This article considers the consequences of explicitly allowing for stochastic technological progress and stochastic labor input in the discrete-time Solow-Swan and AK growth models. It shows that the capital-output ratio, but not output per capita, is ergodic irrespective of whether there is a...

This Paper develops a theoretical framework for the analysis of small sample properties of forecasts from general autoregressive models under structural breaks. Finite-sample results for the mean-squared forecast error of one-step-ahead forecasts are derived, both conditionally and...

The authors consider the solution of multivariate linear rational expectations models in the presence of heterogeneous information and social interactions. To overcome the 'infinite regress in expectations' problem that arises in the solution of these models, we assume that agents' expectations...

This paper focuses on whether to use macro or micro equations to predict aggregate variables. The Grunfeld-Griliches prediction criterion is generalized to allow for contemporaneous covariances across the micro equations and for parametric restrictions on the disaggregate equations. An...

This paper discusses alternative methods of testing for aggregation bias and proposes direct tests of the discrepancy of the macroparameters from the average of the corresponding microparameters, and derives tests of aggregation bias in the general case where the parameters of interest may...

This paper argues that probability forecasts convey information on the uncertainties that surround macro-economic forecasts in a straightforward manner which is preferable to other alternatives, including the use of confidence intervals. Point and probability forecasts obtained using a small...

This paper derives a distribution free procedure for testing the accuracy of forecasts when the focus of the analysis is on the correct prediction of the direction of change in the variable under consideration. The test applies to a general m x n contingency table and it is shown that the...