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Are All U.S. Credit Unions Alike? A Generalized Model of Heterogeneous Technologies with Endogenous Switching and Correlated Effects

Author

Listed:
  • Malikov, Emir
  • Restrepo-Tobon, Diego A
  • Kumbhakar, Subal C.

Abstract

Credit unions differ in the types of financial services they offer to their members. This paper explicitly models this observed heterogeneity using a generalized model of endogenous ordered switching. Our approach captures the endogenous choice that credit unions make when adding new products to their financial services mix. Failure to do so is likely to yield biased and inconsistent estimates. The model that we develop also allows for the dependence between unobserved effects and regressors in both the selection and outcome equations and can accommodate the presence of predetermined covariates in the model. We use this model to estimate returns to scale for U.S. retail credit unions from 1996 to 2011. We document strong evidence of persistent technological heterogeneity among credit unions offering different financial service mixes, which, if ignored, can produce quite misleading results. Employing our generalized model, we find that credit unions of all types exhibit substantial economies of scale.

Suggested Citation

  • Malikov, Emir & Restrepo-Tobon, Diego A & Kumbhakar, Subal C., 2014. "Are All U.S. Credit Unions Alike? A Generalized Model of Heterogeneous Technologies with Endogenous Switching and Correlated Effects," MPRA Paper 55994, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:55994
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    Citations

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    Cited by:

    1. Badunenko, Oleg & Kumbhakar, Subal C., 2017. "Economies of scale, technical change and persistent and time-varying cost efficiency in Indian banking: Do ownership, regulation and heterogeneity matter?," European Journal of Operational Research, Elsevier, vol. 260(2), pages 789-803.
    2. Carolina Ortega Londono, 2018. "Transmission of Monetary Policy and Bank Heterogeneity in Colombia," Documentos de Trabajo de Valor Público 16792, Universidad EAFIT.
    3. Carolina Ortega Londono & Diego Restrepo, 2018. "Transmission of Monetary Policy and Bank Heterogeneity in Colombia," Documentos de Trabajo de Valor Público 16987, Universidad EAFIT.
    4. Malikov, Emir & Kumbhakar, Subal C. & Sun, Yiguo, 2016. "Varying coefficient panel data model in the presence of endogenous selectivity and fixed effects," Journal of Econometrics, Elsevier, vol. 190(2), pages 233-251.
    5. Gregory McKee & Albert Kagan, 2016. "Determinants of recent structural change for small asset U.S. credit unions," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 775-795, October.

    More about this item

    Keywords

    Credit Union; Correlated Effects; Panel Data; Returns to Scale; Selection; Switching Regression;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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