Quality of Expenditure Data Collected With a Mobile Receipt Scanning App in a Probability Household Panel

Abstract

This paper reports on a novel approach using smartphone technology to collect expenditure data in a probability household panel of the general population in Great Britain. Respondents were asked to download an app on their smartphone and report their purchases of goods and services over the period of one month. The app directed respondents to use the built-in camera to photograph all paper receipts that they received at a point of sale. In a separate diary section of the app, they were able to manually enter other expenditures, such as non-receipted payments. In this paper, we compare the quality of the reported expenditure with benchmark data from the Living Costs and Food Survey, the national budget survey in the United Kingdom. The results suggest that total expenditure reported with scanned receipts plus direct entry aligns closely with the national budget survey whereas app data from scanned receipts only clearly underestimate expenditure. Examining category-level expenditure similarly shows that for most categories, the reported expenditure from scanned receipts plus direct entry aligns more closely with the benchmark than scanned receipts only. In addition, the app data align more closely with the national budget survey for respondents who are older, male, have an above-median income, and live in rural areas. The implications of measurement differences vary: comparisons of estimated budget shares are closer to the benchmark for some categories than others.