The Forecasting Performance of Business Economists During the Great Recession

It is generally believed that the recession of 2007-2009 was not foreseen by business economists. Is this perceived view accurate? We explore this issue by examining business economists’ published statements about economic conditions. We compare these qualitative forecasts with the Beige Book. We conclude that both sets of data are similar and that business economists are responsive to information about the economy and adjust their predictions quickly.Business forecasts; Great Recession; Beige Book; Payroll Data

Predicting the Outcomes of NCAA Basketball Championship Games

This paper uses the difference in seeding ranks to predict the outcome of March Madness games. It updates the Boulier-Stekler method by predicting the outcomes by rounds. We also use the consensus rankings obtained from individuals, systems and poll. We conclude that the consensus rankings were slightly better predictors in the early rounds but had the same limitations as the seedings in the later rounds.Sports forecasts, March Madness, Ranking methods, Expert forecasts, Consensus forecasts

Evaluating Current Year Forecasts Made During the Year: A Japanese Example

Forecasts for the current year that are made sometime during the current year are not true annual forecasts because they include already known information for the early part of the year. The current methodology that evaluates these ¡°forecasts¡± does not take into account the known information. This paper presents a methodology for calculating an implicit forecast for the latter part of a year conditional on the known information. We then apply the procedure to Japanese forecasts for 1988-2003 and analyze some of the characteristics of those predictions.Length: 24 pagesForecasting, Japanese forecasts, evaluation techniques

Examining the Quality of Early GDP Component Estimates

In this paper we examine the quality of the initial estimates of headline GDP and 10 major components of both real and nominal U.S. GDP. We ask a number of questions about various characteristics of the differences between the initial estimates available one month after the end of the quarter to the estimates available three months after the end of the quarter. Do the first estimates have the same directional signs as the later numbers? Are the original numbers unbiased estimates of the later figures? Are any observed biases related to the state of the economy? Finally, we determine whether there is a significant difference between the vector of the 30 day estimates of the 10 major components and the vector of the 90 day estimates of the same components. We conclude that, despite the existence of some bias, under most circumstances, an analyst could use the early data to obtain a realistic picture of what had happened in the economy in the previous quarter.Flash Estimates, Data Revisions, GDP Components, Statistical Tests, Business Cycles

Differences in Early GDP Component Estimates Between Recession and Expansion

In this paper we examine the quality of the initial estimates of the components of both real and nominal U.S. GDP. We introduce a number of new statistics for measuring the magnitude of changes in the components from the initial estimates available one month after the end of the quarter to the estimates available 3 months after the end of the quarter. We further specifically investigate the potential role of changes in the state of the economy for these changes. Our analysis shows that the early data generally reflected the composition of the changes in GDP that was observed in the later data. Thus, under most circumstances, an analyst could use the early data to obtain a realistic picture of what had happened in the economy in the previous quarter. However, the differences in the composition of the vectors of the two vintages were larger during recessions than in expansions. Unfortunately, it is in those periods when accurate information is most vital for forecasting.Flash Estimates, Data Revisions, GDP Components, Statistical Tests, Business Cycles

Jointly Evaluating the Federal Reserve’s Forecasts of GDP Growth and Inflation

In this paper we jointly evaluate the Federal Reserve staff forecasts of U.S. real output growth and the inflation rate assuming the forecasts are to be used as inputs for the Taylor rule. Our simple methodology generates “policy forecast errors” which have a direct interpretation for the impact of forecast errors on the target interest rate given by the Taylor rule. Without interest rate smoothing, we find that, on average, the Taylor rule target interest rate would have been approximately a full percentage point away from the intended target because of errors in forecasting output growth and inflation. Our results are robust to changes in the forecast horizon and to changes in the weights on the variables in the policy rule.Evaluating Forecasts, Macroeconomic Forecasts, Loss Function,Inflation Forecasting, GDP Growth Forecasting, Monetary Policy