The Value of University System of Georgia Education Funded by the Intellectual Capital Partnership Program Board of Regents, University System of Georgia Prepared by William J. Drummond, City Planning Program Jan L. Youtie, Economic Development Institute Georgia Institute of Technology June 2003 Copyright 2003 Georgia Tech Research Corporation Centennial Research Building Atlanta, Georgia 30332 Table of Contents Acknowledgements........................................................................................................................1 Executive Summary .......................................................................................................................1 Section 1. Introduction...................................................................................................................5 Introduction................................................................................................................................6 Scope of Work ...........................................................................................................................7 Section 2. Future Demand for College Education .........................................................................8 How Occupational Demand Is Forecast ....................................................................................9 Georgia's Fastest-Growing Higher Education-Related Occupations Are Similar to the Nation's ..................................................................................................................................9 College Education Will Be More Important to Georgia in 2010.............................................11 Conclusions..............................................................................................................................12 Section 3. Shortfall Analysis .......................................................................................................14 Annual Job Openings...............................................................................................................15 Annual Openings .................................................................................................................15 Occupational Supply............................................................................................................15 Net Migration.......................................................................................................................18 Crosswalk and Shortfalls .....................................................................................................19 Findings ...................................................................................................................................19 Only 12 Higher Education-Related Occupations Have Sizable Annual Shortfalls .............19 Education Occupations ........................................................................................................20 Health Care Occupations .....................................................................................................20 Bioscience Occupations .......................................................................................................21 Information Technology Occupations .................................................................................22 Limitations ...............................................................................................................................23 Section 4. External and Internal Migration..................................................................................24 The Importance of Migration...................................................................................................25 External Migration...................................................................................................................25 Approach..............................................................................................................................25 Findings ...............................................................................................................................25 Internal Migration ....................................................................................................................29 Method .................................................................................................................................29 Findings ...............................................................................................................................31 Conclusions..............................................................................................................................33 Section 5. Economic Value of USG Students: A Wage-Based Analysis ....................................34 Method .....................................................................................................................................35 Findings: Total Economic Impact of USG in 1998 Nearly $1.25 Billion ............................37 Conclusion ...............................................................................................................................41 Section 6. Future Directions ........................................................................................................43 Section 7. References...................................................................................................................45 Appendix 1. Intrastate Migration Model .....................................................................................47 Appendix 2. Economic Impact of Higher Education by CIP.......................................................50 Appendix 3. Economic Impact of Higher Education by County .................................................56 List of Figures Figure 2.1. College Degrees Will Account for a Larger Share of the Jobs in 2010 than in 200012 Figure 3.1. Nearly Half of All Higher Education Graduates Are from the University System of Georgia.................................................................................................................................16 Figure 3.2. Health Care-Related Occupations with Annual Shortfalls of 50 or More ................21 Figure 4.1. In-migration and Out-migration From 1995 to 2025: ...............................................27 Figure 4.2. Percentage of Georgia's Adult Population by Level of Education of Continuous Residents, In-migrants, and Out-migrants ...........................................................................28 Figure 4.3. Student Flow Path: Home, School, Work .................................................................30 Figure 4.4. Flow Path of Student Working Near Home County..................................................30 Figure 4.5. Model Results: Home, School, Work Flow Path Weights ........................................31 Figure 5.1. Economic Impact by County (in Millions of Dollars) ..............................................40 Figure 5.2. Average Economic Impact per Graduate (in Dollars)...............................................41 List of Tables Table 2.2. Top 10 Occupations by Numerical Growth in Job Openings, 2000-2010: Georgia vs. United States ........................................................................................................................10 Table 2.3. Top 10 Occupations by Percentage Growth in Job Openings, 2000-2010: Georgia vs. United States ........................................................................................................................11 Table 2.4. Every Category of College Degree-Related Occupations Is Increasing in Percentage of Total Jobs in 2010, While Non-Degree Occupations Are Decreasing ................................13 Table 3.2. Number of Degree Graduates by Level and Type of Georgia Institution, Academic Year 2000.............................................................................................................................17 Table 3.3. Occupations with Statewide Shortfalls of More than 100 Annually Through 2010* 20 Table 4.1. Interstate Migration Projections, 1995 and 2025........................................................26 Table 4.2. Levels of Education of Georgia Residents, In-migrants, and Out-migrants...............28 Table 5.1. Earnings by Education Level from Census PUMS Data ............................................36 Table 5.2. Earnings Due to Higher Education by Education Level.............................................37 Table 5.3. 1998 Economic Impact of Higher Education by Institution.......................................38 Table 5.4. Top 10 Programs With the Greatest Total Economic Impact in 1998 Based on Educational Value................................................................................................................39 Table 5.5. Top 10 Programs with the Greatest Average Economic Impact in 1998 Based on Educational Value................................................................................................................39 Acknowledgements Acknowledgements ! 2 Several individuals provided valuable support for this project. The Intellectual Capital Partnership Program inspired the development of new ways to value higher education. We thank Joy Hymel, Executive Director; Terry Durden, Director of Operations; and Will Hearn, Program Director, for encouraging us to pay more attention to the employment needs of certain economic sectors and explore effective ways of using USG graduates' wage information. The Board of Regents planning group challenged us to depict future scenarios for longrange planning. We thank Shelley Clark Nickel, Special Assistant to the Chancellor, and Dr. Cathie Mays Hudson, Associate Vice Chancellor, for involving us in the planning process, which served as the inspiration for the external migration analysis in Section 4 of this report. Assistant Commissioner Amelia Butts and her staff at the Georgia Department of Labor's Workforce Information and Analysis Unit furnished vital information for this analysis. In particular, recent occupational employment demand projections for 2010 were critical to our analysis. This report reflects the conclusions of the authors, and not of the Georgia Institute of Technology or the sponsor. Executive Summary Executive Summary ! 