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How might in-home scanner technology be used in budget surveys?


  • Andrew Leicester

    () (Institute for Fiscal Studies)


This paper considers what role in-home barcode scanner data could play in collecting household expenditure information as part of national budget surveys. One role is as a source of validation. We make detailed micro-level comparisons of food and drink expenditures in two British datasets: the Living Costs and Food Survey (the main budget survey) and Kantar Worldpanel scanner data. We find that levels of spending are significantly lower in scanner data. A large part (but not all) of the gap is explained by weeks in which no spending at all is recorded in scanner data. Demographic differences between the surveys accentuate rather than close the gap. We also demonstrate that patterns of expenditure across the surveys are much more similar, as are Engel curves relating food commodity budget shares to total food expenditures. A key finding is that the period over which we observe households in the scanner data significantly alters the distribution, but not the average, of weekly food expenditures and budget shares, which has important implications for whether two-week spending diaries common to budget surveys are giving a truly accurate reflection of a household's typical spending patterns. A second, more involved use of scanner data would be to impute detailed commodity-level expenditure patterns given only information on total expenditures, as a way of reducing respondent burden in budget surveys. We find that observable demographics in the scanner data explain little of the variation in store-specific expenditure patterns, and so caution against relying too heavily on imputation.

Suggested Citation

  • Andrew Leicester, 2012. "How might in-home scanner technology be used in budget surveys?," IFS Working Papers W12/01, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:12/01

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    References listed on IDEAS

    1. Matthew Harding & Ephraim Leibtag & Michael F. Lovenheim, 2012. "The Heterogeneous Geographic and Socioeconomic Incidence of Cigarette Taxes: Evidence from Nielsen Homescan Data," American Economic Journal: Economic Policy, American Economic Association, vol. 4(4), pages 169-198, November.
    2. Jayson L. Lusk & Kathleen Brooks, 2010. "Who Participates in Household Scanning Panels?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 226-240.
    3. Andrew Leicester & Zoë Oldfield, 2009. "Using Scanner Technology to Collect Expenditure Data," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 309-337, December.
    4. repec:oup:revage:v:31:y:2009:i:3:p:470-492. is not listed on IDEAS
    5. Chen Zhen & Justin L. Taylor & Mary K. Muth & Ephraim Leibtag, 2009. "Understanding Differences in Self-Reported Expenditures between Household Scanner Data and Diary Survey Data: A Comparison of Homescan and Consumer Expenditure Survey," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 470-492.
    6. 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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    Cited by:

    1. Brewer, Mike & O'Dea, Cormac, 2012. "Measuring living standards with income and consumption: evidence from the UK," ISER Working Paper Series 2012-05, Institute for Social and Economic Research.
    2. Mike Brewer & Cormac O'Dea, 2012. "Measuring living standards with income and consumption: evidence from the UK," IFS Working Papers W12/12, Institute for Fiscal Studies.

    More about this item


    Scanner data; expenditure; inflation; food; measurement.;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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