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xtdcce: Estimating Dynamic Common Correlated Effects in Stata

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  • Jan Ditzen

    (Heriot-Watt University)

Abstract

This article introduces a new Stata command, xtdcce, to estimate a dynamic common correlated effects model with heterogeneous coefficients. The estimation procedure mainly follows Chudik and Pesaran (2015b), in addition the common correlated effects estimator (Pesaran, 2006), as well as the mean group (Pesaran and Smith, 1995) and the pooled mean group estimator (Shin et al., 1999) are supported. Coefficients are allowed to be heterogeneous or homogeneous. In addition instrumental variable regressions and unbalanced panels are supported. The Cross Sectional Dependence Test (CD Test) is automatically calculated and presented in the estimation output. Small sample time series bias can be corrected by jackknife correction or recursive mean adjustment. Examples for empirical applications of all estimation methods mentioned above are given

Suggested Citation

  • Jan Ditzen, 2016. "xtdcce: Estimating Dynamic Common Correlated Effects in Stata," SEEC Discussion Papers 1601, Spatial Economics and Econometrics Centre, Heriot Watt University.
  • Handle: RePEc:hwe:seecdp:1601
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    References listed on IDEAS

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    Cited by:

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    2. Dobdinga Cletus Fonchamnyo & Ongo Nkoa Bruno Emmanuel & Gildas Dohba Dinga, 2021. "The effects of trade, foreign direct investment, and economic growth on environmental quality and overshoot: a dynamic common correlation effects approach," SN Business & Economics, Springer, vol. 1(10), pages 1-27, October.
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    5. Kyle McNabb, 2016. "Tax structures and economic growth: New evidence from the Government Revenue Dataset," WIDER Working Paper Series 148, World Institute for Development Economic Research (UNU-WIDER).
    6. Gildas Dohba Dinga & Dobdinga Cletus Fonchamnyo & Giyoh Gideon Nginyu & Chuo Joshua Njuh, 2020. "Short and Long Run Dynamic Common Correlation Effects of External Capital Inflow on Economic Growth in SSA Countries," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 8(4), pages 218-226, December.
    7. Vasudeva N. R. Murthy & Natalya Ketenci, 2020. "Capital mobility in Latin American and Caribbean countries: new evidence from dynamic common correlated effects panel data modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-17, December.
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    10. Kvedaras, Virmantas & Garcimartín, Carlos & Astudillo, Jhonatan, 2020. "Balance-of-Payments constrained growth dynamics: An empirical investigation," Economic Modelling, Elsevier, vol. 89(C), pages 232-244.
    11. Amèvi Rocard Kouwoaye, 2019. "Trade tax reforms and poverty in developing countries: Why do some countries benefit and others lose?," WIDER Working Paper Series wp-2019-66, World Institute for Development Economic Research (UNU-WIDER).
    12. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.
    13. Ariff, Mohamed & Zarei, Alireza & Bhatti, M. Ishaq, 2021. "Monitoring exchange rate instability in 12 selected Islamic economies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    14. Diallo, Ibrahima Amadou, 2017. "The role of human assets in economic growth: theory and empirics," MPRA Paper 80402, University Library of Munich, Germany.
    15. Kyle McNabb, 2016. "Tax structures and economic growth: New evidence from the Government Revenue Dataset," WIDER Working Paper Series wp-2016-148, World Institute for Development Economic Research (UNU-WIDER).
    16. Elio Shijaku & Martin Larraza-Kintana & Ainhoa Urtasun-Alonso, 2020. "Network centrality and organizational aspirations: A behavioral interaction in the context of international strategic alliances," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 51(5), pages 813-828, July.

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    More about this item

    Keywords

    xtdcce; parameter heterogeneity; dynamic panels; cross section dependence; common correlated effects; pooled mean-group estimator; mean-group estimator; instrumental variables; ivreg2;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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