Path forecasts, defined as sequences of individual forecasts, generated by vector autoregressions are widely used in applied work. It has been recognized that a profound econometric analysis often requires, besides the path forecast, a joint prediction region that contains the whole future path with a prespecified coverage probability. The forecasting literature offers several different methods...

The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should be implemented. Relative to the previous literature, this paper is novel in several respects. First of all, we test and systematically evaluate the ability of several alternative econometric specifications proposed in the literature to capture the dynamics of oil prices. Sec...

this paper is a survey of recent contributions to and developments in the relationship between efficiency and productivity via the production function. the objective is to provide a brief discussion on data and on the methods of measuring efficiency and productivity. first, we introduce the reader to the measurement of partial and total factor productivity in the context of static and firm - sp...

This study presents the implication of Bayesian technique on simple statistical and econometric forecasting models to improve the forecast performances of the models. We consider a nonlinear, non-stationary time series of household electricity demand to demonstrate the Bayesian implication to statistical techniques. In this forecasting process, the electricity demand is considered a function of...

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