This paper surveys recent developments in the evaluation of point forecasts. Taking West’s (2006) survey as a starting point, we brie‡y cover the state of the literature as of the time of West’s writing. We then focus on recent developments, including advancements in the evaluation of forecasts at the population level (based on true, unknown model coe¢ cients), the evaluation of forecasts in th...

Can a relatively small numerical weather prediction ensemble produce any more forecast information than can be reproduced by a Gaussian probability density function (PDF)? This question is examined using site-specific probability forecasts from the UK Met Office. These forecasts are based on the 51-member Ensemble Prediction System of the European Centre for Medium-range Weather Forecasts. Veri...

Binary events are involved in many economic decision problems. In recent years, considerable progress has been made in diverse disciplines in developing models for forecasting binary outcomes. We distinguish between two types of forecasts for binary events that are generally obtained as the output of regression models: probability forecasts and point forecasts. We summarize specification, estim...

As the old saying goes, “Don’t put all of your eggs in one basket lest you drop the basket and lose all of your eggs.” Suppose the head of a forecasting division of a company has two sources of forecasts for the company’s sales, one source being the forecasts generated by the division’s econometrics group using an econometric time series model and the other source being the aggregated forecasts...

Probabilistic forecasts of atmospheric variables are often given as relative frequencies obtained from ensembles of deterministic forecasts. The detrimental effects of imperfect models and initial conditions on the quality of such forecasts can be mitigated by calibration. This paper shows that Bayesian methods currently used to incorporate prior information can be written as special cases of a...

A Bayesian approach is developed to generate constrained and unconstrained forecasts in autoregressive-moving average time series models. Both are calculated by formulating the ARMA(p,q) model in such a way that it is possible to numerically compute the predictive distribution for any number of forecasts as in de Alba (1993). We obtain the posterior distribution of the parameters via Gibbs samp...

We extend research on fundamental accounting signals (signals) to a quarterly context and investigate the relative efficiency of analysts and whisperers in using signals in generating onequarter-ahead EPS forecasts. We find (1) a subset of signals found to be relevant in predicting one-year-ahead EPS changes are also relevant in predicting one-quarter-ahead EPS changes, (2) neither analysts nor...

Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF) temperature and wind...

This research evaluates the accuracy of demand forecasts using a sample of recently-completed projects in Minnesota and identifies the factors influencing the inaccuracy in forecasts. Based on recent research on forecast accuracy, the inaccuracy of traffic forecasts is estimated as the difference between forecast traffic and actual traffic, standardized by the actual traffic. The analysis indic...

The WMO (World Meteorological Organization) weather research programme, THORPEX (The Observing System Research and Predictability Experiment), ‘responds to the challenges associated with accelerating improvements in the skill of highimpact weather forecasts that (firstly) reduce and mitigate weather disasters and (secondly) increase the benefits provided by improved forecasts...(because) the te...