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Rural Development

Paper Session

Sunday, Jan. 7, 2024 1:00 PM - 3:00 PM (CST)

Marriott Rivercenter, Conference Room 5
Hosted By: Society of Government Economists
  • Chair: Sandy Dall'erba, University of Illinois-Urbana-Champaign

USDA Farm Service Agency’s Loan Programs: Evaluating their mission of providing loans to credit-constrained agricultural producers

Sarah A. Atkinson
,
U.S. Department of Agriculture

Abstract

USDA is tasked with the mandate of ensuring that agricultural producers have access to credit at reasonable terms and rates to maintain vibrant and diverse family farm population (1). To fulfill this mandate, the USDA’s Farm Service Agency (FSA) provides direct and guaranteed loans (2) to credit worthy family-sized farms who are unable to obtain credit elsewhere, at reasonable rates and terms. Direct loans, while comprising only 7 percent of all U.S. agricultural debt in 2020 (3), serve as an important tool in ensuring that the most vulnerable producers have access to credit.

To evaluate how well this program is serving the intended populations I will calculate merge annual Agricultural Resource Management Survey (ARMS) records and FSA administrative loan data over the 20113-2021 time period and calculate farm debt market penetration rates for FSA loan programs by farm size, commodity type, beginning farmer status, ethnic minority group, and women as primary operator. By examining the distribution of FSA borrowers in these categories compared to the general farm population, we can identify patterns in the type of producers utilizing FSA loan programs, while controlling for trends in overall U.S. farm debt levels, farm size, and producer demographics.

The results will provide indicators of where FSA programs are either succeeding in or failing to reach their targeted populations and guide future research as well as generating a lively discussion on possible means to improve these outcomes moving forward; the goal being to ensure that all qualifying family-sized farms have adequate access to farm credit.


(1) Ahredsen et al. “Beginning farmer and rancher credit usage by socially disadvantaged status.” Agricultural Finance Review. October 2021.
(2) through loans directly to qualifying producers and guarantees on loans made by approved lenders
(3) Monke, Jim. "Agricultural Credit:

Impacts of the USDA ReConnect and Community Connect Grant Broadband Programs on Broadband Speeds in Rural Areas

Joshua Goldstein
,
University of Virginia
John Pender
,
U.S. Department of Agriculture
G. Leonel Siwe
,
University of Virginia
Zhengyuan Zhu
,
Iowa State University

Abstract

The COVID-19 pandemic dramatically demonstrated the importance of reliable high-speed
broadband access for all Americans. Despite large and increasing investments by the Federal
Government and others to promote broadband deployment and use, a large digital divide
between rural and urban America persists. In November 2021, 41 percent of rural households
lacked high-speed wired broadband service, compared to 27 percent of urban households. In this
study, we investigate impacts of USDA’s ReConnect and Community Connect programs on
broadband speeds in rural areas of the United States. ReConnect – established in 2018 and
funded by more than $5 billion in appropriations through FY 2023 – is the largest USDA rural
broadband program. Community Connect is much smaller, with $35 million appropriated in FY
2023. Few studies have investigated impacts of any Federal broadband programs, and none has
investigated impacts of the ReConnect program.

We investigate the impacts of ReConnect and Community Connect projects approved between
FY 2018 and FY 2021 on broadband speeds by 2023, using program data provided by the Rural
Utilities Service (RUS), Ookla data on realized broadband speeds, and other data to control for
confounding factors. We use matched difference-in-difference estimation at the census tract
level, with changes in broadband speeds in ReConnect and Community Connect project areas
from before to after project implementation compared to changes in broadband speeds in
matched tracts outside of service areas of these and other Federal broadband programs.
Treatment and control tracts are matched on the share of tract area eligible for these programs
(using RUS and FCC data), prior broadband speeds (using Ookla data), and prior demographic
and socioeconomic characteristics (using 2020 Population Census data and 2015-19 American
Community Survey data).

USDA Rural Development Distance Learning and Telehealth Grants: Impacts on Rural Communities before and during the COVID-19 Pandemic

Cristina D. M. Miller
,
U.S. Department of Agriculture

Abstract

Rural schools face a number of challenges, such as attracting and retaining qualified teachers and offering students a comprehensive course offering (such as AP classes, language classes, or advanced STEM classes). Rural America is faced with low student populations and limited school and community resources compared to urban areas. Rural schools are bridging the gaps in education by offering distance education—connecting students, via the internet, to AP classes, advanced STEM courses, or classes at a college/university. Distance learning may also be a useful tool to help with rural teacher retention, by using the distance learning technology for teacher training—enabling teachers to do online continuing education/teacher training without the additional costs of travel. Several studies have shown that rural schools lacked funding to purchase the needed technology and software to foster the distance learning. USDA Rural Development, through Distance Learning and Telehealth (DLT) grants, provides grant funding up to $1 million to eligible schools enabling them to purchase the technology needed for distance learning. Using USDA administrative data on DLT grants between 2004 and 2021, we estimate the impact of distance learning on measures of rural school quality. We hypothesize that rural school quality improved in rural counties that received USDA DLT grant funding compared to similar rural counties that did not receive the funding.

Local Income Impacts of USDA Water & Environmental Programs

Robert Dinterman
,
U.S. Department of Agriculture

Abstract

Water and waste systems (WWS) provide clear benefits to the health and wellness of individuals within a community, however what is less clear is the economic benefits of having dependable WWS. While a lack of adequate water and waste systems makes it difficult for individuals to live in the area or business to operate, does the existence/improvement of WWS bring in more individuals and/or businesses vis-à-vis increased economic activity? And how much increased economic activity? Rural communities with improved WWS should theoretically benefit from an influx in employment for its surrounding area, although this has yet to be tested in the literature.
Our research implements an event study design to determine how WEP projects have impacted local incomes of the residents of a community. This study utilizes USDA obligation data on WEP projects and its associated funding amount as well as IRS data on zip code (and county) level adjusted gross income. These data span annually from 2005 through 2020 and are supplemented with additional covariates related to eligibility of areas for receiving WEP funding. We utilize a difference in differences approach where our treatment group are the locations that receive a WEP funded project in its boundaries while our control group is comprised of areas that are eligible for WEP funding but do not receive any funded projects throughout the period of our analysis.
Preliminary results indicate areas receiving WEP projects experience an increase in local area income for up to 10 years after project’s implementation. These effects follow an inverse U shape with a peak of around 4% increase in local area income occurring around 7 years after deployment of a project where the county level estimates have a larger magnitude than our ZIP code level estimates which suggests WEP projects have substantial spatial spillover effects.

Discussant(s)
Jennifer Ifft
,
Kansas State University
Alex Marre
,
National Telecommunications and Information Administration
Sabrina Wulff Pabilonia
,
U.S. Bureau of Labor Statistics
JEL Classifications
  • Q1 - Agriculture
  • O1 - Economic Development