Structural econometric modeling and time series analysis: an integrated approach (1983)

doi:10.1017/CBO9780511493171.004

3 - Structural econometric modeling and time series analysis: an integrated approach (1983)

Published online by Cambridge University Press: 24 October 2009

Franz C. Palm ,

Carl F. Christ and

Christopher A. Sims

Edited by

Arnold Zellner and

Franz C. Palm

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Franz C. Palm: Affiliation:
Professor of Econometrics, Faculty of Economics and Business Administration, Maastricht University
Arnold Zellner: Affiliation:
University of Chicago
Franz C. Palm: Affiliation:
Universiteit Maastricht, Netherlands

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Summary

Introduction

An important and difficult part of econometric modeling is the specification of the model. Any applied econometrician knows how troublesome it can be to obtain a satisfactory specification of the model. While the problem of specification analysis has received increasing attention in econometric research in recent years, many of the existing econometric textbooks provide few guidelines on how to obtain a satisfactory specification. This is surprising as the specification of the model is necessary in order to justify the choice of an estimation or testing procedure among the large variety of existing procedures, the properties of which are well established given that the true model is known. The consequences of misspecification errors due to the exclusion of relevant explanatory variables are more extensively discussed in standard textbooks on econometrics. Misspecification tests such as the Durbin–Watson test belong to the tools of any empirical econometrician. Among the exceptions to what has been said about the treatment of specification analysis in textbooks, we should mention the book by Leamer (1978), in which he distinguishes six types of specification searches and presents solutions for each of them within a Bayesian framework. But the present state of econometric modeling leads us to stress once more Zellner's (1979, p. 640) conclusion concerning the research on structural econometric models (SEMs): “Most serious is the need for formal, sequential statistical procedures for constructing SEMs.”

Type: Chapter
Information: The Structural Econometric Time Series Analysis Approach , pp. 96 - 174

DOI: https://doi.org/10.1017/CBO9780511493171.004 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2004

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References

Anderson, T. W. (1971), The Statistical Analysis of Time Series (New York, John Wiley)

Barnett, W. A. (1980), “Economic monetary aggregates,” Journal of Econometrics 14, 11–48CrossRef Google Scholar

Blommestein, H. J. and F. C. Palm (1980), “Econometric specification analysis – an application to the aggregate demand for money in the Netherlands,” Paper presented at the Econometric Society World Meeting, Aix-en-Provence

Box, G. E. P. and G. M. Jenkins (1970), Time Series Analysis, Forecasting and Control (San Francisco, Holden-Day)

Box, G. E. P. and Pierce, D. A. (1970), “Distribution of residual autocorrelations in autoregressive integrated moving average time series models,” Journal of the American Statistical Association 65, 1509–26CrossRef Google Scholar

Box, G. E. P. and Tiao, G. C. (1975), “Intervention analysis with applications to economic and environmental problems,” Journal of the American Statistical Association 70, 70–9CrossRef Google Scholar

Byron, R. P. (1974), “Testing structural specification using the unrestricted reduced form,” Econometrica 42, 869–83CrossRef Google Scholar

Christ, C. F. (1975), “Judging the performance of econometric models of the US economy,” International Economic Review 16, 54–74CrossRef Google Scholar

Darroch, J. N. and Silvey, S. D. (1963), “On testing more than one hypothesis,” Annals of Mathematical Statistics 34, 555–67CrossRef Google Scholar

Davidson, J. E. H.et al. (1978), “Econometric modelling of aggregate time series relationship between consumers' expenditure and income in the United Kingdom,” Economic Journal 88, 661–92CrossRef Google Scholar

den Butter, F. A. G. and M. M. G. Fase (1979), “The demand for money in EEC countries,” Research Report, De Nederlandsche Bank NV

Dhrymes, Ph. J., et al. (1972), “Criteria for evaluation of econometric models,” Annals of Economic and Social Measurement 1/3, 291–324Google Scholar

Drèze, J. H. (1976), “Bayesian limited information analysis of the simultaneous equations model,” Econometrica 44, 1045–76CrossRef Google Scholar

