Appendix A

Technical Appendix Chapter 1

Section 1-a.

Identifying and providing summary reports of occupations, educational and experience levels, residency, levels of attachment to the labor market (e.g., steady employment for a single employer, multiple job holding), commuting patterns, and other characteristics or behaviors of individuals is possible, but more problematic than providing characteristics such as age, gender, and earnings levels.

One way Research & Planning (R&P) plans to meet our clients' needs for various workforce information is through the Wyoming Workforce Information System (WYWINS). WYWINS is a map-driven, Internet database of demographic and labor market information, representing Wyoming's contribution to America's Labor Market Information System (ALMIS). ALMIS is a federal initiative attempting to create an interstate network of localized labor market information. Each state compiles information on labor demand and supply in standard formats to facilitate data sharing and support local, regional, and national economic and workforce development. The database includes access to a comprehensive directory of Wyoming employers that can be searched according to industry, size of business, and zip code among other criteria. Once it is released, a link to WYWINS will initially be available at our home page.

Section 1-b.

There are several possible explanations for missing demographics. Agriculture's employees, for example, may be less likely to use employment services than employees of other industries, due to physical distance from employment centers. Thus, their demographic data would not be part of the Employment Services databases. This may change as governmental services increasingly reach people in their homes, local libraries, and elsewhere through the Internet. Many young people, particularly those who are school aged and are new participants in the labor market, may not have earned their driver's licenses yet. Demographic data would therefore not be available through the Driver's License database on these individuals, many of whom hold their first jobs in the Retail Trade industry (e.g., fast food restaurants). The Construction and Services industries employ many contract workers holding out-of-state driver's licenses. If workers have not filed for UI claims or registered with Employment Services in Wyoming, we are less likely to have demographic information on them.

Technical Appendix Chapter 3

Where do Occupational Projections Come From?

Occupational projections are derived from Industry projections and data collected for the Occupational Employment Statistics (OES) survey. Industry projections use historical trends in employment within an industry to predict whether the industry is expected to expand or contract over the next decade. OES collects data at the establishment level on the number of employees in an occupation within an industry. Table 3-1 is an example of how the two sets of data combine to produce the occupational projections. Table 3-8 shows a complete listing of Wyoming's occupational projections.

From the industry projections (see Table 3-9), we see general merchandise stores (SIC 53) has a base (current year) employment of 4,936. Employment is projected to reach 5,992 by 2008. From the OES survey we learn the percent of the employment in that occupation-industry combination within the specific 2-digit industry as shown in Table 3-9. Lastly, by multiplying the base employment (4,936 for SIC 53) with the percent of employment in the occupation-industry combination (36.1% for retail salespersons), we can determine the number of individuals (1,780) working as retail salespersons within general merchandise stores. The same principle applies to the projected employment.

These methods are applied to the remaining 2-digit industries, and the data are aggregated to the desired industry level. From the example in Table 3-9, the occupation cashiers occurs in both of the industries presented. The aggregate of the two industries combined is the number of cashiers in SIC 53 plus the number of cashiers in SIC 54 for both the base and projected years. Therefore, the new aggregated base and projected employment for cashiers becomes 2,443 and 2,712, correspondingly.

The demonstration of calculating occupational projections was necessarily simple. The software used to do the actual computations takes other factors into consideration including census data, national trends in occupations, and national staffing patterns to adjust for missing data. The end product however is the ability to produce occupational projections at the 2-digit, major industry, and statewide levels.

Technical Appendix Chapter 5

Occupational Employment Statistics (OES) Wage Survey

The Occupational Employment Statistics (OES) wage program collects wages and employment, for the 50 states and U.S. territories, for over 750 occupations. The OES program surveys approximately 400,000 establishments 23 per year nationwide. The 1998 OES data is actually a combination of survey data collected for the years 1996, 1997, and 1998, thus including over 1.2 million establishments. Each state is responsible for collecting its own data and submitting the data to the Bureau of Labor Statistics (BLS) for compilation. One product of this endeavor is the annual Wyoming Wage Survey.24

The data collected by the OES survey includes the industry of the employer (via ES-202)25 and information about jobs including the occupation of jobs worked in each firm and the rate of compensation (hourly wage). The OES survey includes all full-time and part- time wage and salary jobs in non-farm industries. The survey does not cover the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers. As the survey only collects data on a sample of representative firms, data are adjusted to the full universe count of employment (using the ES-202 data). For example, if data were collected from 25 establishments in the metal mining industry, representing 50 percent of the employment in that industry, the number of jobs in a specific sampled occupation would be adjusted to represent the total employment for the metal mining industry.

Although the OES program collects data on more than 750 occupations, not every state reports data on all occupations. This is due to issues surrounding confidentiality and/or the absence of industries only in some states. For example, if there were only three lawyers in the state of Wyoming and their occupational wage data were published, it becomes possible to ascertain an individual's wages. In this case, the data are suppressed to assure anonymity of the individual. Therefore, Wyoming's 1998 Wage Survey only presents data for 417 occupations.

Wage and Occupation Table

The "Occupation, Wage, and Employment Table" was created using the data from BLS, which include occupational information on total employment and average hourly wage for the nation, each of the 50 states, and U.S. territories. The education/typical experience level was downloaded from the BLS's "Occupational Employment, Training, and Earnings" Internet site, and matched to the OES survey data on the specific occupation.


The data provided in the "Occupation, Wage, and Employment Table" were grouped on typical education/experience level. It is not appropriate to calculate the average wage per education/experience level without considering the total employment for each occupation in the individual states. For example, suppose there are only two occupations in Wyoming and Texas requiring an associate's degree (see Table 5-4). The hypothetical example given in Table 5-4 demonstrates the difference between straight and weighted averages. The problems with straight averaging arise because not all occupations requiring a specified level of training are distributed evenly from state to state. This problem is compounded when it is known that specific occupations are paid different wages from state to state. The lower tier of Table 5-4 shows the steps needed to correct for the variations in employment and wages. It also shows how to calculate the percent difference in the wages of Texas and Wyoming.

23 An establishment is the physical location of a certain economic activity, for example, a factory, mine, store, or office. Generally a single establishment produces a single good or provides a single service. An enterprise (a private firm, government, or non-profit organization) could consist of a single establishment or multiple establishments. A multi-establishment enterprise could have all its establishments in one industry (i.e., a chain), or could have various establishments in different industries (i.e., a conglomerate).

24 Wyoming Department of Employment, Research & Planning, Wyoming Wage Survey, January 2000.

25 The ES-202 program derives its data from quarterly tax reports submitted to State Employment Security Agencies by employers subject to State Unemployment Insurance (UI) laws and from Federal agencies subject to the Unemployment Compensation for Federal Employees (UCFE) program. These reports provide information on the number of people employed and the wages paid to the employees each quarter. The program obtains information on the location and industrial activity of each reported establishment, and assigns location and standard industrial classification codes accordingly. This establishment level information is aggregated, by industry code, to the county level, and to higher aggregate levels.

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Last modified on August 9, 2001 by Valerie A. Davis.