Poverty Measurement: We Know Less than Policy Makers Realize

Abstract

There is a widespread policy interest in poverty estimates at both national and global level. There has been an explosion of poverty measurement in the last two decades enabled by the growing availability of household survey data. These measurements are used by policymakers to assess progress towards national and global goals for inclusive growth and poverty reduction. But the evidence base rests on shaky foundations, and policy-makers may have undue confidence in poverty and inequality estimates. Many household surveys are poorly designed to measure monetary living standards and poverty in an era of rising affluence and urban transition. Some key problems in measuring food consumption, housing services and the cost of living are discussed here. Alternatives to monetary measurement, such as using questions on life satisfaction and happiness, also rest on shaky foundations.

Are You Estimating the Right Thing? An Editor Reflects

“…Consequently, unit values cannot be a consistent indicator of the group price level over time and space. Evidence for these effects, and the distortion caused when unit values are wrongly used as a proxy for prices, is reported by Gibson and Kim (2015) and Gibson (2016).…”

Multidimensional Poverty Analysis of Urban and Rural Households in South Africa

“…Similarly, the use of non-monetary one-dimensional approach of subjective measure has also been argued against in literature. Gibson (2016) argued that welfare economics does not provide a justification for maximizing either happiness or life satisfaction, because neither corresponds to utility. Accordingly, Jansen et al (2015) argued that subjective indicators might be less expedient for practical policy and targeting purposes as people may project themselves as poor only because they are not satisfied with their lives, which is challenging for instance, when targeting the public for welfare programmes.…”

Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments

“…While we should be mindful of the various assumptions underlying imputation 35 There appears no consensus yet even on the use of subjective well-being data. While some researchers (see, for example, Bond and Lang (2014) and Gibson (2016)) remain skeptical, others are more optimistic (see, for example, Allin and Hand (2017) and Helliwell, Layard, and Sachs (2017)). 36 Kilic et al (2017) estimate the average cost of implementing a recent household consumption survey (in 2014 or later) to range from approximately US$800,000 to US$5 million, depending on the context and sample sizes.…”