Driehuis, W. (1972), Fluctuations and Growth in a Near Full Employment Economy (Rotterdam, Universitaire Pers Rotterdam)

Engle, R. F., D. F. Hendry and J. F. Richard (1980), “Exogeneity, causality and structural invariance in econometric modelling,” CORE Discussion Paper 8038, University of Louvain

Geweke, J. (1978), “Testing the exogeneity specification in the complete dynamic simultaneous equation model,” Journal of Econometrics 7, 163–86CrossRef Google Scholar

Godfrey, L. G. (1976), “Testing for serial correlation in dynamic simultaneous equation models,” Econometrica 44, 1077–84CrossRef Google Scholar

Granger, C. W. J. (1969), “Investigating causal relationships by econometric models and cross-spectral methods,” Econometrica 37, 424–38CrossRef Google Scholar

Granger, C. W. J. (1981), “Some properties of time series data and their use in econometric model specification,” Journal of Econometrics 16, 121–30CrossRef Google Scholar

Granger, C. W. J. and P. Newbold (1977), Forecasting Economic Time Series (New York, Academic Press)

Hannan, E. J. (1971), “The identification problem for multiple equation systems with MA errors,” Econometrica 39, 751–65CrossRef Google Scholar

Haugh, L. D. and Box, G. E. P. (1977), “Identification of dynamic regression (distributed lag) models connecting two time series,” Journal of the American Statistical Association 72, 121–30CrossRef Google Scholar

Hendry, D. F. (1974), “Stochastic specification in an aggregate demand model of the United Kingdom,” Econometrica 42, 559–78CrossRef Google Scholar

Hendry, D. F. (1980), “Predictive failure and econometric modelling in macroeconomics: the transactions demand for money,” in P. Ormerod (ed.), Modelling the Economy (London, Heinemann Educational)

Hendry, D. F. and Von Ungern-Sternberg, Th. (1980), “Liquidity and inflation effects on consumers' expenditure,” in A. S. Deaton (ed.), Essays in the Theory and Measurement of Consumers' Behaviour (Cambridge, Cambridge University Press)

Hernández-Iglesias, C. and Hernández-Iglesias, F. (1980), “Causality and the independence phenomenon: the case of the demand for money,” Journal of Econometrics 15, 247–64CrossRef Google Scholar

Jenkins, G. M. and Alavi, A. S. (1981), “Some aspects of modelling and forecasting multivariate time series,” Journal of Time Series Analysis 2, 1–48CrossRef Google Scholar

Kiviet, J. (1979), “Bounds for the effects of ARMA disturbances on tests for regression coefficients,” Report, University of Amsterdam

Leamer, E. (1978), Specification Searches – Ad Hoc Inference With Nonexperimental Data (New York, John Wiley)

Litterman, R. B. (1980), “A Bayesian procedure for forecasting with vector autoregressions,” manuscriptGoogle Scholar

Malinvaud, E. (1981), “Econometrics faced with the needs of macroeconomic policy,” Econometrica 49, 1363–77CrossRef Google Scholar

McCallum, B. T. (1976), “Rational expectations and the natural rate hypothesis: some consistent estimates,” Econometrica 44, 43–52CrossRef Google Scholar

Mizon, G. E. (1977), “Model selection procedures,” in G. J. Artis and A. R. Nobay (eds.) Studies in Modern Economic Analysis (Oxford, Basil Blackwell)

Mizon, G. E. and Hendry, D. F. (1980), “An empirical application and Monte Carlo analysis of tests of dynamic specification,” Review of Economic Studies 47, 21–46CrossRef Google Scholar

Nerlove, M. (1972), “Lags in economic behaviour,” Econometrica 40, 221–51CrossRef Google Scholar

Newbold, P. (1981), “Model checking in time series analysis,” Paper presented at the ASA–CENSUS–NBER Conference on Applied Time Series Analysis of Economic Data, Washington, DC, October

Nieuwenhuis, A. (1980), “Aggregate price equations,” Central Planning Bureau, The Hague, manuscript

Palm, F. C. (1981), “Structural econometric modelling and time series analysis – towards an integrated approach,” Vrije Universiteit, Economic Faculty, R. M. 1981–4

