Has the accuracy of german macroeconomic forecasts improved?

The major focus of this paper is to determine whether the accuracy of German macroeconomic forecasts has improved over time. We examine 1-year-ahead forecasts of real GDP and inflation for 1967 to 2001 made by three major German forecasting groups and the OECD. We examine the accuracy of the forecasts over the entire period and in three sub-periods. We conclude that, with some exceptions, the errors of the German forecasters were similar to those of their US and UK counterparts. While the absolute size of the forecast errors has declined, this is not the case for relative accuracy. A benchmark comparison of these predictions with the ex post forecasts of a macroeconometric model indicates that the quality of the growth forecasts can be improved but that the expected increase in accuracy may not be substantial

Forecasting with macroeconometric models: A report from the trenches

Econometric models are a widely used and powerful tool in macroeconomic analysis and forecasting. Admittedly, their acceptance by the scientific community has had some hard times during the seventies and eighties: a general decline in the reputation of macroeconomics, the Lucas critique, and failures of the model community to make their often opaque practice transparent had left their marks. Closer looks at the criticism, however, revealed its limited relevance, and the „new/old macroeconomic consensus“ (Blinder, Zarnowitz) of the early 1990s seems to have restored much of the lost credibility. A lack of transparency, however, still diminishes acceptance and credibility of the results, at least within the academic community3. The apparent deficit in model transparency has a number of causes, a major one being the fact that the literature on the practice of macroeconometric forecasting is still sparse (cf. e.g., Klein, Young 1980, pp. 75ff., Adams 1986, pp. 106ff.) and, given the new technical opportunities for model and forecast analysis, it is also somewhat outdated. One explanation for this is that economic deliberations in the model industry back such disregard (Daub 1987, pp. 73ff.) and it may still take some time until the industry realises that transparency is the models' biggest asset. This paper describes in detail the production of a macroeconometric forecast, complementing and enlarging on two earlier papers on the subject (Heilemann 1985, 1990). The model used is the business cycle model of the Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI) which has been applied for forecasting since 1978

Deutschland im internationalen Vergleich - einige Fragezeichen

Die Debatte um den „Standort Deutschland“ wird durch immer neue Ergebnisse angeheizt. Was ist von den vorgestellten Befunden zu halten? Professor Ullrich Heilemann weist auf die oft willkürlichen inhaltlichen Verengungen, methodischen Mängel und die defizitäre empirische Basis hin. --

Deutschland im internationalen Vergleich - einige Fragezeichen

Die Debatte um den „Standort Deutschland“ wird durch immer neue Ergebnisse angeheizt. Was ist von den vorgestellten Befunden zu halten? Professor Ullrich Heilemann weist auf die oft willkürlichen inhaltlichen Verengungen, methodischen Mängel und die defizitäre empirische Basis hin

The economics of German Unification reconsidered

The task of vitalizing the east German economy was severely underestimated—by politicians as well as by both the academic and the business community. Despite all the encouraging signs in east Germany, which undeniably exist, the process will take more time, require more money, and need more east German commitment than had widely been expected. But will fiscal backing alone be enough to vitalize the east German economy? What are the tasks ahead? Are they being tackled in an adequate way

Bald so wie überall? Strukturwandel der ostdeutschen Wirtschaft 1992-2006

Ullrich Heilemann und Stefan Wappler, Universität Leipzig, untersuchen die strukturelle - vor allem die sektorale - Dimension des Anpassungs- und Aufholprozesses der ostdeutschen Wirtschaft

Classification and Clustering in Business Cycle Analysis

The analysis of cyclical macroeconomic phenomena is an important field of econometric research. In the recent past, research interests have de-emphasized quantitative forecasting exercises and have addressed the qualitative diagnosis of the relative stance of the economy regarding "upswing", "recession", or "boom" periods, i. e. the classification of the state of the economy into a limited number of discrete states. In this context the principal challenge is to reduce the multifaceted and sometimes abundant quantitative information about the business cycle to such qualitative statements in an efficient way. For more than six years this task was the focus of the project "Multivariate determination and analysis of business cycles" within the SFB 475 "Reduction of complexity in multivariate data structures", funded by the German Research Foundation (DFG). The necessity for complexity reduction is, of course, not unique to business cycle analysis but is studied in many fields and in a number of ways. This broad interest in the reduction of problem dimensionality and in the appropriate combination of data and of theory caused the RWI Essen and the Statistical Department of the University of Dortmund in January 2002 to hold a workshop at the RWI Essen where the findings of this and similar projects were presented and discussed. The present publication collects revised versions of the papers presented at this workshop. Although the workshop took place some five years ago, these papers mark an importent juncture in the development of business cycle research