Semi-nonparametric test of second degree stochastic dominance with respect to a function
In an expected utility framework, assuming a decision maker operates under utility k([dot operator][theta]), for two risky alternatives X and Y with respective distribution functions F and G, alternative X is said to dominate alternative Y with respect to k([dot operator][theta]) if for all y. Utilizing the empirical distribution functions of F and G, a statistical test is presented to test the null hypothesis of indifference between X and Y given k([dot operator][theta]) against the hypothesis that X dominates Y with respect to k([dot operator][theta]). This is a large sample testing application of stochastic dominance with respect to a function. The asymptotic distribution of the test statistic associated with the null hypothesis given a sub-set of the utility function parameter space is developed. Based on large sample rejection regions, the hypothesis of preference of one alternative over another is demonstrated with an empirical example.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Edward Seiler, 2001. "A nonparametric test for marginal conditional stochastic dominance," Applied Financial Economics, Taylor & Francis Journals, vol. 11(2), pages 173-177.
- Haim Shalit & Shlomo Yitzhaki, 1994. "Marginal Conditional Stochastic Dominance," Management Science, INFORMS, vol. 40(5), pages 670-684, May.
- J. Brian Hardaker & James W. Richardson & Gudbrand Lien & Keith D. Schumann, 2004.
"Stochastic efficiency analysis with risk aversion bounds: a simplified approach,"
Australian Journal of Agricultural and Resource Economics,
Australian Agricultural and Resource Economics Society, vol. 48(2), pages 253-270, 06.
- Hardaker, J. Brian & Richardson, James W. & Lien, Gudbrand D. & Schumann, Keith D., 2004. "Stochastic efficiency analysis with risk aversion bounds: a simplified approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), June.
- Kaur, Amarjot & Prakasa Rao, B.L.S. & Singh, Harshinder, 1994. "Testing for Second-Order Stochastic Dominance of Two Distributions," Econometric Theory, Cambridge University Press, vol. 10(05), pages 849-866, December.
- Ian Crawford, 2005. "A nonparametric test of stochastic dominance in multivariate distributions," School of Economics Discussion Papers 1205, School of Economics, University of Surrey.
- Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56, pages 279.
- Meyer, Jack, 1977. "Second Degree Stochastic Dominance with Respect to a Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 477-87, June.
- Milton Friedman & L. J. Savage, 1952. "The Expected-Utility Hypothesis and the Measurability of Utility," Journal of Political Economy, University of Chicago Press, vol. 60, pages 463.
- Russell Davidson & Jean-Yves Duclos, 2006.
"Testing for Restricted Stochastic Dominance,"
Cahiers de recherche
- Russell Davidson & Jean-Yves Duclos, 2006. "Testing for Restricted Stochastic Dominance," Working Papers 36, ECINEQ, Society for the Study of Economic Inequality.
- Davidson, Russell & Duclos, Jean-Yves, 2006. "Testing for Restricted Stochastic Dominance," IZA Discussion Papers 2047, Institute for the Study of Labor (IZA).
- Russell Davidson & Jean-Yves Duclos, 2006. "Testing For Restricted Stochastic Dominance," Departmental Working Papers 2006-20, McGill University, Department of Economics.
- Russell Davidson & Jean-Yves Duclos, 2009. "Testing for restricted stochastic dominance," Working Papers halshs-00443560, HAL.
- Hanoch, G & Levy, Haim, 1969. "The Efficiency Analysis of Choices Involving Risk," Review of Economic Studies, Wiley Blackwell, vol. 36(107), pages 335-46, July.
- Diamond, Peter A. & Stiglitz, Joseph E., 1974. "Increases in risk and in risk aversion," Journal of Economic Theory, Elsevier, vol. 8(3), pages 337-360, July.
- Rothschild, Michael & Stiglitz, Joseph E., 1971. "Increasing risk II: Its economic consequences," Journal of Economic Theory, Elsevier, vol. 3(1), pages 66-84, March.
- Rothschild, Michael & Stiglitz, Joseph E., 1970. "Increasing risk: I. A definition," Journal of Economic Theory, Elsevier, vol. 2(3), pages 225-243, September.
- Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-93, September.
- McDonald, Jeffrey D. & Moffitt, L. Joe & Willis, Cleve E., 1997. "Application of mean-Gini stochastic efficiency analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 41(1), March.
- Meyer, Jack, 1977. "Further Applications of Stochastic Dominance to Mutual Fund Performance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(02), pages 235-242, June.
- Meyer, Jack, 1975. "Increasing risk," Journal of Economic Theory, Elsevier, vol. 11(1), pages 119-132, August.
- Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
- Yitzhaki, Shlomo, 1991. "Calculating Jackknife Variance Estimators for Parameters of the Gini Method," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 235-39, April.
When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:162:y:2011:i:1:p:71-78. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.