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Testing for Poverty Dominance: an Application to Canada

  • Wen-Hao Chen
  • Jean-Yves Duclos

The paper proposes and applies statistical tests for poverty dominance that check for whether poverty comparisons can be made robustly over ranges of poverty lines and classes of poverty indices. This helps provide both normative and statistical confidence in establishing poverty rankings across distributions. The tests, which can take into account the complex sampling procedures that are typically used by statistical agencies to generate household-level surveys, are implemented using the Canadian Survey of Labour and Income Dynamics (SLID) for 1996, 1999 and 2002. Although the yearly cumulative distribution functions cross at the lower tails of the distributions, the more recent years tend to dominate earlier years for a relatively wide range of poverty lines. Failing to take into account SLID's sampling variability (as is sometimes done) can inflate significantly one's confidence in ranking poverty. Taking into account SLID's complex sampling design (as has not been done before) can also decrease substantially the range of poverty lines over which a poverty ranking can be inferred.

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Paper provided by CIRPEE in its series Cahiers de recherche with number 0836.

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Date of creation: 2008
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Handle: RePEc:lvl:lacicr:0836
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  1. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
  2. Beach, Charles M & Davidson, Russell, 1983. "Distribution-Free Statistical Inference with Lorenz Curves and Income Shares," Review of Economic Studies, Wiley Blackwell, vol. 50(4), pages 723-35, October.
  3. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2002. "Consistent Testing for Stochastic Dominance: A Subsampling Approach," FMG Discussion Papers dp407, Financial Markets Group.
  4. Bishop, John A & Formby, John P & Thistle, Paul D, 1992. "Convergence of the South and Non-South Income Distributions, 1969-1979," American Economic Review, American Economic Association, vol. 82(1), pages 262-72, March.
  5. Atkinson, A B, 1987. "On the Measurement of Poverty," Econometrica, Econometric Society, vol. 55(4), pages 749-64, July.
  6. Davidson, R. & Duclos, J.-Y., 1998. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," G.R.E.Q.A.M. 98a14, Universite Aix-Marseille III.
  7. Foster, James E & Shorrocks, Anthony F, 1988. "Poverty Orderings," Econometrica, Econometric Society, vol. 56(1), pages 173-77, January.
  8. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
  9. 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.
  10. Valentino Dardanoni & Antonio Forcina, 1999. "Inference for Lorenz curve orderings," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 49-75.
  11. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-93, September.
  12. Howes, Stephen & Lanjouw, Jean Olson, 1998. "Does Sample Design Matter for Poverty Rate Comparisons?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 44(1), pages 99-109, March.
  13. Osberg, Lars, 2002. "Trends in poverty: the UK in international perspective: how rates mislead and intensity matters," ISER Working Paper Series 2002-10, Institute for Social and Economic Research.
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