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Sequential (two-stage) estimation of linear panel-data models

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  • Sebastian Kripfganz

    (University of Exeter Business School)

Abstract

I present the new Stata command xtseqreg, which implements sequential (two-stage) estimators for linear panel-data models. In general, the conventional standard errors are no longer valid in sequential estimation when the residuals from the first stage are regressed on another set of (often time-invariant) explanatory variables at a second stage. xtseqreg computes the analytical standard-error correction of Kripfganz and Schwarz (2015), which accounts for the first-stage estimation error. The command can be used to fit both stages of a sequential regression or either stage separately. OLS and 2SLS estimation are supported, as well as one-step and two-step "difference"-GMM and "system"-GMM estimation in the spirit of Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (1998), with flexible choice of the instruments and weighting matrix. Available postestimation statistics include the Arellano–Bond test for absence of autocorrelation in the first-differenced errors and Hansen's J-test for the validity of the overidentifying restrictions. While I do not intend to introduce xtseqreg as a competitor for existing commands, it can mimic part of their behavior. In particular, xtseqreg can replicate results obtained with xtdpd and xtabond2. In that regard, I will illustrate some pitfalls in the estimation of dynamic panel models.

Suggested Citation

  • Sebastian Kripfganz, 2017. "Sequential (two-stage) estimation of linear panel-data models," German Stata Users' Group Meetings 2017 03, Stata Users Group.
    • Handle: RePEc:boc:dsug17:03
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    References listed on IDEAS

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    1. 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.
    2. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    3. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    4. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    5. 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.
    6. Reinhard Schunck, 2013. "Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models," Stata Journal, StataCorp LP, vol. 13(1), pages 65-76, March.
    7. Peter Egger & Michael Pfaffermayr, 2004. "Distance, trade and FDI: a Hausman-Taylor SUR approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 227-246.
    8. Reinhard Schunck & Francisco Perales, 2017. "Within- and between-cluster effects in generalized linear mixed models: A discussion of approaches and the xthybrid command," Stata Journal, StataCorp LP, vol. 17(1), pages 89-115, March.
    9. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    10. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    11. 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.
    12. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    13. Sebastian Kripfganz, 2017. "Sequential (two-stage) estimation of linear panel data models," United Kingdom Stata Users' Group Meetings 2017 09, Stata Users Group.
    14. 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.
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