It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean squared error (PMSE) in simulated out-of-sample (SOOS) forecasts. Alternatively, forecast models may be selected using information criteria (IC). We compare the asymptotic and...

Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date. This approach is based on the premise that demand for crude oil derives...

This paper analyses two features of concern to policy-makers in the countries of the prospective European Monetary Union: the solvency of their government’s finances; and the accuracy of fiscal forecasts. Extending the existing methodology of solvency tests, the paper finds that, with few...

This paper provides forecasts derived from Bayesian vector autoregressive (BVAR) models for the output growth, inflation and balance of payments of the G-5 and G-7 countries. These forecasts are compared with those derived from alternative time series models and with those provided by the...

We consider the problem of optimally combining individual forecasts of gross domestic product (GDP) and inflation from the Survey of Professional Forecasters (SPF) dataset for the Euro Area. Contrary to the common practice of using equal combination weights, we compute optimal weights which...

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known that exchange rate fluctuations are very difficult to predict using economic models, and that a random walk forecasts exchange rates...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single-period horizon with increasing...

Data sharing is common practice in forecasting experiments in situations where fresh data samples are difficult or expensive to generate. This means that forecasters often analyze the same data set using a host of different models and sets of explanatory variables. This practice introduces...

Forecasts guide decisions in all areas of economics and finance and their value can only be understood in relation to, and in the context of, such decisions. We discuss the central role of the loss function in helping determine the forecaster's objectives and use this to present a unified...

The efficient market hypothesis gives rise to forecasting tests that mirror those adopted when testing the optimality of a forecast in the context of a given information set. However, there are also important differences arising from the fact that market efficiency tests rely on establishing...