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Haavelmo's Identification Theory

Published online by Cambridge University Press:  11 February 2009

John Aldrich
John Aldrich
Affiliation:
University of Southampton
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Abstract

This paper treats the theory of identification presented in Haavelmo's classic work, The Probability Approach in Econometrics. This was the first identification theory for stochastic models to be developed in econometrics. The paper presents a detailed commentary on Haavelmo's analysis. It also examines the development of Haavelmo's theory from Frisch's analysis of multicollinearity and also the relationship between Haavelmo's analysis and later work on identification.

Type
Articles
Information
Econometric Theory , Volume 10 , Issue 1 , March 1994 , pp. 198 - 219
Copyright
Copyright © Cambridge University Press 1994

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References

1.Aitchison, J. & Silvey, S.D.. Maximum-likelihood estimation procedures and associated tests of significance. Journal of the Royal Statistical Society B 22 (1960): 154–171.Google Scholar
2.Aldrich, J.Autonomy. Oxford Economic Papers 41 (1989): 15–34.CrossRefGoogle Scholar
3.Aldrich, J.Reiersol, Geary and the idea of instrumental variables. Economic and Social Review 24 (1993): 247–273.Google Scholar
4.Anderson, T.W.Estimating linear restrictions on regression coefficients for multivariate normal distributions. Annals of Mathematical Statistics 22 (1951): 327–351.CrossRefGoogle Scholar
5.Blackwell, D. & Koopmans, L.. On the identifiability problem for functions of finite Markov chains. Annals of Mathematical Statistics 28 (1957): 1011–1015.CrossRefGoogle Scholar
6.Bowden, R.The theory of parametric identification. Econometrica 41 (1973): 1069–1074.CrossRefGoogle Scholar
7.Box, G.E.P. & Jenkins, G.M.. Time Series Analysis, Forecasting and Control. San Francisco: Holden-Day, 1970.Google Scholar
8.Christ, C.Early progress in estimating quantitative economic relationships in America. American Economic Review 75 (1985): 39–52.Google Scholar
9.Corlett, W.J. Multicollinearity. In Eatwell, J. et al. (eds.), The New Palgrave, A Dictionary of Economics, Vol. 3, pp. 561–562London: Macmillan, 1987.Google Scholar
10.Epstein, R.J.A History of Econometrics. Amsterdam: North-Holland, 1987.Google Scholar
11.Fischer, F.M.The Identification Problem in Econometrics. Huntingdon, New York: Krieger, (Reprint with new preface of book originally published in 1966 by McGraw-Hill.)CrossRefGoogle Scholar
12.Frisch, R.Correlation and scatter in statistical variables. Nordic Statistical Journal 8 (1929): 36–102.Google Scholar
13.Frisch, R. Pitfalls in the statistical construction of demand and supply curves. Veröffentlichungen der Frankfurter Gesellschaft für Konjuncturforschung. Leipzig: Hans Buske, 1933.Google Scholar
14.Frisch, R.Statistical Confluence Analysis by Means of Complete Regression Systems. Oslo: University Institute of Economics, 1934.Google Scholar
15.Frisch, R. Statistical versus theoretical relations in economic macrodynamics. League of Nations Memorandum. Geneva: League of Nations, 1938.Google Scholar
16.Gallant, A.R. & White, H.. A Unified Theory of Estimation and Inference for Nonlinear Dynamic Models. Oxford: Basil Blackwell, 1988.Google Scholar
17.Geary, R.C.Studies in relations between economic time series. Journal of the Royal Statistical Society, B 10 (1948): 140–158.Google Scholar
18.Girshick, M.A. & Haavelmo, T.. Statistical analysis of the demand for food: examples of simultaneous estimation of structural equations. Econometrica 15 (1947): 79–110.CrossRefGoogle Scholar
19.Haavelmo, T.The method of supplementary confluent relations, illustrated by a study of stock prices. Econometrica 6 (1938): 203–218.CrossRefGoogle Scholar
20.Haavelmo, T.The problem of testing economic theories by means of passive observationsPaper presented at the 1940 Cowles Commission Conference.Google Scholar
21.Haavelmo, T.On the Theory and Measurement of Economic Relations. Mimeo, Cambridge, Massachusetts, (Published as Haavelmo [22].)Google Scholar
22.Haavelmo, T.The statistical implications of a system of simultaneous equations. Econometrica 11 (1943): 1–12.CrossRefGoogle Scholar
23.Haavelmo, T.The probability approach in econometrics. Supplement to Econometrica 12 (1944).CrossRefGoogle Scholar
