Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-30T15:41:50.049Z Has data issue: false hasContentIssue false
  • English
  • Français

A DIALOGUE CONCERNING A NEW INSTRUMENT FOR ECONOMETRIC MODELING

Published online by Cambridge University Press:  08 February 2005

Clive W.J. Granger  and
David F. Hendry
Clive W.J. Granger
Affiliation:
University of California, San Diego
David F. Hendry
Affiliation:
University of Oxford
Get access Rights & Permissions [Opens in a new window]

Extract

This paper presents a set of questions prepared by Clive Granger with responses by David Hendry on the use of PcGets (see Hendry and Krolzig, 2001) in data modeling and as a new research tool. PcGets is an Ox package (see Doornik, 2001) implementing automatic general-to-specific (Gets) modeling for linear regression models based on the theory of reduction, as in Hendry (1995, Ch. 9).

Type
Research Article
Information
Econometric Theory , Volume 21 , Issue 1 , February 2005 , pp. 278 - 297
Copyright
© 2005 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Akaike, H. (1969) Fitting autoregressive models for prediction. Annals of the Institute of Statistical Mathematics 21, 243–247.Google Scholar
Andrews, D.W.K. (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817–858.Google Scholar
Bontemps, C. & G.E. Mizon (2003) Congruence and encompassing. In B.P. Stigum, (ed.), Econometrics and the Philosophy of Economics, pp. 354–378. Princeton University Press.
Brüggemann, R., H.-M. Krolzig, & H. Lütkepohl (2002) Comparison of Model Selection Procedures for VAR Processes. Mimeo, Humboldt-University, Berlin.
Campos, J., D.F. Hendry, & H.-M. Krolzig (2003) Consistent model selection by an automatic Gets approach. Oxford Bulletin of Economics and Statistics 65, 803–819.Google Scholar
Claeskens, G. & N.L. Hjort (2003) The focussed information criterion (with discussion). Journal of the American Statistical Association 98, 879–945.Google Scholar
Clements, M.P. & D.F. Hendry (1999) Forecasting Non-stationary Economic Time Series. MIT Press.
Dickey, D.A. & W.A. Fuller (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49, 1057–1072.Google Scholar
Doornik, J.A. (2001) Object-Oriented Matrix Programming Using Ox, 4th ed. Timberlake Consultants Press.
Haldrup, N., H. van Dijk, & D.F. Hendry (eds.) (2003) Oxford Bulletin of Economics and Statistics 65, special issue, Model Selection and Evaluation.
Hannan, E.J. & B.G. Quinn (1979) The determination of the order of an autoregression. Journal of the Royal Statistical Society, Series B 41, 190–195.Google Scholar
Heckman, J.J. (1976) The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement 5, 475–492.Google Scholar
Hendry, D.F. (1995) Dynamic Econometrics. Oxford University Press.
Hendry, D.F. & J.A. Doornik (2001) Empirical Econometric Modelling Using PcGive 10, Volume 1. Timberlake Consultants Press.
Hendry, D.F. & H.-M. Krolzig (2001) Automatic Econometric Model Selection. Timberlake Consultants Press.
Hendry, D.F. & H.-M. Krolzig (2004a) The properties of automatic Gets modelling. Economic Journal (forthcoming).Google Scholar
Hendry, D.F. & H.-M. Krolzig (2004b) Resolving Three “Intractable” Problems Using a Gets Approach. Manuscript, Economics Department, University of Oxford.
Hendry, D.F. & H.-M. Krolzig (2004c) Unbiased Estimation in Gets Modelling. Manuscript, Economics Department, Oxford University.
Hoover, K.D. & S.J. Perez (1999) Data mining reconsidered: Encompassing and the general-to-specific approach to specification search. Econometrics Journal 2, 167–191.Google Scholar
Krolzig, H.-M. (2003) General-to-specific model selection procedures for structural vector autoregressions. Oxford Bulletin of Economics and Statistics 65, 769–802.Google Scholar
Krolzig, H.-M. & D.F. Hendry (2004) Sub-sample model selection procedures in general-to-specific modelling. In R. Becker & S. Hurn (eds.), Contemporary Issues in Economics and Econometrics: Theory and Application, pp. 53–75. Edward Elgar.
Leeb, H. & B.M. Pötscher (2003a) Can One Estimate the Conditional Distribution of Post-Model-Selection Estimators? Working paper, Department of Statistics, Yale University.
Leeb, H. & B.M. Pötscher (2003b) The finite-sample distribution of post-model-selection estimators, and uniform versus non-uniform approximations. Econometric Theory 19, 100–142.Google Scholar
Leeb, H. & B.M. Pötscher (2005) Model selection and inference: Facts and fiction. Econometric Theory (this issue).Google Scholar
Lovell, M.C. (1983) Data mining. Review of Economics and Statistics 65, 1–12.Google Scholar
Omtzig, P. (2002) Automatic Identification and Restriction of the Cointegration Space. Thesis chapter, Economics Department, Copenhagen University.
Perez-Amaral, T., G.M. Gallo, & H. White (2003) A flexible tool for model building: The relevant transformation of the inputs network approach (RETINA). Oxford Bulletin of Economics and Statistics 65, 821–838.Google Scholar
Perez-Amaral, T., G.M. Gallo, & H. White (2005) A comparison of complementary automatic modeling methods: RETINA and PcGets. Econometric Theory (this issue).Google Scholar
Phillips, P.C.B. (1994) Bayes models and forecasts of Australian macroeconomic time series. In Hargreaves, C. (ed.), Non-stationary Time-Series Analyses and Cointegration. Oxford University Press.
Phillips, P.C.B. (1995) Automated forecasts of Asia-Pacific economic activity. Asia-Pacific Economic Review 1, 92–102.Google Scholar
Phillips, P.C.B. (1996) Econometric model determination. Econometrica 64, 763–812.Google Scholar
Phillips, P.C.B. (2003) Laws and limits of econometrics. Economic Journal 113, C26–C52.Google Scholar
Schwarz, G. (1978) Estimating the dimension of a model. Annals of Statistics 6, 461–464.Google Scholar
Sims, C.A., J.H. Stock, & M.W. Watson (1990) Inference in linear time series models with some unit roots. Econometrica 58, 113–144.Google Scholar
Sullivan, R., A. Timmermann, & H. White (2001) Dangers of data-driven inference: The case of calendar effects in stock returns. Journal of Econometrics 105, 249–286.Google Scholar
Wold, H.O.A. (1949) Statistical estimation of economic relationships. Econometrica 17, supplement, 1–21.Google Scholar
Wooldridge, J.M. (1999) Asymptotic properties of some specification tests in linear models with integrated processes. In R.F. Engle & H. White (eds.), Cointegration, Causality and Forecasting, pp. 366–384. Oxford University Press.