We suggest a new class of cross-sectional space-time models based on local AR models and nearest neighbors using distances between observations. For the estimation we use a tightness prior for prediction of regional GDP forecasts. We extend the model to the model with exogenous variable model...

We use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of...

Completing data sets that are collected in heterogeneous units is a quite frequent problem. Chow and Lin (1971) were the first to develop a united framework for the three problems (interpolation, extrapolation and distribution) of predicting times series by related series (the 'indicators')....

The paper compares the cointegration methods of Johansen and Bierens by means of simulations and a real world example. Drawing on the fact developed in a companion paper that the Johansen procedure has robustness properties against ARMA systems and the Bierens procedure is designed for ARMA...

The aggregate production function approach is one way to forecast future energy demand (a step in forecasting carbon dioxide emissions, for example) and to analyze the aggregate economic effects of measures such as the increase of taxes on energy use. The results of such an approach tend to...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...