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Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations

Author

Listed:
  • Luciano de Castro

    (University of Iowa)

  • Antonio F. Galvao

    (University of Arizona)

  • David M. Kaplan

    () (University of Missouri)

Abstract

WP 17-10 has now been replaced by working paper WP 18-03.

Suggested Citation

  • Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
  • Handle: RePEc:umc:wpaper:1710
    as

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    File URL: https://economics.missouri.edu/sites/default/files/wp-files/dcgkl_2018_quantile_gmm.pdf
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    References listed on IDEAS

    as
    1. Manski, C.F., 1988. "Ordinal Utility Models Of Decision Making Under Uncertainty," Working papers 363, Wisconsin Madison - Social Systems.
    2. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
    3. Hansen, Lars Peter & Singleton, Kenneth J, 1983. "Stochastic Consumption, Risk Aversion, and the Temporal Behavior of Asset Returns," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 249-265, April.
    4. Giovannetti, Bruno C., 2013. "Asset pricing under quantile utility maximization," Review of Financial Economics, Elsevier, vol. 22(4), pages 169-179.
    5. Potscher, Benedikt M. & Prucha, Ingmar R., 1994. "Generic uniform convergence and equicontinuity concepts for random functions : An exploration of the basic structure," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 23-63.
    6. Chen, Xiaohong & Liao, Zhipeng, 2015. "Sieve semiparametric two-step GMM under weak dependence," Journal of Econometrics, Elsevier, vol. 189(1), pages 163-186.
    7. Kinal, Terrence W, 1980. "The Existence of Moments of k-Class Estimators," Econometrica, Econometric Society, vol. 48(1), pages 241-249, January.
    8. Alexis Akira Toda & Kieran James Walsh, 2017. "Fat tails and spurious estimation of consumption‐based asset pricing models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1156-1177, September.
    9. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    10. Kaplan, David M. & Sun, Yixiao, 2017. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," Econometric Theory, Cambridge University Press, vol. 33(01), pages 105-157, February.
    11. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 433-495.
    12. Oberhofer, Walter & Haupt, Harry, 2016. "Asymptotic Theory For Nonlinear Quantile Regression Under Weak Dependence," Econometric Theory, Cambridge University Press, vol. 32(03), pages 686-713, June.
    13. Alexis Akira Toda & Kieran Walsh, 2015. "The Double Power Law in Consumption and Implications for Testing Euler Equations," Journal of Political Economy, University of Chicago Press, vol. 123(5), pages 1177-1200.
    14. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    15. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    16. Zhenlin Yang & Liangjun Su, 2007. "Instrumental Variable Quantile Estimation of Spatial Autoregressive Models," Working Papers 05-2007, Singapore Management University, School of Economics.
    17. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    18. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Hwang, Jungbin & Sun, Yixiao, 2015. "Should We Go One Step Further? Â An Accurate Comparison of One-step and Two-step Procedures in a Generalized Method of Moments Framework," University of California at San Diego, Economics Working Paper Series qt58r2z98m, Department of Economics, UC San Diego.
    20. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
    21. Kengo Kato, 2012. "Asymptotic normality of Powell’s kernel estimator," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 255-273, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    instrumental variables; nonlinear quantile regression; quantile utility maximization;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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