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On Optimal Simulations of Econometric Models
Published online by Cambridge University Press: 17 August 2016
Extract
In a recent note [Rouzier (1973, a)] we indicated a method for correcting certain parameters of an econometric model in order to minimize a weighted sum of mean square errors for the endogenous variables. A crude justification of this method was that, since the equations are generally estimated separately, there is no obvious reason why the complete model should lead to consistent solutions. Indeed, when a model is being constructed, there are implicit interactions whose effects are not revealed until numerical simulations are performed.
The final run of a model differs a lot from the first one because the builder adds subjective informations to the results of the estimation. But when changing a coefficient, or when opting for another specification, he is probably paying a price in terms of the economic meaning of certain trade-offs. This is a rather vague statement, but we think that this study is able to contribute to a more complete understanding of the mechanisms of our models.
In this paper, we intend to show that the above mentioned method can in fact be used not only to improve the performances, but also as a tool to analyze the trade-offs of a model.
- Type
- Research Article
- Information
- Recherches Économiques de Louvain/ Louvain Economic Review , Volume 41 , Issue 1 , March 1975 , pp. 35 - 49
- Copyright
- Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1975
Footnotes
*
Support from the Fonds de la Recherche Fondamentale Collective is gratefully acknowledged. I would to thank A.P. Barten and V. Ginsburgh for their helpful suggestions and E. de Souza for criticisms on earlier drafts. None of them, however, should be taken responsible for my errors.
References
Barten, A.P. and Carrin, G. (1972), The Degree ofcapacity Utilization Revisited, CORE, Heverlee, COMET 9.Google Scholar
Evans, M.K. and Klein, L.R. (1968), The Wharton Econometric Forecasting Model, University of Pennsylvania,Studies in Quantitative Economics, n° 2.Google Scholar
Fitzgerald, V.W. (1973), Dynamic Properties of a Non-Linear Econometric Model, in R.A. Williams and A.A. Powell (ed.), Econometric Studies of Macro and Monetary Relations, North-Holland Amsterdam.Google Scholar
Friedman, M. (1968), The Role of Monetary Policy, The American Economic Review, Vol.58 nr1.Google Scholar
Fromm, G. and Klein, L.R. (1969), Solutions of the Complete System, in The Brookings Model:
Some Further Results, North-Holland, Amsterdam.Google Scholar
Holbrook, R.S. (1973), An Approach to the Choice of Optimal Policy Using Large Econometric Models, Bank of Canada Staff Research Studies, n° 8.Google Scholar
Howrey, P. and Kelejian, H. (1971), Simulation Versus Analytical Solutions : The Case of Econometric Models, in Naylor, H.
Computer Simulations Experiments with Models of Economic Systems, Wiley.Google Scholar
Luenberger, D. (1973), Introduction to Linear and Nonlinear Programming, Addison-Wesley Publ. Co.
Google Scholar
Phelps, E.S. (1967), Phillips' Curves, Expectations of Inflation and Optimal Unemployment over Time, Economica, Vol.34, n° 135.10.2307/2552025Google Scholar
Philips, A.W. (1958), The Relationship Between Unemployment and the Rate of Change of Money Wage Rates in the U.K.: 1861-1957,
Economica, Vol.25, n° 100.10.2307/2550759Google Scholar
Philips, L. (1971), Substitution, Complementarity and the Residual Variations Around Dynamic Demand Curves, The American Economic Review, Vol.61, n° 4.Google Scholar
Rouzier, P. (1973), On Optimol Simularions of Econometric Models, A Note, lnstitut des Sciences Economiques, Louvain, Working Paper n° 7408.Google Scholar
Zellner, A., An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias, Journal of fhe American Statisrical Association, Vol.57, n° 2.Google Scholar