2 What is the value of higher education? The University System of Georgia's (USG) Intellectual Capital Partnership Program (ICAPP) has asked Georgia Tech to examine this question in studies conducted over the past six years. Through these studies, a rich base of knowledge has been developed in three areas: Demand and shortfall analysis, which addresses the question, Are there enough USG graduates in high-demand occupations? Migration analysis, which addresses the question, What impacts do USG institutions have on the flow of students across the state? Wage analysis, which addresses the questions, To what extent does higher education yield greater earnings, and, What is the impact on state and county economies? Demand and Shortfall Analysis New 2010 projections from the Georgia Department of Labor indicated that higher education-related occupations will compose 25 percent of all jobs in 2010, an increase over 2000 levels. Georgia's top three higher education-related occupations based on numeric employment increases are forecast to be registered nurses, computer support specialists, and accountants and auditors; and based on percentage increases, survey researchers, computer support specialists, and physician's assistants. These projections were compared to the number of graduates from all postsecondary institutions in the state in 2000 by major area of specialization. USG was the single largest supplier of higher education graduates, producing nearly half of all of Georgia's graduates. The shortfall analysis also accounted for the number of workers moving into the state (minus the number leaving) based on new data from the 2000 census. Only 12 higher education-related occupations were found to have shortfalls of more than 100. The largest shortfall was in elementary and kindergarten teaching occupations. Four health care occupations also had significant shortfalls: registered nurses, pharmacists, medical records and health information technicians, and medical and clinical laboratory technicians. Shortfalls in the information technology area were significantly reduced, although scarcities continued in certain computer software engineering and systems occupations. The shortfalls in these 12 occupations exceed 3,000 unfilled positions annually. Executive Summary ! 3 Migration Analysis The top 12 occupations with shortfalls of more than 100 a year would have had nearly double the deficits without in-migration. Forecasts through 2025 suggest that Georgia will have fewer in-migrants than in the past. Because in-migrants tend to have higher education levels than those staying in the state, the decline in in-migration may have a detrimental affect on the state's ability to fill higher education-related occupations. Workers migrate within the state as well as between states. Based on a gravity model, researchers found that the location of USG institutions significantly affects the internal flow of graduates in the state. Graduates are more likely to work in the local area after graduation, especially graduates of research universities. Also, the size of the pool of graduates has a significant effect on intrastate migration. Wage Analysis An economic impact analysis of the value of higher education in Georgia drew on a methodology developed by the U.S. Census Bureau in its 2002 landmark study "The Big Payoff." A comparison of the earnings of high school graduates to USG graduates showed that graduating from a USG institution paid off. Not only did it pay off to the average graduate in the 1993 to 1997 timeframe, to the tune of about $14,000 in 1998, but more significantly, it paid off to the state as a whole, by nearly $1.25 billion. And it paid off to 93 counties, which benefited by more than $1 million from USG graduate earnings. These impacts reflect only a single year of benefits in the careers of a five-year graduate cohort. The total benefits could be as much as 40 times higher over this cohort's full work-life. Future Directions Based on these findings, USG should continue to monitor the relationship between supply and demand at the state and sub-state levels, given projected changes in in-migration. USG should also initiate another round of matching of its graduates with Georgia Department of Labor employment security data for multiple years beyond 1998. It is further recommended that Executive Summary ! 4 the wage-based economic impact analysis be extended to a more complete benefit-cost analysis to better demonstrate the value of higher education in Georgia. Section 1 Introduction Section 1CIntroduction ! 