Clustering Regression Functions in a Panel
AbstractWhen time series data of a reasonable length for several cross sectional units are available (for example in the analysis of CO2 emission in industrial countries, or the estimation of production functions for 20 manufacturing sectors), researchers begin by testing whether the data can be pooled and a single dynamic model can be built for all cross sectional units. The "pooling restriction" is often rejected, and then researchers usually proceed by estimating separate dynamic regressions for each cross sectional unit. However, it has been noted in many of such situations that using the pooled model, or shrinking the individual models towards the pooled model, produces superior forecasts relative to individual models. We note that rejecting the grand pooling restriction does not necessarily imply that all cross sectional units must be different. This paper suggests a hierarchical clustering algorithm with a global objective function, to partially pool regressions when the overall pooling restriction is rejected by the data. In addition to the lack of fit and lack of parsimony, the objective function also penalizes lack of conformity with theoretical priors and imprecision in the estimated parameters. This algorithm is used for clustering the gasoline demand functions of OECD countries. The results are compared with those of an alternative method based on a classification and regression tree (CART) procedure. Keywords: Medium sized panels, cluster analysis, information criteria, minimum message length, classification and regression tree (CART).
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0251.
Date of creation: 01 Aug 2000
Date of revision:
Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Burnside, Craig, 1996. "Production function regressions, returns to scale, and externalities," Journal of Monetary Economics, Elsevier, Elsevier, vol. 37(2-3), pages 177-201, April.
- repec:att:wimass:9419 is not listed on IDEAS
- Bearse, Peter M & Bozdogan, Hamparsum & Schlottmann, Alan M, 1997. "Empirical Econometric Modelling of Food Consumption Using a New Informational Complexity Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 12(5), pages 563-86, Sept.-Oct.
- Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, Elsevier, vol. 13(2), pages 161-174, June.
- Durlauf, S.M. & Johnson, P.A., 1995.
"Multiple Regimes and Cross-Country Growth Behavior,"
Working papers, Wisconsin Madison - Social Systems
9419r, Wisconsin Madison - Social Systems.
- Durlauf, Steven N & Johnson, Paul A, 1995. "Multiple Regimes and Cross-Country Growth Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 10(4), pages 365-84, Oct.-Dec..
- Vahid, Farshid & Engle, Robert F., 1997. "Codependent cycles," Journal of Econometrics, Elsevier, Elsevier, vol. 80(2), pages 199-221, October.
- Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, Elsevier, vol. 77(2), pages 303-327, April.
- Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 15(1), pages 90-100, January.
- Hirschberg, Joseph G. & Maasoumi, Esfandiar & Slottje, Daniel J., 1991. "Cluster analysis for measuring welfare and quality of life across countries," Journal of Econometrics, Elsevier, Elsevier, vol. 50(1-2), pages 131-150, October.
- Boozer, Michael A., 1997. "Econometric Analysis of Panel Data Badi H. Baltagi Wiley, 1995," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 13(05), pages 747-754, October.
- Baltagi, Badi H. & Griffin, James M., 1983. "Gasoline demand in the OECD : An application of pooling and testing procedures," European Economic Review, Elsevier, Elsevier, vol. 22(2), pages 117-137, July.
- Duck, Nigel W, 1993. "Some International Evidence on the Quantity Theory of Money," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 25(1), pages 1-12, February.
- Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 8(4), pages 341-60, Oct.-Dec..
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 251-76, March.
- Anderson, Heather M. & Vahid, Farshid, 1998. "Testing multiple equation systems for common nonlinear components," Journal of Econometrics, Elsevier, Elsevier, vol. 84(1), pages 1-36, May.
- Enrica De Cian & Elisa Lanzi & Roberto Roson, 2013. "Seasonal temperature variations and energy demand," Climatic Change, Springer, Springer, vol. 116(3), pages 805-825, February.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.