Estimating Utility-Consistent Poverty Lines

Arndt, Channing; Simler, Kenneth

doi:10.2139/ssrn.1288817

Cited by 11 publications

(14 citation statements)

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“…It should be noted that these poverty lines, and the poverty measures presented in Tables 3 and 4, differ from the official poverty lines reported elsewhere (MPF, 2004; Arndt and Simler, 2005). The official poverty lines include a relatively novel entropy estimation adjustment to ensure that the basic needs food bundles satisfy revealed preference conditions across regions and over time.…”

contrasting

confidence: 77%

“…Recent poverty studies that use region‐specific poverty bundles and prices include Tarp et al. (2002), Mukherjee and Benson (2003), Gibson and Rozelle (2003), Ravallion and Lokshin (2006), Datt and Jolliffe (2005), and Arndt and Simler (2005). Note that the same arguments in favor of allowing the bundle to vary over space can also be applied to comparisons over time.…”

Section: Methodsmentioning

confidence: 99%

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Poverty Comparisons With Absolute Poverty Lines Estimated From Survey Data

Simler

Arndt

2007

Review of Income and Wealth

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The objective of measuring poverty is usually to make comparisons over time or between two or more groups. Common statistical inference methods are used to determine whether an apparent difference in measured poverty is statistically significant. Studies of relative poverty have long recognized that when the poverty line is calculated from sample survey data, both the variance of the poverty line and the variance of the welfare metric contribute to the variance of the poverty estimate. In contrast, studies using absolute poverty lines have ignored the poverty line variance, even when the poverty lines are estimated from sample survey data. Including the poverty line variance could either reduce or increase the precision of poverty estimates, depending on the specific characteristics of the data. This paper presents a general procedure for estimating the standard error of poverty measures when the poverty line is estimated from survey data. Based on bootstrap methods, the approach can be used for a wide range of poverty measures and methods for estimating poverty lines. The method is applied to recent household survey data from Mozambique. When the sampling variance of the poverty line is taken into account, the estimated standard errors of Foster-Greer-Thorbecke and Watts poverty measures increase by 15-30 percent at the national level, with considerable variability at lower levels of aggregation. Copyright 2007 The Authors; Journal compilation International Association for Research in Income and Wealth 2007.

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confidence: 77%

Section: Methodsmentioning

confidence: 99%

Poverty Comparisons With Absolute Poverty Lines Estimated From Survey Data

Simler

Arndt

2007

Review of Income and Wealth

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“…The obvious solution to dealing with the shortcomings of a single bundle is to develop multiple bundles, each associated with a different time period (or region), to account for the shifts in consumption patterns brought about by the differences in relative prices through time (or across space). Multiple bundles have been used by, for example, Datt et al (2001), Gibson and Rozelle (2003), Ravallion and Lokshin (2006), Tarp et al (2002), and Arndt and Simler (2005). Though conceptually straightforward, the practical difficulties associated with choosing multiple bundles that yield the same (or nearly the same) level of well‐being are considerable.…”

Section: Meeting Two Methodological Challengesmentioning

confidence: 99%

“…The focus in this section is on the intuition behind the need for methodological improvement and the logic of the proposed changes. Separate papers describe the application of each new method in detail (Arndt and Simler, 2005; Simler and Arndt, 2007).…”

Section: Introductionmentioning

confidence: 99%

Consistent poverty comparisons and inference

Arndt¹,

Simler

2007

Agricultural Economics

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Building upon the cost of basic needs (CBN) approach, an integrated approach to making consumption-based poverty comparisons is presented. This approach contains two principal modifications to the standard CBN approach. The first permits the development of multiple poverty bundles that are utility consistent. The second recognizes that the poverty line itself is a random variable whose variation influences the degree of confidence in poverty measures. We illustrate the empirical importance of these two methodological changes for the case of Mozambique. With utility consistency imposed, estimated poverty rates tend to be systematically higher in rural areas and lower in urban areas. We also find that the true confidence intervals on the poverty estimates-those incorporating poverty line variance-tend to be considerably larger than those that ignore poverty line variance. Finally, we show that these two methodological changes interact. Specifically, we find that imposing utility consistency on poverty bundles tends to tighten confidence intervals, sometimes dramatically, on provincial poverty estimates. We conclude that this revised approach represents an important advance in poverty analysis. The revised approach is straightforward and directly applicable in empirical work. Copyright 2007 International Association of Agricultural Economists.

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“…Additionally, since Mozambican household budget survey data includes information on local prices, region-specific price indexes can be calculated. This is pertinent because prices differ significantly across space (Arndt and Simler, 2010). Consequently, our chosen welfare outcome (denoted c) is the natural logarithm of per capita household consumption deflated by the region-specific poverty line (multiplied by 100).…”

Section: Empirical Approachmentioning

confidence: 99%

Priorities for Boosting Employment in Sub‐Saharan Africa: Evidence for Mozambique

Jones¹,

Tarp²

2015

African Development Review

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Should policy-makers, including foreign donors, focus employment strategies in sub-Saharan Africa on strengthening access to formal wage employment or on raising productivity in the informal sector? We examine the evidence in Mozambique and show that crude distinctions between formality and informality are not illuminating. The observed welfare advantage of formal sector workers essentially derives from differences in endowments and local conditions. Non-agricultural informal work can yield higher returns than formal work. The implication is that the informal sector must not be marginalized; and raising productivity in agriculture must be accorded a central place in boosting employment.

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Estimating Utility-Consistent Poverty Lines

Abstract: IFPRI's Discussion Papers contain preliminary material and research results. They have not been subject to formal review by IFPRI's Publications Review Committee. They are circulated in order to stimulate discussion and critical comment.

Cited by 11 publications

References 11 publications

Poverty Comparisons With Absolute Poverty Lines Estimated From Survey Data

Poverty Comparisons With Absolute Poverty Lines Estimated From Survey Data

Consistent poverty comparisons and inference

Priorities for Boosting Employment in Sub‐Saharan Africa: Evidence for Mozambique

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