6 Introduction For the past six years, the Board of Regents of the University System of Georgia (USG) through the Intellectual Capital Partnership Program (ICAPP) has asked Georgia Tech to examine the relationship between the demand for workers in various occupations and the supply of postsecondary institutional program graduates. The most recent study (referred to here as the 2001 study) showed that three factors were important in understanding the economic development impact of higher educational institutions from a human capital perspective-- migration, shortfall, and wages. It reported that while most university-related occupations were well supplied by workers from the USG, other postsecondary institutions, and people moving into the state, there was a significant shortfall of information technology (IT) workers. (Drummond and Youtie, 2001) In the intervening period, the information technology sector shrank along with the rest of the economy. Public-sector cutbacks have become necessary to balance many state and local budgets. In this climate, policy-makers pay increased attention to value of state services, including highly regarded services such as higher education. Traditionally, the value of higher education has been portrayed based on institutional and student spending. Such methodologies compute capital expenditures on buildings and equipment, salary and operating expenses, and purchases made by students and apply multipliers to estimate the extent to which these expenditures generated subsequent rounds of additional spending. (Humphries, et al., 1999; Duhart, 2002.) This is a very useful methodology that has been applied to a broad range of public programs--from education to prisons to road construction. Although spending by higher educational institutions is important, the core mission of universities and colleges is to educate students. Students undertake higher education for many reasons, but the chief one is that they expect it to lead to future economic success. It would be particularly beneficial to identify methodologies that can capture the economic value of this education mission on the future economic success of students. Section 1CIntroduction ! 7 Scope of Work This study aims to demonstrate the value of higher education from three perspectives. First, it will examine the benefits of higher education in addressing the employment needs of high-demand occupations. Section 2 will present recently released employment projections for 2000 to 2010 and show the fastest-growing occupations requiring higher education in Georgia and the nation. Section 3 will relate these projections to the existing supply of USG graduates and graduates of other postsecondary institutions in the state, as well as the supply of in-migrants based on information from the 2000 U.S. Census released in June 2003. This analysis will highlight which higher education-related occupations are unlikely to have enough graduates and in-migrants to fill employers' needs through 2010. Second, Section 4 of this study will investigate the relationship between USG institutions and migration. Migration has two components: external migration and internal migration. The former looks at the extent to which the state can continue to expect educated workers from other state to fill high-demand occupations in Georgia. Projections from the U.S. Census Bureau through 2025 by educational attainment will be the primary source of data for the external migration analysis. Internal migration focuses on the impact of USG institution location on the flow of students into the economy. Specifically, it examines the extent to which USG institutions affect where a student chooses to work (relative to other factors such as level of wages offered and home county influences). An economic impact analysis of the value of higher education is presented in Section 5. In its recent landmark study, "The Big Payoff," the U.S. Census Bureau developed an approach for using wages and educational attainment to demonstrate the economic value of education. (Day and Newburger, 2002). Annual earnings of higher education graduates were compared to annual earnings of high school graduates, and the difference was deemed to be the value of higher education. "The Big Payoff" estimated that college graduates earn 1.8 times more than high school graduates. Section 5 presents a variation of the methodology in "The Big Payoff" to show the overall impact of USG institutions and programs on state and county economies. Section 2 Future Demand for College Education Section 2CFuture Demand for College Education ! 9 What is the demand for employees with college education? One way to answer this question is by investigating occupations that require higher education. The U.S. Bureau of Labor Statistics has found in national surveys that certain occupations are linked to certain levels of education and work experience. (Wash, 1996). For example, physicians and lawyers typically have a professional degree; school teachers typically have a bachelor's degree; medical technicians typically have an associate's degree; general managers typically have work experience plus a bachelor's degree; cashiers typically have short-term on-the-job training; and upholsterers typically have long-term on-the-job training. By knowing the demand for employees in these occupations, one can address the demand for higher education. How Occupational Demand Is Forecast Occupational employment demand is based on long-range projections