Seasonal streamflow forecasts contingent on climate information are essential for shortterm planning and for setting up contingency measures during extreme years. Recent research shows that operational climate forecasts obtained by combining different General Circulation Models (GCM) have improved predictability/skill in comparison to the predictability from single GCMs [Rajagopalan et al., 200...

With the global proliferation of wind power, accurate short-term forecasts of wind resources at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological and statistical expertise to obtain accurate and calibrated, fully probabilistic forecasts of wind speed and wind power. The model formulation is parsimonious, yet takes account of all the salient ...

This paper examines the predictive power of weather for electricity prices in dayahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of Scandinavian day-ahead electricity prices substantially in terms of point forecasts, suggesting that weather forecasts can price the weather premium. This improvement strengthens the confidence in the forecasting mo...

This paper examines factors influencing voluntary forecast disclosure by target companies, whether good/bad news forecasts are disclosed and the influence of forecasts on the outcome of hostile bids. Disclosure was significantly more likely during contested bids. In agreed bids, probability of forecast disclosure was greater the shorter the bid horizon. In contested bids, forecasts were more li...

We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects the forecasters to report their posterior expectations honestly, ...

This article provides a simple shrinkage representation that describes the operational characteristics of various forecasting methods designed for a large number of orthogonal predictors (such as principal components). These methods include pretest methods, Bayesian model averaging, empirical Bayes, and bagging. We compare empirically forecasts from these methods with dynamic factor model (DFM)...

We defend the forecasting performance of the FOMC against a criticism of Christina and David Romer (2008) by assuming that the FOMC’s forecasts depict a worst-case scenario that it uses to design decisions that are robust to misspecification of the staff’s model. We use a simple macro model and a plausible loss function to illustrate how such an interpretation of the FOMC’s forecasts can explai...

We compare the performance of a subset of CBO’s economic forecasts against that of an unrestricted vector autoregression (VAR) model. We evaluate forecasts of real economic indicators as well as budget-related nominal statistics. We find that under most specifications, the VAR performs competitively with, if slightly worse than, the corresponding CBO forecasts at up to 20 quarters. Therefore, a...

Standard forecasting criteria like the mean square error (MSE) compare point forecasts or a location parameter of the forecasting distribution with actual observations. Such criteria are less suited to comparing forecasts of volatile time series. Therefore we use the average predictive ordinate (APOC) criterion which evaluates the ordinate of the predictive distribution. Using the comparison to...

We analyze the narratives that accompany the numerical forecasts in the Bank of England’s Inflation Reports. We focus on whether the narratives contain useful information about the future course of key macro variables over and above the point predictions, in terms of whether the narratives can be used to enhance the accuracy of the numerical forecasts. We also consider whether the narratives ar...