IDEAS home Printed from https://ideas.repec.org/p/max/cprwps/214.html
   My bibliography  Save this paper

Structural Changes in Heterogeneous Panels with Endogenous Regressors

Author

Listed:

Abstract

This paper extends Pesaran (2006) common correlated e¤ects (CCE) by allowing for endogenous regressors in large heterogeneous panels with unknown common structural changes in slopes and error factor structure. Since endogenous regressors and structural breaks are often encountered in empirical studies with large panels, this extension makes the Pesaran’s (2006) CCE approach empirically more appealing. In addition to allowing for slope heterogeneity and cross-sectional dependence, we find that Pesaran’s CCE approach is also valid when dealing with unobservable factors in the presence of endogenous regressors and structural changes in slopes and error factor loadings. This is supported by Monte Carlo experiments.

Suggested Citation

  • Badi Baltagi & Qu Feng & Chihwa Kao, 2019. "Structural Changes in Heterogeneous Panels with Endogenous Regressors," Center for Policy Research Working Papers 214, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:214
    as

    Download full text from publisher

    File URL: https://surface.syr.edu/cpr/246/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jushan Bai, 1997. "Estimation Of A Change Point In Multiple Regression Models," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 551-563, November.
    2. Otilia Boldea & Alastair Hall & Sanggohn Han, 2012. "Asymptotic Distribution Theory for Break Point Estimators in Models Estimated via 2SLS," Econometric Reviews, Taylor & Francis Journals, vol. 31(1), pages 1-33.
    3. Hall, Alastair R. & Han, Sanggohn & Boldea, Otilia, 2012. "Inference regarding multiple structural changes in linear models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 281-302.
    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. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    6. Badi H. Baltagi & Chihwa Kao & Long Liu, 2017. "Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 85-102, March.
    7. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.
    8. G. Forchini & Bin Jiang & Bin Peng, 2015. "Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure Endogeneity," Monash Econometrics and Business Statistics Working Papers 14/15, Monash University, Department of Econometrics and Business Statistics.
    9. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    10. Degui Li & Junhui Qian & Liangjun Su, 2016. "Panel Data Models With Interactive Fixed Effects and Multiple Structural Breaks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1804-1819, October.
    11. Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2014. "Detecting big structural breaks in large factor models," Journal of Econometrics, Elsevier, vol. 180(1), pages 30-48.
    12. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 71-84, July.
    13. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2016. "Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(4), pages 1511-1543.
    14. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    15. Pierre Perron & Yohei Yamamoto, 2015. "Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 119-144, January.
    16. Yamamoto, Yohei & Tanaka, Shinya, 2015. "Testing for factor loading structural change under common breaks," Journal of Econometrics, Elsevier, vol. 189(1), pages 187-206.
    17. Perron, Pierre & Yamamoto, Yohei, 2014. "A Note On Estimating And Testing For Multiple Structural Changes In Models With Endogenous Regressors Via 2sls," Econometric Theory, Cambridge University Press, vol. 30(2), pages 491-507, April.
    18. Chen, Bin, 2015. "Modeling and testing smooth structural changes with endogenous regressors," Journal of Econometrics, Elsevier, vol. 185(1), pages 196-215.
    19. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    20. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.
    21. Giovanni Forchini & Bin Jiang & Bin Peng, 2015. "Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure and Endogeneity," School of Economics Discussion Papers 0315, School of Economics, University of Surrey.
    22. Harding, Matthew & Lamarche, Carlos, 2011. "Least squares estimation of a panel data model with multifactor error structure and endogenous covariates," Economics Letters, Elsevier, vol. 111(3), pages 197-199, June.
    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


    Cited by:

    1. Amendolagine, Vito & De Pascale, Gianluigi & Faccilongo, Nicola, 2021. "International capital mobility and corporate tax revenues: How do controlled foreign company rules and innovation shape this relationship?," Economic Modelling, Elsevier, vol. 101(C).
    2. Seymur Ağazade, 2021. "Service Exports and Productivity: Evidence from OECD Panel Data," Politická ekonomie, Prague University of Economics and Business, vol. 2021(3), pages 298-321.
    3. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.
    4. Trung V. Vu, 2023. "Life expectancy and human capital: New empirical evidence," Health Economics, John Wiley & Sons, Ltd., vol. 32(2), pages 395-412, February.
    5. De Pascale, Gianluigi & Fiore, Mariantonietta & Contò, Francesco, 2021. "Short and long run environmental tax buoyancy in EU-28: a panel study," International Economics, Elsevier, vol. 168(C), pages 1-9.
    6. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    7. Yu Bai & Massimiliano Marcellino & George Kapetanios, 2023. "Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 13/23, Monash University, Department of Econometrics and Business Statistics.

    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. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    2. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    3. Oka, Tatsushi & Perron, Pierre, 2018. "Testing for common breaks in a multiple equations system," Journal of Econometrics, Elsevier, vol. 204(1), pages 66-85.
    4. Jan Ditzen & Yiannis Karavias & Joakim Westerlund, 2022. "Multiple Structural Breaks in Interactive Effects Panel Data and the Impact of Quantitative Easing on Bank Lending," Papers 2211.06707, arXiv.org, revised Jan 2023.
    5. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    6. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    7. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    8. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    9. Ma, Chenchen & Tu, Yundong, 2023. "Group fused Lasso for large factor models with multiple structural breaks," Journal of Econometrics, Elsevier, vol. 233(1), pages 132-154.
    10. Yiannis Karavias & Paresh Kumar Narayan & Joakim Westerlund, 2023. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 653-666, July.
    11. Feng, Qu, 2020. "Common factors and common breaks in panels: An empirical investigation," Economics Letters, Elsevier, vol. 187(C).
    12. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    13. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    14. Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    15. Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024. "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, vol. 238(2).
    16. Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.
    17. Horváth, Lajos & Rice, Gregory, 2019. "Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 138-165.
    18. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    19. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    20. Ma, Shujie & Su, Liangjun, 2018. "Estimation of large dimensional factor models with an unknown number of breaks," Journal of Econometrics, Elsevier, vol. 207(1), pages 1-29.

    More about this item

    Keywords

    Structural Changes; Heterogeneous Panels; Common Correlated Effects; Endogeneity;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:max:cprwps:214. 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: Katrina Fiacchi (email available below). General contact details of provider: https://edirc.repec.org/data/cpsyrus.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.