Model-based Clustering of non-Gaussian Panel Data
AbstractIn this paper we propose a model-based method to cluster units within a panel. The underlying model is autoregressive and non-Gaussian, allowing for both skewness and fat tails, and the units are clustered according to their dynamic behaviour and equilibrium level. Inference is addressed from a Bayesian perspective and model comparison is conducted using the formal tool of Bayes factors. Particular attention is paid to prior elicitation and posterior propriety. We suggest priors that require little subjective input from the user and possess hierarchical structures that enhance the robustness of the inference. Two examples illustrate the methodology: one analyses economic growth of OECD countries and the second one investigates employment growth of Spanish manufacturing firms
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 University Library of Munich, Germany in its series MPRA Paper with number 880.
Date of creation: 20 Nov 2006
Date of revision:
autoregressive modelling; employment growth; GDP growth convergence; hierarchical prior; model comparison; posterior propriety; skewness;
Find related papers by JEL classification:
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
This paper has been announced in the following NEP Reports:
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.:
- Miguel A. Juárez & Mark F. J. Steel, 2010.
"Non‐gaussian dynamic bayesian modelling for panel data,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 25(7), pages 1128-1154, November/.
- Juarez, Miguel A. & Steel, Mark F. J., 2006. "Non-Gaussian dynamic Bayesian modelling for panel data," MPRA Paper 450, University Library of Munich, Germany.
- Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
- Fruhwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2008.
"Model-Based Clustering of Multiple Time Series,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 26, pages 78-89, January.
- Carmen Fernandez & Mark F. J. Steel, 2004.
"Bayesian Regression Analysis with scale mixtures of normals,"
ESE Discussion Papers
27, Edinburgh School of Economics, University of Edinburgh.
- Fern ndez, Carmen & Steel, Mark F.J., 2000. "Bayesian Regression Analysis With Scale Mixtures Of Normals," Econometric Theory, Cambridge University Press, vol. 16(01), pages 80-101, February.
- Marin, Jean-Michel & Mengersen, Kerrie & Robert, Christian P., 2005. "Bayesian Modelling and Inference on Mixtures of Distributions," Economics Papers from University Paris Dauphine 123456789/6069, Paris Dauphine University.
- repec:ner:dauphi:urn:hdl:123456789/6069 is not listed on IDEAS
- Nerlove,Marc, 2005. "Essays in Panel Data Econometrics," Cambridge Books, Cambridge University Press, number 9780521022460, October.
- Steven N. Durlauf & Danny T. Quah, 1998.
"The New Empirics of Economic Growth,"
98-01-012, Santa Fe Institute.
- S Durlauf & Danny Quah, 1998. "The New Empirics of Economic Growth," CEP Discussion Papers dp0384, Centre for Economic Performance, LSE.
- Durlauf,S.N. & Quah,D.T., 1998. "The new empirics of economic growth," Working papers 3, Wisconsin Madison - Social Systems.
- Steven N. Durlauf & Danny T. Quah, 1998. "The New Empirics of Economic Growth," NBER Working Papers 6422, National Bureau of Economic Research, Inc.
- Durlauf, Steven N & Johnson, Paul A, 1995.
"Multiple Regimes and Cross-Country Growth Behaviour,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 10(4), pages 365-84, Oct.-Dec..
- Durlauf, S.M. & Johnson, P.A., 1995. "Multiple Regimes and Cross-Country Growth Behavior," Working papers 9419r, Wisconsin Madison - Social Systems.
- Durlauf, S.N. & Johnson, P.A., 1994. "Multiple Regimes and Cross-Country Growth Behavior," Working papers 9419, Wisconsin Madison - Social Systems.
- BAUWENS, Luc & ROMBOUTS, Jeroen VK, .
"Bayesian clustering of many GARCH models,"
CORE Discussion Papers RP
-1916, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Alonso-Borrego, Cesar & Arellano, Manuel, 1999.
"Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 17(1), pages 36-49, January.
- Alonso-Borrego, César & Arellano, Manuel, 1999. "Symmetrically normalized instrumental-variable estimation using panel data," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/4655, Universidad Carlos III de Madrid.
- Sylvia Fruhwirth-Schnatter, 2004. "Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 143-167, 06.
- Nandram, Balgobin & Petruccelli, Joseph D, 1997. "A Bayesian Analysis of Autoregressive Time Series Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 328-34, July.
- Liu, Lon-Mu & Tiao, George C., 1980. "Random coefficient first-order autoregressive models," Journal of Econometrics, Elsevier, vol. 13(3), pages 305-325, August.
- Canova, Fabio, 2001.
"Testing for convergence clubs in income per-capita : a predictive density approach,"
HWWA Discussion Papers
139, Hamburg Institute of International Economics (HWWA).
- Fabio Canova, 2004. "Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 49-77, 02.
- Fabio Canova, 1997. "Testing for convergence clubs in income per-capita: A predictive density approach," Economics Working Papers 404, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 1999.
- Canova, Fabio, 1999. "Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach," CEPR Discussion Papers 2201, C.E.P.R. Discussion Papers.
- Ishwaran H. & James L.F. & Sun J., 2001. "Bayesian Model Selection in Finite Mixtures by Marginal Density Decompositions," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1316-1332, December.
- G. Casella & K. L. Mengersen & C. P. Robert & D. M. Titterington, 2002. "Perfect samplers for mixtures of distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 777-790.
- Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Modelling of Fat Tails and Skewness," Discussion Paper 1996-58, Tilburg University, Center for Economic Research.
- Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
- Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March.
- Sylvia Frühwirth-Schnatter & Christoph Pamminger & Andrea Weber & Rudolf Winter-Ebmer, 2010.
"Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering,"
NRN working papers
2010-14, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
- Sylvia Frühwirth‐Schnatter & Christoph Pamminger & Andrea Weber & Rudolf Winter‐Ebmer, 2012. "Labor market entry and earnings dynamics: Bayesian inference using mixtures‐of‐experts Markov chain clustering," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1116-1137, November.
- Sylvia Frühwirth-Schnatter & Andrea Weber & Rudolf Winter-Ebmer, 2010. "Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering," Economics working papers 2010-11, Department of Economics, Johannes Kepler University Linz, Austria.
- Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.