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How Connected Are Counties in the Fifth District?

Regional Matters
October 20, 2022

Access to expanded employment opportunities and local goods and services is an important factor explaining why certain rural areas are able to retain people and grow. However, this access is far from uniform across rural areas. One way of assessing the economic linkages across areas is by examining intercounty commuting flows. This post classifies rural areas based on commuting flows and uses this information to establish the degree of spatial interactions or connectivity across areas.

Measuring Economic Connectivity through Commuting Patterns

Locations benefit from their interaction with surrounding areas in several ways. Labor markets that spread across geographies provide employment opportunities to residents in neighboring jurisdictions. At the same time, workers' willingness to travel to a location for work also indicates feasible regular travel to that location for broader reasons, such as commerce or recreation. Commuting patterns are therefore assumed to reflect the degree of economic interactions or connectivity across locations.

This post uses the 2019 Longitudinal Employer-Household Dynamics (LEHD) data to study commuting patterns in the Fifth District. The U.S. Census Bureau manages and publishes the LEHD dataset, which contains information on how many workers live and work in pairs of locations. This information reveals how many people from a given home geography commute to a specific workplace.

There are three types of commuting movements from the perspective of a given county: intracounty commuting, commuting inflows, and commuting outflows. For example, consider rural Augusta County in Virginia:

  1. Intracounty: These workers live and work in Augusta County.
  2. Worker outflows: These workers live in Augusta County and commute to an outside urban or rural county.
  3. Employee inflows: These employees commute into Augusta County from an outside urban or rural county.

To compare counties, the present analysis calculates outflows as a share of total workers who live in a given county and commute to a different county for work and inflows as a share of total employees who work in a given county and commute from a different county where they live.

Across the Fifth District overall, the median outflow is 69 percent, and the median inflow is 56 percent. Inflows and outflows tend to be lower for rural counties. (See table.) This means that it is more common for rural residents to live and work in the same county and that they are therefore less connected to other counties. However, considering inflow and outflow metrics on a county-by-county basis reveals that some rural counties are just as connected as some urban counties.

Rural Fifth District CountiesUrban Fifth District Counties
Median outflow as a share of total workers65 percent72 percent
Median inflows as a share of total employees53 percent60 percent
Note: Here and throughout this post, counties are defined as rural if they have a USDA Rural-Urban Continuum code of 3-9, as discussed in the Richmond Fed's Rural Spotlight series.
Source: U.S. Census Bureau LEHD, USDA RUCCs, author's calculations.

In the Fifth District, rural counties with low shares of worker inflows and outflows tend to be located in mountainous areas that are relatively more difficult to traverse. Considering geographic inflow and outflow trends together, there appear to be many origins where a relatively large share of workers commute across county lines (as seen in the outflows map) but comparatively few destinations where a relatively large share of employees commute across county lines (as seen in the inflows map). This suggests that places where people live are more dispersed across the Fifth District, and places where people work are relatively concentrated.

Note: This analysis also considered worker inflows and outflows from states adjacent to the Fifth District states, including Pennsylvania, Delaware, Ohio, Kentucky, Tennessee, Georgia, and New Jersey.

Source: U.S. Census Bureau LEHD and author’s calculations.

Categorizing Connectedness

Looking at outflows and inflows separately tells two sides of the story about how connected a given county is to other places. Taken together, they can provide a more complete picture of how counties are connected to one another. Using the overall median outflows and inflows as thresholds, counties can be categorized into four groups:

  1. Connected (high inflow, high outflow): Relatively high shares of employed people commute both into and out of these counties. These counties benefit from increased productive capacity by integrating their labor market with surrounding counties.
  2. Bedroom communities (low inflow, high outflow): Relatively few of the employees in these counties commute in from outside counties, but a relatively high share of employed residents commute out of the county. These counties serve residents who prefer to live in communities that are more residential than commercial.
  3. Employment centers (high inflow, low outflow): The opposite of a bedroom community, a large share of employees commutes in from outside counties, but a small share of employed residents commute out of the county for work. These counties are more likely to have collocated employment opportunities that may complement one another and benefit from an expanded pool of workers beyond what the county itself has to offer.
  4. Mostly intracounty commuters (low inflow, low outflow): Relatively low shares of employed people commute both into and out of these counties. These communities are characterized by high levels of intracounty commuting. This group includes counties that may be located in isolated geographical areas and counties that may be economically self-sufficient.

While urban and rural communities are represented in all four categories, most counties belong to the connected or mostly intracounty commuters groups. Urban counties are more likely to be either connected or employment centers, whereas rural counties are more likely to be mostly intracounty commuters or bedroom communities. (See chart).

Connected communities tend to be clustered in eastern and central Virginia and dispersed throughout Maryland, West Virginia, and the Carolinas. One of the reasons why we see such strong connectivity in Virginia is that independent cities are treated as counties in Virginia and are not in other Fifth District states (except for Baltimore City in Maryland). Commuting between small, independent cities in Virginia and the surrounding counties contributes to commuting inflows and outflows between those two geographies. However, the same type of movement would be treated as intracounty commuting had the independent cities been considered part of the county. (See map).

Source: U.S. Census Bureau LEHD and author’s calculations.

How do counties' labor markets interact?

In relation to where they live, a worker can either work intracounty or commute to an outside county. In the latter case, they can decide to commute to either a rural or urban county. Thus, each worker in the Fifth District has three possible commuting outcomes: intracounty commuting, intercounty commuting to a rural county, and intercounty commuting to an urban county. On aggregate in the Fifth District, rural residents are slightly more likely to commute to another rural county or commute intracounty than to commute to an urban county. For urban areas, residents tend to predominantly commute to another urban area (about 65 percent of urban residents). (See chart.)

Residents in rural counties in Maryland, central Virginia, and central North and South Carolina counties are more likely to commute to urban counties. This is likely because these counties usually border one or more urban counties. On the other hand, residents in rural West Virginia, western Virginia, and eastern North Carolina counties are more likely to commute to other rural counties. These areas are characterized by clustered rural counties and include some rural counties that do not border any urban counties at all. (See map.)

Note: Urban counties were excluded from this analysis and appear in grey on the maps.

Source: U.S. Census Bureau LEHD, USDA RUCCs, and author’s calculations.


Communities differ, among other things, on their level of economic connectivity to other jurisdictions. Regional policies aimed at supporting different geographic areas should differentiate between those regions that are closely attached and connected and those with limited economic interactions.

An important caveat is that the present analysis uses pre-pandemic data on commuting flows. To the extent that COVID has permanently shifted people's commuting patterns, then it would be necessary to incorporate other information to understand the degree of economic interactions between residents in different communities.

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