Multidimensional Poverty: Measurement, Estimation, and Inference

REFERENCES

• Alkire , S. , Foster , J. ( 2008 ). Counting and multidimensional poverty measurement. OPHI Working Paper No. 7, University of Oxford .
   Google Scholar
• Alkire , S. , Seth , S. ( 2008 ). Multidimensional poverty measurement and BPL methods in India: A comparison of methods. OPHI Working Paper No. 15, University of Oxford .
   Google Scholar
• Anderson , G. ( 1996 ). Nonparametric tests of stochastic dominance in income distributions . Econometrica 64 ( 5 ): 1183 – 1193 .
   Web of Science ®Google Scholar
• Barrett , G. F. , Donald , S. G. ( 2003 ). Consistent tests for stochastic dominance . Econometrica 71 ( 1 ): 71 – 104 .
   Web of Science ®Google Scholar
• Batana , Y. ( 2008 ). Multidimensional measurement of poverty in Sub-Saharan Africa. OPHI Working Paper No. 13, University of Oxford .
   Google Scholar
• Bennett , C. J. ( 2010 ). Improving the power of multiple testing procedures via single-step methods. Working Paper No. 1654062, SSRN .
   Google Scholar
• Bhattacharya , D. ( 2007 ). Inference on inequality from household survey data . Journal of Econometrics 137 ( 2 ): 674 – 707 .
   Web of Science ®Google Scholar
• Bourguingnon , F. , Chakravarty , S. R. ( 2005 ). The measurement of multidimensional poverty . Journal of Economic Inequality 1 : 25 – 49 .
   Google Scholar
• Davidson , R. , Duclos , J.-Y. ( 2000 ). Statistical inference for stochastic dominance and for the measurement of poverty and inequality . Econometrica 68 ( 6 ): 1435 – 1464 .
   Web of Science ®Google Scholar
• Davidson , R. , Duclos , J.-Y. ( 2006 ). Testing for restricted stochastic dominance. IZA Discussion Paper No. 2047 .
   Google Scholar
• Duclos , J.-Y. , Sahn , D. E. , Younger , S. D. ( 2006 ). Robust multidimensional poverty comparisons . Economic Journal 116 ( 514 ): 943 – 968 .
   Web of Science ®Google Scholar
• Foster , J. , Greer , J. , Thorbecke , E. ( 1984 ). A class of decomposable poverty measures . Econometrica 52 ( 3 ): 761 – 66 .
   Web of Science ®Google Scholar
• Hsu , P.-H. , Hsu , Y.-C. , Kuan , C.-M. (2010). Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias. Journal of Empirical Finance 17(3):471–484.
   Web of Science ®Google Scholar
• Kakwani , N. , Silber , J. ( 2008 ). Quantitative Approaches to Multidimensional Poverty Measurement . Basingstoke , UK : Palgrave Macmillan .
   Google Scholar
• Kodde , D. A. , Palm , F. C. ( 1986 ). Wald criteria for jointly testing equality and inequality restrictions . Econometrica 54 ( 5 ): 1243 .
   Web of Science ®Google Scholar
• Kosorok , M. R. ( 2008 ). Introduction to Empirical Processes and Semiparametric Inference . New York : Springer .
   Google Scholar
• Linton , O. , Maasoumi , E. , Whang , Y.-J. ( 2005 ). Consistent testing for stochastic dominance under general sampling schemes . Review of Economic Studies 72 ( 3 ): 735 – 765 .
   Web of Science ®Google Scholar
• Maasoumi , E. , Lugo , M. A. ( 2008 ). The information basis of multivariate poverty assessments . In: Quantitative Approaches to Multidimensional Poverty Measurement . Oxford , UK : Palgrave-MacMillan , pp. 1 – 29 .
   Google Scholar
• Mitra , S. ( 2011 ). Topics in Measurement: Multidimensional Poverty and Polarization, PhD Thesis, Vanderbilt University .
   Google Scholar
• Romano , J. P. , Wolf , M. ( 2005 ). Stepwise multiple testing as formalized data snooping . Econometrica 73 ( 4 ): 1237 – 1282 .
   Web of Science ®Google Scholar
• Santos , M. E. , Ura , K. ( 2008 ). Multidimensional poverty in Bhutan: Estimates and policy implications. OPHI Working Paper No. 14, University of Oxford .
   Google Scholar
• Sen , A. ( 1976 ). Poverty: An ordinal approach to measurement . Econometrica 44 ( 2 ): 219 – 231 .
   Web of Science ®Google Scholar
• Tsui , K.-y. ( 2002 ). Multidimensional poverty indices . Social Choice and Welfare 19 : 69 – 93 .
   Web of Science ®Google Scholar
• Wolak , F. ( 1989 ). Local and global testing of linear and nonlinear inequality constraints in nonlinear econometric models . Econometric Theory 5 : 1 .
   Web of Science ®Google Scholar
• The views expressed here are those of the author and should not be attributed to the World Bank or any affiliated organization.
   Google Scholar