Developing a Wealth Index for the World's Largest Population Census Database

Rodrigo Lovaton Davila, University of Minnesota
Phatta Kirdruang, University of Minnesota
Dorothy Gondwe, University of Minnesota
Aine Seitz McCarthy, University of Minnesota
Uttam Sharma, University of Minnesota

This research aims to develop a reliable and robust measure for socioeconomic status at the household level using census data available from the Integrated Public Use Microdata Series- International (IPUMS-I), the world's largest census database. First, we use principal component analysis to compute a wealth index based on housing characteristics and asset ownership, with separate measures for rural and urban areas. The validation strategies include comparing our proposed index with the widely used Demographic and Health Survey (DHS) wealth indices and then verifying the predictive power of our index on selected outcomes. Moreover, we attempt to identify general conditions necessary to produce a robust asset index based on census data. Preliminary results based on the wealth indices from four separate samples reveal estimates comparable to the DHS indices. Conditioned on the reliability of the results, this measure will be included in the IPUMS-I database for further research.