24.Haavelmo, T. Remarks on Frisch's confluence analysis and its use in econometrics. In Koopmans, T.C. (ed.), Statistical Inference in Dynamic Economic Models, Chapter 5 and pp. 258–265New York: Wiley, 1950.Google Scholar
25.Hendry, D.F. & Morgan, M.S.. A re-analysis of confluence analysis. Oxford Economic Papers 41 (1989): 35–52.CrossRefGoogle Scholar
26.Hsiao, C. Identification. In Griliches, Z. and Intriligator, M. (eds.), Handbook of Econometrics, Vol. I, Chapter 4 and pp. 224–283Amsterdam: North-Holland, 1983.Google Scholar
27.Johansen, S.Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. Econometrica 59 (1991): 1551–1580.CrossRefGoogle Scholar
28.Kalman, R.E. System identification from noisy data. In Bednarek, A.R. and Cesari, L. (eds.), Dynamical Systems II, Lecture 9 and pp. 135–164San Diego: Academic Press, 1982.Google Scholar
29.Koopmans, T.C.Linear Regression Analysis of Economic Time Series. Haarlem: F. Bohn, 1937.Google Scholar
30.Koopmans, T.C.Identification problems in economic model construction. Econometrica 17 (1949): 125–144.CrossRefGoogle Scholar
31.Koopmans, T.C. When is an equation system complete for statistical purposes? In Koopmans, T.C. (ed.), Statistical Inference in Dynamic Economic Models, Chapter 17 and pp. 393–409. New York: Wiley, 1950.Google Scholar
32.Koopmans, T.C. & Reiersol, O.. The identification of structural characteristics. Annals of Mathematical Statistics 21 (1950): 165–181.CrossRefGoogle Scholar
33.Koopmans, T.C., Rubin, H. & Leipnik, R.B.. Measuring the equation systems of dynamic economics. In Koopmans, T.C. (ed.), Statistical Inference in Dynamic Economic Models, Chapter 2 and pp. 52–237. New York: Wiley, 1950.Google Scholar
34.Malinvaud, E.Econometric methodology: rise and maturity. Econometric Theory 5 (1988): 405–429.Google Scholar
35.Mann, H.B. & Wald, A.. On the statistical treatment of linear stochastic difference equations. Econometrica 11 (1943): 173–220.CrossRefGoogle Scholar
36.Marschak, J. Economic interdependence and statistical analysis. In Lange, O. et al. (eds.), Studies in Mathematical Economics and Econometrics in Memory of Henry Schultz, Chapter 12 and pp. 135–150Chicago: Chicago University Press, 1942.Google Scholar
37.Moore, E.F. Gedanken-experiments on sequential machines. In Shannon, C.E. and McCarthy, J. (eds.), Automata Studies, pp. 129–153. Princeton: Princeton University Press, 1956.Google Scholar
38.Morgan, M.S.The History of Econometric Ideas. New York: Cambridge University Press, 1990.CrossRefGoogle Scholar
39.Qin, D.Formalisation of identification theory. Oxford Economic Papers 41 (1989): 73–93.CrossRefGoogle Scholar
40.Rothenberg, T.J.Identification in parametric models. Econometrica 39 (1971): 577–591.CrossRefGoogle Scholar
41.Shilov, G.E.An Introduction to the Theory of Linear Spaces. Englewood Cliffs, New Jersey: Prentice-Hall, 1961.Google Scholar
42.Silvey, S.D.The lagrangian multiplier test. Annals of Mathematical Statistics 30 (1959): 389–407.CrossRefGoogle Scholar
43.Spanos, A.On rereading Haavelmo: a retrospective view of econometric modelling. Econometric Theory 5 (1989): 405–429.CrossRefGoogle Scholar
44.Tinbergen, J.Statistical Testing of Business Cycle Theories, I: A Method and Its Application to Investment Activity. Geneva: League of Nations, 1939.Google Scholar
45.Tintner, G.A note on rank, multicollinearity and multiple regression. Annals of Mathematical Statistics 16 (1945): 304–308.CrossRefGoogle Scholar
46.Tintner, G.Multiple regression for systems of equations. Econometrica 14 (1946): 5–36.CrossRefGoogle Scholar
47.Wald, A.Review of Haavelmo's Probability Approach. Mathematical Reviews 6 (1945): 93–94.Google Scholar
48.Wald, A.Note on the consistency of the maximum likelihood estimate. Annals of Mathematical Statistics 20 (1949): 595–601.CrossRefGoogle Scholar
49.Wald, A. Note on the identification of economic relations. In Koopmans, T.C. (ed.), Statistical Inference in Dynamic Economic Models, Chapter 3 and pp. 238–243New York: Wiley, 1950.Google Scholar
50.Wegge, L.L.Identifiability criteria for a system of equations as a whole. Australian Journal of Statistics 7 (1965): 65–77.CrossRefGoogle Scholar
51.Zadeh, L.From circuit theory to system theory. Proceedings of the Institute of Radio Engineers 50 (1962): 856–865.Google Scholar