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Can diaries help improve agricultural production statistics ? Evidence from Uganda

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Listed:
  • Carletto,Calogero
  • Deininger,Klaus W.
  • Muwonge, James
  • Savastano,Sara
  • Carletto,Calogero
  • Deininger,Klaus W.
  • Muwonge, James
  • Savastano,Sara

Abstract

Although good and timely information on agricultural production is critical for policy-decisions, the quality of underlying data is often low and improving data quality could have a high payoff. This paper uses data from a production diary, administered concurrently with a standard household survey in Uganda to analyze the nature and incidence of responses, the magnitude of differences in reported outcomes, and factors that systematically affect these. Despite limited central supervision, diaries elicited a strong response, complemented standard surveys in a number of respects, and were less affected by problems of respondent fatigue than expected. The diary-based estimates of output value consistently exceeded that from the recall-based production survey, in line with reported disposition. Implications for policy and practical administration of surveys are drawn out.

Suggested Citation

  • Carletto,Calogero & Deininger,Klaus W. & Muwonge, James & Savastano,Sara & Carletto,Calogero & Deininger,Klaus W. & Muwonge, James & Savastano,Sara, 2011. "Can diaries help improve agricultural production statistics ? Evidence from Uganda," Policy Research Working Paper Series 5717, The World Bank.
    • Handle: RePEc:wbk:wbrwps:5717
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    References listed on IDEAS

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    1. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries," World Bank Publications - Books, The World Bank Group, number 25338, December.
    2. 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.
    3. John Gibson, 2002. "Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-359, September.
    4. Gibson, John, 2002. "Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-359, September.
    5. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
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    2. Bachewe, Fantu Nisrane & Berhane, Guush & Minten, Bart & Taffesse, Alemayehu Seyoum, 2015. "Agricultural growth in Ethiopia (2004-2014): Evidence and drivers:," ESSP working papers 81, International Food Policy Research Institute (IFPRI).
    3. Arthi, Vellore & Beegle, Kathleen & De Weerdt, Joachim & Palacios-López, Amparo, 2018. "Not your average job: Measuring farm labor in Tanzania," Journal of Development Economics, Elsevier, vol. 130(C), pages 160-172.
    4. Durante, Anna Christine & Lapitan, Pamela & Megill, David & Rao , Lakshman Nagraj, 2018. "Improving Paddy Rice Statistics Using Area Sampling Frame Technique," ADB Economics Working Paper Series 565, Asian Development Bank.
    5. Bachewe, Fantu N. & Berhane, Guush & Minten, Bart & Taffesse, Alemayehu S., 2018. "Agricultural Transformation in Africa? Assessing the Evidence in Ethiopia," World Development, Elsevier, vol. 105(C), pages 286-298.

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    Keywords

    Crops and Crop Management Systems; Climate Change and Agriculture; Food Security; Educational Sciences; Labor&Employment Law; Gender and Development;
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