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International Income Comparisons and Location Choice: Methodology, Analysis, and Implications

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Abstract

This paper contributes to ongoing debates on international income comparisons by deploying a novel methodology for constructing empirical distribution functions for the United States and Canada over the period 1993 - 2000. We also conduct tests for first, second, third order stochastic dominance and of intersection of distributions, to determine which,if either, country might be a preferred destination for migration. Our findings are for that all of the years for which there is comparable data, the Canadian income distribution second order stochastically dominates the US income distribution. We provide an interpretation in terms of expected utility theory, considering the case of log utility, and relate our findings to an argument by Joseph Stiglitz, that in the face of skewness of income distributions a potential migrant should look at the median rather than the mean. It turns out that Stiglitz's intuition is correct, at least in the context of our study.

Suggested Citation

  • Vivek Dehejia & Marcel Voia, 2008. "International Income Comparisons and Location Choice: Methodology, Analysis, and Implications," Carleton Economic Papers 08-02, Carleton University, Department of Economics.
  • Handle: RePEc:car:carecp:08-02
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    References listed on IDEAS

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    1. Isaias H. Salgado-Ugarte & Marco A. Perez-Hernandez, 2003. "Exploring the use of variable bandwidth kernel density estimators," Stata Journal, StataCorp LP, vol. 3(2), pages 133-147, June.
    2. Horvath, Lajos & Kokoszka, Piotr & Zitikis, Ricardas, 2006. "Testing for stochastic dominance using the weighted McFadden-type statistic," Journal of Econometrics, Elsevier, vol. 133(1), pages 191-205, July.
    3. Vivek Dehejia, 2008. "Risk Aversion, Stochastic Dominance, and Rules of Thumb: Concept and Application," Carleton Economic Papers 08-01, Carleton University, Department of Economics.
    4. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
    5. Burkhauser, Richard V, et al, 1999. "Testing the Significance of Income Distribution Changes over the 1980s Business Cycle: A Cross-National Comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 253-272, May-June.
    6. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, May.
    7. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    8. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-1193, September.
    9. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
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    12. Thomas Fraker & Rebecca Maynard, 1987. "The Adequacy of Comparison Group Designs for Evaluations of Employment-Related Programs," Journal of Human Resources, University of Wisconsin Press, vol. 22(2), pages 194-227.
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    Cited by:

    1. Vivek Dehejia & Jiankang Zhang, 2008. "Can Median-Maximizing Behavior Be Rational?," Carleton Economic Papers 08-09, Carleton University, Department of Economics.

    More about this item

    Keywords

    Non-parametrics; Finite Mixtures; Heterogeneous Income Distribution; Stochastic Dominance; Kolmogorov-Smirnov type statistic; Bootstrap.;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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