A Bayesian framework for estimating human capabilities
Heath Henderson and
World Development, 2020, vol. 129, issue C
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)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:wdevel:v:129:y:2020:i:c:s0305750x19305212
Access Statistics for this article
World Development is currently edited by O. T. Coomes
More articles in World Development from Elsevier
Bibliographic data for series maintained by Nithya Sathishkumar ().