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Reliability of recall in agricultural data

  • Beegle, Kathleen
  • Carletto, Calogero
  • Himelein, Kristen

Despite the importance of agriculture to economic development, and a vast accompanying literature on the subject, little research has been done on the quality of the underlying data. Due to survey logistics, agricultural data are usually collected by asking respondents to recall the details of events occurring during past agricultural seasons that took place a number of months prior to the interview. This gap can lead to recall bias in reported data on agricultural activities. The problem is further complicated when interviews are conducted over the course of several months, thus leading to recall of variable length. To test for such recall bias, the length of time between harvest and interview is examined for three African countries with respect to several common agricultural input and harvest measures. The analysis shows little evidence of recall bias impacting data quality. There is some indication that more salient events are less subject to recall decay. Overall, the results allay some concerns about the quality of some types of agricultural data collected through recall over lengthy periods.

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Paper provided by The World Bank in its series Policy Research Working Paper Series with number 5671.

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Date of creation: 01 Jun 2011
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Handle: RePEc:wbk:wbrwps:5671
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  1. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, June.
  2. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
  3. James P. Smith & Duncan Thomas, 2004. "Remembrances of Things Past: Test-Retest Reliability of Retrospective Migration Histories," Labor and Demography 0403026, EconWPA.
  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 341-59, September.
  5. 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).
  6. Davis, Benjamin & Winters, Paul & Carletto, Gero & Covarrubias, Katia & Quiñones, Esteban J. & Zezza, Alberto & Stamoulis, Kostas & Azzarri, Carlo & DiGiuseppe, Stefania, 2010. "A Cross-Country Comparison of Rural Income Generating Activities," World Development, Elsevier, vol. 38(1), pages 48-63, January.
  7. Fermont, Anneke & Benson, Todd, 2011. "Estimating yield of food crops grown by smallholder farmers: A review in the Uganda context," IFPRI discussion papers 1097, International Food Policy Research Institute (IFPRI).
  8. 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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