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 macroeconomic forecasts and how a forecasting service should be chosen. The role of judgement in producing the forecasts is also considered where the evidence unequivocally favors such interventions. Finally the use of macroeconomic forecasts and their effectiveness is discussed. The conclusion drawn is that researchers have paid too little attention to the issue of improving the forecasting accuracy record. Areas where improvements would be particularly valuable are highlighted.Keywords: econometric models, macroeconomic forecasting, rationality, forecast evaluation, structural breaks, cliometrics, industry structure Considerable intellectual activity within the economics profession is devoted to the production, interpretation and analysis of forecasts of major economic variables. Since such forecasts are important to both government planning and industry, it is material to determine how well we, as a profession, have performed this activity and what lessons may lead to improvements. Given the number of analyses that have included predictions of one economic variable or another and the range and depth of the macroeconomic forecasting industry (as surveyed by Fildes, 1995), it is impossible, in one paper, to review all aspects of the field. We will, therefore, concentrate on surveying and analyzing the predictions of short-run GDP (GNP), with particular emphasis upon real GDP and inflation forecasts for the US and the UK, bringing in data from other countries only when necessary in order to have a common set of information about cyclical conditions, etc. We focus on GDP and inflation forecasts because these much predicted variables are of interest to the entire profession. Unfortunately, this emphasis precludes an analysis of the characteristics of the forecasts of other variables and leaves many questions unanswered, e.g. which GDP components were the hardest to predict and which contributed the most to the inaccuracy of the aggregate forecasts?While many techniques have been used to make short-run GDP forecasts, the focus of this article will be on quantitative methods. In examining methods designed to provide quantitative estimatesThe State of Macroeconomic Forecasting 2 of GDP, we will consider time series analyses, econometric models (as well as forecasts made using judgmental techniques), and the contribution that expert judgment has made to the modeling process. As the survey evidence in Fildes (1995, p.6) showed, this range of methods covers those used by macroeconomic forecasting services. Since other articles have compared the structure of many of the econometric models used in macroeconomic forecasting, f...
