Abstract
Many economic models have lagged values of the regressors in the regression equation. For example, it takes time to build roads and highways. Therefore, the effect of this public investment on growth in GNP will show up with a lag, and this effect will probably linger on for several years. It takes time before investment in research and development pays off in new inventions which in turn take time to develop into commercial products. In studying consumption behavior, a change in income may affect consumption over several periods. This is true in the permanent income theory of consumption, where it may take the consumer several periods to determine whether the change in real disposable income was temporary or permanent. For example, is the extra consulting money earned this year going to continue next year? Also, lagged values of real disposable income appear in the regression equation because the consumer takes into account his life time earnings in trying to smooth out his consumption behavior. This is the view of the life cycle hypothesis of consumption, and one’s life time income may be guessed by looking at past as well as current earnings.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
This chapter is based on the material in Maddala (1977), Johnston (1984), Kelejian and Oates (1989) and Davidson and MacKinnon (1993). Additional references on the material in this chapter include:
Akaike, H. (1973), “Information Theory and an Extension of the Maximum Likelihood Principle,” in B. Petrov and F. Csake, eds. 2nd. International Symposium on Information Theory, Budapest: Akademiai Kiado.
Almon, S. (1965), “The Distributed Lag Between Capital Appropriations and Net Expenditures,” Econometrica, 30: 407–423.
Breusch, T.S. (1978), “Testing for Autocorrelation in Dynamic Linear Models,” Australian Economic Papers, 17: 334–355.
Davidson, J.E.H., D.F. Hendry, F. Srba and S. Yeo (1978), “Econometric Modelling of the Aggregate Time-Series Relationship Between Consumers’ Expenditure and Income in the United Kingdom,” Economic Journal, 88: 661–692.
Dhrymes, P.J. (1971), Distributed Lags: Problems of Estimation and Formulation ( Holden-Day: San Francisco).
Durbin, J. (1970), “Testing for Serial Correlation in Least Squares Regression when Some of the Regressors are Lagged Dependent Variables,” Econometrica, 38: 410–421.
Fomby, T.B. and D.K. Guilkey (1983), “An Examination of Two-Step Estimators for Models with Lagged Dependent and Autocorrelated Errors,” Journal of Econometrics, 22: 291–300.
Gilbert, C.L. (1986), “Professor Hendry’s Econometric Methodology,” Oxford Bulletin of Economics and Statistics, 48: 283–307.
Godfrey, L.G. (1978), “Testing Against General Autoregressive and Moving Average Error Models when the Regressors Include Lagged Dependent Variables,” Econometrica, 46: 1293–1302.
Griliches, Z. (1961), “A Note on Serial Correlation Bias in Estimates of Distributed Lags,” Econometrica, 29: 65–73.
Hatanaka, M. (1974), “An Efficient Two-Step Estimator for the Dynamic Adjustment Model with Autocorrelated Errors,” Journal of Econometrics, 2: 199–220.
Jorgenson, D.W. (1966), “Rational Distributed Lag Functions,” Econometrica, 34: 135–149.
Kiviet, J.F. (1986), “On The Vigor of Some Misspecification Tests for Modelling Dynamic Relationships,” Review of Economic Studies, 53: 241–262.
Klein, L.R. (1958), “The Estimation of Distributed Lags,” Econometrica, 26: 553–565.
Koyck, L.M. (1954) Distributed Lags and Investment Analysis ( North-Holland: Amsterdam).
Maddala, G.S. and A.S. Rao (1971), “Maximum Likelihood Estimation of Solow’s and Jorgenson’s Distributed Lag Models,” Review of Economics and Statistics, 53: 80–88.
Nerlove, M. and K.F. Wallis (1967), “Use of the Durbin-Watson Statistic in Inappropriate Situations,” Econometrica, 34: 235–238.
Schwarz, G. (1978), “Estimating the Dimension of a Model,” Annals of Statistics, 6: 461–464.
Schmidt, P. (1974), “An Argument for the Usefulness of the Gamma Distributed Lag Model,” International Economic Review, 15: 246–250.
Schmidt, P. (1975), “The Small Sample Effects of Various Treatments of Truncation Remainders on the Estimation of Distributed Lag Models,” Review of Economics and Statistics, 57: 387–389.
Schmidt, P. and R. N. Waud (1973), “The Almon Lag Technique and the Monetary Versus Fiscal Policy Debate,” Journal of the American Statistical Association, 68: 11–19.
Solow, R.M. (1960), “On a Family of Lag Distributions,” Econometrica, 28: 393–406.
Wallace, T.D. (1972), “Weaker Criteria and Tests for Linear Restrictions in Regression,” Econometrica, 40: 689–698.
Wallis, K.F. (1967), “Lagged Dependent Variables and Serially Correlated Errors: A Reappraisal of Three-Pass Least Squares, Review of Economics and Statistics,49: 555–567.
Zellnner, A. and M. Geisel (1970), “Analysis of Distributed Lag Models with Application to Consumption Function Estimation,” Econometrica, 38: 865–888.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin · Heidelberg
About this chapter
Cite this chapter
Baltagi, B.H. (1998). Distributed Lags and Dynamic Models. In: Econometrics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-00516-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-662-00516-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63617-5
Online ISBN: 978-3-662-00516-3
eBook Packages: Springer Book Archive