that use sophisticated econometric models. These models account for the size and demographic composition of the labor force, the growth of the aggregate economy, final demand or gross domestic product (GDP), and interindustry relationships (input-output). Surveys of employers conducted every three years by the Georgia Department of Labor furnish information for the instate estimation process. Projections are first made for industries, then a staffing pattern matrix is used to produce projections by occupation. This set of projections marks the first time that standard occupational classifications (SOCs) were used. Projections were made for nearly 650 SOCs nationally and more than 750 occupations in Georgia. Unfortunately, no sub-state occupational employment projections were available for SOCs 2010, so researchers did not conduct a regional supply-demand analysis Georgia's Fastest-Growing Higher Education-Related Occupations Are Similar to the Nation's Which occupations are projected to add the most jobs? There are two approaches to determining the fastest-growing jobs: numerical growth and percentage growth. Numerical growth shows the raw numbers of job openings over the next 10 years. Table 2.2 compares numerical growth projections for Georgia and the nation, focusing only on occupations that generally require a university degree. The top two occupations with the most projected new jobs Section 2CFuture Demand for College Education ! 10 are the same in Georgia as in the nation--registered nurses and computer support specialists. Accountants and auditors are on both lists, but rank higher in Georgia than in the nation. A second way to examine the fastest-growing occupations is percentage growth. Percentage growth indicates how fast employment changes will occur. Table 2.3 compares the percentage growth in jobs projected for higher education-related occupations in Georgia and the nation. Survey researchers are the occupation with the biggest percentage growth rate in Georgia whereas computer software applications engineers top the national list. Computer support specialists rank second on both lists, but physician's assistants rank third on the Georgia list compared to eighth on the national list. Table 2.2. Top 10 Occupations by Numerical Growth in Job Openings, 2000-2010: Georgia vs. United States* U.S. Openings, 2000-2010 (000s) Georgia Openings, (2000-2010) 1. Registered Nurses 2,762 1. Registered Nurses 18,130 2. Computer Support Specialists 2,376 2. Computer Support Specialists 15,130 3. Computer Software Engineers, Applications 1,867 3. Accountants and Auditors 10,060 4. Computer Software Engineers, Systems Software 1,410 4. Computer Software Engineers, Applications 6,320 5. Computer Systems Analysts 1,208 5. Network and Computer Systems Administrators 6. Network and Computer Systems 6. Preschool Teachers, Except Special Administrators 912 Education 7. Accountants and Auditors 7. Elementary School Teachers, 866 Except Special Education 8. Elementary School Teachers, Except Special Education 8. Computer Software Engineers, 816 Systems Software 9. Secondary School Teachers, Except 748 Special and Vocational Education 9. Computer Systems Analysts 10. Secondary School Teachers, Except 10. Lawyers 529 Special and Vocational Education *List of occupations excludes occupational categories with titles that begin with "All other...". Source: U.S. Bureau of Labor Statistics and the Georgia Department of Labor, data accessed April 2003. 5,940 5,550 5,450 4,480 4,180 3,600 Section 2CFuture Demand for College Education ! 11 Table 2.3. Top 10 Occupations by Percentage Growth in Job Openings, 20002010: Georgia vs. United States* U.S. Percent Growth, 2000-2010 (000s) Georgia Percent Growth (2000-2010) 1. Computer Software Engineers, Applications 101% 2. Computer Support Specialists 98% 3. Computer Software Engineers, Systems Software 89% 1. Survey Researchers 2. Computer Support Specialists 100% 80% 3. Physician's Assistants 75% 4. Network and Computer Systems Administrators 5. Network Systems and Data Communications Analysts 6. Database Administrators 4. Environmental Engineering 83% Technicians 72% 5. Medical Records and Health 79% Information Technicians 69% 6. Network and Computer 65% Systems Administrators 66% 7. Computer Systems Analysts 7. Network Systems and Data 60% Communications Analysts 63% 8. Physician's Assistants 54% 8. Public Relations Specialists 59% 9. Medical Records and Health 9. Environmental Information Technicians 50% Engineers 58% 10. Physical Therapist Aides 46% 10. Computer Software Engineers, 57% 10. Audiologists 46% Systems Software *List of occupations excludes occupational categories with titles that begin with "All other...". Source: U.S. Bureau of Labor Statistics and the Georgia Department of Labor, data accessed April 2003. College Education Will Be More Important to Georgia in 2010 Georgia will add 805,570 new jobs through 2010 or nearly 20 percent more new jobs than in 2000. Occupations that typically require higher education will account for a larger share of jobs in 2010 than in 2000. By 2010, a higher education degree will be required for occupations employing nearly 25 percent of workers compared to 23 percent in 2000. Occupations linked to all types of college degrees--from associate's to doctoral and professional Section 2CFuture Demand for College Education ! 