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1. 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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2. 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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3. Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty

   https://doi.org/http://dx.doi.org/10.18653/v1/2020.nlpcss-1.13  

   Keith, Katherine; Teichmann, Christoph; O'Connor, Brendan; Meij, Edgar (January 2020, Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science)

   null (Ed.)

   Methods and applications are inextricably linked in science, and in particular in the domain of text-as-data. In this paper, we examine one such text-as-data application, an established economic index that measures economic policy uncertainty from keyword occurrences in news. This index, which is shown to correlate with firm investment, employment, and excess market returns, has had substantive impact in both the private sector and academia. Yet, as we revisit and extend the original authors’ annotations and text measurements we find interesting text-as-data methodological research questions: (1) Are annotator disagreements a reflection of ambiguity in language? (2) Do alternative text measurements correlate with one another and with measures of external predictive validity? We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index. 

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4. Redesigning On-Line Food Consumption to Enhance Racial and Social Inclusion Through Generative Production Networks

   Johnson, Keesa V.; Eglash, Ron (June 2021, New design ideas)

   Bennett, Audrey; Eglash, Ron (Ed.)

   The food system in the US has supported growing dominance of industrial agriculture, corporate distribution chains, and other means by which power is exerted at the expense of environmental sustainability, citizen health and wealth inequality. Economic impacts have been most damaging to low resourced and racialized communities. Online purchasing creates new opportunities--particularly in the context of the covid epidemic--but barriers may arise that are also along race and class divisions. This paper examines an initial data set for two Black led collaborative Food System projects (two urban farms and a mobile farmers market initiative), all of which are primarily staffed by African American leadership and serve a diverse set of community members with Black consumers being of the majority. While issues such as government benefit payments constitute formal economic barriers, other challenges are better illuminated through the lens of the extraction of value: the loss of community connections and increased dependency on modes of production that do not return value to the community. We define “generative production networks” as those which maximize unalienated value return rather than value extraction. We utilize this framework to examine alternative online systems to overcome these barriers. 

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5. Latent demand for electricity in sub-Saharan Africa: a review

   https://doi.org/10.1088/2634-4505/ac5fb2  

   Van-Hein Sackey, Charles; Levin, Todd; Nock, Destenie (June 2022, Environmental Research: Infrastructure and Sustainability)

   Abstract Universal access to electricity is an essential part of sub-Saharan Africa’s path to development. With the United Nations setting Goal 7 of its sustainable development goals to be universal access to clean, reliable and affordable electricity, substantial research efforts have been made to optimize electricity supply based on projected demand in sub-Saharan African (SSA) countries. Our study reviews the literature on electricity demand, with a specific focus on latent demand (i.e., electricity demand that would exist if the necessary techno-economic conditions were met) in SSA. We found that out of 57 electricity demand papers reviewed, only 3 (5%) incorporated latent demand in their electricity demand projections. Furthermore, majority of the literature on electricity consumption and demand estimation in SSA use econometric models to identify determinants of electricity consumption and project future demand. We find that population density, urbanization, household income, electricity price, market value of crops and availability of natural resources to be significant determinants of electricity consumption in SSA. We conclude the review by proposing a methodology, and providing an initial proof of concept, for more accurately projecting latent demand in sub-Saharan Africa. Incorporating latent demand in electrification models would help inform energy sector stakeholders (e.g., investors and policymakers) about which sectors and geographic locations hold potential for wealth creation via electricity access. 

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