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Model selection for factor analysis: Some new criteria and performance comparisons

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  • In Choi
  • Hanbat Jeong

Abstract

This paper derives Akaike information criterion (AIC), corrected AIC, the Bayesian information criterion (BIC) and Hannan and Quinn’s information criterion for approximate factor models assuming a large number of cross-sectional observations and studies the consistency properties of these information criteria. It also reports extensive simulation results comparing the performance of the extant and new procedures for the selection of the number of factors. The simulation results show the difficulty of determining which criterion performs best. In practice, it is advisable to consider several criteria at the same time, especially Hannan and Quinn’s information criterion, Bai and Ng’s ICp2 and BIC3, and Onatski’s and Ahn and Horenstein’s eigenvalue-based criteria. The model-selection criteria considered in this paper are also applied to Stock and Watson’s two macroeconomic data sets. The results differ considerably depending on the model-selection criterion in use, but evidence suggesting five factors for the first data and five to seven factors for the second data is obtainable.

Suggested Citation

  • In Choi & Hanbat Jeong, 2019. "Model selection for factor analysis: Some new criteria and performance comparisons," Econometric Reviews, Taylor & Francis Journals, vol. 38(6), pages 577-596, July.
    • Handle: RePEc:taf:emetrv:v:38:y:2019:i:6:p:577-596
    DOI: 10.1080/07474938.2017.1382763
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    Cited by:

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    2. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org, revised Mar 2026.
    3. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    4. Lena Janys & Bettina Siflinger, 2021. "Mental Health and Abortions among Young Women: Time-Varying Unobserved Heterogeneity, Health Behaviors, and Risky Decisions," ECONtribute Discussion Papers Series 083, University of Bonn and University of Cologne, Germany.
    5. Janys, Lena & Siflinger, Bettina, 2024. "Mental health and abortions among young women: time-varying unobserved heterogeneity, health behaviors, and risky decisions," Journal of Econometrics, Elsevier, vol. 238(1).
    6. Guo, Xiao & Chen, Yu & Tang, Cheng Yong, 2023. "Information criteria for latent factor models: A study on factor pervasiveness and adaptivity," Journal of Econometrics, Elsevier, vol. 233(1), pages 237-250.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Choi, In & Lin, Rui & Shin, Yongcheol, 2023. "Canonical correlation-based model selection for the multilevel factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 22-44.
    9. Byoungsoo Cho, 2020. "The Monetary Policy Reaction Function in Korea with Multi-level Factors," Korean Economic Review, Korean Economic Association, vol. 36, pages 353-376.
    10. Chen, Yunxiao & Li, Xiaoou, 2022. "Determining the number of factors in high-dimensional generalized latent factor models," LSE Research Online Documents on Economics 111574, London School of Economics and Political Science, LSE Library.
    11. Eric Hillebrand & Jakob Guldbæk Mikkelsen & Lars Spreng & Giovanni Urga, 2023. "Exchange rates and macroeconomic fundamentals: Evidence of instabilities from time‐varying factor loadings," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 857-877, September.
    12. Davis, J. Scott & Valente, Giorgio & van Wincoop, Eric, 2021. "Global drivers of gross and net capital flows," Journal of International Economics, Elsevier, vol. 128(C).
    13. Petro Maziku & Bertha Bankwa, 2024. "The impact of non-aeronautical revenues on airport performance at Julius Nyerere International Airport in Dar Es Salaam, Tanzania," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 13(5), pages 607-614, July.
    14. Alexander Chudik & M. Hashem Pesaran, 2013. "Large Panel Data Models with Cross-Sectional Dependence: A Survey," CESifo Working Paper Series 4371, CESifo.
    15. 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.
    16. Luca Margaritella & Joakim Westerlund, 2023. "Using information criteria to select averages in CCE," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 405-421.
    17. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
    18. Lena Janys & Bettina Siflinger, 2021. "Mental Health and Abortions among Young Women: Time-varying Unobserved Heterogeneity, Health Behaviors, and Risky Decisions," Papers 2103.12159, arXiv.org, revised May 2022.
    19. Zhao Zhao & Guowei Cui & Shaoping Wang, 2017. "A Monte Carlo comparison of estimating the number of dynamic factors," Empirical Economics, Springer, vol. 53(3), pages 1217-1241, November.

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