WCC_PSEIS_Business_MainReport

29 Chapter 3: Methodology Business program student headcount over the past 44 years, from 1978-79 to FY 2021-22. We apply a 44-year time horizon to include all alumni active in the regional workforce who have not reached the average retirement age of 67. The time horizon, or number of years in the workforce, is calculated by subtracting SUNYWCC Business program students’ average age from the retirement age of 67. We multiply the 5.6 average CHEs per student by the headcounts that we estimate are still actively employed from each of the previous years.22 Students who enroll in the Business program at the college more than one year are counted at least twice in the historical enrollment data. However, CHEs remain distinct regardless of when and by whom they were earned, so there is no duplication in the CHE counts. We estimate there are approximately 167,033 CHEs from alumni active in the workforce. In order to capture the impact at the program level, we must map the program to the occupations students are likely to enter upon completion of the program. This is done by mapping the Classification of Instructional Programs (CIP) for the program to the appropriate Standard Occupational Classification (SOC) codes and then to the appropriate industries. CIP codes are how the National Center for Education Statistics (NCES) categorizes and tracks an enrollee’s field of study. SOC codes are used by the Bureau of Labor Statistics (BLS) to categorize and track employment trends for jobs with similar duties, skills, and/or education. The link between CIPs and SOCs was provided by Lightcast and reviewed by SUNY WCC (Appendix 1). This mapping provides the basis for calculating and attributing earnings to a program. To calculate the wage earned by the Business program’s alumni, we use a CIP to SOC mapping and the earnings associated with the occupations that alumni of the Business program are likely to enter. For multiple occupations, we use a weighted average by annual job openings to calculate the likely average earnings of workers in occupations mapped to the Business program. This is then adjusted to reflect each education level. Note that for the earnings of workers with only a high school diploma or less, an additional adjustment is made. Specifically, to account for the probability of entering the mapped occupations by workers with such education level, the estimated regional earnings at the high school or less education level are weighted by the actual percentage of workers with only a high school diploma or less education in the considered occupations in FY 2021-22. We also use Lightcast Job Postings Analytics data to ensure the resulting weighted average earnings are consistent with the real region-specific job listings for the given occupations. The earnings data is specific to the education level being trained. For example, for business specialists, we included the earnings from job postings in the region looking for business specialists with an associate and below degrees. Next, we estimate the value of CHEs, or the skills and human capital acquired by alumni of the Business program. This is done using the incremental added labor income stemming from the students’ higher wages. The incremental added labor income is 22 This assumes the average credit load and level of study from past years is equal to the credit load and level of study of students today.

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