A) Introduction & Context: Why Does Rural Development Matter?

Having grown up in a more rural town in Oklahoma and now having the opportunity to attend a 4-year university, I have noticed the stark contrasts in resources between rural cities and more developed ones. Since coming to the University of Virginia, I have heard the stereotype that Southern states are less well-off than states elsewhere in the US, but had never delved into the topic nor thought about why this was the case until recently. I knew that many states in the South have more areas that are considered rural. Are all Southern states “poor?” Are there regions in the US besides the South that contain states that have a relatively lower state of living, that people tend to overlook? These were all questions I sought to answer through my research.

I was interested in exploring the resources that are available to help serve rural communities. In particular, I wanted to better understand where exactly the money from the US Department of Agriculture Rural Development division goes—what programs are funded? Which industry sectors receive the most investments? Which states get the most funding? Are the states that get the most funding the ones that would most benefit from additional investments?

1) Shiny: Map of % of Population in Poverty by State

To better understand the need for USDA investments in rural communities, it is important to take a look at poverty rates across the United States. Rural communities have higher poverty rates, so states with more rural communities may have a higher poverty rate. The highest poverty rates in the US are in the South—both the Southeast and the Southwest show considerable poverty rates. Mississippi, New Mexico, and Kentucky have a high poverty rate, demonstrating their need for additional economic resources. Exploring poverty rates is important as it shows where USDA investments are needed the most. States with higher poverty rates should receive more funding from the USDA as they have the highest need. As I continued my exploration into USDA investments, I kept in mind the regions that have the highest poverty rates to determine if they were receiving the most funding.

B) Funding By Geography: Who Receives the Money?

2) Map of USDA Investments by State

To determine if the regions that have the highest poverty rates are receiving the most funding from the USDA, I create a plotly map shows USDA’s investments per state in 2025. The light beige color correlates to a smaller dollar value of investments, while dark green shows a higher dollar value of investments. Appalachian and South receives more funding than the other areas of the US. The size of the state does not necessarily correlate to the amount of funding they receive—for example, New Mexico is a larger state in terms of land mass, but it receives visibly less funding than its surrounding states.

3) Bar Chart of Top & Bottom 10 Counties by USDA Investment

The bar graph shows that there are considerable disparities in USDA’s investments. While the highest funded county received over $80K, the lowest funded county received a mere $294, which questions the accessibility of USDA’s financial resources. I further noticed that some of the top-funded counties are in the South and Central America, where there are more rural communities, some of the top-funded countries like Los Angeles are not rural. However, some of the lowest-funded counties, including Clark, Missouri and Mason, Michigan are more rural. The observations from the bar graph suggest that not all USDA investments may be reaching their intended audience of rural areas.

4) Shiny App of USDA Projects v Total Investments

To provide a bigger-picture view of the disparities of the USDA’s Rural Development funding, I took a look at a scatterplot of the dollars of investments and number of projects for each state. The data is highly skewed, with some projects receiving just a few thousand dollars and other projects receiving hundreds of billions of dollars. This Shiny app plots the number of projects against the amount investment dollars, with each point representing a different state. Checking the “add trendline” box reveals that the number of projects and amount invested have a relatively positive, linear relationship. Colorado is an exception to the linear relationship demonstrated among the other states, with a relatively low number of projects but a high total investment dollars. So, we should expect Colorado’s average investment dollars per project to be higher than most if not all of the other states. For all of the other states, we expect the average investment dollars per project to be proportional to the number of projects. The points representing the South and North Central states tend to have both a greater number of projects and a greater number of investment dollars.

C) Funding by Program Area: What Initiatives Does the USDA Prioritize?

5) Shiny Treemap of USDA Investment by Program Area

In addition to prioritizing certain states that could benefit from additional resources, I was interested to see which specific initiatives the USDA prioritizes, if any. This treemap shows how total investment dollars are distributed across program areas. Each rectangle represents a different program area, and the size of each rectangle demonstrates the investment amount in comparison to other program areas. Single family housing received the most funding, showing the USDA’s priority of access to housing in rural communities. Single family housing is the most-funded program area in every year except 2024, when electric programs took the lead. After single family housing, the USDA provided considerable investments for electric programs, helping to strengthen rural electrification. Multifamily housing and business programs received similar amounts of funding, while investments of telecommunications programs and community facilities make up a minimal amount of the total funding the USDA has provided in the past 5 years.

6) Animated Plot of USDA Investment by Industry

There is a considerable decrease in Real Estate & Rental & Leasing between 2021 and 2025. This could be attributed to an increase in interest rates, which would have led to a decrease in mortgage demand, causing the USDA loan participation in the sector to decrease. Over the 5 years, there is a noticeable increase in the number of investment dollars for Utilities, while the number of projects stays constant. With the modernization of technology and transitioning to smart grids, there may have been higher capital costs despite the number of projects staying the same.

7) Histogram of Distribution of USDA Investment Dollars

The majority of USDA’s projects lie in the $50K to $200K range, with the most number of projects at around $120K. There is another peak that is smaller at around $50K, which could represent small business loans and grants for home repairs. Since the distribution is a bell-shape on a log scale, the data is highly right-skewed. This shows that there exists some projects that are over $1M.

8) Shiny App: Boxplots of USDA Investment per Project (by Program Area)

Because the data is highly skewed, as previously mentioned, the boxplots for some program areas are initially compressed and difficult to read. The option to view boxplots for log-transformed data for each program area allows the viewer to more easily view the boxplot for the majority of the data, excluding the outliers. The electric programs area has the highest median investment per project out of all of the program areas. Mutlifamily housing shows a high investment per project, and has a wide IQR, showing more variablility across housing developments. This shows that the investment size depends on the project size. Electric and multifamily housing have the highest per-project costs. Single family housing and business programs have the most diverse sizes of investment.

Conclusion

I explored how USDA investments are distributed across states, counties, and program areas, with a focus on equity in rural economic development. Through a combination of visualizations, I identified significant disparities in how funds are allocated—both geographically and by program type. By analyzing poverty rates and investment patterns, I discovered that the regions with the highest poverty rates, especially in the South, don’t always receive the most funding from the USDA.

In terms of program areas, the USDA consistently prioritizes housing initiatives, while Telecommunications and Community Facilities are underfunded, which could result in gaps in digital access for those in rural communities. There are also disparities at the county level, with some counties receiving millions of dollars in investment while others received less than $1,000.

Exploration of this topic is important for challenging assumptions and informing future conversations about resource distribution and policy effectiveness in rural communities. These findings demonstrate the need for a more balanced and data-driven funding strategy to ensure that the initiatives and geographic regions that could highly benefit from additional funding from the USDA receive it.