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An Analysis of the Impact of Various Sampling Designs on the Headcount Index: A Simulation Study Based on the EU-SILC
[journal article]
Abstract The analysis and the comparison of poverty between regions and countries are important topics in social sciences, which have relevant demands of many national (Cáritas, Intermón Oxfam, Cruz Roja, etc) and international (UN, World Bank, OECD, Eurostat, IMF, etc) agencies and organizations. One of the... view more
The analysis and the comparison of poverty between regions and countries are important topics in social sciences, which have relevant demands of many national (Cáritas, Intermón Oxfam, Cruz Roja, etc) and international (UN, World Bank, OECD, Eurostat, IMF, etc) agencies and organizations. One of the most common poverty indicators in practice is the headcount index, which analyzes the proportion of individuals considered as poor in a population. In this paper, we first analyze the impact on the headcount index when different sampling designs are considered. Note that this study is based on real data sets taken from different countries of the European Union, and the empirical measures for comparisons are based on different Monte Carlo simulation studies. For instance, we observe that stratified sampling has the best performance in comparison to alternative sampling designs. Post-stratification performs similar to simple random sampling without replacement, and the use of auxiliary information provides similar results to ones derived from stratified sampling. Second, we also analyze the empirical performance of different variance estimators under the commented sampling designs. We conclude that they have a similar empirical performance, and they provide, in general, confidence intervals with desirable coverage rates.... view less
Keywords
poverty; sample; simulation
Classification
Research Design
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Social Problems
Free Keywords
EU-SILC 2011; poverty line; proportion; random sample; Monte Carlo simulation; confidence interval; headcount index
Document language
English
Publication Year
2020
Page/Pages
p. 914-922
Journal
The Journal of Social Sciences Research, 6 (2020) 10
DOI
https://doi.org/10.32861/jssr.610.914.922
ISSN
2411-9458
Status
Published Version; peer reviewed