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The Impact of Decentralized Data Entry on the Quality of Household Survey Data in Developing Countries: Evidence from a Randomized Experiment in Vietnam

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  • Paul Glewwe
  • Hai-Anh Hoang Dang

Abstract

Computers were provided to randomly selected districts participating in a household survey in Vietnam to assess the impact on data quality of entering data within a day or two of completing the interview rather than several weeks later in the provincial capital. Provision of computers had no significant effect on the observed distribution of household expenditures and thus no effect on measured poverty. Provision of computers reduced the mean number of errors per household by 5--23 percent, depending on the type of error. Given the already low rate of errors in the survey, however, the goal of increasing the precision of the estimated mean of a typical variable can be achieved at a much lower cost by slightly increasing the sample size. Provision of additional computers did substantially reduce the time interviewers spent adding up and checking the data in the field, with the value of the time saved close to the cost of purchasing desktop computers. Copyright The Author 2008. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / the world bank . All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Paul Glewwe & Hai-Anh Hoang Dang, 2008. "The Impact of Decentralized Data Entry on the Quality of Household Survey Data in Developing Countries: Evidence from a Randomized Experiment in Vietnam," The World Bank Economic Review, World Bank, vol. 22(1), pages 165-185, January.
  • Handle: RePEc:oup:wbecrv:v:22:y:2008:i:1:p:165-185
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    File URL: http://hdl.handle.net/10.1093/wber/lhm023
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    Cited by:

    1. Brooks, Mark & Lippe, Rattiya S. & Waibel, Hermann, 2021. "PAPI is gone, but errors remain: Non-sampling errors in household surveys," 2021 Conference, August 17-31, 2021, Virtual 315277, International Association of Agricultural Economists.
    2. Phung, T.D. & Hardeweg, B. & Praneetvatakul, S. & Waibel, H., 2015. "Non-Sampling Error and Data Quality: What Can We Learn from Surveys to Collect Data for Vulnerability Measurements?," World Development, Elsevier, vol. 71(C), pages 25-35.
    3. George Judge & Laura Schechter, 2009. "Detecting Problems in Survey Data Using Benford’s Law," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).

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