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Measurement errors in recall food consumption data

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Author Info

  • Naeem Ahmed
  • Matthew Brzozowski
  • Thomas Crossley

    ()
    (Institute for Fiscal Studies and University of Cambridge)

Abstract

Recall food consumption data, which is the basis of a great deal of empirical work, is believed to suffer from considerable measurement error. Diary records are believed to be very accurate. We study a unique data set that collects recall and diary data from the same households. Measurement errors in recall food consumption data appear to be substantial, and they do not have the properties of classical measurement error. We also find evidence that the diary measures are themselves imperfect. We consider the implications of our findings for modelling demand, measuring inequality, and estimating inter-temporal preference parameters. Keywords: expenditure, consumption, measurement error, survey data

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Bibliographic Info

Paper provided by Institute for Fiscal Studies in its series IFS Working Papers with number W06/21.

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Length: 41 pp.
Date of creation: Oct 2006
Date of revision:
Handle: RePEc:ifs:ifsewp:06/21

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  1. Angus Deaton & Christina Paxson, 1998. "Economies of Scale, Household Size, and the Demand for Food," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 897-930, October.
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  7. Sule Alan & Orazio Attanasio & Martin Browning, 2009. "Estimating Euler equations with noisy data: two exact GMM estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 309-324, 03.
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  9. 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.
  10. Orazio Attanasio & Erich Battistin & Hidehiko Ichimura, 2004. "What Really Happened to Consumption Inequality in the US?," NBER Working Papers 10338, National Bureau of Economic Research, Inc.
  11. 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.
  12. Dirk Krueger & Fabrizio Perri, 2006. "Does Income Inequality Lead to Consumption Inequality? Evidence and Theory -super-1," Review of Economic Studies, Oxford University Press, vol. 73(1), pages 163-193.
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Citations

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Cited by:
  1. Campos, Rodolfo G. & Reggio, Iliana, 2014. "Measurement error in imputation procedures," Economics Letters, Elsevier, vol. 122(2), pages 197-202.
  2. John Gibson & Kathleen Beegle & Joachim De Weerdt & Jed Friedman, 2013. "What Does Variation in Survey Design Reveal About the Nature of Measurement Errors in Household Consumption?," Working Papers in Economics 13/01, University of Waikato, Department of Economics.
  3. Beegle, Kathleen & De Weerdt, Joachim & Friedman, Jed & Gibson, John, 2010. "Methods of household consumption measurement through surveys : experimental results from Tanzania," Policy Research Working Paper Series 5501, The World Bank.
  4. Timothy K.M. Beatty, 2007. "Expenditure Dispersion and Dietary Quality: Evidence from Canada," Health, Econometrics and Data Group (HEDG) Working Papers 07/13, HEDG, c/o Department of Economics, University of York.
  5. Derek Yu, 2008. "The comparability of Income and Expenditure Surveys 1995, 2000 and 2005/2006," Working Papers 11/2008, Stellenbosch University, Department of Economics.
  6. Thomas F. Crossley & Joachim K. Winter, 2012. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures National Bureau of Economic Research, Inc.
  7. Derek Yu, 2013. "Some factors influencing the comparability and reliability of poverty estimates across household surveys," Working Papers 03/2013, Stellenbosch University, Department of Economics.
  8. Deininger, Klaus & Carletto, Calogero & Savastano, Sara & Muwonge, James, 2012. "Can diaries help in improving agricultural production statistics? Evidence from Uganda," Journal of Development Economics, Elsevier, vol. 98(1), pages 42-50.
  9. Andrew Leicester, 2012. "How might in-home scanner technology be used in budget surveys?," IFS Working Papers W12/01, Institute for Fiscal Studies.
  10. Alice sanwald & Engelbert Theurl, 2014. "What drives out-of pocket health expenditures of private households? - Empirical evidence from the Austrian household budget survey," Working Papers 2014-04, Faculty of Economics and Statistics, University of Innsbruck.
  11. Vassilopoulos, Achilleas & Klonaris, Stathis & Drichoutis, Andreas C. & Lazaridis, Panagiotis, 2012. "Modeling quality demand with data from Household Budget Surveys: An application to meat and fish products in Greece," Economic Modelling, Elsevier, vol. 29(6), pages 2744-2750.
  12. Rodolfo G. Campos & Ilina Reggio, 2012. "Measurement error and imputation of consumption in survey data," Economics Working Papers we1219, Universidad Carlos III, Departamento de Economía.
  13. Adam Bee & Bruce D. Meyer & James X. Sullivan, 2013. "The Validity of Consumption Data: Are the Consumer Expenditure Interview and Diary Surveys Informative?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures National Bureau of Economic Research, Inc.
  14. Deininger, Klaus & Carletto, Calogero & Savastano, Sara & Muwonge, James, 2011. "Can diaries help improve agricultural production statistics ? Evidence from Uganda," Policy Research Working Paper Series 5717, The World Bank.
  15. Martin Browning & Thomas Crossley, 2009. "Are Two Cheap, Noisy Measures Better Than One Expensive, Accurate One?," American Economic Review, American Economic Association, vol. 99(2), pages 99-103, May.
  16. Broer, Tobias, 2011. "The wrong shape of insurance? What cross-sectional distributions tell us about models of consumption-smoothing," CEPR Discussion Papers 8701, C.E.P.R. Discussion Papers.

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