12 degrees--will compose a greater share of the workforce in 2010 than in 2000, whereas those requiring on-the-job training or work experience will represent a declining share of new jobs in 2010. (See Figure 2.1 and Table 2.4.) Figure 2.1. College Degrees Will Account for a Larger Share of the Jobs in 2010 than in 2000* Short-term on-the-job training Moderate-term on-the-job training Long-term on-the-job training Work experience Post-secondary vocational training Associate's degree Bachelor's degree Work experience plus bachelor's degree Master's degree Doctoral degree First professional degree -0.80% -0.60% -0.40% -0.20% 0.00% 0.20% 0.40% 0.60% 0.80% *This chart represents the percentage of jobs in 2010 requiring certain degrees or non-college training minus the percentage of jobs in these same categories in 2000. Source: Georgia Department of Labor, 2003. Conclusions Georgia's 2010 workforce will present new challenges. There will be more than 800,000 new jobs than in 2010. While three-quarters of these jobs still require no formal college degree, the latest projections show that these jobs are on a declining path. College degree-related jobs will account for 1.5 percent more of the jobs in 2010 than in 2000. This may not seem like much, but it represents more than 262,000 new jobs. More important, it shows that college education will be even more valuable to Georgia's citizens and ultimately to the Georgia economy than it is today. Section 2CFuture Demand for College Education ! 13 Table 2.4. Every Category of College Degree-Related Occupations Is Increasing in Percentage of Total Jobs in 2010, While Non-Degree Occupations Are Decreasing Education level Percent 2000 2010 2000 Percent 2010 Percent Change Employment Employment Employment Employment Employment Share First professional degree Doctoral degree Master's degree Work experience plus bachelor's Bachelor's degree Associate's degree 41,100 24,950 21,690 275,750 468,500 135,120 52,650 33,670 27,170 336,790 590,920 188,380 1.0% 0.6% 0.5% 6.7% 11.3% 3.3% 1.1% 0.7% 0.6% 6.8% 12.0% 3.8% 0.1% 0.1% 0.0% 0.1% 0.6% 0.5% College degree 967,110 1,229,580 23.4% 24.9% 1.5% Post-secondary vocational training Work experience Long-term on-the-job training Moderate-term on-the-job training Short-term on-the-job training 117,220 287,880 405,820 640,300 1,715,300 145,000 329,340 473,840 733,310 2,028,130 Less than college degree 3,166,520 3,709,620 2.8% 7.0% 9.8% 15.5% 41.5% 76.6% 2.9% 6.7% 9.6% 14.8% 41.1% 75.1% 0.1% -0.3% -0.2% -0.6% -0.4% -1.5% Total 4,133,630 4,939,200 Source: Georgia Department of Labor, 2003. 100.0% 100.0% 100.0% Section 3 Shortfall Analysis Section 3CShortfall Analysis ! 15 Shortfall analysis estimates the long-term need that Georgia companies will have for employees in particular occupations. This estimate is over and above employment needs filled by postsecondary institution graduates available for hire and employees moving into the state (minus the number leaving the state). All estimates are based on 10-year projections made in 2000. Four elements compose shortfall analysis. These are summarized in Table 3.1 and described in the sections that follow. Annual Job Openings Annual Openings For this analysis, researchers used annual Table 3.1. Shortfall Analysis University System Annual job openings in occupations typically requiring a university degree, projected from 2000-2010 openings, rather than the 10-year growth rates discussed in Section 2. Annual openings enable comparisons to be made with other annual data such as the supply of university graduates in a given year. Annual openings are based on annualized 10-year growth rates; however, they MINUS Supply of graduates in majors for 1999-2000 in all public and private postsecondary institutions in Georgia MINUS Supply of net migrants or employees (in occupations typically requiring a university degree) coming into Georgia from other states (and out from Georgia to other states) from the 2000 census also include net replacements. Net replacements consist of workers who transfer from other EQUALS Occupations with annual shortfalls through 2010 occupations or who leave the workforce, but do not include persons leaving the state, and persons changing occupations. Occupational Supply This study defines occupational supply as the number of graduates by major from all Georgia's postsecondary educational institutions. The significance of the supply component in the shortfall analysis is as follows. If postsecondary institutions continue to graduate the same number of students with the same majors, what impact will that have on filling the demand for workers in occupations critical to the state's economy? To estimate supply, researchers gathered data on number of graduates by major in Section 3CShortfall Analysis ! 