IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

Non‐gaussian dynamic bayesian modelling for panel data

  • Miguel A. Juárez
  • Mark F. J. Steel

A first order autoregressive non-Gaussian model for analysing panel data is proposed. The main feature is that the model is able to accommodate fat tails and also skewness, thus allowing for outliers and asymmetries. The modelling approach is designed to gain sufficient flexibility, without sacrificing interpretability and computational ease. The model incorporates individual effects and covariates and we pay specific attention to the elicitation of the prior. As the prior structure chosen is not proper, we derive conditions for the existence of the posterior. By considering a model with individual dynamic parameters we are also able to formally test whether the dynamic behaviour is common to all units in the panel. The methodology is illustrated with two applications involving earnings data and one on growth of countries. Copyright (C) 2009 John Wiley & Sons, Ltd.

If 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.

File URL: http://hdl.handle.net/10.1002/jae.1113
Download Restriction: no

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 25 (2010)
Issue (Month): 7 (November/December)
Pages: 1128-1154

as
in new window

Handle: RePEc:jae:japmet:v:25:y:2010:i:7:p:1128-1154
Contact details of provider: Web page: http://www.interscience.wiley.com/jpages/0883-7252/

Order Information: Web: http://www3.interscience.wiley.com/jcatalog/subscribe.jsp?issn=0883-7252 Email:


References listed on IDEAS
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.:

as in new window
  1. Evans, Paul & Karras, Georgios, 1996. "Do Economies Converge? Evidence from a Panel of U.S. States," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 384-88, August.
  2. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
  3. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
  4. Michael Lee & Ritchard Longmire & Laszlo Matyas & Mark Harris, 1998. "Growth convergence: some panel data evidence," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 907-912.
  5. 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..
  6. 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).
  7. Islam, Nazrul, 1995. "Growth Empirics: A Panel Data Approach," The Quarterly Journal of Economics, MIT Press, vol. 110(4), pages 1127-70, November.
  8. 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.
  9. Pesaran, M.H., 2004. "A Pair-wise Approach to Testing for Output and Growth Convergence," Cambridge Working Papers in Economics 0453, Faculty of Economics, University of Cambridge.
  10. Giuseppe Arbia & Gianfranco Piras, 2005. "Convergence in per-capita GDP across European regions using panel data models extended to spatial autocorrelation effects," ISAE Working Papers 51, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  11. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
  12. Bernard, A.B. & Durlauf, S.N., 1994. "Interpreting Tests of the Convergence Hypothesis," Working papers 9401r, Wisconsin Madison - Social Systems.
  13. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
  14. Hsiao, Cheng & Pesaran, M. Hashem, 2004. "Random Coefficient Panel Data Models," IZA Discussion Papers 1236, Institute for the Study of Labor (IZA).
  15. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew "t"-distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389.
  16. Pesaran, H. & Smith, R. & Im, K.S., 1995. "Dynamic Linear Models for Heterogeneous Panels," Cambridge Working Papers in Economics 9503, Faculty of Economics, University of Cambridge.
  17. 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.
  18. Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March.
  19. repec:dgr:kubcen:199658 is not listed on IDEAS
  20. Guillaume GAULIER & Christophe HURLIN & Philippe JEAN-PIERRE, 1999. "Testing Convergence: A Panel Data Approach," Annales d'Economie et de Statistique, ENSAE, issue 55-56, pages 411-427.
  21. 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.
  22. Tsung-Wu Ho, 2006. "Income Thresholds And Growth Convergence: A Panel Data Approach," Manchester School, University of Manchester, vol. 74(2), pages 170-189, 03.
  23. Liu, Lon-Mu & Tiao, George C., 1980. "Random coefficient first-order autoregressive models," Journal of Econometrics, Elsevier, vol. 13(3), pages 305-325, August.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:jae:japmet:v:25:y:2010:i:7:p:1128-1154. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)

or (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.