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Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes

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  • Daniel Pollmann
  • Thomas Dohmen
  • Franz Palm

Abstract

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment Sample (IABS). We then relate these robust measures of earnings risk to the risk attitudes of individuals working in these occupations. We find that willingness to take risk is positively correlated with the wage dispersion of an individual's occupation.

Suggested Citation

  • Daniel Pollmann & Thomas Dohmen & Franz Palm, 2013. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," SOEPpapers on Multidisciplinary Panel Data Research 572, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Handle: RePEc:diw:diwsop:diw_sp572
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    1. Christian Belzil & Jörgen Hansen, 2004. "Earnings Dispersion, Risk Aversion And Education," Research in Labor Economics, in: Accounting for Worker Well-Being, pages 335-358, Emerald Group Publishing Limited.
    2. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde, 2010. "Are Risk Aversion and Impatience Related to Cognitive Ability?," American Economic Review, American Economic Association, vol. 100(3), pages 1238-1260, June.
    3. Thomas Dohmen & Armin Falk, 2010. "You Get What You Pay For: Incentives and Selection in the Education System," Economic Journal, Royal Economic Society, vol. 120(546), pages 256-271, August.
    4. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    5. Sam Schulhofer-Wohl, 2011. "Heterogeneity and Tests of Risk Sharing," Journal of Political Economy, University of Chicago Press, vol. 119(5), pages 925-958.
    6. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    7. Luojia Hu, 2002. "Estimation of a Censored Dynamic Panel Data Model," Econometrica, Econometric Society, vol. 70(6), pages 2499-2517, November.
    8. Claudia R. Sahm, 2012. "How Much Does Risk Tolerance Change?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-38.
    9. G.S. Maddala & Forrest D. Nelson, 1975. "Specification Errors in Limited Dependent Variable Models," NBER Working Papers 0096, National Bureau of Economic Research, Inc.
    10. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    11. Lawrence F. Katz & Kevin M. Murphy, 1992. "Changes in Relative Wages, 1963–1987: Supply and Demand Factors," The Quarterly Journal of Economics, Oxford University Press, vol. 107(1), pages 35-78.
    12. Mark Ottoni Wilhelm, 2008. "Practical Considerations for Choosing Between Tobit and SCLS or CLAD Estimators for Censored Regression Models with an Application to Charitable Giving," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(4), pages 559-582, August.
    13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    14. Bonin, Holger & Dohmen, Thomas & Falk, Armin & Huffman, David & Sunde, Uwe, 2007. "Cross-sectional earnings risk and occupational sorting: The role of risk attitudes," Labour Economics, Elsevier, vol. 14(6), pages 926-937, December.
    15. Cramer, J. S. & Hartog, J. & Jonker, N. & Van Praag, C. M., 2002. "Low risk aversion encourages the choice for entrepreneurship: an empirical test of a truism," Journal of Economic Behavior & Organization, Elsevier, vol. 48(1), pages 29-36, May.
    16. Belzil, Christian & Leonardi, Marco, 2007. "Can risk aversion explain schooling attainments? Evidence from Italy," Labour Economics, Elsevier, vol. 14(6), pages 957-970, December.
    17. Fouarge, Didier & Kriechel, Ben & Dohmen, Thomas, 2014. "Occupational sorting of school graduates: The role of economic preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 335-351.
    18. Donald, Stephen G., 1995. "Two-step estimation of heteroskedastic sample selection models," Journal of Econometrics, Elsevier, vol. 65(2), pages 347-380, February.
    19. Khan, Shakeeb & Powell, James L., 2001. "Two-step estimation of semiparametric censored regression models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 73-110, July.
    20. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    21. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    22. Arabmazar, Abbas & Schmidt, Peter, 1982. "An Investigation of the Robustness of the Tobit Estimator to Non-Normality," Econometrica, Econometric Society, vol. 50(4), pages 1055-1063, July.
    23. Stacey H. Chen, 2008. "Estimating the Variance of Wages in the Presence of Selection and Unobserved Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 275-289, May.
    24. Paarsch, Harry J., 1984. "A Monte Carlo comparison of estimators for censored regression models," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 197-213.
    25. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    26. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    27. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    28. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    29. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
