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Estimating long run effects and the exponent of cross-sectional dependence: an update to xtdcce2

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  • Jan Ditzen

    (Free University of Bozen-Bolzano, Italy, and Center for Energy Economics Research and Policy (CEERP), Heriot-Watt University, Edinburgh, UK)

Abstract

In this paper I describe several updates to xtdcce2 (Ditzen 2018). First I explain how to estimate long run effects in models with cross-sectional dependence. Three methods to estimate the long run effects are reviewed and their implementation into Stata using xtdcce2 discussed. Two of the estimation methods build on Chudik et al. (2016); the CS-DL and the CS-ARDL estimator. As a third alternative I review an error correction model in the presence of cross-sectional dependence. Second, I explain how to estimate the exponent of cross-sectional dependence using xtcse2 following Bailey et al. (2016, 2019).

Suggested Citation

  • Jan Ditzen, 2021. "Estimating long run effects and the exponent of cross-sectional dependence: an update to xtdcce2," BEMPS - Bozen Economics & Management Paper Series BEMPS81, Faculty of Economics and Management at the Free University of Bozen.
    • Handle: RePEc:bzn:wpaper:bemps81
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    References listed on IDEAS

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    1. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2016. "Exponent of Cross‐Sectional Dependence: Estimation and Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 929-960, September.
    2. Karabiyik, Hande & Reese, Simon & Westerlund, Joakim, 2017. "On the role of the rank condition in CCE estimation of factor-augmented panel regressions," Journal of Econometrics, Elsevier, vol. 197(1), pages 60-64.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    4. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Hashem Pesaran, M. & Yamagata, Takashi, 2008. "Testing slope homogeneity in large panels," Journal of Econometrics, Elsevier, vol. 142(1), pages 50-93, January.
    7. Lee, Kevin & Pesaran, M Hashem & Smith, Ron, 1997. "Growth and Convergence in Multi-country Empirical Stochastic Solow Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 357-392, July-Aug..
    8. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    9. Edward F. Blackburne III & Mark W. Frank, 2007. "Estimation of nonstationary heterogeneous panels," Stata Journal, StataCorp LP, vol. 7(2), pages 197-208, June.
    10. Jan Ditzen, 2018. "Estimating dynamic common-correlated effects in Stata," Stata Journal, StataCorp LP, vol. 18(3), pages 585-617, September.
    11. 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.
    12. Gerdie Everaert & Tom De Groote, 2016. "Common Correlated Effects Estimation of Dynamic Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 428-463, March.
    13. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    14. Alexander Chudik & Kamiar Mohaddes & M. Hashem Pesaran & Mehdi Raissi, 2013. "Debt, inflation and growth robust estimation of long-run effects in dynamic panel data models," Globalization Institute Working Papers 162, Federal Reserve Bank of Dallas.
    15. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    16. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LP, vol. 12(1), pages 61-71, March.
    17. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    18. Blomquist, Johan & Westerlund, Joakim, 2013. "Testing slope homogeneity in large panels with serial correlation," Economics Letters, Elsevier, vol. 121(3), pages 374-378.
    19. Westerlund, Joakim & Urbain, Jean-Pierre, 2015. "Cross-sectional averages versus principal components," Journal of Econometrics, Elsevier, vol. 185(2), pages 372-377.
    20. Jan Ditzen, 2019. "xthst: Testing for slope homogeneity in Stata," CEERP Working Paper Series 011, Centre for Energy Economics Research and Policy, Heriot-Watt University.
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    More about this item

    Keywords

    cross section dependence; common correlated effects; error correction model; long run coefficients;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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