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Econometric Methodology at the Cowles Commission: Rise and Maturity

Published online by Cambridge University Press:  18 October 2010

E. Malinvaud
E. Malinvaud*
Affiliation:
Collège de France
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Abstract

Considering the contribution of the Cowles research institute to the development of econometrics, one has little choice in this address and must mainly focus attention on one major achievement, namely, the building of the simultaneous equation methodology. One does not need to demonstrate the indisputable fact that this methodology was conceived and elaborated at the Cowles Commission in the forties. Neither does one need to insist on the long standing significance of this achievement nor on its central place in any education or reflection concerning statistical inference about economic phenomena. More interesting is the question of how research at Cowles during the first 15 years of its existence led to this result and how further econometric research here during the last 30 years relates to the simultaneous equation achievement. Also relevant is the following question: how does the message that was sent out by the Cowles people to the world in 1950 stand today? Should it be replaced by another different one? Or should it simply be somewhat amended and supplemented?

To do full justice to the research work and achievements of the many econometricians that were associated with Cowles through the years would require a much longer paper than the present one. But one must at least try also to summarize here those main concerns that stood outside the simultaneous equation methodology.

Type
Research Article
Information
Econometric Theory , Volume 4 , Issue 2 , August 1988 , pp. 187 - 209
Copyright
Copyright © Cambridge University Press 1988 

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References

1. This information, as well as many others used in this text, is taken from Economic Theory and Measurement: A Twenty Year Research Report, 1932–1952, Cowles Commission for Research in Economics, University of Chicago, 1952.

2. A simple count of the number of Cowles Commission or Foundation Papers is admittedly not a very reliable measure of the number of publications that directly resulted from research made at Cowles, not to speak of a measure of the significance of this research. Publications sometimes occurred several years after the author had left Cowles and the decision to include reprints of the article in the series of papers implied submission, or at least approval, by the author and judgment on the part of the Foundation staff. But if, for this reason, the measure is biased against papers on econometric methodology, the fact is also revealing. Since 1982 the situation has definitely changed: during the five following years, the proportion of Cowles Foundation papers dealing primarily with econometric methodology exceeded 30%.

3. Sentence taken from the review of A Twenty Year Research Report, op. cit., that was published by Kenneth E. Boulding in Kyklos.

4. Tinbergen, J., Statistical Testing of Business-cycle Theories, Vol. I, A Method and Its Application to Investment Activity, Vol. II, Business Cycles in the United States of America, 1919–1932, League of Nations, Geneva, 1939.Google Scholar

5. Klein, L., Economic Fluctuations in the United States, 1921–1941, Cowles Commission Monograph No. 11, John Wiley, New York, 1950.Google Scholar

6. Koopmans, T. C., ed., Statistical Inference in Dynamic Economic Models, Cowles Commission Monograph No. 10, John Wiley, New York, 1950.Google Scholar

7. The text of the paper is available in mimeographed form together with the reply of J. Tinbergen and papers by T. Haavelmo and T. C. Koopmans; these are also available in print, within a Memorandum of the Oslo Institute of Economics, dated November 6, 1948, and entitled “Autonomy of Economic Relations.” I received the text of the paper, thanks to the assistance of T. C. Koopmans and P. Meinich, University of Oslo.

8. See A Twenty Year Research Report, p. 27 (op. cit.).

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17. For a recent presentation of this work see Fair, R., Specification, Estimation and Analysis of Macroeconometric Models, Harvard University Press, 1984.Google Scholar Readers acquainted with this work and with my writings about the present confusion of ideas in macroeconomics understand that I do appreciate Fair's macroeconomic contributions.

18. See in particular Chapter 8 of the book quoted above.

19. Rothenberg, T., Efficient Estimation with a priori Information, New Haven, Yale University Press, 1973.Google Scholar

20. Frankfurter Gesellschaft für Konjunkturforschung, Heft 5, Leipzig, 1933.

21. Frisch, R., Statistical Confluence Analysis by Means of Complete Regression Systems, Ÿkonomiste Institute, Oslo, 1934.Google Scholar

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23. Haavelmo, T., “The Probability Approach in Econometrics, Econometrica, Supplement, July 1944.CrossRefGoogle Scholar

24. Cowles Commission Monograph No. 10, p. 265.

25. Fisher, R. A., Statistical Methods for Research Workers, Oliver and Boyd, Edinburgh, first edition 1925, eleventh edition 1950.Google Scholar

26. Burns, A. F. and Mitchell, W. C., Measuring Business Cycles, National Bureau of Economic Research, New York, 1946.Google Scholar

27. Koopmans, T., “Measurement without Theory,” Review of Economic Statistics, 1947, pp. 161–172.CrossRefGoogle Scholar The article, as well as a thirty-page interchange about it between R. Vining and T. Koopmans in the same journal in 1949, was reprinted both in Gordon, R. A. and Klein, L. R., eds., Readings in Business Cycles, Homewood, Illinois, R. D. Irwin, 1965 Google Scholar, and in Scientific Papers of Tjalling C. Koopmans, Springer-Verlag, Berlin-Heidelberg, 1970.

28. Indeed, Chapter 2 of my Statistical Methods of Econometrics (North Holland Publishing Co., Amsterdam, third edition, 1980) strongly argues in favor of the probability approach and I repudiate nothing of it.

29. Cowles Commission Monograph No. 11, John Wiley, New York, 1950.

30. Learner, E. E., Specification Searches-Ad hoc Inference with Nonexperimental Data, John Wiley, New York, 1978.Google Scholar

31. Careful readers of Chapter 2 of my Statistical Methods of Econometrics may have noted that, after arguing for the explicit specification of a stochastic model formalizing the prior knowledge about the phenomenon, I explain what a Bayesian inference would be; classical principles of inference are then presented as providing ways of avoiding the difficult choice of prior distributions.

32. Sims, C. A., “Macroeconomics and Reality,” Econometrica, January 1980.CrossRefGoogle Scholar

33. One might, however, reflect on the lack of consistency between the various critiques now attacking macroeconomic practice. While C. Sims argues for a more careful reference to the facts, other economists are strongly stating sweeping conclusions based on very simple models that are much more incredible than current macroeconometric ones. What should we think, for instance, of studies on the role of monetary policy for economic stabilization when it is assumed that the price level instantaneously adapts to what is required for equality between the demand for money and the money supply?

34. See my comments on Doan, T., Litterman, R., and Sims, C., “Forecasting and Conditional Projection Using Realistic Prior Distributions,” Econometric Reviews, Spring 1984.CrossRefGoogle Scholar