Abstract We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run...

Summary We consider estimating a probability density p based on a random sample from this density by a Bayesian approach. The prior is constructed in two steps, by first constructing priors on a collection of models each expressing a qualitative prior guess on the true density, and next...

We investigate the effect of forecast uncertainty in a cointegrating vector error correction model for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of averaging over forecasts from different models....

Recently, there has been increasing interest in forecasting methods that utilise large datasets. We explore the possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist setting, using the predictive likelihood. We apply...

This paper examines the structural determinants of output volatility in developing countries, and especially the roles of geography and institutions. We investigate the volatility effects of market access, climate variability, the geographic predisposition to trade, and various measures of...

We examine the view that high-quality macroeconomic policy is a necessary, but not sufficient, condition for economic growth. We first construct a new index of the quality of macroeconomic policy. We then directly compare growth rate distributions across countries with good and bad policies; use...