A Bayesian framework for estimating human capabilities

Heath Henderson and Lendie Follett

World Development, 2020, vol. 129, issue C

Abstract: The capabilities approach provides a rich framework for welfare assessment, but its practical relevance is limited by methodological difficulties associated with the measurement of human capabilities. We argue that, unlike existing approaches to capability estimation, Bayesian stochastic frontier analysis (BSFA) is consistent with the key features of the capabilities approach and thus provides a natural framework for estimating capabilities. Using simulated data, we show that BSFA outperforms the leading alternatives (e.g., structural equation models) in comparable settings. We further show that our approach is more flexible than the alternatives: BSFA can provide cardinal representations of entire capability sets and can be used with continuous, discrete, and multivariate outcomes. Finally, we provide an empirical illustration of our estimator by examining the impact of Uganda’s Youth Opportunities Program on the educational capabilities of children in the treated households.

Keywords: Bayesian inference; Capabilities approach; Human development; Stochastic frontier analysis; Welfare measurement (search for similar items in EconPapers)
JEL-codes: C11 D63 I32 O15 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:wdevel:v:129:y:2020:i:c:s0305750x19305212

DOI: 10.1016/j.worlddev.2019.104872

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