A set of rigorous diagnostic techniques is used to evaluate the forecasting performance of five multivariate time-series models for the U.S. cattle sector. The root-meansquared-error criterion along with an evaluation of the rankings of forecast errors reveals that the Bayesian vector autoregression (BVAR) and the unrestricted VAR (UVAR) models generate forecasts which are superior to both a re...

This article continues study of the prequential framework for evaluating a probability forecaster. Testing the hypothesis that the sequence of forecasts issued by the forecaster is in agreement with the observed outcomes can be done using prequential notions of probability. It turns out that there are two natural notions of probability in the prequential framework: game-theoretic, whose idea go...

"This article is a review of--and response to--a special issue of Mathematical Population Studies that focused on the relative performance of simpler vs. more complex population projection models. I do not attempt to summarize or comment on each of the articles in the special issue, but rather present an additional perspective on several points: definitions of simplicity and complexity, empiric...

This paper introduces new ways to construct probability integral transforms of random vectors that complement the approach of Diebold, Hahn, and Tay (1999) for evaluating multivariate conditional density forecasts. Our approach enables us to “scan” multivariate densities in various different ways. A simple bivariate normal example is given that illustrates how “scanning” a multivariate density ...

In this paper a number of alternative ACD models are compared using a sample of data for three major companies traded on the Australian Stock Exchange. The comparison is performed by employing the methodology for evaluating density and interval forecasts, developed by Diebold, Gunther and Tay (1998) and Christoffersen (1998), respectively. Our main finding is that the generalized gamma and log-...

Skillful medium-range weather forecasts are critical for water resources planning and management. This study aims to improve 15-day-ahead accumulated precipitation forecasts by combining biweekly weather and disaggregated climate forecasts. A combination scheme is developed to combine reforecasts from a numerical weather model and disaggregated climate forecasts from ECHAM4.5 for developing 15-...

Probabilistic population forecasts are useful because they describe uncertainty in a quantitatively useful way. One approach (that we call LT) uses historical data to estimate stochastic models (e.g., a time series model) of vital rates, and then makes forecasts. Another (we call it RS) began as a kind of randomized scenario: we consider its simplest variant, in which expert opinion is used to ...

In this study, an investigation of long-term forecasts relating to the development of the transport sector in Poland is performed, including the ones by 2030 and 2050. Selected transport development forecasts from the perspective of the membership of Poland in the European Union are presented and most of all, from the perspective of national studies. The basement for the review was the prognosi...

Recent research has begun to question the importance of forecasts to sell-side analysts. Prior research established the co-existence of longer horizon optimism and short-term pessimism in sell-side forecasts. These factors motivate us to explore a new phenomenon – crowdsourcing, as an alternative source of forecasts. We obtain revenue and earnings forecasts from estimize, an entity which crowds...