Location Quotients
COMMUNITY INDICATORS
| Community Indicators are intended to stimulate thoughtful dialogue about your community, they can help identify potential issues, opportunities and problems facing your community. This communication piece is also intended to increase use and understanding of readily accessible demographic data on the web. |
Issue 4, July, 2003
By: Bill Pinkovitz
Center for Community Economic Development
University of Wisconsin Extension 610 Langdon Street, Room 334
Madison, WI 53703 (608) 265-8136, cced@uwex.edu , http://www.uwex.edu/ces/cced/
We have all seen employment data presented as displayed in Table 1 -- employment in each major industry sector as a percentage of total employment. According to the 2000 Census, 20% of all workers in Rhinelander Wisconsin were employed in Retail in 1999. Similarly, 15.8% were employed in Health Care and Social Assistance , and 10.5% in Manufacturing .
TABLE 1
Percentage of 1999 Employment by Industry Sector
Rhinelander, WI
| INDUSTRY |
Rhinelander, WI |
| Agriculture; forestry; fishing and hunting |
3.0% |
| Mining |
0.0% |
| Construction |
5.1% |
| Manufacturing |
10.5% |
| Wholesale trade |
4.0% |
| Retail trade |
20.0% |
| Transportation and warehousing |
2.5% |
| Utilities |
0.9% |
| Information |
4.4% |
| Finance and insurance |
1.6% |
| Real estate and rental and leasing |
1.2% |
| Scientific; and technical services |
2.0% |
| Management of companies and enterprises |
0.0% |
| Administrative and support and waste management services |
2.4% |
| Educational services |
7.6% |
| Health care and social assistance |
15.8% |
| Arts; entertainment; and recreation |
1.0% |
| Accommodation and food services |
9.2% |
| Other services (except public administration) |
4.1% |
| Public administration |
4.6% |
Are these percentages higher than average? Are they lower than average? Comparing employment in Rhinelander to other similar Wisconsin cities, can provide additional useful insights into the Rhinelander economy. Table 2 includes similar data for the United States, Wisconsin, and a group of comparable Wisconsin communities (Ashland, Hayward, Hurley, Marshfield, Shawano, and Superior).
Table 2
Percentage of 1999 Employment by Industry Sector
INDUSTRY |
Rhinelander |
Comparable Communities |
US |
WI |
Agriculture; forestry; fishing and hunting |
3.0% |
1.2% |
1.5% |
2.7% |
Mining |
0.0% |
0.0% |
0.4% |
0.1% |
Construction |
5.1% |
5.3% |
6.8% |
5.9% |
Manufacturing |
10.5% |
15.8% |
14.1% |
22.2% |
Wholesale trade |
4.0% |
2.5% |
3.6% |
3.2% |
Retail trade |
20.0% |
15.0% |
11.7% |
11.6% |
Transportation and warehousing |
2.5% |
2.7% |
4.3% |
3.7% |
Utilities |
0.9% |
0.7% |
0.9% |
0.8% |
Information |
4.4% |
1.7% |
3.1% |
2.2% |
Finance and insurance |
1.6% |
2.6% |
5.0% |
4.9% |
Real estate and rental and leasing |
1.2% |
0.8% |
1.9% |
1.2% |
Scientific; and technical services |
2.0% |
3.1% |
5.9% |
4.0% |
Management of companies and enterprises |
0.0% |
0.0% |
0.1% |
0.1% |
Administrative/support/waste mgmt services |
2.4% |
1.4% |
3.4% |
2.5% |
Educational services |
7.6% |
9.2% |
8.8% |
8.5% |
Health care and social assistance |
15.8% |
19.8% |
11.2% |
11.6% |
Arts; entertainment; and recreation |
1.0% |
2.3% |
1.8% |
1.5% |
Accommodation and food services |
9.2% |
7.6% |
6.1% |
5.8% |
Other services (except public administration) |
4.1% |
5.0% |
4.9% |
4.1% |
Public administration |
4.6% |
3.1% |
4.8% |
3.5% |
Table 2 reveals that Rhinelander has a significantly higher percentage of employees working in Retail and a much lower percentage of the workforce employed in Manufacturing than Wisconsin, the United States, or the Comparable Communities. Accommodations and Food Service and Information also rank relatively high when compared to the other categories.
Comparing these percentages is useful, but somewhat cumbersome. Location Quotients provide an easier way to compare communities and analyze the Rhinelander economy. A Location Quotient for an industry is the simple ratio of the percentage of local employment in the industry divided by the percentage of national employment in the industry.
