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Two-Stage Instrumental Variable Estimation of Linear Panel Data Models with Interactive Effects

Author

Listed:
  • Milda Norkute

    (Bank of Lithuania, Vilnius University)

  • Guowei Cui

    (Huazhong University of Science and Technology)

  • Vasilis Sarafidis

    (Monash University)

  • Takashi Yamagata

    (University of York)

Abstract

This paper analyses the instrumental variables (IV) approach put forward by Norkutė et al. (2021), in the context of static linear panel data models with interactive effects present in the error term and the regressors. Instruments are obtained from transformed regressors, thereby it is not necessary to search for external instruments. We consider a two-stage IV (2SIV) and a mean-group IV (MGIV) estimator for homogeneous and heterogeneous slope models, respectively. The asymptotic analysis reveals that: (i) the √𝑁𝑇-consistent 2SIV estimator is free from asymptotic bias that may arise due to the estimation error of the interactive effects, whilst (ii) existing estimators can suffer from asymptotic bias; (iii) the proposed 2SIV estimator is asymptotically as efficient as existing estimators that eliminate interactive effects jointly in the regressors and the error, whilst; (iv) the relative efficiency of the estimators that eliminate interactive effects only in the error term is indeterminate. A Monte Carlo study confirms good approximation quality of our asymptotic results.

Suggested Citation

  • Milda Norkute & Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2021. "Two-Stage Instrumental Variable Estimation of Linear Panel Data Models with Interactive Effects," Bank of Lithuania Working Paper Series 90, Bank of Lithuania.
    • Handle: RePEc:lie:wpaper:90
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    1. Vasilis Sarafidis & Neville Weber, 2015. "A Partially Heterogeneous Framework for Analyzing Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 274-296, April.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Norkutė, Milda & Sarafidis, Vasilis & Yamagata, Takashi & Cui, Guowei, 2021. "Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 416-446.
    4. Artūras Juodis & Vasilis Sarafidis, 2022. "A Linear Estimator for Factor-Augmented Fixed-T Panels With Endogenous Regressors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 1-15, January.
    5. Hyungsik Roger Moon & Martin Weidner, 2015. "Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects," Econometrica, Econometric Society, vol. 83(4), pages 1543-1579, July.
    6. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
    7. Riccardo Colacito & Bridget Hoffmann & Toan Phan, 2019. "Temperature and Growth: A Panel Analysis of the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(2-3), pages 313-368, March.
    8. Moon, Hyungsik Roger & Weidner, Martin, 2017. "Dynamic Linear Panel Regression Models With Interactive Fixed Effects," Econometric Theory, Cambridge University Press, vol. 33(1), pages 158-195, February.
    9. Guowei Cui & Milda NorkutÄ— & Vasilis Sarafidis & Takashi Yamagata, 2022. "Two-stage instrumental variable estimation of linear panel data models with interactive effects [Eigenvalue ratio test for the number of factors]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 340-361.
    10. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    11. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    12. Hansen, Christian B., 2007. "Asymptotic properties of a robust variance matrix estimator for panel data when T is large," Journal of Econometrics, Elsevier, vol. 141(2), pages 597-620, December.
    13. Guowei Cui & Kazuhiko Hayakawa & Shuichi Nagata & Takashi Yamagata, 2018. "A robust approach to heteroskedasticity, error serial correlation and slope heterogeneity for large linear panel data models with interactive effects," ISER Discussion Paper 1037r, Institute of Social and Economic Research, Osaka University, revised Jun 2019.
    14. Jiang, Bin & Yang, Yanrong & Gao, Jiti & Hsiao, Cheng, 2021. "Recursive estimation in large panel data models: Theory and practice," Journal of Econometrics, Elsevier, vol. 224(2), pages 439-465.
    15. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    16. Kapetanios, George, 2010. "A Testing Procedure for Determining the Number of Factors in Approximate Factor Models With Large Datasets," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 397-409.
    17. Simon Reese & Joakim Westerlund, 2018. "Estimation of factor-augmented panel regressions with weakly influential factors," Econometric Reviews, Taylor & Francis Journals, vol. 37(5), pages 401-465, May.
    18. George Kapetanios & M. Hashem Pesaran, 2005. "Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns," CESifo Working Paper Series 1416, CESifo.
    19. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    20. 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.
    21. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    22. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2012. "Temperature Shocks and Economic Growth: Evidence from the Last Half Century," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(3), pages 66-95, July.
    23. Sebastian Kripfganz & Vasilis Sarafidis, 2021. "Instrumental-variable estimation of large-T panel-data models with common factors," Stata Journal, StataCorp LP, vol. 21(3), pages 659-686, September.
    24. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    25. Juodis, Artūras & Karabiyik, Hande & Westerlund, Joakim, 2021. "On the robustness of the pooled CCE estimator," Journal of Econometrics, Elsevier, vol. 220(2), pages 325-348.
    26. George Kapetanios & M. Hashem Pesaran, 2005. "Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns," CESifo Working Paper Series 1416, CESifo.
    27. Westerlund, Joakim & Urbain, Jean-Pierre, 2015. "Cross-sectional averages versus principal components," Journal of Econometrics, Elsevier, vol. 185(2), pages 372-377.
    28. Lee, Nayoung & Moon, Hyungsik Roger & Zhou, Qiankun, 2017. "Many IVs estimation of dynamic panel regression models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 251-259.
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    Cited by:

    1. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    2. Stauskas, Ovidijus & De Vos, Ignace, 2024. "Handling Distinct Correlated Effects with CCE," MPRA Paper 120194, University Library of Munich, Germany.
    3. Wen, Jun & Zhao, Xin-Xin & Fu, Qiang & Chang, Chun-Ping, 2023. "The impact of extreme weather events on green innovation: Which ones bring to the most harm?," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Sebastian Kripfganz & Vasilis Sarafidis, 2021. "Instrumental-variable estimation of large-T panel-data models with common factors," Stata Journal, StataCorp LP, vol. 21(3), pages 659-686, September.
    5. Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2020. "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude," Monash Econometrics and Business Statistics Working Papers 11/20, Monash University, Department of Econometrics and Business Statistics.
    6. Jia Chen Author-Name-First: Jia & Yongcheol Shin & Chaowen Zheng, 2023. "Dynamic Quantile Panel Data Models with Interactive Effects," Economics Discussion Papers em-dp2023-06, Department of Economics, University of Reading.
    7. De Vos, Ignace & Everaert, Gerdie & Sarafidis, Vasilis, 2021. "A method for evaluating the rank condition for CCE estimators," MPRA Paper 112305, University Library of Munich, Germany, revised 09 Mar 2022.
    8. Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2023. "IV estimation of spatial dynamic panels with interactive effects: large sample theory and an application on bank attitude towards risk," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 124-146.
    9. repec:ags:aaea22:335448 is not listed on IDEAS
    10. Guowei Cui & Milda NorkutÄ— & Vasilis Sarafidis & Takashi Yamagata, 2022. "Two-stage instrumental variable estimation of linear panel data models with interactive effects [Eigenvalue ratio test for the number of factors]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 340-361.
    11. Ben Cheikh, Nidhaleddine & Ben Zaied, Younes & Nguyen, Duc Khuong, 2023. "Understanding energy poverty drivers in Europe," Energy Policy, Elsevier, vol. 183(C).
    12. Le Clech, Néstor A., 2024. "Policy market orientation, property rights, and corruption effects on the rent of non-renewable resources in Latin America and the Caribbean," Resources Policy, Elsevier, vol. 91(C).
    13. Okere, Kingsley Ikechukwu & Dimnwobi, Stephen Kelechi & Ekesiobi, Chukwunonso & Onuoha, Favour Chidinma, 2023. "Turning the tide on energy poverty in sub-Saharan Africa: Does public debt matter?," Energy, Elsevier, vol. 282(C).
    14. De Vos, Ignace & Stauskas, Ovidijus, 2024. "Cross-section bootstrap for CCE regressions," Journal of Econometrics, Elsevier, vol. 240(1).
    15. Bidzha, Mashudu Lucas & Ngepah, Nicholas & Greyling, Talita, 2024. "The impact of antiretroviral treatment on the relationship between HIV/AIDS and economic growth," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 368-387.
    16. Agoraki, Maria-Eleni & Aslanidis, Nektarios & Kouretas, Georgios P., 2021. "U.S. Banks’ lending behaviour, financial stability, and investor sentiment: A textual analysis," Working Papers 2072/534915, Universitat Rovira i Virgili, Department of Economics.
    17. Zhenhao Gong & Min Seong Kim, 2024. "Improved Inference for Interactive Fixed Effects Model under Cross-Sectional Dependence," Working papers 2024-02, University of Connecticut, Department of Economics.

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    More about this item

    Keywords

    Large panel data; interactive effects; common factors; principal components analysis; instrumental variables.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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

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