Methods of Household Consumption Measurement Through Surveys: Experimental Results from Tanzania

By Kathleen G. Beegle, J. Weerdt, Jed Friedman, John Gibson. 2010

360 citations recorded by the source corpus.

Consumption expenditure has long been the preferred measure of household living standards. However, accurate measurement is a challenge and household expenditure surveys vary widely across many dimensions, including the level of reporting, the length of the reference period, and the degree of commodity detail. These variations occur both across countries and also over time within countries. There is little current understanding of the implications of such changes for spatially and temporally consistent measurement of household consumption and poverty. A field experiment in Tanzania tests eight alternative methods to measure household consumption on a sample of 4,000 households. There are significant differences between consumption reported by the benchmark personal diary and other diary and recall formats. Under-reporting is particularly relevant in illiterate households and for urban respondents completing household diaries; recall modules measure lower consumption than a personal diary, with larger gaps among poorer households and households with more adult members. Variations in reporting accuracy by household characteristics are also discussed and differences in measured poverty as a result of survey design are explored. The study concludes with recommendations for methods of survey based consumption measurement in low-income countries.

Subfields: Gender Studies, Safety Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/a6c93b223f0741fc4816f1f7e011ff261604e16a

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In Gender Studies

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Citations in the corpus

Heterogeneity, Measurement Error, and Misallocation: Evidence from African Agriculture (2019, neutral): “In this sense, our results are not necessarily inconsistent with those of Adamopoulos and 4 See, e.g., Beegle et al. (2012), Deininger et al. (2012), and De Nicola and Giné (2014), although Beegle, Carletto, and Himelein (2012) offer a more positive view.”
Improving the Measurement of Food Security (2012, neutral): “Experimental research on survey design has demonstrated that the choice of survey instrument matters substantively to expenditure-based results (Beegle et al. 2012).”
Not Your Average Job: Measuring Farm Labor in Tanzania (2016, neutral): “…methods hamper comparisons over time and space if survey methods differ, as has been shown in the context of the measurement of welfare, poverty, and hunger (Backiny-Yetna, Steele, and Djima 2014; Beegle et al. 2012, 2016; De Weerdt et al. 2016) and labor measurement (Bardasi et al. 2011).”
The impact of household food consumption data collection methods on poverty and inequality measures in Niger (2014, neutral): “Each of these elements affect the distribution of the expenditure and the methodology chosen has an effect on the distribution of expenditure, and therefore on the poverty levels (Lanjouw and Lanjouw, 2001; Tarozzi, 2007; Beegle et al., 2010).”
Correlated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture (2019, background): “8 may cause them to forget details of past events (Beegle et al., 2012; Arthi et al., 2018) or season-specific harvests (Ali et al.”
Land productivity and plot size : is measurement error driving the inverse relationship ? (2017, neutral): “This paper adds another example to the literature demonstrating that not all measurement error is white noise (Aguiar and Bils, 2015; Beegle et al., 2012; Gibson and Kim, 2007).”
Universal Basic Income in the Developing World (2019, neutral): “On the pure measurement error and recall issues, as an example, Beegle et al. (2012) show that this error can be significant and worse for illiterate”