Location Quotients (LQ) are used to help identify export industries in a community, those industries producing more than needed to meet local demand and import industries, those producing less than enough to meet local demand. A Location Quotient greater than 1.0 indicates that a community has proportionately more people than the national average employed in a specific industry sector. This implies that a community is producing more of a product or service than is consumed by local residents. The excess is available for export outside the community. A Location Quotient less than 1.0 suggests that a community is not producing enough of a product or service to meet local demand, and is importing to meet local demand. A Location Quotient approximately equal to 1.0 indicates that a community is producing enough to meet local demand.
In Community Economic Analysis: A How to Manual , Hustedde, Shaffer, and Pulver suggest that a location quotient of at least 1.25 is required to consider classifying a local industry as an exporter. Similarly, they recommend that a location quotient of .75 or less is needed to categorize an industry as an importing sector.
Location Quotient |
Export/Import Status |
= .75 |
Import Industry |
.75 to 1.24 |
Self-Sufficient Industry |
= 1.25 |
Export Industry |
Identifying local export industries (LQ > 1.25) is useful as it provides a measure of the degree of industry specialization within a community. A community with a high location quotient in a specific industry may mean that the local economy has a competitive advantage in that industry. There may be economic development opportunities because of existing economies or synergies that make a community more attractive to businesses in related industries. A Location Quotient significantly lower than 1.0 may indicate an import substitution opportunity, the potential to develop local businesses to fill the gap and meet local demand.
Location Quotients and Industry Clusters: An industry cluster is a geographic concentration of firms in the same or related industries. Typically, firms in an industry cluster serve similar markets, share a common labor pool, use common production inputs and/or related technologies. The use of industry clusters is becoming the priority economic development strategy for many states. Wisconsin and other states are using Location Quotients as a way to identify potential industry clusters. Location Quotients provide an easy method to identify existing industry clusters or industries with the potential to develop into a cluster.
Traditionally, Location Quotient s are calculated by comparing local employment to national or regional employment. Calculating Location Quotients by comparing a local community to other similar communities provides a new perspective and insight into the local economy. The following example compares employment in Rhinelander, Wisconsin to six comparable northern Wisconsin communities (Ashland, Superior, Hayward, Hurley, Shawano, and Marshfield).
For more information on industry clusters, I recommend the Governor's Guide to Cluster-Based Economic Development available free at the National Governor's Association website at:
http://www.nga.org/center/divisions/1,1188,C_ISSUE_BRIEF^D_4063,00.html
You can also read the past discussion of the Governor's Guide in the Reading Room at:
http://www1.uwex.edu/ces/cced/readingroom/reviewedbook.cfm?book_id=48
|
Table 3 LOCATION QUOTIENTS -- 2000 RHINELANDER, WI |
|
INDUSTRY |
COMPARABLES |
US |
Wi |
Agriculture; forestry; fishing and hunting |
2.35 |
1.99 |
1.10 |
Construction |
0.97 |
0.76 |
0.87 |
Manufacturing |
0.67 |
0.75 |
0.47 |
Wholesale trade |
1.67 |
1.12 |
1.26 |
Retail trade |
1.32 |
1.70 |
1.72 |
Transportation and warehousing |
0.86 |
0.58 |
0.67 |
Utilities |
1.35 |
1.03 |
1.15 |
Information |
2.63 |
1.42 |
1.98 |
Finance and insurance |
0.64 |
0.32 |
0.33 |
Real estate and rental and leasing |
1.25 |
0.64 |
0.99 |
Scientific; and technical services |
0.68 |
0.35 |
0.51 |
Administrative/support/waste mgmt services |
1.81 |
0.72 |
0.98 |
Educational services |
0.84 |
0.87 |
0.90 |
Health care and social assistance |
0.80 |
1.41 |
1.36 |
Arts; entertainment; and recreation |
0.42 |
0.54 |
0.65 |
Accommodation and food services |
1.20 |
1.51 |
1.59 |
Other services (except public administration) |
0.81 |
0.84 |
1.01 |
Public administration |
1.43 |
0.97 |
1.01 |
Calculating Location Quotients for the City of Rhinelander compared to the United States shows high location quotients for Retail Trade (1.70), Information (1.42 ), Health Care and Social Assistance (1.41), and Accommodations and Food Services (1.51). The ratios are similar when comparing Rhinelander to the U.S. and Wisconsin . However, a very different picture emerges when Location Quotients are calculated for Rhinelander against six other Northern Wisconsin communities. For example, when compared to other communities in the region, the location quotient for Health Care and Social Assistance falls from 1.41 to .80. The Location Quotient for Information increases from 1.42 to 2.63.
To generate similar data for other Wisconsin counties or communities, download our Excel ® worksheet by clicking here.
