Advanced Search
MyIDEAS: Login to save this article or follow this journal

Quantile regression for dynamic panel data with fixed effects

Contents:

Author Info

  • Galvao Jr., Antonio F.
Registered author(s):

    Abstract

    This paper studies a quantile regression dynamic panel model with fixed effects. Panel data fixed effects estimators are typically biased in the presence of lagged dependent variables as regressors. To reduce the dynamic bias, we suggest the use of the instrumental variables quantile regression method of Chernozhukov and Hansen (2006) along with lagged regressors as instruments. In addition, we describe how to employ the estimated models for prediction. Monte Carlo simulations show evidence that the instrumental variables approach sharply reduces the dynamic bias, and the empirical levels for prediction intervals are very close to nominal levels. Finally, we illustrate the procedures with an application to forecasting output growth rates for 18 OECD countries.

    Download Info

    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://www.sciencedirect.com/science/article/pii/S0304407611000443
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 164 (2011)
    Issue (Month): 1 (September)
    Pages: 142-157

    as in new window
    Handle: RePEc:eee:econom:v:164:y:2011:i:1:p:142-157

    Contact details of provider:
    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Quantile regression Dynamic panel Fixed effects Instrumental variables;

    References

    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. Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 5(1), pages 53-67, January.
    2. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
    3. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 58(2), pages 277-97, April.
    4. R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
    5. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, Econometric Society, vol. 78(3), pages 1093-1125, 05.
    6. Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, Elsevier, vol. 21(2), pages 201-218.
    7. Alvarez, J. & Arellano, M., 1998. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Papers, Centro de Estudios Monetarios Y Financieros- 9808, Centro de Estudios Monetarios Y Financieros-.
    8. Giorgio Canarella & Stephen Pollard, 2004. "Parameter Heterogeneity In The Neoclassical Growth Model: A Quantile Regression Approach," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, Chung-Ang Unviersity, Department of Economics, vol. 29(1), pages 1-31, June.
    9. Hsiao,Cheng, 2003. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9780521522717, 9.
    10. Jinyong Hahn & Whitney Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP17/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, Econometric Society, vol. 70(4), pages 1639-1657, July.
    12. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    13. Hoogstrate, Andre J & Palm, Franz C & Pfann, Gerard A, 2000. "Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 18(3), pages 274-83, July.
    14. Elliott, Graham & Timmermann, Allan G, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    15. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.
    16. Bun,M.J.G. & Carree,M.A., 2002. "Bias-corrected estimation in dynamic panel data models," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    17. Giacomini, Raffaella & Komunjer, Ivana, 2002. "Evaluation and Combination of Conditional Quantile Forecasts," University of California at San Diego, Economics Working Paper Series qt4n99t4wz, Department of Economics, UC San Diego.
    18. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 46(1), pages 33-50, January.
    19. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, Elsevier, vol. 21(4), pages 785-794.
    20. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780199245291, October.
    21. Cai, Yuzhi, 2007. "A quantile approach to US GNP," Economic Modelling, Elsevier, vol. 24(6), pages 969-979, November.
    22. Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, Elsevier, vol. 40(1), pages 63-86, January.
    23. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 50(1), pages 43-61, January.
    24. Jesus Crespo-Cuaresma & Neil Foster-McGregor & Robert Stehrer, 2009. "The Determinants of Regional Economic Growth by Quantile," wiiw Working Papers 54, The Vienna Institute for International Economic Studies, wiiw.
    25. William T. Gavin & Athena T. Theodorou, 2005. "A common model approach to macroeconomics: using panel data to reduce sampling error," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 203-219.
    26. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, Econometric Society, vol. 49(6), pages 1417-26, November.
