Nothing Special   »   [go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/scp/wpaper/05-33.html
   My bibliography  Save this paper

Why Panel Data?

Author

Listed:
  • Cheng Hsiao
Abstract
We explain the proliferation of panel data studies in terms of (i) data availability, (ii) the more heightened capacity for modeling the complexity of human behavior than a single cross-section or time series data can possibly allow, and (iii) challenging methodology. Advantages and issues of panel data modeling are also discussed.

Suggested Citation

  • Cheng Hsiao, 2005. "Why Panel Data?," IEPR Working Papers 05.33, Institute of Economic Policy Research (IEPR).
  • Handle: RePEc:scp:wpaper:05-33
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699.
    2. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    3. Nerlove,Marc, 2005. "Essays in Panel Data Econometrics," Cambridge Books, Cambridge University Press, number 9780521022460, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pablo Lavado & Gonzalo Rivera, 2016. "Identifying Treatment Effects with Data Combination and Unobserved Heterogeneity," Working Papers 79, Peruvian Economic Association.
    2. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    3. Pablo Lavado & Gonzalo Rivera, 2015. "Identifying treatment effects and counterfactual distributions using data combination with unobserved heterogeneity," Working Papers 15-14, Centro de Investigación, Universidad del Pacífico.
    4. Pillai N., Vijayamohanan, 2016. "Panel Data Analysis with Stata Part 1 Fixed Effects and Random Effects Models," MPRA Paper 76869, University Library of Munich, Germany.
    5. Sorin Daniel Manole & Antonio Tache & Monica Tache, 2014. "Regional Development Survey by Data Panel Models," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 62(8), pages 19-33, August.
    6. Pablo Lavado, "undated". "Identifying Treatment Effects and Counterfactual Distributions using Data Combination with Unobserved Heterogeneity," Working Papers 13-25, Departamento de Economía, Universidad del Pacífico.
    7. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany.
    8. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja & Tristan Zajonc, 2011. "Do Value-Added Estimates Add Value? Accounting for Learning Dynamics," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 29-54, July.
    9. Carrión-Flores, Carmen E. & Innes, Robert, 2010. "Environmental innovation and environmental performance," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 27-42, January.
    10. Paul Raschky, 2007. "Estimating the effects of risk transfer mechanisms against floods in Europe and U.S.A.: A dynamic panel approach," Working Papers 2007-05, Faculty of Economics and Statistics, Universität Innsbruck.
    11. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    12. Rode, Martin & Gwartney, James D., 2012. "Does democratization facilitate economic liberalization?," European Journal of Political Economy, Elsevier, vol. 28(4), pages 607-619.
    13. Anne Musson & Damien Rousselière, 2020. "Exploring the effect of crisis on cooperatives: a Bayesian performance analysis of French craftsmen cooperatives," Applied Economics, Taylor & Francis Journals, vol. 52(25), pages 2657-2678, May.
    14. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    15. Xiaohong Chen & Andres Santos, 2018. "Overidentification in Regular Models," Econometrica, Econometric Society, vol. 86(5), pages 1771-1817, September.
    16. Jan Fałkowski & Maciej Jakubowski & Paweł Strawiński, 2014. "Returns from income strategies in rural Poland," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 22(1), pages 139-178, January.
    17. Johannes Blum & Klaus Gründler, 2020. "Political Stability and Economic Prosperity: Are Coups Bad for Growth?," CESifo Working Paper Series 8317, CESifo.
    18. Marktanner Marcus & Makdisi Samir, 2008. "Development against All Odds? The Case of Lebanon," Review of Middle East Economics and Finance, De Gruyter, vol. 4(3), pages 101-133, September.
    19. Gabriel Burdí­n & Andrés Dean, 2009. "Las decisiones de empleo y salarios de cooperativas de trabajo y empresas capitalistas : evidencia para Uruguay en base a datos de panel," Documentos de Trabajo (working papers) 09-02, Instituto de Economía - IECON.
    20. Silvio R. Rendon, 2013. "Fixed and Random Effects in Classical and Bayesian Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 460-476, June.

    More about this item

    Keywords

    Panel data; Longitudinal data; Unobserved heterogeneity; Random effects; Fixed effects;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:scp:wpaper:05-33. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/ieuscus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.