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Research grants

Research grants provide funding to design and implement, or scale a research project that builds deeper understanding of our strategic priorities and focus areas, addresses gaps in our research, and translates research findings into practice. Research build plays a vital role in helping to dismantle systemic barriers and achieve our 2035 strategic vision.

Research Grants

Funding amount:

$250,000 or more per year

Funds disbursed: Q2 2025 | LOI cycles: Twice annually


What are Research grant opportunities?

The Kauffman Foundation’s Research grant opportunities offer funding for forward-facing research projects that both catalyze the field and develop greater understanding of how to close racial wealth gaps.

By deepening our understanding of how racial wealth gaps are built, sustained, and dismantled, the Research grant opportunity aims to strengthen the Foundation’s ability to catalyze our investments across the three strategic priorities and accelerate equitable economic opportunity in the Kansas City region.

Rigorous, cross-cutting, forward-facing, and innovative research is necessary to understand how to advance equitable economic mobility. Through this funding opportunity, the Foundation solicits high-quality research projects that advance the field and develop a greater understanding of how to close racial wealth gaps.

Understanding wealth gaps

The wealth gap is persistent and expanding in Kansas City and across the nation (Perry et al 2024). National data paints a stark picture: even as median wealth has increased across the board, so too has the gap in median wealth between white and Black households (Perry et al 2024).

Existing research shows fine-grained variance in how wealth gains have been made, and where barriers remain. For example, housing equity (a key driver of wealth) has increased for Black and Hispanic households, but racial inequity continues to affect homeownership – only 44% of Black individuals own a home (Perry et al 2024), and Black-owned homes are both undervalued and overtaxed (Fields et al 2023).

Rates of business ownership, a significant mechanism for wealth-gap closing, have increased for Black and Hispanic Americans (Aladangady et al 2023), but significant revenue disparities remain for Black and Hispanic-owned firms (Wheat et al 2024). Even at the current pace, it will take 256 years for the rate of Black business ownership to reach parity with the share of Black people in America (Perry et al 2023).

Even race-neutral tax mechanisms have been found to play a role in maintaining and widening the racial wealth gap. We see this, for example, in how the tax treatment of various asset classes provides greater advantages to white families than Black families (white students receive an implicit subsidy of $2,200 more per year, on average, than Black students) ultimately creating racial inequity in the college financial aid system (Levine and Ritter 2022).

Everyday bias and discrimination compound the impact of these economic inequities – racial disparities in wages, hiring, college access, and lending lead to inequities in our workforce, in college access and completion, and in the success of Black and Hispanic business owners (Fields et al 2023). These economic inequities further widen the racial wealth gap.


Examples

The examples listed are not exhaustive or intended as prescriptive. This opportunity solicits innovative and field-advancing proposals that explore efforts to close racial wealth gaps in a variety of ways leveraging various methodological approaches.

Research questions could explore, for example:

Are we, as researchers across disciplines, asking the right questions and using the most appropriate measures to understand and close racial wealth gaps?

How can we ensure that data collection and data infrastructure measure and highlight root causes of wealth gaps rather than symptoms (Bates et al 2023)? What methods and measures – at both the individual and population level – are most appropriate to assess the impact of social determinants of the racial wealth gap? In what ways could we strengthen quantitative and qualitative methods to enable meaningful analysis of small populations in order to better highlight wealth-gap closing opportunities? What models are most impactful for predicting the impact of wealth-gap closing interventions (Nascimento et al 2023)?

What interventions would close racial wealth gaps within underserved Kansas City communities without contributing to the displacement of Black and Hispanic residents?

Research has shown the negative impacts that concentrated poverty and segregation have on many measures of life outcomes, including educational attainment, career and earning trajectory, and rates of successful business ownership (Chetty 2017; Fairchild 2008). How can regional stakeholders work to address hypersegregation, while ensuring Black and Hispanic residents benefit from economic development? What data-informed approaches can regional stakeholders take to increase place-based economic mobility, without contributing to displacement (Acharya and Morris 2022)? What does research tell us about how to support emerging and existing small business owners in regions experiencing economic growth (Rodriquez et al 2023)?

