Measuring poverty with administrative data in data deprived contexts: The case of Nicaragua

Jose Cuesta and Cristian Chagalj ()

Economics Letters, 2019, vol. 183, issue C, -

Abstract: Microsimulations are routinely used to estimate poverty in contexts of data deprivation. This paper explores how microsimulations can be enhanced by adding widely available macroeconomic and administrative data. In concrete terms, we analyze the effects of including unemployment rates and affiliation to social security in microsimulations of poverty headcounts in Nicaragua. The recent political crisis in this Central American country has interrupted data collection efforts, making it impossible to monitor poverty or quantify the effect of the crisis. We consider several methods, including incorporating unemployment in our simulations; using alternative poverty lines; and comparing with a counterfactual of no crisis. Including readily available administrative data may have significant effects on the estimated poverty headcount, with this effect yielding between 0.1 and 4.6 percentage points in difference in Nicaragua. More generally, while worthwhile efforts to utilize machine learning and cross-survey imputation to estimate poverty in data deprived contexts continue, inexpensive and comparatively straightforward microsimulations can still provide substantive insights on poverty dynamics.

Keywords: Microsimulations; Poverty; Administrative data; Nicaragua (search for similar items in EconPapers)
JEL-codes: C53 I32 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176519302824
Full text for ScienceDirect subscribers only

Related works:
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:ecolet:v:183:y:2019:i:c:2

DOI: 10.1016/j.econlet.2019.108573

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().