Conference Paper
Micro-Level Estimation of Poverty in Iran: Evidence from 2016 Census Data
No.
ERF32AC_103
Publisher
ERF
Date
May, 2026
Topic
I3. Welfare, Well-Being, and Poverty
O1. Economic Development
Effective poverty alleviation requires identifying deprived populations at a geographic scale that is small enough for targeted interventions but still statistically reliable. This paper produces county-level poverty estimates for Iran by combining the 2016 Household Expenditure and Income Survey (HEIS) with a 2% random sample of the 2016 General Population and Housing Census. We implement a unit-level small-area estimation approach following Elbers, Lanjouw, and Lanjouw (2003), enriched with k-means clustering of counties and LASSO-based variable selection, to generate headcount poverty rates and poverty maps for 429 counties. County-level headcount ratios range from about 7 to 83 percent, while provincial poverty varies between roughly 10 and 39 percent, with Sistan & Baluchestan, Qom, and Kermanshah at the top and Semnan and Mazandaran at the bottom. High-poverty counties are concentrated in Sistan & Baluchestan but also appear in provinces with relatively low average poverty—for example, Miami in Semnan—indicating substantial within-province heterogeneity. Standard errors of county estimates fall mostly between 0.03 and 0.13, and comparison with existing estimates based on survey data alone shows close agreement in levels and rankings. The resulting poverty maps highlight that relying on provincial averages can seriously misguide targeting, and they provide a practical tool for prioritizing socioeconomic, health, and education programs at both national and regional levels.
Authors
Sadegh Hossein Zadeh
University of Tehran
Authors
Atiyeh Vahidmanesh
Assistant Professor of Economics, University of Tehran