Über Konjunkturprognosen auf der Grundlage einer monetären Schätzgleichung
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Über Konjunkturprognosen auf der Grundlage einer monetären Schätzgleichung
Eine Fallstudie
Credit and Capital Markets – Kredit und Kapital, Vol. 19 (1986), Iss. 1 : pp. 25–57
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Eirik Svindland, Berlin
References
-
Brunner, Karl (1970): The “Monetarist” Revolution in Monetary Theory, Weltwirtschaftliches Archiv, 105, S.1- 30.
Google Scholar -
Brunner, Karl und Allan H. Meltzer (1971): The Uses of Money, The American Economic Review 61, S. 784 – 805.
Google Scholar -
Brunner, Karl und Allan H. Meltzer (1972): Friedman’s Monetary Theory, The Journal of Political Economy 80, S. 837 – 851.
Google Scholar -
Brunner, Karl und Allan H. Meltzer (1974): Ein monetaristischer Rahmen für die aggregative Analyse, in Karl Brunner, Hans G. Monissen, ManfredJ. M. Neumann (Hrsg.), Geldtheorie, Köln 1974, S. 235 – 266.
Google Scholar -
Dean, James (1981): The Inflation Process: Where Conventional Theory Falters, American Economic Review 71, S. 362 – 367.
Google Scholar -
Friedman, Milton (1956): The Quantity Theory of Money: A Restatement, in ders. (Hrsg.): Studies in the Quantity Theory of Money, Chicago.
Google Scholar -
Friedman, Milton (1958): The Supply of Money and Changes in Prices and Output, in: The Relationship of Prices to Economic Stability and Growth, Compendium of Papers Submitted by Panelists Appearing before the Joint Economic Committee, Washington D.C. 1958, S. 241 – 256.
Google Scholar -
Friedman, Milton (1969): The Optimum Quantity of Money and Other Essays, Chicago, deutsche Ausgabe: Die optimale Geldmenge und andere Essays, München 1970.
Google Scholar -
Friedman, Milton (1971): A Theoretical Framework for Monetary Analysis, New York: National Bureau of Economic Research, Occasional Paper 112.
Google Scholar -
Friedman, Milton und Schwartz, Anna (1963): A Monetary History of the United States 1867 – 1960, New York, 1963.
Google Scholar -
Gebauer, Wolfgang (1975): Die Kausalitätsbeziehungen zwischen Geldmenge, Preisen und Produktion
Google Scholar -
Eine empirische Untersuchung für die Bundesrepublik Deutschland, Zeitschrift für die gesamte Staatswissenschaft 131, S. 603 – 625.
Google Scholar -
Haavelmo, T. (1944): The Probability Approach in Econometrics, Supplement to Econometrica, Bd. 12.
Google Scholar -
Johnston, J. (1979): Econometric Methods, 2nd Edition, International Student Edition, Tokyo, Auckland u.a. – Langfeldt, Enno und Peter Trapp (1982): The Relationship between Money, Economic Activity, and Prices in Norway, Kieler Arbeitspapier No. 140, Kiel: Institut für Weltwirtschaft an der Universität Kiel.
Google Scholar -
Langfeldt, Enno (1983, a): Kann eine monetäre Schätzgleichung zur Verbesserung der Konjunkturprognosen beitragen? Kredit und Kapital 16, Heft 2, S. 205 – 219.
Google Scholar -
Langfeldt, Enno (1983, b): Kann eine monetäre Schätzgleichung zur Verbesserung der Konjunkturprognosen beitragen? Erwiderung zum Beitrag von Charles C. Roberts, Kredit und Kapital 16, Heft 4, S. 528 – 530.
Google Scholar -
Mitchell, Wesley C. und Arthur F. Burns (1938): Statistical Indicators of Cyclical Revivals, New York: National Bureau of Economic Research, Bulletin No. 69.
Google Scholar -
Mosteller, Frederick und John W. Tukey (1977): Data Analysis and Regression, Reading, Mass. – Pigou, A. C. (1917): The Value of Money, Quarterly Journal of Economics, 32, S. 38 – 65, repr.: Readings in Monetary Theory; Ausgewählt von einem Ausschuß der American Economic Association, London 1952, S. 162 – 183.
Google Scholar -
Roberts, Charles C. (1983): Kann eine monetäre Schätzgleichung zur Verbesserung der Geldpolitik beitragen? Kommentar zum Beitrag von Enno Langfeldt, Kredit und Kapital 16, Heft 2, S. 220 – 236.
Google Scholar -
Spinanger, Dean und Norbert Walter (1983): The Reliability of Macroeconomic Forecasts, Kieler Arbeitspapiere Nr. 181, Kiel: Institut für Weltwirtschaft an der Universität Kiel.
Google Scholar -
Trapp, Peter (1976): Geldmenge, Ausgaben und Preisanstieg in der Bundesrepublik Deutschland, Kieler Studien Nr. 138, Kiel: Institut für Weltwirtschaft an der Universität Kiel.
Google Scholar -
Wagemann, Ernst (1928): Konjunkturlehre, Berlin.
Google Scholar
Abstract
On Trade Cycle Forecasts Based on a Monetary Estimating Equation
The tested Kiel estimating equation is wrongly specified, if it is understood as a dynamic version of the simple quantity theory. Its alternative monetaristic conception as the reduced form of an impulse model contains no statement on real development in conjunction with a specific steady growth of the monery supply. This argumentation is based on a weak hypothesis concerning structural constancy -- the numerical values of the parameters may vary with the algebraic sign remaining unchanged. Estimates and applications for short-range forecasts should take account of this variability. The information on monetary policy time lags implies that the assumed lag relationships lie within a single year. Consequently, estimates were also made on the basis of quarterly data. In comparison with the preceding quarter, good adjustment of the estimating equation to seasonal annual cycles was found. The quarterly data compared to the preceding year, however, exhibit a mixture of seasonal and cyclical fluctuations, which are not covered by the estimating equation. Cyclical fluctuations of the annual data, on the other hand, are well approximated. In all three cases, both the retrospective adjustment of the equation to the data and the result of the forecasting experiments are considerably better, if fresh data are used for shifting instead of prolonging the estimation interval. Since the changes in the estimation interval also occasion many changes in the algebraic signs of the parameters, correspondence of the data with the given monetaristic substantiation of the equation is very questionable. For the annual data equation, particularly interesting interrelationships were found between parameter changes and changes in the macroeconomic problems. As a forecasting instrument basedon time-series analysis, the eguation must be used with the same caution as all other extrapolations of time-series patterns