What does research highlight about the role Black and Hispanic communities could play in leveraging and advancing technology to close the racial wealth gap?

Research shows that technological advances, such as artificial intelligence (AI), can perpetuate bias without intentional, equitable design (Eubanks 2018; Noble 2018). What role is generative AI playing in closing or widening the racial wealth gap, and how could it be used to support economic mobility for Black and Hispanic learners, workers, and entrepreneurs? What impact would equity interventions have on generative AI’s ability to advance economic mobility for underserved populations (i.e., regulation, democratized access, or participatory design) (Brown et al 2023)?

What are the most effective ways to aggregate, share, and build community capacity for data collection and ownership – in service of closing racial wealth gaps?

Investments in infrastructure that support open or aggregated data have the capacity to surface racial wealth gaps and impact economic development efforts (Yoon and Copeland 2020). Extant research has highlighted both the opportunities and the limitations in supporting place-based change through data intermediaries – how can we effectively increase community capacity for data collection and utilization (Yoon and Copeland 2020; Busette et al 2024)? How can we foster linkages and translative capacity between existing and emerging data sources, in order to more swiftly assess and address wealth gaps? How can we advance data equity as we work toward concerted wealth-gap closing efforts (Hendey and Pettit 2021)?


Methodology

We welcome proposals that employ a wide variety of methodological approaches from all disciplinary backgrounds. Teams or individuals are invited to utilize the most appropriate methodological approach for the question being explored, and should also articulate why this approach is best suited for the work. Proposed approaches and methodologies could include but are not limited to:

  • Modeling or simulations
  • Policy or ecosystem studies, participatory or engaged designs
  • Qualitative analysis
  • Quantitative analysis
  • Quasi-experimental designs
  • Secondary data analysis


Assessment criteria of applications

A panel of the Foundation’s Research, Learning, and Evaluation (RLE) staff and impact officers will review all LOI. Full proposals will be reviewed by the RLE and impact officer panel, and will also be sent to external content experts for peer review.

Strong proposals at both the LOI and full application stage are expected to evidence the following criteria in their applications:

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Adherence to proposal guidelines

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Clarity in thought

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Timelines, budget, and staffing plans are appropriate for the proposed work

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Strong direct or transferrable experience; relevant and appropriate subject matter expertise

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Clear alignment with strategic priorities and focus areas

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Strong articulation of how the research could inform efforts to close racial wealth gaps in Kansas City

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Feasible, logical, and appropriate methods for the proposed work

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Thoughtful and rigorous dissemination and evaluation plans that create and capture impact

More information about required criteria of strong applicants:

  • For research not conducted in Kansas City, applicants are expected to make appropriate comparisons between the research context and the Kansas City context.
  • For research analyzing large-, community-, or population-level datasets that align with the Foundation’s strategic priorities, applicants are expected to provide a rationale for how their findings may be applicable to the Kansas City community or population.
  • For research proposals that incorporate a community-engaged approach, applicants are expected to demonstrate robust plans to develop and sustain partnerships, strong experience working with community partners in mutually beneficial relationships, and appropriate financial compensation plans for engaged work.
  • For all research proposals, applicants are expected to demonstrate equitable approaches and processes (i.e., clearly articulated plans to mitigate bias in the research; disaggregate by race, gender, geography; engage communities in ownership and sense-making of findings; or other approaches).


Letters of Interest process & timeline

To provide transparency and clear information, we’ve outlined every step of the application process and timeline for potential applicants. Learn more >


Reporting & evaluation expectations for funded research

Measuring impact, communicating research findings, and disseminating learnings are priorities for the Foundation. We encourage applicants with skillsets in research translation and impact to emphasize this experience in their proposals. Regardless of previous experience, all funded applicants will work with RLE staff to ensure research products are shared with relevant audiences. Grantees can expect to work with RLE staff throughout the duration of their grant in the following ways:​

  • Potential participation in ongoing learning and convening as part of communities of practice​.
  • Engagement with grantees across research and practice to facilitate translation, community resonance, and impact.

Need more information?

