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1. An Agricultural Wealth Index for Multidimensional Wealth Assessments

   https://doi.org/10.31235/osf.io/gqxby  

   Hackman, JV; Hruschka, DJ; Vizireanu, M (March 2020, OpenScience)

   Social scientists have increasingly used asset-based wealth scores, like the 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 market-based 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. 

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2. An Agricultural Wealth Index for Multidimensional Wealth Assessments

   https://doi.org/10.1111/padr.12367  

   Hackman, Joseph; Hruschka, Daniel; Vizireanu, Mariya (October 2020, Population and Development Review)

   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 market‐based 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. 

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3. Intergenerational Wealth Mobility and Racial Inequality

   https://doi.org/10.1177/2378023119831799  

   Pfeffer, Fabian T.; Killewald, Alexandra (January 2019, Socius: Sociological Research for a Dynamic World)

   The black-white gap in household wealth is large and well documented. Here, we visualize how this racial wealth gap persists across generations. Animating the flow of individuals between the relative wealth position of parents and their adult children, we show that the disadvantage of black families is a consequence both of wealth inequality in prior generations and race differences in the transmission of wealth positions across generations: Black children both have less wealthy parents on average and are far more likely to be downwardly mobile in household wealth. By displaying intergenerational movements between parental and offspring wealth quintiles, we underline how intergenerational fluctuation coexists with the maintenance of a severely racialized wealth structure. 

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4. Wealth Dynamics Over Generations: Analysis and Interventions

   https://doi.org/10.1109/SaTML54575.2023.00013  

   Acharya, Krishna; Arunachaleswaran, Eshwar Ram; Kannan, Sampath; Roth, Aaron; Ziani, Juba (February 2023, IEEE Conference on Secure and Trustworthy Machine Learning (SaTML))

   We present a stylized model with feedback loops for the evolution of a population's wealth over generations. Individuals have both talent and wealth: talent is a random variable distributed identically for everyone, but wealth is a random variable that is dependent on the population one is born into. Individuals then apply to a downstream agent, which we treat as a university throughout the paper (but could also represent an employer) who makes a decision about whether to admit them or not. The university does not directly observe talent or wealth, but rather a signal (representing e.g. a standardized test) that is a convex combination of both. The university knows the distributions from which an individual's type and wealth are drawn, and makes its decisions based on the posterior distribution of the applicant's characteristics conditional on their population and signal. Each population's wealth distribution at the next round then depends on the fraction of that population that was admitted by the university at the previous round. We study wealth dynamics in this model, and give conditions under which the dynamics have a single attracting fixed point (which implies population wealth inequality is transitory), and conditions under which it can have multiple attracting fixed points (which implies that population wealth inequality can be persistent). In the case in which there are multiple attracting fixed points, we study interventions aimed at eliminating or mitigating inequality, including increasing the capacity of the university to admit more people, aligning the signal generated by individuals with the preferences of the university, and making direct monetary transfers to the less wealthy population. 

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5. Should We Tax Capital Income or Wealth?

   https://doi.org/10.1257/aeri.20220192  

   Boar, Corina; Midrigan, Virgiliu (June 2023, American Economic Review: Insights)

   We study optimal capital income and wealth taxation in an economy that reproduces the importance of private businesses for output and inequality. If entrepreneurs are subject to collateral constraints, they face heterogeneous rates of return, which generate a meaningful distinction between capital income and wealth taxation. We find that taxing capital income is preferable to taxing wealth because the efficiency gains from wealth taxation are swamped by the redistributional benefits of taxing the profits of richer entrepreneurs. Consequently, the gains from taxing wealth are modest. This conclusion is robust to the planner’s preference for redistribution and allowing for nonlinear taxes. (JEL D31, H21, H23, H24, H25, K34, L26) 

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