Rural Utilities Service Broadband Loans and Economic Performance in Rural America
19 Pages Posted: 29 Mar 2015 Last revised: 15 Aug 2015
Date Written: March 27, 2015
This paper examines the Rural Utilities Service’s (RUS) Rural Broadband Access Loan and Loan Guarantee Program, which finances the development of broadband infrastructure in rural areas, and provides estimates of the effects of the program on economic performance. Access to broadband is often seen as vital to economic growth and improved quality of life, and broadband access is no less and perhaps more critical in rural areas, where the possibilities of advanced communications can reduce the isolation of remote communities and individuals. Provision of broadband infrastructure in rural areas has occurred at a slower pace than in more densely populated areas. Issues of density, among other factors, affect the expected returns to rural telecommunications projects. Profit-motivated lenders or other providers of project financing may rationally view the expected revenues derived from rural broadband projects as insufficient to justify investments in them. In response to limited funding from private sources, the Congress authorized the RUS broadband loan program, which finances the construction of broadband projects in rural areas.
We use information on the RUS broadband loan program to estimate the effects of the loans on economic performance. From program records, we know the geographic footprints of projects that submitted loan applications to RUS. We know whether RUS approved or rejected the loan application, and in the case of approvals, we know the timing of that approval. We map the geographic footprint of projects into counties served. While county level observations may not be a perfect level of observation, previous studies have used county-level data as there are advantages with respect to data availability. We develop a time series data set of county-level measures of employment, payroll, and the number of business establishments over the relevant time period, and examine different rural definitions to filter the set of counties used in the analysis.
Using a panel model with county and year fixed effects, we produce estimates of the effect of the broadband loan on the three measures of economic performance. Our estimation technique is best thought of in treatment terms, where the loan approval represents the treatment. The selection of control groups is important in a treatment context, and to this end, we develop several distinct control groups of rural counties. Specifically, we develop a control group of rural counties that were in the footprint of projects rejected for RUS funding; this control group represents a set of counties that may be similar to the treatment group in unobservable ways. We also use a propensity scoring technique to generate two control groups based on demographic characteristics of approved counties and on the pattern of economic growth leading up to the evaluation time period. Finally, we define a control group of rural counties adjacent to the set of counties with approved loans.
In general, we found modest but statistically significant relationships between the RUS broadband loan program and county employment and payroll, but no relationship between the program and the number of business establishments. These estimates suggest that economic performance was in the range of 1 to 4 percent higher in counties receiving a RUS broadband loan. These results were robust across the set of control groups. However, very few loans went to projects in the most rural of counties, such as those with only very small towns. Results restricting the sample to this set of rural counties showed no relationship between the RUS broadband loan program and economic performance.
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