    27. James W. Taylor & Derek W. Bunn, 1999. "A Quantile Regression Approach to Generating Prediction Intervals," Management Science, INFORMS, INFORMS, vol. 45(2), pages 225-237, February.
    28. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 68(1), pages 5-27, July.
    29. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(05), pages 793-813, December.
    30. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 73(1), pages 245-261, 01.
    31. Koenker, Roger & Bassett Jr., Gilbert W., 2010. "March Madness, Quantile Regression Bracketology, and the Hayek Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 28(1), pages 26-35.
    32. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, Elsevier, vol. 132(2), pages 491-525, June.
    33. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    34. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
    35. Yuzhi Cai, 2010. "Forecasting for quantile self-exciting threshold autoregressive time series models," Biometrika, Biometrika Trust, Biometrika Trust, vol. 97(1), pages 199-208.
    36. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, Elsevier, vol. 32(1), pages 143-155, June.
    37. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    38. Lamarche, Carlos, 2010. "Robust penalized quantile regression estimation for panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 157(2), pages 396-408, August.
    39. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 18(1), pages 47-82, January.
    40. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    41. Schmidt, Peter, 1974. "The Asymptotic Distribution of Forecasts in the Dynamic Simulation of an Econometric Model," Econometrica, Econometric Society, Econometric Society, vol. 42(2), pages 303-09, March.
    42. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, Elsevier, vol. 142(1), pages 379-398, January.
    43. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Harding, Matthew & Lamarche, Carlos, 2014. "Estimating and testing a quantile regression model with interactive effects," Journal of Econometrics, Elsevier, Elsevier, vol. 178(P1), pages 101-113.
    2. Klomp, Jeroen, 2013. "Government interventions and default risk: Does one size fit all?," Journal of Financial Stability, Elsevier, Elsevier, vol. 9(4), pages 641-653.
    3. Michele Aquaro & Pavel Čížek, 2014. "Robust estimation of dynamic fixed-effects panel data models," Statistical Papers, Springer, vol. 55(1), pages 169-186, February.
    4. Galina Besstremyannaya, 2014. "The efficiency of labor matching and remuneration reforms: a panel data quantile regression approach with endogenous treatment variables," Working Papers w0206, Center for Economic and Financial Research (CEFIR).
    5. Nadine Levratto & Aziza Garsaa & Luc Tessier, 2013. "La Corse est-elle soluble dans le modèle méditerranéen ?," Working Papers hal-00842059, HAL.
    6. Matano, Alessia & Naticchioni, Paolo, 2012. "Rent Sharing as a Driver of the Glass Ceiling Effect," IZA Discussion Papers 6875, Institute for the Study of Labor (IZA).
    7. Coad, Alex & Segarra Blasco, Agustí, 1958- & Teruel, Mercedes, 2013. "Innovation and firm growth: Does firm age play a role?," Working Papers 2072/211886, Universitat Rovira i Virgili, Department of Economics.
    8. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    9. Nadine Levratto & Aziza Garsaa & Luc Tessier, 2013. "La Corse est-elle soluble dans le modèle méditerranéen ? Une analyse à partir d’une régression quantile sur données d’entreprises en panel entre 2004 et 2010. Is the Corsican economy a part ," EconomiX Working Papers 2013-20, University of Paris West - Nanterre la Défense, EconomiX.
    10. Andini, Corrado, 2014. "Persistence Bias and Schooling Returns," IZA Discussion Papers 8143, Institute for the Study of Labor (IZA).
    11. Daunfeldt, Sven-Olov & Halvarsson, Daniel, 2012. "Are high-growth firms one-hit wonders? Evidence from Sweden," HUI Working Papers, HUI Research 73, HUI Research.
    12. David Powell, 2010. "Unconditional Quantile Regression for Panel Data with Exogenous or Endogenous Regressors," Working Papers, RAND Corporation Publications Department 710-1, RAND Corporation Publications Department.
    13. Lee, Jen-Sin & Huang, Gow-Liang & Kuo, Chin-Tai & Lee, Liang-Chien, 2012. "The momentum effect on Chinese real estate stocks: Evidence from firm performance levels," Economic Modelling, Elsevier, vol. 29(6), pages 2392-2406.

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:164:y:2011:i:1:p:142-157. 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: (Zhang, Lei).

    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.