16 Georgia's postsecondary institutions. These institutions include USG colleges and universities, private colleges and universities, Georgia Department of Technical and Adult Education (DTAE) colleges, and nonprofit and proprietary technical institutions. The Integrated Postsecondary Education Data System (IPEDS) serves as the primary data source for occupational supply analysis. Administered by the National Center for Educational Statistics (NCES) of the U.S. Department of Education, IPEDS includes national, state, and institution-level information (such as enrollment program completion, faculty, staff, finances, and academic libraries) from some 12,000 postsecondary institutions. The most recent data available on completions (graduates) from these institutions is as of 2000. More recent data about graduates is directly available from the USG and DTAE. However to maintain comparability with private institutions, researchers relied on the 2000 IPEDS data. The USG is the major source of postsecondary graduates in the state. About half of all postsecondary institution graduates in Georgia were educated by a USG institution. (See Figure 3.1.) The USG also supplies roughly 60 percent of all graduates with associate's degrees. USG is even more important for bachelor's level and higher education. Two-thirds of all graduates with bachelor's, master's, doctoratal, and professional degrees came from a USG institution. Figure 3.1. Nearly Half of All Higher Education Graduates Are from the University System of Georgia Section 3CShortfall Analysis ! 17 Table 3.2. Number of Degree Graduates by Level and Type of Georgia Institution, Academic Year 2000. Number of Graduates Percent of Graduates Degree Level USG DTAE Private Total USG DTAE Private Total Awards of less than 1 academic year 47 Awards between 1 and 2 acad. yrs. 629 Associate's degrees 4,568 Awards between 2 and 4 acad. yrs. - Bachelor's degrees 20,271 Postbaccalaureate certificates 8 Master's degrees 7,083 Post-Master's certificates 515 Doctoral degrees 721 First-professional degrees 767 6,370 4,817 1,180 2,190 - 2,970 1,498 2,056 257 8,950 34 3,327 91 311 1,781 9,387 6,944 7,804 2,447 29,221 42 10,410 606 1,032 2,548 0.5% 9.1% 58.5% 0.0% 69.4% 19.0% 68.0% 85.0% 69.9% 30.1% 67.9% 69.4% 15.1% 89.5% 31.6% 21.6% 26.3% 10.5% 30.6% 81.0% 32.0% 15.0% 30.1% 69.9% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% Total 34,609 14,557 21,275 70,441 49.1% 20.7% 30.2% 100% Source: Georgia Tech's City Planning Program and Economic Development Institute, calculated from U.S. Department of Education IPEDS 2000 data. Private 30% USG 49% DTAE 21% Section 3CShortfall Analysis ! 18 The occupational supply analysis focuses on the data relating to the classification of instructional programs (CIP). The CIP represents all primary fields of study leading to degrees or certificates. There are nearly 900 such classifications. Net Migration As part of the shortfall forecasts, Georgia Tech researchers estimated the effects of net migration of talent into the state. Net migration, or the number of people moving into the state minus the number leaving the state, is an important factor in Georgia. During the April 1, 2000 to July 1, 2001 time period, Georgia ranked third among all 50 states in domestic net migration and eighth in international net migration. The 2001 study showed that there are two types of migration. The first type consists of graduates of Georgia institutions who leave the state immediately after graduation. International or out-of-state students may go back to their home regions. Some students may remain in the state but leave the Georgia workforce for personal reasons. As a result, the first year sees a rather big loss. To estimate the size of this out-migration, researchers used an earlier data set that combines USG student data with Georgia Department of Labor workforce data. Seventy percent of the graduates from 1993-1997 were found in the 1998 workforce data. From this comparison, researchers calculated graduate loss rates by institution. The second type of migration is slower and steadier. Smaller numbers of people drift in or out of the state over time or leave the Georgia workforce for personal reasons. The best source of state-to-state occupational migration data has been the U.S. Decennial Census and its resulting Public Use Microdata Sample (PUMS) data sets. These data sets were just released in the second quarter of 2003. To track Georgia's out-migrants, researchers analyzed data for each of the 50 states (plus Washington, D.C.) to find out who previously lived in Georgia. To track Georgia in-migrants, researchers simply processed the Georgia data. Based on this data, a net migration rate was calculated for each SOC in Georgia and applied to the employees in that SOC, resulting in the number of net migrants for each occupation. The state has gained more workers than it has lost in nearly all occupational categories. The top five higher education-related occupations based on net migration are registered nurses, accountants and auditors, business operations specialists, elementary school teachers, and Section 3CShortfall Analysis ! 