Why the big differences? Anyone familiar with Northern Wisconsin knows that Marshfield is home to a large regional medical center. Removing Marshfield from the list of comparable communities increases the location quotient for Rhinelander for Health Care and Social Assistance from .80 to 1.16. This indicates that proportionately, Rhinelander employs a few more people in the Health Care and Social Assistance category than the five comparable communities. Comparing Marshfield to the other six communities results in an expected high location quotient of 1.88 for Health Care and Social Assistance .
So, why the high location quotient for Rhinelander in the Information group? First, let's take a look at what comprises the NAISC Information category.
According to the U.S. Census Bureau, the NAICS category Information (51) includes establishments engaged in: (1) producing and distributing information and cultural products, (2) providing the means to transmit or distribute these products as well as data or communications, and (3) processing data. Specific businesses include: Publishing industries, including software publishing, and both traditional publishing and publishing exclusively on the Internet; motion picture and sound recording industries; broadcasting industries, including traditional broadcasting and those broadcasting exclusively over the Internet; the telecommunications industries; the industries known as Internet service providers and web search portals, data processing industries, and the information services industries. So, what is going on in Rhinelander?
Looking at the raw U.S. Census data helps answer this question. The Census reports that in 1999, there were 149 Rhinelander residents (4.4% of total employment) employed in the Information industry. That is not a lot of people when compared to the 687 employed in Rhinelander in Retail and 539 employed in Health Care, but the percentage of people in Rhinelander employed in the Information industry is significantly higher than Wisconsin, the U.S. or the six Comparable Communities.
A conversation with the Donna Rae Jacobsen, Oneida County Extension educator, provided some addition insight on this seemingly high Location Quotient for Information for Rhinelander . She explained that Rhinelander, a community of 7,749 is home to three radio stations, one television station, a newspaper and a weekly shopper, an internet service provider, and headquarters of a large ( > 600 employee) internet-based retail/wholesale distributor that includes a retail call center subsidiary that likely reports under the Information NAISC code.
Mystery solved? Perhaps, but this example again illustrates that Location Quotients or any other Community Indicator only provides one snapshot of a community. To provide any real value, the information they provide must be supplemented with other tools, information, and local knowledge.
Some Other Caveats: Location quotients provide a quick and easy method to identify potential opportunities in a community. However, Shaffer warns that because they can be easily and inexpensively calculated using readily available data, location quotients are often misused. He offers the following caveats:
• A location quotient greater than 1.25 does not necessarily mean that a local industry is exporting. There may simply be excessive local demand. Similarly, a location quotient near 1.0 or less than .75 does not mean a community is self-sufficient or that import substitution opportunities exist.
• Location quotients assume that productivity levels are the same throughout the country. If local productivity is high, local industries may be exporting much more than the location quotient implies. If lagging technology or an inefficient labor force depress local productivity levels, location quotients may be artificially high.
• Location quotients may be distorted by cross hauling , a phenomenon that occurs when a community produces goods or services for export and simultaneously imports the same goods and services.
• In many cases, employment data is only available in very broad categories. A location quotient of 1.0 for manufacturing may obscure the fact that a community has a very high location quotient in one manufacturing sector that is being overshadowed by other local manufacturing sectors with very low location quotients.
Mindful of the shortcomings of location quotients, they represent a good starting point to begin identifying potential economic development opportunities, enhance local residents' understanding of the local economy, stimulate local discussion, and provide useful information to support local planning efforts.
To learn more about Location Quotients and other economic analysis tools, I recommend:
Community Economics, Ron Shaffer, Iowa State University Press, 1989 (Ron's new edition of Community Economics is expected to be available Fall 2003).
Community Economic Analysis: A How to Manual , Hustedde, Shaffer, and Pulver, North Central Regional Cneter for Rural Development, 1995
Using Employment Data to Better Understand Your Local Community, Community and Economic Development Toolbox, Martin Shields. Cornell University and Pennsylvania State University Cooperative Extension, http://www.cardi.cornell.edu/cd_toolbox_2/tools/empdata/intro.cfm
Understanding Your Industries , University of Minnesota Institute of Public Affairs, http://www.hhh.umn.edu/centers/slp/projects/edweb/indcook.htm#access
Would you like to be able to generate data like this for your county or community? It is easy. We have done most of the work for you.
Simply go to the CCED Website at: http://www.uwex.edu/ces/cced/Indicators_Links.htm#location. Then, download the Excel® spreadsheet and view the Powerpoint® presentation that provides easy step-by-step instructions that will enable you to generate similar data for any Wisconsin county and most Wisconsin communities. If you have questions or problems contact us at: cced@uwex.edu
