Measuring vulnerability to multidimensional poverty with Bayesian network classifiers

Mauricio Gallardo

Economic Analysis and Policy, 2022, vol. 73, issue C, 492-512

Abstract: Bayesian network methods have recently gained great popularity in machine learning literature and applications to model uncertainty in complex phenomena that include relationships between multiple random variables. However, these models are not commonly applied in economics and development studies. Here, we introduce the Bayesian network classifier models to estimate the probability of a person to be welfare deprived in one and multiple dimensions. These probabilities are then used for measuring vulnerability to multidimensional poverty (VMP) in four alternative measurement frameworks. Currently, two of them can be found in the literature, but have been estimated with Probit and Logit models, which are unidimensional strategies. Instead of that, in this study, we follow a multidimensional strategy to solve an estimation problem that is multidimensional in nature. Two new VMP measurement procedures based on Bayesian network classifiers estimates are also introduced in this article. We illustrate the four estimation procedures using the household survey and the census data from Chile 2017. A 5-fold cross-validation exercise verifies a high predictive performance of these Bayesian network classifier models, with the highest accuracy being that of one of the new measurements that we put forward. Our findings reveal that the Bayesian network classifier models offer an adequate alternative to face the policy challenge of measuring vulnerability to multidimensional poverty.

Keywords: Poverty; Vulnerability; Bayesian networks; Bayesian classifiers; Latin America; Chile; Downside risk; Social risk (search for similar items in EconPapers)
JEL-codes: D81 I31 I32 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0313592621001685
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Measuring vulnerability to multidimensional poverty with Bayesian network classifiers (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:73:y:2022:i:c:p:492-512

DOI: 10.1016/j.eap.2021.11.018

Access Statistics for this article

Economic Analysis and Policy is currently edited by Clevo Wilson

More articles in Economic Analysis and Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().