Abstract: Using evaluation methodologies for rare events from meteorology and psychology, we examine the value of probability forecasts of real GDP declines during the current and each of the next four quarters using data from the Survey of Professional Forecasters. We study the quality of these probability forecasts in terms of calibration, resolution, the relative operating characteristic (RO...

The forecast evaluation literature has traditionally focused on methods for assessing point-forecasts. However, in the context of risk models, interest centers on more than just a single point of the forecast distribution. For example, value-at-risk (VaR) models which are currently in extremely wide use form interval forecasts. Many other important financial calculations also involve estimates ...

BACKGROUND Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs. generative methods, and so on. In some of the more popular comparative methods, researchers compare observed epidemiological data from the early stages...

In this paper, we develop parametric tests for the correct density forecasts. Similar to Berkowitz (2001), we construct our tests by nesting a series of i.i.d. uniform random variables in a class of stationary Markov processes. Unlike Berkowitz (2001), the class of Markov processes in this paper is constructed via the copula approach, which allows the separate modeling of the marginal distribut...

Macroeconomic forecasts are used extensively in industry and government The historical accuracy of US and UK forecasts are examined in the light of different approaches to evaluating macro forecasts. Issues discussed include the comparative accuracy of macroeconometric models compared to their time series alternatives, whether the forecasting record has improved over time, the rationality of ma...

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertai...

Capturing the uncertainty in probabilistic wind power forecasts is challenging, especially when uncertain input variables, such as weather, play a role. Since ensemble weather predictions aim to capture system, they can be used propagate this through subsequent forecasting models. However, systems are known biased and underdispersed, meteorologists post-process ensembles. This post-processing s...

In many different contexts, decision-making is improved by the availability of probabilistic predictions. The accuracy forecasting methods can be compared using scoring functions and insight provided calibration tests. These tests evaluate consistency predictions with observations. Our main agenda in this paper interval forecasts their evaluation. Such are usually bounded two quantile forecasts...