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Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures

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  • Justin L. Tobias
  • Mingliang Li

Abstract

In this paper, we review and unite the literatures on returns to schooling and Bayesian model averaging. We observe that most studies seeking to estimate the returns to education have done so using particular "and often different across researchers" model specifications. Given this, we review Bayesian methods which formally account for uncertainty in the specification of the model itself, and apply these techniques to estimate the economic return to a college education. The approach described in this paper enables us to determine those model specifications which are most favored by the given data, and also enables us to use the predictions obtained from all of the competing regression models to estimate the returns to schooling. The reported precision of such estimates also account for the uncertainty inherent in the model specification. Using U.S. data from the National Longitudinal Survey of Youth "NLSY", we also revisit several 'stylized facts' in the returns to education literature and examine if they continue to hold after formally accounting for model uncertainty. Copyright Blackwell Publishers Ltd, 2004.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Economic Surveys.

Volume (Year): 18 (2004)
Issue (Month): 2 (04)
Pages: 153-180

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Handle: RePEc:bla:jecsur:v:18:y:2004:i:2:p:153-180

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Cited by:
  1. Enrique Moral-Benito, 2010. "Model Averaging In Economics," Working Papers, CEMFI wp2010_1008, CEMFI.
  2. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2012. "Bayesian model averaging in the instrumental variable regression model," Journal of Econometrics, Elsevier, Elsevier, vol. 171(2), pages 237-250.
  3. Eduardo Ley & Mark F.J. Steel, 2011. "Mixtures of g-priors for bayesian model averaging with economic applications," Statistics and Econometrics Working Papers, Universidad Carlos III, Departamento de Estadística y Econometría ws112116, Universidad Carlos III, Departamento de Estadística y Econometría.
  4. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.

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