption at the individual consumer level are marketing communication and interpersonal communication. Although evidence of the effect of these two influences is abundant at the market level, there is a paucity of research documenting the simultaneous effect of...

Organizations that use time series forecasting on a regular basis generally forecast many variables, such as demand for many products or services. Within the population of variables forecasted by an organization, we can expect that there will be groups of analogous time series that follow...

In this paper we propose a strategy for forecasting the term structure of interest rates which may produce significant gains in predictive accuracy. The key idea is to use the restrictions implied by Affine Term Structure Models (ATSM) on a vector autoregression (VAR) as prior information rather...

Repeated dichotomous choice contingent valuation data are generated from responses to a succession of binary questions regarding alternative prices for an environmental good. In this paper we propose a simultaneous equation model that allows for endogeneity and error correlation across the...

The issue of normalization arises whenever two different values for a vector of unknown parameters imply the identical economic model. A normalization implies not just a rule for selecting which among equivalent points to call the maximum likelihood estimate (MLE), but also governs the...