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Decomposing response errors in food consumption measurement : implications for survey design from a survey experiment in Tanzania

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  • Friedman,Jed
  • Beegle,Kathleen G.
  • De Weerdt,Joachim
  • Gibson,John

Abstract

There is wide variation in how consumption is measured in household surveys both across countries and over time. This variation may confound welfare comparisons in part because these alternative survey designs produce consumption estimates that are differentially influenced by contrasting types of survey response error. Although previous studies have documented the extent of net error in alternative survey designs, little is known about the relative influence of the different response errors that underpin a survey estimate. This study leverages a recent randomized food consumption survey experiment in Tanzania to shed light on the relative influence of these various error types. The observed deviation of measured household consumption from a benchmark is decomposed into item-specific consumption incidence and consumption value so as to investigate effects related to (a) the omission of any consumption and then (b) the error in value reporting conditional on positive consumption. The results show that various survey designs exhibit widely differing error decompositions, and hence a simple summary comparison of the total recorded consumption across surveys will obscure specific error patterns and inhibit the lessons for improved consumption survey design. In light of these findings, the relative performance of common survey designs is discussed, and design lessons are drawn to enhance the accuracy of item-specific consumption reporting and, consequently, the measures of total household food consumption.

Suggested Citation

  • Friedman,Jed & Beegle,Kathleen G. & De Weerdt,Joachim & Gibson,John, 2016. "Decomposing response errors in food consumption measurement : implications for survey design from a survey experiment in Tanzania," Policy Research Working Paper Series 7646, The World Bank.
  • Handle: RePEc:wbk:wbrwps:7646
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    References listed on IDEAS

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    1. Beegle, Kathleen & De Weerdt, Joachim & Friedman, Jed & Gibson, John, 2012. "Methods of household consumption measurement through surveys: Experimental results from Tanzania," Journal of Development Economics, Elsevier, vol. 98(1), pages 3-18.
    2. John Gibson & Kathleen Beegle & Joachim De Weerdt & Jed Friedman, 2015. "What does Variation in Survey Design Reveal about the Nature of Measurement Errors in Household Consumption?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 466-474, June.
    3. de Nicola, Francesca & Giné, Xavier, 2014. "How accurate are recall data? Evidence from coastal India," Journal of Development Economics, Elsevier, vol. 106(C), pages 52-65.
    4. Andrew Halpern-Manners & John Warren, 2012. "Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1499-1519, November.
    5. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries : Lessons from 15 Years of the Living Standards Measurement Study, Volume 3," World Bank Publications, The World Bank, number 15195, June.
    6. Kathleen Beegle & Luc Christiaensen & Andrew Dabalen & Isis Gaddis, 2016. "Poverty in a Rising Africa," World Bank Publications, The World Bank, number 22575, June.
    7. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries," World Bank Publications, The World Bank, number 25338, June.
    8. Menon, Geeta, 1993. "The Effects of Accessibility of Information in Memory on Judgments of Behavioral Frequency," Journal of Consumer Research, Oxford University Press, vol. 20(3), pages 431-440, December.
    9. Blair, Edward & Burton, Scot, 1987. "Cognitive Processes Used by Survey Respondents to Answer Behavioral Frequency Questions," Journal of Consumer Research, Oxford University Press, vol. 14(2), pages 280-288, September.
    10. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries : Lessons from 15 Years of the Living Standards Measurement Study, Volume 2," World Bank Publications, The World Bank, number 15194, June.
    11. De Weerdt, Joachim & Beegle, Kathleen & Friedman,, Jed & Gibson, John, 2014. "The challenge of measuring hunger," Policy Research Working Paper Series 6736, The World Bank.
    12. John Gibson & Bonggeun Kim, 2007. "Measurement Error in Recall Surveys and the Relationship between Household Size and Food Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 473-489.
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    2. Fiedler, John L. & Mwangi, Dena M., 2016. "Improving household consumption and expenditure surveys’ food consumption metrics: Developing a strategic approach to the unfinished agenda:," IFPRI discussion papers 1570, International Food Policy Research Institute (IFPRI).

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    More about this item

    Keywords

    Inequality;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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