© Copyright 2000 by the Wyoming Department of Employment, Research & Planning

Analysis of Wyoming State Government Attrition: Focus on Information Technology Staff1
by: Craig Radden Henderson, One Stop Program Supervisor

"For information technology occupations, wage differences between Wyoming and other states are substantial. ...Wyoming ranks forty-eighth among the fifty states [in average annual wages for information technology workers]."

In February 2000, the Program Evaluation section of the Wyoming Legislative Services Office (LSO) contracted with Research & Planning (R&P) to produce summary data and an analysis relating to post State Government employment experiences for four occupations. Our analysis was used by the LSO to prepare a more formal report to the Wyoming State Legislature, Management Audit Committee.1

This article relates the findings and shares part of the analysis we provided to LSO. Due to the length of our earlier report, the tables we reproduce here focus exclusively on the exits of Information Technology (IT) staff from State Government. Tabular data for three other occupations — case workers with the Department of Family Services (DFS), corrections officers with the Department of Corrections (DOC), and highway patrol officers with the Department of Transportation (DOT) — are included in the full report.2 By quantifying some aspects of IT attrition, at least as it impacts State Government, and communicating our findings and research methods to a wider audience, we hope to expand the policy debate and help inform future policy choices.

Research Methods

There is a continuous flow of population and labor into and out of Wyoming. As required by Wyoming statute, the vast majority of the stock of labor for employment and wages are reported to the Department of Employment (DOE) by employers on their quarterly Unemployment Insurance (UI) tax forms. Our analysis uses those quarterly reports and other administrative databases3  to describe the earnings and work experiences of State IT employees and three other occupations. Data regarding dates of employment for these occupations were provided to R&P and merged with Wyoming Wage Records earnings and demographic databases to produce our analysis. The full report includes a technical appendix detailing research methods.

Findings on All Four Occupations

• All four occupational classifications demonstrated above normal attrition rates with migration from the state as the most likely explanation.

• The highest attrition rate – for former IT employees – suggests a much higher rate of out-migration.

• For 38 former DFS employees, average wages two quarters after their exit represented a 20.1 percent decrease. The wages of the case workers may or may not have been the primary impetus for leaving their jobs.

• The analysis of highway patrol officers and IT staff show that, on average, those who exited their jobs and stayed in Wyoming to work in the private sector increased their wages.

• Corrections officers have an increased likelihood of holding a secondary job. Highway patrol officers demonstrated the highest level of multiple-job holding.

• For all four occupational groups, multiple-job holding rates fell within the normal range of labor attachment for State Government as a whole.

• Multiple-job holding by State Government employees is associated with the greater likelihood that these employees may exit State employment.

Employee Strategies and Labor Market Flow

For any given stock of employed workers at any given point in time, it is normal for that stock of workers to diminish, or experience attrition, over time. Attrition occurs due to worker death, injury, retirement, withdrawal to meet the needs of young or sick family members, new job opportunities in another state, and for other reasons. During the period of study, 1995-1998, all four occupational classifications demonstrated above normal attrition rates with out-migration the most likely explanation.

In the first quarter after exit from their State jobs, only 50.0 percent of DFS staff were found working in Wyoming. This contrasts markedly with the normal attrition rate. The rate at which all workers in the 25-34 year age group (the interval containing the mean age of former employees for DFS, DOC, DOT, and many IT occupations) exit the Wyoming Wage Records file is 9.9 percent with 90.1 percent still working after one quarter. Therefore, the norm indicates that on average, among all occupations, only about 10 percent of employees of this age group failed to appear on Wage Records in the following quarters (see Figure 1). One interpretation is that much of the difference between the 90.1 percent retention rate for all workers aged 25-34 and the 50.0 percent retention rate for DFS employees represents out-migration. Other interpretations are identified in the discussion of limitations near the end of this report. The highest attrition rate difference among our selection of occupations – between 90.1 percent on the WR file and 33.7 percent for former IT employees – suggests a much higher rate of out-migration.

For IT occupations, wage differences between Wyoming and other states are substantial. For example, the wage for public and private IT systems analysts [Occupational Employment Statistics (OES) code 25102] was $19.53 per hour in Wyoming in 1998. For computer programmers (OES 25105), the 1998 wage was $16.67. In Utah, the hourly wages for systems analysts and computer programmers were $22.80 and $21.90, respectively, and in Colorado they were even higher (systems analysts, $28.71/hour; computer programmers, $25.26/hour). See Figure 2 for a broad-based index of state wage differences for all IT occupations. Wyoming ranks forty-eighth among the fifty states.

