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Cross-sectional averages versus principal components

Author

Listed:
  • Westerlund, Joakim
  • Urbain, Jean-Pierre

Abstract

In spite of the increased use of factor-augmented regressions in recent years, little is known regarding the relative merits of the two main approaches to estimation and inference, namely, the cross-sectional average and principal component estimators. By providing a formal comparison of the approaches, the current paper fills this gap in the literature.

Suggested Citation

  • Westerlund, Joakim & Urbain, Jean-Pierre, 2015. "Cross-sectional averages versus principal components," Journal of Econometrics, Elsevier, vol. 185(2), pages 372-377.
  • Handle: RePEc:eee:econom:v:185:y:2015:i:2:p:372-377
    DOI: 10.1016/j.jeconom.2014.09.014
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    References listed on IDEAS

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    1. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Asymptotic distribution of factor augmented estimators for panel regression," Journal of Econometrics, Elsevier, vol. 169(1), pages 48-53.
    2. 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.
    3. 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 Group Munich.
    4. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
    5. 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.
    6. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
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    Citations

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    Cited by:

    1. Milda Norkuté & Vasilis Sarafidis & Takashi Yamagata, 2018. "Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure," ISER Discussion Paper 1019, Institute of Social and Economic Research, Osaka University.
    2. repec:hal:journl:halshs-01318131 is not listed on IDEAS
    3. Daniel M. Bernhofen & Markus Eberhardt & Jianan Li & Stephen Morgan, 2015. "Assessing Market (Dis)Integration in Early Modern China and Europe," CESifo Working Paper Series 5580, CESifo Group Munich.
    4. repec:bla:jtsera:v:38:y:2017:i:4:p:610-636 is not listed on IDEAS
    5. Anindya Banerjee & Josep Lluís Carrion-i-Silvestre, 2017. "Testing for Panel Cointegration Using Common Correlated Effects Estimators," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 610-636, July.
    6. Peter Fuleky & Luigi Ventura & Qianxue Zhao, 2018. "Common correlated effects and international risk sharing," International Finance, Wiley Blackwell, vol. 21(1), pages 55-70, March.
    7. Olivier Damette & Mathilde Maurel & Michael A. Stemmer, 2016. "What does it take to grow out of recession? An error-correction approach towards growth convergence of European and transition countries," Documents de travail du Centre d'Economie de la Sorbonne 16041, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Carlos Vladimir Rodríguez-Caballero, 2016. "Panel Data with Cross-Sectional Dependence Characterized by a Multi-Level Factor Structure," CREATES Research Papers 2016-31, Department of Economics and Business Economics, Aarhus University.
    9. 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 1037, Institute of Social and Economic Research, Osaka University.
    10. R. Golinelli & I. Mammi & A. Musolesi, 2018. "Parameter heterogeneity, persistence and cross-sectional dependence: new insights on fiscal policy reaction functions for the Euro area," Working Papers wp1120, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. Evan Totty, 2017. "The Effect Of Minimum Wages On Employment: A Factor Model Approach," Economic Inquiry, Western Economic Association International, vol. 55(4), pages 1712-1737, October.
    12. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2016. "Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure," IEAS Working Paper : academic research 16-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    13. 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.
    14. repec:bla:presci:v:96:y:2017:i:3:p:571-602 is not listed on IDEAS
    15. Salmensuu, Olli, 2017. "Macroeconomic Trends and Factors of Production Affecting Potato Producer Price in Developing Countries," MPRA Paper 79163, University Library of Munich, Germany.

    More about this item

    Keywords

    Factor-augmented panel regressions; Common factor models; Principal components; Cross-section averages; Cross-section dependence;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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