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Efficiency in Large Dynamic Panel Models with Common Factor

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  • Patrick GAGLIARDINI

    (Crest)

  • Christian GOURIEROUX

    (Crest)

Abstract

This paper deals with asymptotically efficient estimation in exchangeable nonlinear dynamicpanel models with common unobservable factor. These models are especially relevantfor applications to large portfolios of credits, corporate bonds, or life insurance contracts, andare recommended in the current regulation in Finance (Basel II and Basel III) and Insurance(Solvency II). The specification accounts for both micro- and macro-dynamics, induced bythe lagged individual observation and the common stochastic factor, respectively. For largecross-sectional and time dimensions n and T, respectively, we derive the efficiency boundand introduce computationally simple efficient estimators for both the micro- and macroparameters.In particular, we show that the fixed effects estimator of the micro-parameteris asymptotically efficient. The results are based on an asymptotic expansion of the loglikelihoodfunction in powers of 1=n. This expansion is used to investigate the second-orderbias properties of the estimators. The results are illustrated with the stochastic migrationmodel for credit risk analysis.

Suggested Citation

  • Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Efficiency in Large Dynamic Panel Models with Common Factor," Working Papers 2010-05, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2010-05
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    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. repec:hal:spmain:info:hdl:2441/1mc4dip81d9t8r0t57fe1h8lap is not listed on IDEAS
    3. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    4. 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.
    5. Dhaene, Geert & Jochmans, Koen, 2016. "Likelihood Inference In An Autoregression With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1178-1215, October.
    6. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    7. Carlos Perez Montes, 2015. "Estimation of Regulatory Credit Risk Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 48(2), pages 161-191, October.
    8. Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2016. "Is Industrial Production Still the Dominant Factor for the US Economy?," Swiss Finance Institute Research Paper Series 16-11, Swiss Finance Institute.
    9. Gregory Connor & Robert A Korajczyk, 2024. "Semi-Strong Factors in Asset Returns," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 70-93.
    10. Francesco Audrino & Fulvio Corsi & Kameliya Filipova, 2016. "Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators," Econometric Reviews, Taylor & Francis Journals, vol. 35(2), pages 232-256, February.
    11. Gagliardini, Patrick & Gouriéroux, Christian, 2019. "Identification by Laplace transforms in nonlinear time series and panel models with unobserved stochastic dynamic effects," Journal of Econometrics, Elsevier, vol. 208(2), pages 613-637.
    12. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    13. Christian Gourieroux & Joann Jasiak, 2022. "Long Run Risk in Stationary Structural Vector Autoregressive Models," Papers 2202.09473, arXiv.org.
    14. Gagliardini, Patrick & Gouriéroux, Christian, 2017. "Double instrumental variable estimation of interaction models with big data," Journal of Econometrics, Elsevier, vol. 201(2), pages 176-197.
    15. Antoine Djogbenou & Christian Gouri'eroux & Joann Jasiak & Maygol Bandehali, 2021. "Composite Likelihood for Stochastic Migration Model with Unobserved Factor," Papers 2109.09043, arXiv.org, revised Nov 2023.
    16. Carlos Pérez Montes, 2013. "Estimation of Regulatory Credit Risk Models," Working Papers 1305, Banco de España.
    17. Dhaene, Geert & Jochmans, Koen, 2016. "Likelihood Inference In An Autoregression With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1178-1215, October.
    18. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.

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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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