Labor Market Outcomes for Those Exiting State Employment and Remaining in Wyoming

Table 1 shows time lines of employment and wages for IT employees who exited State employment. On average, those who exited their jobs and stayed in Wyoming to work in the private sector increased their wages each of the two quarters following their exit. Among IT staff, 17 of 92 moved to private sector employment in Wyoming, on average earning quarterly wages of $7,887, $770 above the $7,117 they earned the quarter prior to their exit. Those 14 who moved to other positions within Wyoming government earned slightly less than their former quarterly wages ($6,850). The 28 who were found in WR two quarters following their exit earned on average 3.5 percent more than they did when employed as IT staff in State Government.

Employment Strategies of Those Who Exited During 1995-98: Multiple-Job Holding and Secondary Employers

In past editions of Wyoming Labor Force Trends, R&P has published and applied a classification system to labor market research characterizing varying degrees of labor force attachment exhibited in Wage Records.4 Multiple-job holders, one category within this classification system, are defined as those employees found in Wage Records who worked for three or more employers in the same quarter or who worked for the same two employers for each of two consecutive quarters or more. Other categories use incidences of secondary employment on an itinerant or occasional basis which are often associated with employees’ flow in and out of the labor market – or market churning. Table 2 shows the incidences of IT employees who met the definition of multiple-job holder during the year of exit. Our premise for studying this data is to determine whether or not there is a relationship between multiple-job holding and State Government attrition for a given occupation.

The multiple-job holding rate for all State and Local Government workers in 1998 was 14.9 percent.5 For IT staff who exited employment, the data show a normal multiple-job holding pattern of 14.1 percent.

Based on our published data, holding a secondary job (e.g., working in the private sector in the first quarter and then working the third and fourth quarters as a State employee) is normal for 22.6 percent of all State and Local Government workers.6 However, whether for reasons associated with exit (a form of market churning) or other reasons, three of the occupational exit groups in our initial study displayed a higher than normal rate of holding secondary jobs during their exit year (though not strictly meeting our definition of multiple-job holders). DFS case workers held secondary jobs at a rate of 35.5 percent.7 DOC corrections officers held secondary jobs at a rate of 35.3 percent.8 DOT highway patrol officers held secondary jobs at a rate only slightly higher than the norm, 24.3 percent.9 

Table 3 is useful in showing patterns of multiple-job holding and holding of secondary jobs by all of those who were actively employed as IT workers during 1998. Multiple-job holders comprised 10.4 percent of all IT employees in State Government in 1998. Another 9.1 percent worked a secondary job (but are counted separately because they did not meet R&P’s definition of a multiple-job holder). Though multiple-job holding and the holding of secondary jobs by all IT workers (and the active State employees in the other three occupations in our initial study) were within the normal range of labor attachment for Government employees as a whole, those IT workers who eventually exited State employment demonstrated slightly increased rates of multiple-job holding (14.1%) and secondary job holding (20.7%), compared to their occupational group in 1998.

The comparison of data in Table 3 with Table 2 indicates that multiple-job holding and the holding of secondary jobs on an itinerant basis by State employees are indicators associated with the greater likelihood that these employees may exit State employment, whether for financial reasons or driven by other circumstances.

Without data by occupation for all of State Government over time, we cannot determine the extent to which multiple-job holding represents occupation-specific behavior. Without longitudinal data, we cannot determine how extensively multiple-job holding may be considered a function of change in general economic conditions. For example, in 1990 Wyoming’s average weekly wage ranked thirty-seventh among the 50 states, based on UI covered employment and total payroll.10 By 1996, our ranking fell to 45, and we still ranked forty-fifth in the nation in 1998. Only by placing occupational wages within the broader economic context can we begin to understand the labor market strategies of employees.

As an example of how the national market for technology staff affects employment attrition rates of IT staff, Figure 2 shows the distribution of average annual wages of IT staff, including both the public and private sectors for all states and the U.S. Figure 2 has been updated since the initial report was provided to LSO. The data were based on an average of Occupational Employment Statistics (OES) wage survey data aggregated for three years, 1996-1998.11 The mean annual wage for the U.S. was $49,331. The average annual wage for those employed in IT occupations in Wyoming was $33,793. Figure 2 shows only South Dakota, Puerto Rico, and North Dakota had lower IT wages than Wyoming. In contrast, Colorado ranked ninth in the nation ($50,152).

Demographic Comparisons by Occupation of Those Who Exited State Government During 1995-1998 with the Active Occupational Workforce in 1998

Table 4 illustrates the distribution by age and gender of IT staff exiting State employment. Characterizing those actively holding similar IT positions among various State agencies, demographic data in Table 5 permit us to identify the differences between those who work at a given occupation in State Government and those who exit their job.

Analysis of Table 5 shows that IT staff in 1998 had an employment ratio of 61.0 percent male to 29.9 percent female (no demographic data were available for 9.1%). Between 1995-98, female staff exited IT at a rate of 40.2 percent compared to the male exit rate of 48.9 percent. Thus, as a percentage of the IT workforce, younger men are probably more likely to leave State employment. The difference in mean age (8.5 years) between those exiting IT during 1995-98 (34.8 years) and those actively employed in 1998 (43.4 years) probably reflects the national market for IT staff and the likelihood that younger people are more likely to respond to it than older workers who, generally, have more family and community attachments.

