This article suggests the use of simple minimum-distance methods to estimate restricted cointegrating vectors. The method directly employs minimum-distance methods on unrestricted cointegrating matrices estimated in the usual way to estimate restricted parameters that are linearly or nonlinearly...

Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality...

We develop an unobserved-components approach to study surveys of forecasts containing multiple forecast horizons. Under the assumption that forecasters optimally update their beliefs about past, current, and future state variables as new information arrives, we use our model to extract...

Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality...

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...

This article presents empirical evidence on the existence of structural breaks in the fundamentals process underlying U.S. stock prices. I develop an asset-pricing model that represents breaks in the context of a Markov switching process with an expanding set of nonrecurring states. Different...