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Counties with Recreation-Based Economies Show Biggest Recovery from Long-Term Poverty

Recreation may appear to cure rural poverty, but experts suggest that it may just relocate it. 

Figure 1. The percentage of amenity types that comprise rural counties with persistent poverty. “Rural” is not defined by the Census, but includes all areas not in an urban area. About 85% of persistent poverty counties are rural.

According to ERS data from 1979 to 2013, counties that rely on recreation for a lot of their economic productivity tend to fare better than counties with other types of economies– at least on the surface. Between 1979 and 2013, only 1% of recreation-dependent counties remained in persistent poverty. Of the counties that came out of persistent poverty, 24% were dependent on recreation.

The Economic Research Service (ERS) places counties into mutually exclusive economic categories that aid policy and decision-making for a variety of stakeholders including other federal agencies. Each economic category is defined using a different criteria that describes the dominant industry on which the county depends. 

Ashe County, North Carolina, is a recreation-dependent county that was classified as a persistent poverty county in 1979 but did not remain in persistent poverty in 2013. Counties are classified as having persistent poverty when the poverty rate remains greater than or equal to 20% for three decades or more. Tourists visiting Ashe County flock to the New River for tubing, kayaking, and fishing. Also accessible from Ashe County is the Blue Ridge Parkway, a scenic highway that recently received $29 million under the Great American Outdoors Act for repair work on the historic Laurel Fork Bridge. 

Figure 4. 1.6% of rural counties are dependent on recreation. 

But recreation is a double-edged sword. Despite such developments in counties like Ashe, some residents do not share in the economic growth. 

“In those recreation counties, we see displacement,” Headwaters Economics scholar Megan Lawson, Ph.D., said in an interview. “People [move] farther and farther downstream as housing prices and cost of living increases.”

Lawson suggests that a number of the people employed in recreation counties may be commuting from outside the county, where the cost of living is more affordable. 

“We see a lot more inequality even within those communities,” Lawson said. “And so on average it looks like median household income is doing really well – there’s a lot of prosperity, rising wages, and that’s all great. But … we have to be aware of the distribution and what’s happening for those folks earning the lowest income in those communities.”

Episodic and Persistent Poverty 

Figure 5. There are 301 rural counties in persistent poverty. About 15% of rural counties are in persistent poverty, while about 4.4% of urban counties (52 counties) are in persistent poverty.

In contrast to persistent poverty, counties experiencing episodic poverty have high poverty rates in the short-term, possibly due to the temporary decline in a single commodity. 

“[Episodic poverty counties] might be related to economies that tend to be dependent on some sort of cyclical resource … whether that’s agriculture and there was a particularly bad wheat year, or the price of uranium tanked,” Lawson states.

Compared to counties with persistent poverty, counties experiencing episodic poverty are more likely to bounce back from temporary commodity disruptions.

“Places with persistent poverty are more likely to be ones where … whatever that commodity is that the place depends on has declined for the long term,” says Lawson. 

Figure 6. 9.3% of rural counties depend on mining.

Mining dependent Harlan County, Kentucky, for example, was named a persistent poverty county in 2013 in conjunction with a total decline in coal mining employment in the Eastern U.S over the last few decades. The poverty rate in Harlan county today exceeds 35%. 

Many of these rural counties with persistent poverty also lose population. Eighty-five percent of rural counties with persistent poverty lost population between 2010-2020. The mean population change of rural counties with persistent poverty is a decline of 7.14%. Harlan County experienced a 8.9% decrease in population over the last decade, according to the most recent census data. 

Non-specialized Counties 

Despite increasing poverty rates in some mining-dependent counties, rural counties in persistent poverty are more likely to be non-specialized than any other amenity type (see Figure 1). Forty percent of non-specialized counties were experiencing persistent poverty in 2013, compared to 2.1% of recreation counties or 10% of farming counties. 

Figure 7.  The persistent poverty rates in each amenity type. Data from timber-dependent counties may be skewed because there are only six remaining timber counties in the U.S.

While only 2.1% of recreation counties were in persistent poverty in 2013, 40% of non-specialized counties were experiencing persistent poverty. Lawson states that non-specialization in some counties may indicate a diverse economy because these counties are not dominated by one amenity type. But the presence of persistent poverty in 40% of non-specialized counties suggests a lack of economic activity in those areas, Lawson also states. 

In addition to higher poverty rates, non-specialized counties in persistent poverty also tend to lose population at higher rates, at least in the last decade. At an average population change rate of -7.4%, non-specialized rural counties in persistent poverty experienced more population loss than recreation and other specialized counties. For example, Wayne County, Missouri, experienced a 18.8% population loss between 2010 and 2020. Recreation counties in persistent poverty, on the other hand, experienced a mean population change rate of .12%. In recreation – dependent Taos County, New Mexico, the population grew at a rate of 4.7% from 2010 to 2020.

While economic specialization (particularly in recreation) appears to benefit rural counties, Lawson offers a more complex analysis. She mentions that communities like Rifle, Colorado, in mining-dependent Garfield County, may be supplying recreation labor to nearby counties. 

“[Rifle] is definitely an example of a community close to recreation-dependent places like Pitkin County… supporting those recreation destinations,” Lawson says. “So I think it’s a good example of that kind of dynamic.” 

It is not that recreation has necessarily prevented rural counties like Pitkin from experiencing persistent poverty, but that recreation may have increased the cost of living to an extent that people living in poverty relocate to neighboring counties, often supplying the workforce to make recreation possible. 


The Economic Research Service (ERS) is a branch of the USDA devoted to analyzing economic trends to inform policymakers, industry groups, and other federal agencies. The ERS assigns all U.S. counties into one of six mutually – exclusive categories that best describes economic dependence. Timber-dependence data from Headwaters Economics was added as an additional category to the ERS analysis. The ERS defines economic amenity types in the following ways: 

Farming – A farming-dependent county is a county where agriculture contributes to 25% or more of annual labor and earnings or when, during the same period, 16% or more of the county’s jobs were in agriculture in 2010-2012. 

Mining – A mining-dependent county is a county where mining contributes to 13% or more of average annual labor and earnings or when, during the same period, 8% or more of the county’s jobs were in mining in 2010-2012.

Manufacturing – A manufacturing-dependent county is a county where manufacturing contributes to 23% or more of annual labor and earnings or whe, during the same period, 16% or more of the county’s jobs were in manufacturing in 2010-2012. 

Federal/State Government – A federal/state Government-dependent county is a county where government contributes to 14% or more of annual labor and earnings or when, during the same period, 9% or more of the county’s jobs were in government in 2010-2012. 

Recreation – Recreation-dependent counties are defined using a weighted index that considers  three components – jobs, earnings in entertainment, recreation, accommodations, food/drink, and real estate, and the percentage of housing set aside exclusively for seasonal use. Recreation counties are counties with a weighted index one standard deviation or more above the mean. 

Timber – Timber counties are defined as counties where 20% or more employment in industries including or related to timber.

Nonspecialized – Non-specialized counties did not meet thresholds for any economic type.

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