An analysis of RSQE forecasts: 1971–1992

The purpose of this paper is to evaluate the accuracy of ex ante econometric model forecasts of four key macroeconomic variables: real GNP growth, the rate of price inflation measured by the GNP deflator, the civilian unemployment rate, and the Treasury Bill rate. Annual forecasts produced by the Research Seminar in Quantitative Economics (RSQE) based on the Michigan Quarterly Econometric Model of the U.S. Economy are compared with quasi ex ante forecasts from a four-variable vector autoregressive (VAR) model. Statistical tests of the equality of forecast error variances as well as univariate and multivariate forecast encompassing-type tests are conducted. The forecast error variance comparisons indicate that for three of the four variables the RSQE forecasts are more accurate than the VAR forecasts and for one of the variables (real GNP growth) only slightly less accurate. The forecast encompassing-type tests indicate that the RSQE forecasts contain information not contained in the VAR forecasts and, conversely, that VAR forecasts contain information not included in the RSQE forecasts. The scope for improving RSQE forecasts by combining them with VAR forecasts is rather limited, however.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43925/1/11293_2006_Article_BF02299030.pd

Man vs. model? The role of judgment in forecasting

This article presents evidence on the role that judgmental adjustments play in macroeconomic forecast accuracy. It starts by contrasting the predictive records of four prominent forecasters who adjust their models with those of three models that are used mechanically. The adjusted forecasts tend to be more accurate overall, although important exceptions can be found. Next the article compares adjusted forecasts with those generated mechanically by the same models. Again, with some significant exceptions, judgmental adjustments improve accuracy more often than not. ; The article closes by considering whether macroeconomic forecasters should place more or less emphasis on their adjustments relative to their models. The author finds a clear tendency for modelers to overadjust their models, illustrating what prominent psychologists have termed "the major error of intuitive prediction." In short, model builders should not hesitate to adjust their models to offset models’ limitations but should also guard against the tendency to overestimate the value of their personal insights.Forecasting

How fast can we grow?

Nearly thirty years ago, Arthur Okun posed the question, "How much output can the economy produce under conditions of full employment?" He offered a "simple and direct" answer that now, with the benefit of hindsight, seems outmoded and inadequate. This article argues that a minor modification of Okun’s procedure based on demographics can adequately account for changes in the potential growth rate over the last 35 years and provide an idea of what to expect in the next ten years. Specifically, it is suggested that changes in the composition and rate of growth of the working-age population can account for the low rate of growth of potential GNP in the 1980s as well as suggest that it will revert to a more typical 2.5 to 2.75 percent by the late 1990s.Productivity ; Labor supply

A forward-looking monetary policy reaction function: continuity and change

This study suggests that U.S. monetary policy has been influenced by forecasts of and past experience with three broad factors: inflation, economic activity, and the monetary aggregates. The influence of each factor has varied, however, within this common theme. In the past 22 years at least two specific changes have occurred: the October 1979 shift to greater emphasis on a narrow measure of money and a shift in the early 1980s from M1 targeting to M2. ; The author models monetary policy econometrically, testing the influence of numerous factors on monetary policy and investigating whether a formal model can capture variations in these factors and in the policy instrument. The study also tests the influence of a number of other factors that are often thought to have an impact on monetary policy, such as measufes Of fiscal policy, exchange rates, and stock prices, as well as the President and Fed Chairman and the political party in power. The results indicate that monetary policy does not react systematically to these other factors.Monetary policy