The Location Quotient
In an attempt to provide context regarding the employment mix within the “Stateline” region, we use the Location Quotient method. The true Location Quotient approach recognizes that each industry produces partly for export and partly for local consumption. Consider a shoe manufacturer that produces 100 shoes in a market (county) where the residents only demand 50. The result is that the manufacturer exports the extra 50 shoes. A truly accurate Location Quotient requires an accurate description of the local consumption function. However, this cannot be obtained.
As a result, a proxy is used in which we look at the national employment in an industry and the local employment in that industry. In a competitive marketplace, firms exist to fulfill demand. Since the Location Quotient (LQ) is a stylized calculation, we make a number of assumptions. First, we assume that we are not participating in international trade. Second, we assume that the demand for an employee’s output is uniform. Third, we use national employment as an estimator of the necessary employment to fill that demand; any employment beyond that level is anticipated to serve the export market.
The denominator (the share of national employment in manufacturing production) provides a measure of how much local production is needed to satisfy the local demand for manufactured goods. For example, if 15 percent of national employment is in manufacturing production, the city is assumed to need 15 percent of its workforce to satisfy is local manufacturing demand. If the city actually employs 36 percent of its workers in manufacturing production, 15% of the workers are assumed to produce for local consumption and 21% are assumed to produce for export. In this example, the LQ would be 36%/21%. As a result, a location quotient over one implies that the city or the region exports manufactured goods. It also tells us that the region is more reliant on manufacturing that the nation as a whole.
The location quotient provides an interesting perspective into the employment mix in the counties in the “Stateline” region. It tells us which industries we rely and which provide us with export based jobs. The first section of the analysis looks at basic industrial groupings. The second section looks at the specific industries within these groupings.
Basic Industry
Green County
Three industries stand out in this analysis. The first is manufacturing. Manufacturing provided a LQ of 1.73 (see Figure LQ1). This means that the county has 73% more manufacturing jobs than the United States in general. It also means that when confronted with a manufacturing recession, Green County is more susceptible to a downturn. However, since the LQ for manufacturing in Wisconsin is 1.64, the concentration of manufacturing in Green County is not unusual for the State.
The second industry that stands out is Information. This industry has an LQ of 2.14, meaning that Green County had well over twice the reliance on Information employment. This is especially noteworthy since Wisconsin’s LQ is 0.75 in the area of Information. In effect, Wisconsin’s deficit in Information employment exists despite the inclusion of Green County in the equation.
The third industry was Professional and Business Services. The LQ associated with this industry was 0.23. This small LQ was consistent with the level of underemployment in Wisconsin in the field. In effect, the small LQ implies that both Wisconsin and Green County need to import the services provided by Professional and Business Services. Given the LQ of 0.23 and an overall employment level of 411 in the industry, the calculation of the LQ estimates that Green County exports 1375 jobs in this field. Given the LQ calculations for 2001 through 2004, the industrial mix is consistent throughout the time frame. Industries that entered the period dominating the export market continued to dominate at the end of the period.
Jefferson County
One of the more interesting tales presented in the LQ calculations is Jefferson Counties dominance in Manufacturing. While the State of Wisconsin has a traditional reliance on manufacturing, with an LQ of 1.64, Jefferson County has an LQ of 2.45. As noted earlier, a high LQ could be harmful in the event of a slowdown in the industry; this is the case in manufacturing. While the State of Wisconsin witnessed stagnant job growth between 2001 and 2004 (a decline of 0.2%) and the United States experienced a loss of 0.7%, Jefferson County saw a loss of 2.7% of its jobs. This is primarily accounted for by the loss of 13.4% of its manufacturing jobs (a loss of 1510 manufacturing jobs).
It is the case of manufacturing that emphasizes the need for diversity within the employment mix. While the nation and the state experienced job growth in the field of Financial Services, Jefferson County's low LQ (0.43) constrained its ability to grab on to that engine of growth.
Lafayette County
The first industry that stands out in Lafayette County is Natural Resources and Mining. Due to the rural nature of the county, it is not surprising that agriculture is a dominant industry. However, the dominance of this industry has grown significantly over the past four years. In 2001, Natural Resources and Mining’s LQ was 2.87. In 2004, its LQ was 4.62. One explanation could be that there was a decline in the other industries which increased the significance of Natural Resources and Mining. However, in an environment of stagnant job growth, this industry saw an increase of 65 jobs (or 65% increase).
The other noteworthy industry is Trade, Transportation, and Utilities. This field witnessed an LQ of 1.6, while the State of Wisconsin has an LQ of 0.98. Once again, this is a dominant area in which the County exports output to other Counties and States.
Rock County
Rock County, the home to Janesville and Beloit, is another example of a county with a strong manufacturing base. While its employment mix mirrors Jefferson County at the basic industrial level, its size shows how size begins to smooth out the employment mix. While the county sees dominance in manufacturing and a lack of financial services jobs, its LQ is closer to the State of Wisconsin’s. Rock County has an LQ of 1.93, while the state has an LQ of 1.64 in manufacturing.
The diversity provided by the county’s large base offered some protection in the recent economic downturn. While manufacturing jobs fell by 13.5% between 2001 and 2004, overall employment resembled the State and the nation: Rock County saw overall jobs fall by 0.4%. This is due to increases in employment in all fields except Manufacturing and Trade, Transportation & Utilities. It was the existence of a diverse employment base that contributed to the stagnant (but stable) employment levels in both Wisconsin and Rock County.
