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The blog is an extract from a Global Poverty Monitoring Technical Note, which can be found here.
Most countries rely on data collected from household surveys to measure poverty. In household surveys, a representative sample of households of a country are asked a range of questions covering different topics. In low- and middle-income countries, where the value of consumption or consumption expenditure is typically used to inform households’ poverty status, many questions relate to the consumption and spending of households.
The questionnaire design of household surveys greatly influences the data collected. Numerous studies have shown that the design of household surveys impacts measured consumption. For example, when measuring food consumption, it matters whether households are asked to keep a diary of their consumption or to recall their consumption. In the latter case, it is of consequence whether they are asked to recall their consumption over the past seven days or 30 days.
For both food and non-food consumption, it matters how disaggregated the categories are. Also of importance are whether the questionnaire allows for the computation of the value of goods that deliver services repeatedly through an extended period over time, such as cars and household appliances (known as durables); and whether the spending on housing is included for renters and can be imputed for homeowners (known as imputed rent).
Innovations in household surveys often mean that more consumption is captured due to previously overlooked food consumption, as well as the inclusion of durables and/or imputed rent. We have identified 12 countries with large improvements in the quality of their household surveys. On average across these 12 countries, mean consumption increased by 46 percent after adjusting for inflation from the older survey to the newer survey (Figure 1), much of which is due to improved collection of consumption data.
When countries implement new surveys, they often revise their national poverty line upwards. Typically, national poverty lines in low- and middle-income countries are based on the cost of obtaining a set amount of calories per day — for example, 2200 calories per day — plus the non-food consumption of households close to this threshold. For the national poverty line to reflect the newly measured consumption, the line is often revised when the survey design changes.
While the effect of adding more food items and/or changing the recall period on the national poverty line is ambiguous, adding non-food items mechanically increases the national poverty line. We have data on national poverty lines in ten of the 12 countries, lacking data for Mongolia and Senegal. Across the ten countries, the national poverty line increased by an average of 50 percent following the implementation of improved household surveys (Figure 2).
The higher national poverty line often offsets the increased measured consumption, leading to minimal impact on national poverty rates. Consequently, even with more accurate and increased consumption data, the proportion of people considered poor according to the new national poverty line may not decrease. In fact, across the 10 countries studied, the new surveys did not lead to a systematic change in national poverty rates (Figure 3), despite the large increase in recorded consumption.
This is not the case when using the international poverty line (IPL), currently set at US$2.15 per day in 2017 purchasing power parity (PPP) adjusted prices. The IPL is fixed at a given point in time; thus, when new surveys reveal large increases to measured consumption, international poverty rates often drop drastically. Th IPL is applied consistently across countries and over time, even if new household surveys report higher consumption. Across the 12 countries, there are cases where the international poverty rate of the old survey is more than twice that of the new survey. In Guinea-Bissau, the rate decreased from 67 to 22 percent with the newer survey (Figure 3).
When countries implement improved household surveys, international poverty rate comparisons over time should be done with caution as they often overstate declines in poverty. Countries should generally use national poverty lines to look at poverty trends, and this becomes more pertinent when they make drastic changes to their surveys.
When deciding whether to adopt an improved household survey, countries face a trade-off between accuracy, i.e. using the best methods to measure consumption, and temporal comparability. New surveys are needed to improve accuracy, however changes to survey design should be avoided if the gains in accuracy are outweighed by the lack of ability to create a comparable time trend.
This trade-off can be weakened by ex-ante thinking. If the design of a forthcoming survey will change, countries can ensure a smaller sample follows the old questionnaire. Alternatively, countries can use imputation models to predict poverty in one of the two surveys by relying on indicators that are comparable in both surveys. They can then use this model to predict poverty in the other survey. Both options will allow for a comparable trend to be constructed.
The authors gratefully acknowledge financial support from the UK Government through the Data and Evidence for Tackling Extreme Poverty (DEEP) Research Program and are thankful for comments from Barbara Balaj, Carolina Diaz-Bonilla, Christoph Lakner, Francis Mulangu, Maria Eugenia Genoni, Paul Anthony Clare, Rose Mungai, and Salman Zaidi.
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