How can we gain a comprehensive understanding of the economic life of low- and moderate-income communities and those experiencing disinvestment and limited growth? Information on the economic life and spending power of low- and moderate-income communities is limited due to greater use of cash, the prevalence of alternative financial services providers and the limited incentives to conduct a comprehensive analysis of market potential.
This limited view has far-reaching impacts and ultimately inhibits regional economic development, neighborhood growth, and the individual quality of life for those living in areas affected by information inequities.
The Census, along with private data sources, provides a powerful policymaking and budgeting tool for the government and private sector companies alike, informing their investment decisions for new building developments, retail hubs, supermarkets and infrastructure projects. Without a holistic understanding of each neighborhood, the decisions made can further inhibit the economic growth of low- and moderate-income communities.
Building on federal, state and local public information with new data and analytic tools is critical. Part of the solution has involved public participation geographic information systems (PPGIS), a model which has been used to evaluate neighborhood health, wealth and quality of life through a top down/bottom up model to integrate community, university, and municipal information.
The last element needed for understanding community financial power is often inaccessible to community advocates and governments alike: consumer spending insights. These insights may help integrate the above sources into a new model for better understanding the economic life of low- and moderate-income communities.
The Financial Inclusion & Citizen Participation (FI&CP) project, is unique in that it leverages the insight of Mastercard anonymized and aggregated transaction data to evaluate low- and moderate-income community financial health.
Read the full article about bridging the data gap for low-income communities by Michelle Thompson at New America.
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