Walworth County
While Walworth County continues in the pattern of high Location Quotients in manufacturing (LQ=2.01), the loss of jobs in this sector was overcome by the growth in its other dominant field: Leisure and Hospitality. While the State of Wisconsin has an LQ of 0.94, Walworth County has a LQ of 1.84 in Leisure and Hospitality. This is consistent with the entertainment and Lake amenities offered in communities such as Lake Geneva and Delavan. As a result, the losses of 210 jobs in manufacturing were offset in the corresponding field of Leisure and Hospitality. It is noteworthy that while Education and Health Services added 357 jobs, it continues to be an underemployed sector with an LQ of 0.67, while the state offers an LQ of 0.99. It would appear that the county imports its healthcare and education from other counties.
A More Microeconomic Analysis
The earlier section shows that Information has a stronger presence in Green County than it does in the nation or the state. It is possible to go deeper into the data and determine which specific subcategory of Information leads to this high LQ. This information provides the economist with valuable insight into the local economy. First, we can use this information to identify a region’s dominant industries. Since each industry witnesses the impact of external forces in different fashions, we may be able to predict the outcome of interest rate adjustment, wage increases and inflationary movements.
We can also use this data to direct economic growth decisions. For example, if the region is dominated by trucking firms, it could be that pallet manufacture or box manufacture may provide synergies in which the addition of one of these firms offers to create multiple jobs through their sales and purchases within the marketplace. Finally, if we can determine which of these dominant industries is a growing employment sector, we can encourage our educational institutions to place some emphasis on the related skills.
Green County
Not surprisingly, Green County stands out as a producer of livestock (NAICS 112) with an LQ of 5.2 and the manufacture of food products (NAICS 4.5). In a similar fashion, Green differs from the rest of Wisconsin in its lack of employment in spectator sports, accommodations, and professional and technical services. With this concentration in animal production, Green is exposed to movements in commodity prices and the potential for the internationalization of agricultural markets.
Jefferson County
Like Green County, Jefferson County is dominated by the livestock and manufacture of food products. However, it also weights its employment mix towards Printing and Related Activities (NAICS 323), Plastics Rubber Products (NAICS 326), Fabricated Metal Products (NAICS 332) and Furniture and Related Product (NAICS 337). While Jefferson County also exhibits a strong presence in the Publishing Industry (511), it is somewhat underrepresented in Telecommunications (NAICS 517) and accommodations (721). While this area is not included in the overall table due to a lack of county to county data, it appears that in many of the areas of financial services, Jefferson County is underrepresented, along with the other Stateline counties. This is a possible result of a lack of dense population necessary for the efficiencies required in these businesses.
Lafayette County
Lafayette County continues the pattern of being dependent on the Livestock and Food production industries. However, with an LQ of 21.8 as a producer of livestock (NAICS 112), this dependence appears extreme. The other three dominant employers (Nondurable wholesalers, Gasoline Stations, and Truck Transportation) may be the result of the genuinely rural nature of the county where the 129 persons working in gas stations makes it a large employer. This number of employees may also reflect the geography which requires a number of gas stations to serve its region. In terms of underrepresented industries, Printing and Related Activities (NAICS 323) stands out with its low LQ (0.4 vs the State of Wisconsin’s LQ of 2.3). However, a true analysis is difficult due to the large number of omitted industries. In the case of industries with only a few players, the three digit NAICS codes are omitted in an attempt to protect the anonymity of the firm. With a rural county, such as Lafayette, it is not surprising that there are few individual firms in any one industry. Thus the data is unavailable at this micro level.
Rock County
Rock County, the home to Janesville’s General Motor’s factory, is long known as a manufacturing center. As a result, it is not surprising to find the LQ for Transportation Equipment Manufacturing (NAICS 336) is 5.9, while the State of Wisconsin is 1.0. Thus, any news that adversely or positively affects GM also has an enormous impact on Rock County. As the largest of the Stateline Counties, Rock has the tendency to move towards the average on the other areas. It is noteworthy that in Financial Services, specifically Securities, Commodity Contract and Investment (NAICS 523) and Insurance Carriers and related Activities (NAICS 524), are underrepresented in the county. They possess LQ’s of 0.14 and 0.21 while the State LQ’s are 0.56 and 1.38.
Walworth County
With its rich natural resources and abundance of lakes, it is not surprising that Walworth County features employment in the tourism industry. Both Performing Arts and Spectator Sports (NAICS 711) and Accommodations (NAICS 721) have LQ far in excess of the State figures. Accommodations, with an LQ of 3.9, are a reflection of the resort industry in Lake Geneva and surrounding area. The 2.8 LQ for Spectator Sports evolves out of the greyhound track. However, it must be noted that the track is in transition and may contribute differently to the local economy. In addition to these areas, the overall economy also finds a unique manufacturing base. Plastics and Rubber Products (NAICS 326), with an LQ of 6.4, is clearly a dominant manufacturing industry within the area. However, the county also features employment in Fabricated Metal Products (NAICS 332 with a LQ of 2.9) and Machinery Manufacturing (NAICS 333 with an LQ of 4.9).
Conclusion
Most regions and counties rely on a small number of firms to dominate their matrix of employment. As firms grow, labor is trained and attracted to the region. Ancillary firms evolve to serve those initial firms. Specialization and agglomeration ultimately provide opportunities for economies of scale and scope. They provide for the spillover benefits that bind industries together. Crucial to the local government is the knowledge of which industries dominate their region. With this information and proper input-output modeling, predictions and prospects of economic growth can be achieved.