    30. Marco Caliendo & Frank Fossen & Alexander Kritikos, 2009. "Risk attitudes of nascent entrepreneurs–new evidence from an experimentally validated survey," Small Business Economics, Springer, vol. 32(2), pages 153-167, February.
    31. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    32. Nickell, Stephen & Bell, Brian, 1996. "Changes in the Distribution of Wages and Unemployment in OECD Countries," American Economic Review, American Economic Association, vol. 86(2), pages 302-308, May.
    33. Christian Dustmann & Johannes Ludsteck & Uta Schönberg, 2009. "Revisiting the German Wage Structure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(2), pages 843-881.
    34. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    35. Jacob Mincer, 1991. "Education and Unemployment of Women," NBER Working Papers 3837, National Bureau of Economic Research, Inc.
    36. Bernd Fitzenberger & Aderonke Osikominu & Robert Völter, 2006. "Imputation Rules to Improve the Education Variable in the IAB Employment Subsample," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 126(3), pages 405-436.
    37. Kenneth Y. Chay & Bo E. Honoré, 1998. "Estimation of Semiparametric Censored Regression Models: An Application to Changes in Black-White Earnings Inequality during the 1960s," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 4-38.
    38. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-442, June.
    39. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    40. 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.
    41. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.
    42. Guiso, Luigi & Pagel, Michaela, 2004. "The Role of Risk Aversion in Predicting Individual Behaviours," CEPR Discussion Papers 4591, C.E.P.R. Discussion Papers.
    43. Jacob Mincer, 1991. "Education and Unemployment," NBER Working Papers 3838, National Bureau of Economic Research, Inc.
    44. Saks Raven E & Shore Stephen H, 2005. "Risk and Career Choice," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-45, October.
    45. Levhari, David & Weiss, Yoram, 1974. "The Effect of Risk on the Investment in Human Capital," American Economic Review, American Economic Association, vol. 64(6), pages 950-963, December.
    46. Schmillen, Achim & Möller, Joachim, 2012. "Distribution and determinants of lifetime unemployment," Labour Economics, Elsevier, vol. 19(1), pages 33-47.
    47. Ekelund, Jesper & Johansson, Edvard & Jarvelin, Marjo-Riitta & Lichtermann, Dirk, 2005. "Self-employment and risk aversion--evidence from psychological test data," Labour Economics, Elsevier, vol. 12(5), pages 649-659, October.
    48. Vijverberg, Wim P M, 1987. "Non-normality as Distributional Misspecification in Single-Equation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 417-430, November.
    49. Roger Koenker & Zhijie Xiao, 2002. "Inference on the Quantile Regression Process," Econometrica, Econometric Society, vol. 70(4), pages 1583-1612, July.
    50. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    51. Charles Brown & Robert Moffitt, 1983. "The Effect of Ignoring Heteroscedasticity on Estimates of the Tobit Model," NBER Technical Working Papers 0027, National Bureau of Economic Research, Inc.
    52. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
    53. Arabmazar, Abbas & Schmidt, Peter, 1981. "Further evidence on the robustness of the Tobit estimator to heteroskedasticity," Journal of Econometrics, Elsevier, vol. 17(2), pages 253-258, November.
    54. Shaw, Kathryn L, 1996. "An Empirical Analysis of Risk Aversion and Income Growth," Journal of Labor Economics, University of Chicago Press, vol. 14(4), pages 626-653, October.
    55. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    56. Hurd, Michael, 1979. "Estimation in truncated samples when there is heteroscedasticity," Journal of Econometrics, Elsevier, vol. 11(2-3), pages 247-258.
    57. Skeels, Christopher L. & Vella, Francis, 1999. "A Monte Carlo investigation of the sampling behavior of conditional moment tests in Tobit and Probit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 275-294, October.
    58. Don Bellante & Albert N. Link, 1981. "Are Public Sector Workers More Risk Averse Than Private Sector Workers?," ILR Review, Cornell University, ILR School, vol. 34(3), pages 408-412, April.
    59. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
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    More about this item

    Keywords

    dispersion estimation; earnings risk; censoring; quantile regression; occupational choice; sorting; risk preferences; SOEP; IABS;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • D1 - Microeconomics - - Household Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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