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Advancing Small Area Estimation

Author

Listed:
  • Arndt, Channing
  • Salvucci, Vincenzo
  • Tarp, Finn
  • Østerdal, Lars Peter
  • Hussain, M. Azhar

Abstract

The poverty mapping methodology for estimating welfare rankings from small areas has proven to be useful in guiding allocation of government funds, regional planning, and general policy formulation. Nevertheless, poverty mapping also suffers from a series of by now well recognized shortcomings. We apply an approach based on first order dominance (FOD) to small area estimation. Five advantages to the FOD approach are highlighted. First, it can serve as a complement to, substitute for, and/or extension of the poverty mapping methodology. Second, it directly uses census data with a minimum of assumptions imposed. Third, the methodology is straightforward to implement and the concepts are intuitive. Fourth, the FOD approach is multi-dimensional allowing for a broader conception of poverty. Finally, FOD indicators can be chosen that relate directly to public expenditure priorities We apply the approach to census data from Mozambique for 1997 and 2007 and compare results with the poverty mapping methodology. We conclude that the FOD approach is well suited to small area estimation.

Suggested Citation

  • Arndt, Channing & Salvucci, Vincenzo & Tarp, Finn & Østerdal, Lars Peter & Hussain, M. Azhar, 2013. "Advancing Small Area Estimation," WIDER Working Paper Series 053, World Institute for Development Economic Research (UNU-WIDER).
  • Handle: RePEc:unu:wpaper:wp2013-053
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    References listed on IDEAS

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    1. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
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    4. Channing Arndt & M. Azhar Hussain & E. Samuel Jones & Virgulino Nhate & Finn Tarp & James Thurlow, 2013. "Explaining the Evolution of Poverty: The Case of Mozambique," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 206-206.
    5. Alfani, Federica & Azzarri, Carlo & d'Errico, Marco & Molini, Vasco, 2012. "Poverty in Mozambique : new evidence from recent household surveys," Policy Research Working Paper Series 6217, The World Bank.
    6. Østerdal, Lars Peter, 2010. "The mass transfer approach to multivariate discrete first order stochastic dominance: Direct proof and implications," Journal of Mathematical Economics, Elsevier, vol. 46(6), pages 1222-1228, November.
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    Cited by:

    1. Range, Troels Martin & Østerdal, Lars Peter, 2013. "Checking bivariate first order dominance," Discussion Papers of Business and Economics 9/2013, University of Southern Denmark, Department of Business and Economics.
    2. Kristi Mahrt & Gibson Masumbu, 2015. "Estimating multidimensional poverty in Zambia," WIDER Working Paper Series 137, World Institute for Development Economic Research (UNU-WIDER).
    3. Antonio Cruz & Helen Barnes & Gemma Wright & Michell Mpike & Vanda Castelo & Michael Noble & Finório Castigo, 2016. "Tax-benefit microsimulation modelling in Mozambique: A feasibility study," WIDER Working Paper Series 027, World Institute for Development Economic Research (UNU-WIDER).
    4. Masumbu, Gibson & Mahrt, Kristi, 2014. "Multidimensional welfare in districts of Zambia: A first order dominance approach," WIDER Working Paper Series 137, World Institute for Development Economic Research (UNU-WIDER).
    5. M. Azhar Hussain & Mette Møller Jørgensen & Lars Peter Østerdal, 2016. "Refining Population Health Comparisons: A Multidimensional First Order Dominance Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(2), pages 739-759, November.

    More about this item

    Keywords

    Econometric models (Economic development); Expenditures; Public; Methodology (Poverty); Welfare economics;

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