We invite you to explore our funding philosophy, our grant cycle, and our FAQs. You can also sign up to join any of our optional webinars to ask questions and learn more about our grantmaking implementation or subscribe to our newsletter to stay updated on the latest changes.


Literature cited

Aladangady, A., Chang, A., Krimmel, J., & Ma, E. (2023, October 18). “Greater Wealth, Greater Uncertainty: Changes in Racial Inequality in the Survey of Consumer Finances.” The Federal Reserve.

Bates, D., Coon, L., Esenam Dogoe, Kweilin Ellingrud, Singh, A., & Srinivasan, R. (2023, February 27). “Zooming in: Using local insights to inform US racial-equity efforts.” McKinsey & Company.

Brown, S., Finney, M., Korgaonkar, N., McMillan, M., & Perkins, C. (2023, December 19). “The impact of generative AI on Black communities.” McKinsey & Company.

Brown, S., Finney, M., McMillan, M., & Perkins, C. (2023, February 3). “How to close the Black tech talent gap.” McKinsey & Company.

Busette, C., Bennett, C., Sanchez, G. R., Gilbert, K. L., & Frimpong, K. (2024, March 28). “Supporting a community-led data infrastructure to build local and equitable governance that advances policy.” Brookings.

Chaia, A., Julien, J., Pérez, L., Pinder, D., Shelley Stewart III, Williams, D., & Yancy, N. (2024, March 15). “Mapping the road to prosperity and parity for Black and Latino residents across America.” McKinsey & Company.

Chetty, R., & Hendren, N. (2018). “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects*”. The Quarterly Journal of Economics, 133(3), 1107–1162.

Eubanks, V. 2019. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Press.

Fairchild, G. B. (2008). “Residential segregation influences on the likelihood of black and white self-employment.” Journal of Business Venturing, 23(1), 46–74.

Fields, Jordan M., Perry, Andre M., & Donoghoe, Manann. (2023, August 22). “How the property tax system harms Black homeowners and widens the racial wealth gap.” Brookings.

Hendey, L., & Kathryn L.S. Pettit. (2021, December 6). “How Can Local Leaders Use Data to Promote Equity?” Urban Institute.

Julien, J., Pinder, D., Shelley Stewart III, Williams, D., & Yancy, N. (2024, February). “The state of Black residents: The relevance of place to racial equity and outcomes.” McKinsey & Company.

Krivkovitch, A., Field, E., Yee, L., & McConnell, M. (2023, October 5). “Women in the Workplace.” McKinsey & Company.

Levine, P., & Ritter, D. (2022, September 27). “The racial wealth gap, financial aid, and college access.” Brookings.

Nascimento, P., Lamb, J., Osoba, O., & Welburn, J. (2023). “Modeling America’s Racial Wealth Disparities.” Notices of the American Mathematical Society, 70(07), 1136-1141.

Neely, M., Sheehan, P., & Williams, C. L. (2023). “Social Inequality in High Tech: How Gender, Race, and Ethnicity Structure the World’s Most Powerful Industry.” Annual Review of Sociology, 49(1), 319–338.

Noble, S. U. (2018). Algorithms of Oppression. NYU Press.

Perry, A. M., Stephens, H., & Donoghoe, M. (2024, January 9). “Black wealth is increasing, but so is the racial wealth gap.” Brookings.

Perry, A.M., Donoghoe, M., Stephens, H. (2023, May 24). “Who Is Driving Black Business growth? Insights from the Latest Data on Black-owned Businesses.” Brookings.

Rodriguez, R., Lung-Amam, W., Knaap, G., & Johnson, D. (2023, November). “Keeping Small Businesses in Place: Voices from the Field.” Small Business Anti-Displacement Network.

Wheat, C., Chan, S., Tremper, N. (2024, April 3). “Scaling to $1 Million: How Small Businesses Fare by Owner Race and Gender.” JPMorgan Chase Institute.

Yoon, A., & Copeland, A. (2020). “Toward community‐inclusive data ecosystems: Challenges and opportunities of open data for community‐based organizations.” Journal of the Association for Information Science and Technology, 71(12), 1439–1454.