0, despite being consistent for fixed T. Finally, we discuss the properties of a random effects pseudo MLE with unrestricted initial conditions when both T and N tend to infinity. Copyright The Econometric Society 2003."> 0, despite being consistent for fixed T. Finally, we discuss the properties of a random effects pseudo MLE with unrestricted initial conditions when both T and N tend to infinity. Copyright The Econometric Society 2003.">
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/a/ecm/emetrp/v71y2003i4p1121-1159.html
   My bibliography  Save this article

The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators

Author

Listed:
  • Javier Alvarez
  • Manuel Arellano
Abstract
In this paper we derive the asymptotic properties of within groups (WG), GMM, and LIML estimators for an autoregressive model with random effects when both T and N tend to infinity. GMM and LIML are consistent and asymptotically equivalent to the WG estimator. When T/N→ 0 the fixed T results for GMM and LIML remain valid, but WG, although consistent, has an asymptotic bias in its asymptotic distribution. When T/N tends to a positive constant, the WG, GMM, and LIML estimators exhibit negative asymptotic biases of order 1/T, 1/N, and 1/(2N - T), respectively. In addition, the crude GMM estimator that neglects the autocorrelation in first differenced errors is inconsistent as T/N→c>0, despite being consistent for fixed T. Finally, we discuss the properties of a random effects pseudo MLE with unrestricted initial conditions when both T and N tend to infinity. Copyright The Econometric Society 2003.

Suggested Citation

  • Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
  • Handle: RePEc:ecm:emetrp:v:71:y:2003:i:4:p:1121-1159
    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. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    2. 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.
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. Ruth A. Judson & Ann L. Owen, "undated". "Estimating Dynamic Panel Data Models: A Practical Guide for Macroeconomists," Finance and Economics Discussion Series 1997-03, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    5. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    6. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    7. Nerlove, Marc, 1971. "Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross Sections," Econometrica, Econometric Society, vol. 39(2), pages 359-382, March.
    8. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    9. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    10. Morimune, Kimio, 1983. "Approximate Distributions of k-Class Estimators When the Degree of Overidentifiability Is Large Compared with the Sample Size," Econometrica, Econometric Society, vol. 51(3), pages 821-841, May.
    11. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    12. Bekker, Paul A, 1994. "Alternative Approximations to the Distributions of Instrumental Variable Estimators," Econometrica, Econometric Society, vol. 62(3), pages 657-681, May.
    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. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    2. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    3. Hugo J. Faria & Hugo M. Montesinos-Yufa, 2017. "Is the Effect of Income on Democracy Heterogeneous?," Working Papers 2017-05, University of Miami, Department of Economics.
    4. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    5. Hayakawa, Kazuhiko, 2024. "Recent development of covariance structure analysis in economics," Econometrics and Statistics, Elsevier, vol. 29(C), pages 31-48.
    6. Hayakawa, Kazuhiko, 2007. "Small sample bias properties of the system GMM estimator in dynamic panel data models," Economics Letters, Elsevier, vol. 95(1), pages 32-38, April.
    7. Barabas, György & Kitlinski, Tobias & Schmidt, Christoph M. & Schmidt, Torsten & Siemers, Lars-H. & Brilon, Werner, 2010. "Verkehrsinfrastrukturinvestitionen: Wachstumsaspekte im Rahmen einer gestaltenden Finanzpolitik. Endbericht - Januar 2010. Forschungsprojekt im Auftrag des Bundesministeriums der Finanzen. Projektnumm," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 72601.
    8. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
    9. Rodrigo Alfaro, 2008. "Estimation of a Dynamic Panel Data: The Case Of Corporate Investment in Chile," Working Papers Central Bank of Chile 467, Central Bank of Chile.
    10. Chirok Han & Hyoungjong Kim, 2023. "Dynamic panel GMM estimators with improved finite sample properties using parametric restrictions for dimension reduction," Empirical Economics, Springer, vol. 64(6), pages 2589-2610, June.
    11. Bond, Stephen Roy & Hoeffler, Anke & Temple, Jonathan, 2001. "GMM Estimation of Empirical Growth Models," CEPR Discussion Papers 3048, C.E.P.R. Discussion Papers.
    12. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    13. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    14. Huy Quang Doan, 2019. "Trade, Institutional Quality and Income: Empirical Evidence for Sub-Saharan Africa," Economies, MDPI, vol. 7(2), pages 1-23, May.
    15. Guglielmo Maria Caporale & Anamaria Diana Sova & Robert Sova, 2024. "The Covid‐19 pandemic and European trade flows: Evidence from a dynamic panel model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 2563-2580, July.
    16. Wahidin, Deni & Akimov, Alexandr & Roca, Eduardo, 2021. "The impact of bond market development on economic growth before and after the global financial crisis: Evidence from developed and developing countries," International Review of Financial Analysis, Elsevier, vol. 77(C).
    17. Abdul Karim, Zulkefly & Wan Ngah, Wan Azman Saini & Abdul Karim, Bakri, 2010. "Bank lending channel of monetary policy: dynamic panel data evidence from Malaysia," MPRA Paper 26157, University Library of Munich, Germany.
    18. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    19. John M. Clapp & Stephen L. Ross & Tingyu Zhou, 2019. "Retail Agglomeration and Competition Externalities: Evidence from Openings and Closings of Multiline Department Stores in the U.S," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 81-96, January.
    20. Yongfu Huang, 2011. "Private investment and financial development in a globalized world," Empirical Economics, Springer, vol. 41(1), pages 43-56, August.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

    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:ecm:emetrp:v:71:y:2003:i:4:p:1121-1159. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.