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Interactive Effects Panel Data Models with General Factors and Regressors

Author

Listed:
  • Bin Peng
  • Liangjun Su
  • Joakim Westerlund
  • Yanrong Yang
Abstract
This paper considers a model with general regressors and unobservable factors. An estimator based on iterated principal components is proposed, which is shown to be not only asymptotically normal and oracle efficient, but under certain conditions also free of the otherwise so common asymptotic incidental parameters bias. Interestingly, the conditions required to achieve unbiasedness become weaker the stronger the trends in the factors, and if the trending is strong enough unbiasedness comes at no cost at all. In particular, the approach does not require any knowledge of how many factors there are, or whether they are deterministic or stochastic. The order of integration of the factors is also treated as unknown, as is the order of integration of the regressors, which means that there is no need to pre-test for unit roots, or to decide on which deterministic terms to include in the model.

Suggested Citation

  • Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Papers 2111.11506, arXiv.org.
  • Handle: RePEc:arx:papers:2111.11506
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    References listed on IDEAS

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    1. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    2. 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.
    3. 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.
    4. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    5. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    6. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2015. "Inference on factor structures in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 184(1), pages 145-157.
    7. Yoshimasa Uematsu & Takashi Yamagatay, 2020. "Estimation of Weak Factor Models," DSSR Discussion Papers 108, Graduate School of Economics and Management, Tohoku University.
    8. Tomohiro Ando & Jushan Bai, 2017. "Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1182-1198, July.
    9. Chaohua Dong & Jiti Gao & Bin Peng, 2021. "Varying-Coefficient Panel Data Models With Nonstationarity and Partially Observed Factor Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 700-711, July.
    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, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    12. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    13. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    14. Stiroh, Kevin J., 2000. "How did bank holding companies prosper in the 1990s?," Journal of Banking & Finance, Elsevier, vol. 24(11), pages 1703-1745, November.
    15. Castagnetti, Carolina & Rossi, Eduardo & Trapani, Lorenzo, 2019. "A two-stage estimator for heterogeneous panel models with common factors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 63-82.
    16. Feng, Guohua & Gao, Jiti & Peng, Bin & Zhang, Xiaohui, 2017. "A varying-coefficient panel data model with fixed effects: Theory and an application to US commercial banks," Journal of Econometrics, Elsevier, vol. 196(1), pages 68-82.
    17. David C. Wheelock & Paul W. Wilson, 2012. "Do Large Banks Have Lower Costs? New Estimates of Returns to Scale for U.S. Banks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 171-199, February.
    18. 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.
    19. 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.
    20. Feng, Guohua & Zhang, Xiaohui, 2012. "Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1883-1895.
    21. Degui Li & Junhui Qian & Su Liangjun, 2015. "Panel Data Models with Interactive Fixed Effects and Multiple Structural Breaks," Working Papers 12-2015, Singapore Management University, School of Economics.
    22. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    23. Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
    24. Joshua Gallin, 2006. "The Long-Run Relationship between House Prices and Income: Evidence from Local Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 34(3), pages 417-438, September.
    25. Huang, Wenxin & Jin, Sainan & Phillips, Peter C.B. & Su, Liangjun, 2021. "Nonstationary panel models with latent group structures and cross-section dependence," Journal of Econometrics, Elsevier, vol. 221(1), pages 198-222.
    26. Feng, Guohua & Serletis, Apostolos, 2008. "Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions," Journal of Econometrics, Elsevier, vol. 142(1), pages 281-311, January.
    27. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    28. Li, Kunpeng & Cui, Guowei & Lu, Lina, 2020. "Efficient estimation of heterogeneous coefficients in panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 216(2), pages 327-353.
    29. HARRY DeANGELO & RICHARD ROLL, 2015. "How Stable Are Corporate Capital Structures?," Journal of Finance, American Finance Association, vol. 70(1), pages 373-418, February.
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    Cited by:

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    2. Hou, Li & Jin, Baisuo & Wu, Yuehua, 2024. "Estimation and variable selection for high-dimensional spatial dynamic panel data models," Journal of Econometrics, Elsevier, vol. 238(2).

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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