Forward Analytics Release: ‘Deconstructing Depopulation: Rural Characteristics and Population Change’
A new report released Thursday, June 4 from Forward Analytics, looks at rural population decline through two lenses: the source of the loss and the county characteristics that are related to population losses and gains. The study shows that the source of Wisconsin’s rural losses was quite different from losses nationally.
The report is the second in a multi-part series from the research division of the Wisconsin Counties Association and is a follow-up to the February 2020 The Rural Challenge: Depopulation and Its Economic Consequences, which showed both Wisconsin and the nation experiencing rural depopulation at unprecedented rates.
According to Deconstructing Depopulation: Rural Characteristics & Population Change, population decline has two sources. Natural loss occurs when the number of deaths in a county exceeds the number of births. Net outmigration occurs when the number of residents moving out of a county exceeds those moving in.
“During 2010-2018, 92% of rural population loss nationally was the result of net outmigration,” said Forward Analytics Director Dale Knapp. “Wisconsin’s experience was different. Less than half of the loss was due to outmigration, while 53% was due to natural decline, or fewer births than deaths.”
According to Knapp, while a wide range of county characteristics were examined, only six had significant correlations with population loss. A county’s population change over the previous decade was the most important. Eighty-eight percent of counties that lost population in 20002010 also declined during 2010-2018.
Among those that added residents in the 2000s, just over half also grew over the ensuing eight years. A similar pattern emerged for population change in 2000-2010 relative to gains or losses during the 1990s. In other words, it appears that decline begets more decline.
“Among the other county characteristics associated with population change, three are out of the control of state and local policymakers: the presence of a medium-sized city, proximity to a metropolitan area, and desirable natural amenities,” said Knapp. “The first two highlight the overall trend toward urban growth. Having a city between 10,000 and 50,000 residents can help slow rural population loss. Rural counties bordering a metro area have the rural lifestyle some people prefer yet offer access to urban amenities. That access appears to stem decline as well. Natural amenities such as lakes, rivers, forests, and mountains also appear to insulate counties from population loss. Counties with the most natural amenities grew 4.4% during 2010-2018, while those with the fewest declined almost 3%.”
Two factors that help slow rural decline can be affected by state and local policymakers: a diverse industry mix and access to high speed internet. Having a dominant industry that is growing can be advantageous for a county. However, it can also leave it vulnerable when an economic shock affects the industry or the major employer in that industry relocates. Access to high speed internet is critical for business and desirable for residents, particularly young adults. Rural counties with greater broadband coverage tended to add residents or show slower population decline.
Knapp concluded, “That so few controllable factors were statistically associated with growth or decline is a bit troubling, but it does not necessarily mean that there is little that state and local officials can do to stem population loss. The factors examined in this study explain a third of the variation in rural population change. There may be actions that have helped lessen population loss, but are not picked up by the measures studied. That will require a deeper look at individual counties that have bucked the trend of rural population loss.”
It is the mission of Forward Analytics, the research division of the Wisconsin Counties Association, to use the best data available to highlight challenges facing Wisconsin and share this information to assist policymakers in understanding the data in pursuit of informed policy decisions