What Is a Region?
A quick and easy answer to this question comes from National Geographic: “A region is an area of land that has common features.” This often ties in with varieties of spatial geographies. An important consideration of regional differences in North Carolina can be seen below in the following simple map which portrays this excellent article by John Shelton Reed.
NC Regional Differences
Source: http://www.houseofswankclothing.com/north-carolina-bbq-shirt/
Understanding the details and nuances of labor and economic activity requires an analysis of smaller regions in the state. Researchers at the state level need to compare data for smaller substate regions for administrative and policy decision making. Local economic developers need to compare data for substate regions to verify or determine potential partners. The big question becomes: Which regions should be analyzed and for what purpose? This entry will briefly cover four different ways to look at the state for labor and economic analysis: Counties, Prosperity Zones, Office of Management and Budget’s (OMB) Delineations, and Interconnected Markets.
Counties
The 100 counties across North Carolina serve as the building blocks from which other regions are built. Most regional analyses use regions based on counties or groups of counties. For instance, the Department of Commerce developed the Tiers system to distinguish between counties of varying levels of economic well-being for determining policy, including the allocation of discretionary grant funding. The Rural Center and other entities also establish regions that distinguish between rural and urban counties or areas.
Prosperity Zones
Prosperity Zones were recently developed in order to help coordinate economic development initiatives across different agencies. They will provide one-stop state services, as well as aid cooperation with local and regional government and nonprofit entities.
Source: NC Department of Commerce. Current as of July 14, 2014
LEAD will release and create data and reports based on the Prosperity Zones in the coming months. Such work will include data books that give overviews of areas, substate projections, and substate Hot Jobs for 2015. These should help regions better understand the labor market conditions in their Prosperity Zones.
OMB's Delineations: Core-Based Statistical Areas (CBSAs) and Combined Statistical Areas (CSAs)
The federal government’s Office of Management and Budget (OMB) defines geographic entities used by federal statistical agencies and researchers to understand metro areas in our country. Federal agencies keep one (current) classification set for collecting, tabulating, and publishing statistics for these areas. While there are no administrative or governmental entities associated with these groupings, they help standardize statistics across all federal agencies and provide comparisons for researchers.
Classifications worthy of note for North Carolina include:
Core-Based Statistical Areas (CBSAs) have a core central area in one county, and includes outlying counties that have a high degree of social and economic integration as measured by ‘employment interchange’, which is the sum of the percentage of workers commuting from the smaller area to the larger area and the percentage of employment in the smaller area accounted for by workers residing in the larger area. The two CBSAs are:
- Metropolitan Statistical Areas whose core urban area has at least 50,000 people. As of 2013, there are 381 MSAs in the U.S. . Two examples of Metropolitan Statistical Areas in North Carolina include: Asheville (Buncombe, Haywood, Henderson, and Madison counties), and Charlotte-Concord-Gastonia, N.C.-S.C. (Cabarrus, Gaston, Iredell, Lincoln, Mecklenburg, Rowan, and Union counties in N.C.; Chester, Lancaster, and York counties in S.C.).
- Micropolitan Statistical Areas whose core urban cluster has between 10,000 and 49,999 people. As of 2013, there are 541 Micropolitan Statistical Areas in the U.S. and Puerto Rico. Two examples of Micropolitan Statistical Areas in North Carolina include Albemarle (Stanly County) and Boone (Watauga County).
- Combined Statistical Areas (CSAs) are geographic entities that consist of two or more adjacent CBSAs that have sufficient employment interchange. As of 2013, there are 169 Combined Statistical Areas in the U. S. Examples of CSAs in North Carolina include: Asheville-Brevard, N.C. (Asheville Metropolitan plus Brevard Micropolitan); and Charlotte-Concord, N.C.-S.C. (Albemarle Micropolitan plus Charlotte-Concord-Gastonia, N.C.-S.C. Metropolitan plus Shelby Micropolitan).
Metropolitan Statistical Areas 2013
Source: Office of Management and Budget, Feb. 28, 2013
These areas get updates every so often, so caution must be used in interpreting tables and data from different time periods. One recent example of this was the story about the declining income of the Charlotte-Concord-Gastonia, N.C.-S.C. Metropolitan Statistical Area based on analyses of American Community Survey data.
Interconnected Markets
Do we need yet another set of regions to use for economic comparison? If we want to examine the entire state explicitly based on labor flows, then the answer is yes. As seen above, if we only use Office of Management and Budget regions, we will miss important rural parts of the state. If we only use rural versus urban, we will not understand the impact of different labor market and industrial compositions in different parts of the states. While Prosperity Zones are helpful administratively across multiple agencies from DOT to DENR to Commerce, they are too large to precisely match the labor flows and economic relationships between counties in the state.
Using a methodology modeled after work by the USDA Economic Research Service, two former LEAD economists, Zack Oliver and Jimmy Squibb, led a study of North Carolina and its four neighboring states (since labor markets aren’t restricted to political boundaries) as a series of interconnected labor markets. The substate geographies were built by looking at inter-county/regional commuting patterns in North Carolina and the nearby states that share labor flows[i]. We found 24 distinct interconnected labor markets (IMs) with at least one county in North Carolina. These counties were further broken into 18 strongly interconnected IMs (SIMS) (shown in varying degrees of strength in blue, darker being stronger) and six loosely interconnected markets (LIMS) (shown in varying degrees of strength in grey, darker being stronger) based on share of resident workers that work within the IM.
Interconnected Markets 2008–2011
Source: LEAD analysis of data from US Census Bureau Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics 2008–2011.
An interesting note with this modeling is that the two counties whose commuting patterns had the most reciprocation were Durham and Wake counties, counties currently in separate Metropolitan Statistical Areas: Durham-Chapel Hill (Chatham, Durham, Orange and Person counties) and Raleigh (Franklin, Johnston, and Wake counties), respectively.
The interconnected market regions could help facilitate economic development, workforce development, and transportation planning and cooperation based on reciprocal commuting patterns. These could also help assess local labor supply and demand, and identify potential partners for larger regional projects.
In regard to these different regions (including Workforce Development Boards, Tourism, Education for Kids, and Regional Councils), LEAD will continue to provide the people and businesses of North Carolina with the proper data and geography to suit their needs — regardless of barbecue preference.
[i] The methodology is based on the USDA Economic Service’s algorithm to define commuting zones. It first joins the counties with the highest cross-commuting, and then it recalculates the average cross-commuting among the newly defined clusters. It iterates until there is only one cluster or until a predefined stopping point is reached. This methodology does not capture industry linkages or consumption patterns, and it does not directly account for population.