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Nonparametric Applications of Bayesian Inference

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  • Gary Chamberlain
  • Guido W. Imbens

Abstract

The paper evaluates the usefulness of a nonparametric approach to Bayesian inference by presenting two applications. The approach is due to Ferguson (1973, 1974) and Rubin (1981). Our first application considers an educational choice problem. We focus on obtaining a predictive distribution for earnings corresponding to various levels of schooling. This predictive distribution incorporates the parameter uncertainty, so that it is relevant for decision making under uncertainty in the expected utility framework of microeconomics. The second application is to quantile regression. Our point here is to examine the potential of the nonparametric framework to provide inferences without making asymptotic approximations. Unlike in the first application, the standard asymptotic normal approximation turns out to not be a good guide. We also consider a comparison with a bootstrap approach.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0200.

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Date of creation: Aug 1996
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Handle: RePEc:nbr:nberte:0200

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  1. Florens, J.P. & Rolin, J.M., 1994. "Bayes, Bootsrap, Moments," Papers 94.336, Toulouse - GREMAQ.
  2. Hahn, Jinyong, 1995. "Bootstrapping Quantile Regression Estimators," Econometric Theory, Cambridge University Press, vol. 11(01), pages 105-121, February.
  3. Christopher A. Sims & Harald Uhlig, 1988. "Understanding unit rooters: a helicopter tour," Discussion Paper / Institute for Empirical Macroeconomics 4, Federal Reserve Bank of Minneapolis.
  4. Kandel, Shmuel & Stambaugh, Robert F, 1996. " On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
  5. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
  6. Angrist, Joshua D & Krueger, Alan B, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, MIT Press, vol. 106(4), pages 979-1014, November.
  7. Bruce D. Meyer & W. Kip Viscusi & David L. Durbin, 1990. "Workers' Compensation and Injury Duration: Evidence from a Natural Experiment," NBER Working Papers 3494, National Bureau of Economic Research, Inc.
  8. repec:cup:etheor:v:11:y:1995:i:1:p:105-21 is not listed on IDEAS
  9. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  10. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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Cited by:
  1. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
  2. Jesús Fernández-Villaverde, 2009. "The Econometrics of DSGE Models," PIER Working Paper Archive 09-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  3. Frühwirth-Schnatter, Sylvia & Halla, Martin & Posekany, Alexandra & Pruckner, Gerald J. & Schober, Thomas, 2014. "The Quantity and Quality of Children: A Semi-Parametric Bayesian IV Approach," IZA Discussion Papers 8024, Institute for the Study of Labor (IZA).
  4. Jiang, Rong & Zhou, Zhan-Gong & Qian, Wei-Min & Chen, Yong, 2013. "Two step composite quantile regression for single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 180-191.
  5. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
  6. Tony Lancaster & Sung Jae Jun, 2006. "Bayesian quantile regression," CeMMAP working papers CWP05/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Lin, Eric S. & Chou, Ta-Sheng, 2012. "A note on Bayesian interpretations of HCCME-type refinements for nonlinear GMM models," Economics Letters, Elsevier, vol. 116(3), pages 494-497.
  8. Paserman, Daniele, 2004. "Bayesian Inference for Duration Data with Unobserved and Unknown Heterogeneity: Monte Carlo Evidence and an Application," IZA Discussion Papers 996, Institute for the Study of Labor (IZA).
  9. Dale Poirier, 2008. "Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap," Working Papers 080905, University of California-Irvine, Department of Economics.
  10. Tony Lancaster & Sung Jae Jun, 2010. "Bayesian quantile regression methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 287-307.

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