Prothero, D. L. and Wallis, K. F. (1976), “Modelling macroeconomic time series” (with discussion), Journal of the Royal Statistical Society, A 139, 468–500CrossRef Google Scholar

Rao, C. R. (1973), Linear Statistical Inference and its Applications, 2nd edn. (New York, John Wiley)

Samuelson, P. A. (1965), “Proof that properly anticipated prices fluctuate randomly,” Industrial Management Review 6, 41–9Google Scholar

Sargan, J. D. (1964), “Wages and prices in the United Kingdom: a study in econometric methodology,” in P. E. Hart, G. Mills, and J. K. Wittaker (eds.), Econometric Analysis for National Economic Planning (London, Butterworth)

Sargan, J. D. (1980), “Some tests of dynamic specification for a single equation,” Econometrica 48, 879–98CrossRef Google Scholar

Sargent, Th. J. (1981), “Interpreting economic time series,” Journal of Political Economy 89, 213–48CrossRef Google Scholar

Sargent, Th. J. and C. A. Sims (1977), “Business cycle modeling without pretending to have too much a priori economic theory,” in C. A. Sims (ed.), New Methods in Business Cycle Research: Proceedings From a Conference, Federal Reserve Bank of Minneapolis, 45–109

Schwarz, G. (1978), “Estimating the dimension of a model,” Annals of Statistics 6, 461–4CrossRef Google Scholar

Silvey, S. D. (1959), “The Lagrange multiplier test,” Annals of Mathematical Statistics 30, 389–407CrossRef Google Scholar

Sims, C. A. (1977), “Exogeneity and causal ordering in macroeconomic models,” in C. A. Sims, (ed.), New Methods in Business Cycle Research: Proceedings From a Conference, Federal Reserve Bank of Minneapolis, 23–43

Sims, C. A. (1980a), “Macroeconomics and reality,” Econometrica 48, 1–48CrossRef Google Scholar

Sims, C. A. (1980b), “Comparison of interwar and postwar business cycles: monetarism reconsidered,” American Economic Review 70 (2), 250–7Google Scholar

Taylor, D. G. (1972), “The effects of monetary growth on the interest rate,” unpublished PhD dissertation, University of Chicago

Tiao, G. C. and Box, G. E. P. (1981), “Modelling multiple time series with applications,” Journal of the American Statistical Association 76, 802–16Google Scholar

Trivedi, P. K. (1975), “Time series analysis versus structural models: a case of Canadian manufacturing behavior,” International Economic Review 16, 587–608CrossRef Google Scholar

Wallis, K. F. (1977), “Multiple time series analysis and the final form of econometric models,” Econometrica 45, 1481–98CrossRef Google Scholar

Zellner, A. (ed.) (1978), Seasonal Analysis of Economic Time Series (Washington, DC: US Department of Commerce, Bureau of the Census)

Zellner, A. (1979), “Statistical analysis of econometric models,” Journal of the American Statistical Association 74, 628–51; chapter 2 in this volumeCrossRef Google Scholar

Zellner, A. (1980), “Statistical analysis of hypotheses in economics and econometrics,” Business and Economics Statistics Section, Proceedings of the American Statistical Association, 199–203Google Scholar

Zellner, A. C. and Palm, F. (1974), “Time series analysis and simultaneous equation econometric models,” Journal of Econometrics 2, 17–54; chapter 1 in this volumeCrossRef Google Scholar

Zellner, A. C. and Palm, F. (1975), “Time series and structural analysis of monetary models of the US economy,” Sankhyā: The Indian Journal of Statistics, Series C 37, 12–56; chapter 6 in this volumeGoogle Scholar

Zellner, A. and Park, S. (1979), “Minimum expected loss (MELO) estimators for functions of parameters and structural coefficients of econometric models,” Journal of the American Statistical Association 74, 185–93CrossRef Google Scholar

McElroy, F. W. (1978), “A method of causal ordering,” International Economic Review 19, 1–23CrossRef Google Scholar

Zellner, A. and Palm, F. C. (1974), “Time series analysis and simultaneous equation econometric models,” Journal of Econometrics 2, 17–54; chapter 1 in this volumeCrossRef Google Scholar