An Agricultural Wealth Index for Multidimensional Wealth Assessments

Abstract

Social scientists have increasingly used asset-based wealth scores, like the Demographic and Health Survey (DHS) wealth index, to assess economic disparities. However, current indices primarily capture wealth in globalized market economies, thus ignoring other forms of prosperity, such as success in agricultural activities. Using a simple extension to the standard estimation of the DHS wealth index, we describe procedures for estimating an agricultural wealth index (AWI) that complements marketbased wealth indices by capturing household success in agricultural activities. We apply this procedure to household data from 129 DHS surveys from over 40 countries with sufficient land and livestock data to estimate a reliable and consistent AWI. We assess the construct validity of the AWI using benchmarks of growth in both adults and children. This alternative measure of wealth provides new opportunities for understanding the causes and consequences of wealth inequality, and how success along different dimensions of wealth creates different social opportunities and constraints for health and well-being.

Disentangling wealth effects on fertility in 64 low- and middle-income countries

“…Alternatively, future research could use a subset of the underlying asset variables to create the latent variables, rather than the dimension scores produced from the MCA. However, the creation of the MCA dimensions and the process of anchoring the dimensions facilitate a clear interpretation (Hackman et al, 2020;Hruschka et al, 2017). Estimating the latent variables using the raw assets would require an independent method of validating the interpretation of the latent variables.…”

“…TVs, cars) and agricultural wealth (e.g. land and livestock) (Garenne, 2015;Hackman, Hruschka, & Vizireanu, 2020;Hruschka et al, 2017). Using both measures of wealth in a latent variable structural equation model, we estimate how agricultural and market-based wealth reflect economic capacity, and how education and market wealth reflect market opportunities.…”

“…Most DHS surveys contain detailed information on reproduction for women aged 15-49 as well as household economic status. We use available data from 64 countries with reliable estimates of market and agricultural dimensions of wealth (Hackman et al, 2020) and data on completed fertility for women aged 40-50 (562,324 women, across 111,724 sampling clusters; Figure S1 and Table S1 in the Supporting Information). The surveys reflect populations in Europe and Central Asia (n = 11), South Asia and Oceania (n = 10), sub-Saharan Africa (n = 92), the Middle East and North Africa (n = 5), Southeast Asia (n = 16) and Latin America and the Caribbean (n = 17).…”

“…We follow the procedure outlined in prior publications to estimate orthogonal measures of marketbased and agricultural wealth using multiple correspondence analysis (MCA) (Hackman et al, 2020;Hruschka et al, 2017). Household-level wealth dimensions were computed for each survey independently, as the MCA provides estimates of relative ranking of households based on similar asset ownerships within the population, but is not strictly comparable across surveys.…”

“…livestock, and land) and market-oriented goods (e.g. TVs, cars) (Hackman et al, 2020). These dimensions are scaled to have a mean standard deviation (SD) of 1 within surveys.…”