Limitations of Occupational Exit Analysis

While it is possible to place an occupational exit analysis in the context of such broader issues as the “brain drain”12 and historic trends in the level of turnover by industrial sector,13 the time constraints imposed upon the study did not permit more comprehensive analysis.

In addition, since the State lacks comprehensive analysis of exit behavior in general, it is difficult to determine how extensive or how unique the behavior of the four occupations is within State Government or to what extent pay or other policies enhance employee retention and cost control. An ongoing program of market-based occupational analysis would lead to a more complete understanding than the narrow, retrospective focus required by the time constraints in preparing our initial report to LSO.

All of the occupations in this study require some post-high school training. We cannot account for the migration decisions of families when the spouse may be unable to use his or her post-high school education or training in finding suitable work.

Contextual variables for the family (e.g., the availability and cost of day care) are not available to us, nor are non-monetary costs and benefits of the particular type of work part of this study’s components. Given that case workers’ average annual wages during the study period are 173 percent above the poverty level for a family of three ($24,448 compared to $14,150), for example, it may be logical for a DFS case worker to care for children at home rather than work and pay for day care.14 

Additional limitations of the administrative data approach to analysis are discussed at length in the publication cited in Endnote 3.

Conclusions

The State is a large purchaser of some of these occupations, such as IT services. The choice then is to pick up the cost at the point of purchase with a highly visible market signal (e.g., higher wages) or in the less visible system of recruitment and training. The price is the same. For example, “the qualitative costs associated with technology-staff turnover are potentially high, as infrastructure critical to State Government operations could be impacted.”15 The question is how much the service is valued and how and who bears the costs.

Despite the limitations of the administrative records approach to the analysis of market outcomes for State employees who exit employment, it is clear that the approach has promise. Even more promising is the fact that confidentiality agreements between states will eventually permit market-based tracking of former workers beyond state borders for statistical purposes.

 

1Wyoming Legislative Services Office, Program Evaluation Section, Turnover and Retention in Four Occupations, May 2000, http://legisweb.state.wy.us/progeval/reports/2000/turnovr/toc.htm (August 31, 2000).

2Wyoming Department of Employment, Research & Planning, "Analysis of Wyoming State Government Attrition for Selected Occupations," [submitted to Legislative Services Office, Program Evaluation Section pursuant to MOU with Department of Employment, Research & Planning Section], March 10, 2000. The full report appears as Appendix H in Outlook 2000: Detailed Occupational Projections and Labor Supply (see Endnote 7 for full citation).

3Wyoming Department of Employment, Research & Planning, Wyoming Wage Records 1992-1998: A Baseline Study, November 1999, pp. 2-8. This publication contains a comprehensive bibliography of all publications and articles published by the agency that relied on Wage Records research, principally articles published in Wyoming Labor Force Trends.

4Wyoming Department of Employment, Research & Planning, Wyoming Wage Records 1992-1998: A Baseline Study, November 1999.

5Ibid., p. 64.

6Ibid., p. 70. Of those working in Government, 22.6 percent worked more than one job during 1998. This percent was calculated by subtracting the percent of Government workers with no secondary job (77.4%) from 100 percent.

7Wyoming Department of Employment, Research & Planning, Outlook 2000: Detailed Occupational Projections and Labor Supply, Table 5a, p. H-22.

8Ibid., Table 5b, p. H-22.

9Ibid., Table 5c, p. H-23.

10Carol Kjar, "Competitive Wage Ranking: Retaining Wyoming’s Workforce," Wyoming Labor Force Trends, March 2000, pp. 16-17.

11The average was based on the following Occupational Employment Statistics (OES) occupational codes: 25102, 25103, 25104, 25105, 25108, 25111, 25199.

12Steven Butler, Tracking University of Wyoming Graduates into the Wyoming Work-force: A report prepared for the Research and Planning Section of the Employment Resources Division, State of Wyoming, September 17, 1995. See also Wyoming Department of Employment, Research & Planning, Under the Lamppost: A Report to the Wyoming Workforce Development Council, November 1998.

13Mike Evans, "Job Turnover and Hire Rates in Wyoming: Which is Greater: Job Creation or Job Destruction?," Wyoming Labor Force Trends, June 1999, pp. 1-5.

14Tony Glover, "The Flow of Labor in Wyoming: Department of Family Services, Division of Vocational Rehabilitation and Job Training Partnership Act Clients," Wyoming Labor Force Trends, March 2000, pp. 1-7.

15Wyoming Legislative Services Office, Program Evaluation Section, Turnover and Retention in Four Occupations, p. 26.


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