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Improving consumption measurement and other survey data through CAPI: Evidence from a randomized experiment

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  • Caeyers, Bet
  • Chalmers, Neil
  • De Weerdt, Joachim

Abstract

This paper reports on a randomized survey experiment among 1840 households, designed to compare pen-and-paper interviewing (PAPI) to computer-assisted personal interviewing (CAPI). We find that PAPI data contain a large number of errors, which can be avoided in CAPI. Error counts are not randomly distributed across the sample, but are correlated with household characteristics, potentially introducing sample bias if dubious observations need to be dropped. We demonstrate a tendency for the spread of total measured consumption to be higher on paper compared to CAPI, translating into significantly higher measured inequality. Investigating further the nature of PAPI's measurement error for consumption, we fail to reject the hypothesis that it is classical: it attenuates the coefficient on consumption when used as explanatory variable and we find no evidence of bias when consumption is used as dependent variable. Finally, CAPI and PAPI are compared in terms of interview length, costs and respondents' perceptions.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Development Economics.

Volume (Year): 98 (2012)
Issue (Month): 1 ()
Pages: 19-33

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Handle: RePEc:eee:deveco:v:98:y:2012:i:1:p:19-33

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Web page: http://www.elsevier.com/locate/devec

Related research

Keywords: CAPI; Household surveys; Consumption measurement; Measurement error;

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References

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  1. Bart Capéau & Stefan Dercon, 1998. "Prices, Unit Values and Local Measurement Units in Rural Surveys: an Econometric Approach with an Application to Poverty Measurement in Ethiopia," Center for Economic Studies - Discussion papers ces9818, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
  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. Fafchamps, Marcel & McKenzie, David & Quinn, Simon & Woodruff, Christopher, 2012. "Using PDA consistency checks to increase the precision of profits and sales measurement in panels," Journal of Development Economics, Elsevier, vol. 98(1), pages 51-57.
  4. John Bound & Alan B. Krueger, 1989. "The Extent of Measurement Error In Longitudinal Earnings Data: Do Two Wrongs Make A Right?," NBER Working Papers 2885, National Bureau of Economic Research, Inc.
  5. Chesher, Andrew & Schluter, Christian, 2002. "Welfare Measurement and Measurement Error," Review of Economic Studies, Wiley Blackwell, vol. 69(2), pages 357-78, April.
  6. de Leeuw and Nicholls, 1996. "Technological Innovations in Data Collection: Acceptance, Data Quality and Costs," Sociological Research Online, Sociological Research Online, vol. 1(4), pages leeuw.
  7. 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.
  8. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
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Citations

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Cited by:
  1. Marcus Böhme, Tobias Stoehr, 2012. "Guidelines for the Use of Household Interview Duration Analysis in CAPI Survey Management," Kiel Working Papers 1779, Kiel Institute for the World Economy.
  2. De Weerdt, Joachim & Beegle, Kathleen & Friedman,, Jed & Gibson, John, 2014. "The challenge of measuring hunger," Policy Research Working Paper Series 6736, The World Bank.

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