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Poverty Mapping with Aggregate Census Data: What is the Loss in Precision?

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  • Nicholas Minot
  • Bob Baulch

Abstract

Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some countries (notably China and India), national statistics agencies are reluctant, for reasons of confidentiality, to release household-level census data, but they are generally more willing to release aggregated census data, such as village- or district-level means. This paper examines the loss in precision associated with using aggregated census data instead of household-level data to generate poverty estimates. The authors show analytically that using aggregated census data will result in poverty rates that are biased downward (upward) if the rate is below (above) 50%, and that the bias approaches zero as the poverty rate approaches zero, 50%, and 100%. Using data from Vietnam, it is found that the mean absolute error in estimating district-level poverty rates is 2.5 percentage points if the census data are aggregated to the enumeration-area level means, and 3-4 percentage points if the data are aggregated to commune or district level. Finally, the authors propose a method for reducing the error using variances calculated from the census. When this approach is applied to the Vietnam data, this method can cut the size of the aggregation errors by around 75%. Copyright United Nations University 2005.

Suggested Citation

  • Nicholas Minot & Bob Baulch, 2005. "Poverty Mapping with Aggregate Census Data: What is the Loss in Precision?," Review of Development Economics, Wiley Blackwell, vol. 9(1), pages 5-24, February.
  • Handle: RePEc:bla:rdevec:v:9:y:2005:i:1:p:5-24
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    References listed on IDEAS

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    1. Minot, Nicholas, 1998. "Generating disaggregated poverty maps," MTID discussion papers 25, International Food Policy Research Institute (IFPRI).
    2. Minot, Nicholas, 2000. "Generating Disaggregated Poverty Maps: An Application to Vietnam," World Development, Elsevier, vol. 28(2), pages 319-331, February.
    3. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    4. Hentschel, Jesko, et al, 2000. "Combining Census and Survey Data to Trace the Spatial Dimensions of Poverty: A Case Study of Ecuador," World Bank Economic Review, World Bank Group, vol. 14(1), pages 147-165, January.
    5. Bigman, David & Fofack, Hippolyte, 2000. "Geographical Targeting for Poverty Alleviation: An Introduction to the Special Issue," World Bank Economic Review, World Bank Group, vol. 14(1), pages 129-145, January.
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    Cited by:

    1. Bruno Arpino & Arnstein Aassve, 2014. "The role of villages in households’ poverty exit: evidence from a multilevel model for rural Vietnam," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2175-2189, July.
    2. Minot, Nicholas & Baulch, Bob, 2005. "Spatial patterns of poverty in Vietnam and their implications for policy," Food Policy, Elsevier, vol. 30(5-6), pages 461-475.

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