Illustrated History of Employment LogoAn Illustrated History of Employment (1990 & 1994)

Introduction: Purpose and Use of the Data

Effective problem solving is predicated on knowledge about the nature of the problem and the ability to monitor the results of strategies applied to it. The purpose of this publication is to describe in graphic terms the demand side of the labor market equation using the same measurement technique from the national, to the state, to the county level for two periods: 1990 and 1994 (refer to Table 1: Employment for the United States, Neighboring States, Wyoming & Wyoming’s Counties). In general, at the highest conceptual level: comparing the Goods-Producing sectors of the labor market (Mining, Manufacturing and Construction) with the Services-Producing sectors of the labor market, the demand for labor is divided quite consistently between the nation as a whole and the states in the North-Central (Plains and Mountain) Region of the country. When including (by reference only) the share of employment defined as production Agriculture, one-fifth of the employment in the United States and the states in the region falls into the Goods-Producing category. And by this definition, Goods-Production is in decline as a proportion if not in amount of total employment.

Table 1: Employment for the United States,
Neighboring States, Wyoming & Wyoming's Counties
EmploymentChange in Employment
1990-1994
19901994NumericPercent
United States108,658,056112,613,8313,955,7753.6%
Colorado1,503,6731,738,239234,56615.6
Idaho386,056462,65176,59519.8
Montana286,562328,24841,68614.5
Nebraska710,969772,41261,4438.6
North Dakota245,705274,29728,59211.6
South Dakota274,171316,19442,02315.3
Utah694,274827,451133,17719.2
EmploymentChange in Employment
1990-1994
19901994NumericPercent
Wyoming190,705209,43118,7269.8%
Northwest29,69332,7763,08310.4%
Big Horn
3,2113,3211103.4
Fremont
11,70012,7791,0799.2
Hot Springs
1,9102,0751658.6
Park
9,71511,0401,32513.6
Washakie
3,1573,56040312.8
Northeast29,06532,1923,12710.8%
Campbell
14,07215,6401,56811.1
Crook
1,6551,8061519.1
Johnson
2,2262,4131878.4
Sheridan
8,92710,1891,26214.1
Weston
2,1852,143-42-1.9
Southwest41,88747,4285,54113.2%
Lincoln
4,3044,6383347.8
Sublette
1,7632,02326014.7
Sweetwater
18,29019,9351,6459.0
Teton
10,32613,1072,78126.9
Uinta
7,2047,7245207.2
Southeast49,52853,9614,4339.0%
Albany
12,15512,8977426.1
Goshen
3,6353,9663319.1
Laramie
30,26533,4363,17110.5
Niobrara
744758141.9
Platte
2,7292,9041756.4
Central38,10738,8847772.0%
Carbon
6,7386,692-46-0.7
Converse
3,6013,97837710.5
Natrona
27,76828,2144461.6

However, when the analysis shifts to explaining why the value of jobs in Wyoming declined by 3.0 percent between 1990 and 1994 (refer to Table 2: Nominal and Real Pay for the United States, Neighboring States & Wyoming), while the value of jobs in the North-Central Region rose in most states, differences begin to emerge which suggest a stream of questions. In 1994, employment in all states in the region was dominated by Retail Trade, Local Government, Services and Manufacturing while in Wyoming, employment in Mining replaced Manufacturing as the key element in the Goods-Producing sector. (It should also be pointed out that Local Government employment in Wyoming, in contrast to all other states, includes a share of publicly owned medical services.) What this distinction implies, if anything, about falling real earnings demands considerably more research and analysis than we intend to present here. This publication can be treated as a starting point in simply describing the demand side of the equation in the labor market and serve the purpose of assisting in raising more effective questions.

Table 2: Nominal and Real Pay for the United States, Neighboring States & Wyoming
Nominal Annual PayChange in Nominal Annual PayReal Annual PayChange in Real Annual Pay
1990-19941990-1994
19901994NumericPercent19901994NumericPercent
United States$23,602$26,939$3,33714.1%$18,058$18,177$1190.7%
Colorado22,90826,1643,25614.217,52717,6551280.7
Idaho18,98021,9382,95815.614,52214,8032811.9
Montana17,89520,2192,32413.013,69213,643-49-0.4
Nebraska18,57721,5002,92315.714,21314,5072942.1
North Dakota17,62619,8932,26712.913,48613,423-63-0.5
South Dakota16,43019,2552,82517.212,57112,9934223.4
Utah20,07422,8112,73713.615,35915,392330.2
Wyoming$20,057$22,071$2,01410.0%$15,346$14,893-$453-3.0%

Examination of published details (refer to the April 1996 issue of Wyoming Labor Force Trends and the United States Department of Labor’s Bureau of Labor Statistics Bulletin 2467) indicates that—in comparison to Colorado’s labor market, for example—employment in Wyoming’s Retail Trade industry was responsible for 26.2 percent of growth from 1990 to 1994. But it was responsible for only 20.7 percent of growth in Colorado during the same period. Rapid growth in relatively low wage industries is problematic for both states . However, the situation is even more difficult in Wyoming where the average wage in the retail sector is 18.7 percent less than it is in Colorado. This pattern is repeated in the high growth Services industry where Wyoming’s earnings per job fall 31.6 percent below those of Colorado. While Retail Trade and Services growth dominate both labor markets, it is clear that something more complicated “explains” the difference in earnings levels.

Explaining the differences between states that appear in graphic form in this publication is a much more complicated step than we intend to take here. What this publication can do is open the door to understanding some of the basic components of the employment situation and serve as a pointer for those interested in additional research (refer to the Technical Appendix in this publication and Research & Planning’s Annual Covered Employment and Wages publications). Comparison over time is central to any analysis aimed at understanding underlying processes while comparison of the employment situation among states in the region allows one to focus on common factors such as climate, resources, transportation systems, remoteness and population density as factors that may explain the distribution of employment opportunities. The ability to discard an explanation—geographic location as a barrier to growth, for example—is only possible through comparison of labor market outcomes among similarly situated states or similarly situated counties.

 
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