19 computer support specialists. More than 800 employees in these five occupations combined are estimated to move to Georgia each year. Crosswalk and Shortfalls To link the major occupational and instructional classification information, a crosswalk translation database from the National Crosswalk Service Center (NCSC) was used. NCSC employs survey-based relationships to determine the links between graduates and their majors and occupations. Georgia Tech researchers used the crosswalk to allocate graduates, net migrants, and occupational employees. Researchers applied the crosswalk across the entire spectrum of occupations, not just the university-educated subset. Thus, not all the graduates in the university CIPs map into the university occupations. With graduates, net migrants, and occupational employees linked, a simple subtraction furnishes projected shortfalls. Findings Only 12 Higher Education-Related Occupations Have Sizable Annual Shortfalls Table 3.3 shows that there are 12 higher education-related occupations with annual shortfalls of more than 100. The vast majority of occupations do not have significant shortfalls because their needs are filled either by USG or other postsecondary graduates or by in-migration. Most companies' needs for new employees will likely be met through 2010. Nevertheless, the shortfalls in these 12 occupations come to more than 3,000 unfilled positions annually. Elementary school teachers represent the largest shortfall. Nearly 1,000 elementary school teacher jobs a year are projected to go unfilled. Even with more than 800 teachers coming into the state and nearly 800 graduating from postsecondary institutions, the shortage of elementary school teachers is projected to continue through 2010. Four higher education health care occupations have significant shortfalls. Three are at the associate's degree level--registered nurses, medical records and health information technicians, Section 3CShortfall Analysis ! 20 and medical and clinical laboratory technicians. There is also a shortage of pharmacists, who typically must have bachelor's degrees. The biggest change from the 2001 study is that shortfalls in IT-related occupations are much smaller. The only IT-related occupations with a shortfall of more than 100 are computer software engineers for applications and systems software and computer systems analysts. This shortfall is still significant, but not as large as previously determined. Education Occupations Elementary school teachers were the only educational occupation with significant shortfalls. Because Georgia does not offer separate educational programs for kindergarten and elementary school, this analysis has grouped them together. The shortfall finding should be viewed as a joint kindergarten-elementary teacher annual shortfall. Health Care Occupations Shortfalls in health care occupations are a national, if not global, problem. Such is the case in Georgia. About 32 percent of health care jobs with university degree connections are projected to go unfilled. This represents an annual shortfall of more than 2,000 a year. (See Table 3.4.) Most significant is the shortfall of registered nurses, followed by pharmacists. There are also shortfalls in various physician specialties--particularly family and general practitioners, surgeons, dentists, and internists. Physician shortfalls may not cause serious problems because other states produce significant oversupplies that spill over into Georgia. Nevertheless, monitoring of the supply and demand of physicians should be continued to maintain the quality of health care in the state. Table 3.3. Occupations With Statewide Shortfalls of More than 100 Annually Through 2010 Description Openings Graduates Migration Shortfall Education Level Elementary School Teachers, Except Special Education Computer Software Engineers, 2,590 710 783 836 971 Bachelor's degree 32 281 397 Bachelor's degree Section 3CShortfall Analysis ! 21 Applications Registered Nurses Business Operations Specialists, All Other Pharmacists Property, Real Estate, and Community Association Managers Medical Records and Health Information Technicians Medical and Clinical Laboratory Technicians Computer Software Engineers, Systems Software Family and General Practitioners Engineers, All Other Computer Systems Analysts Detectives and Criminal Investigators 2,920 1,370 370 240 310 260 500 430 100 520 120 1,528 18 152 1,018 1,014 (59) 28 14 90 35 41 40 132 191 170 90 8 (57) 198 200 5 10 374 Associate's degree 338 Bachelor's degree 277 First professional degree 198 Bachelor's degree 185 Associate's degree 179 Associate's degree 178 Bachelor's degree 170 First professional degree 149 Bachelor's degree 122 Bachelor's degree 105 Bachelor's degree Source: Georgia Tech's City Planning Program and Economic Development Institute, calculated from U.S. Department of Education, Georgia Department of Labor, and U.S. Census Bureau data. Figure 3.2. Health-Care Related Occupations with Annual Shortfalls of 50 or More Registered Nurses Pharmacists Medical Records and Health Information Technicians Medical and Clinical Laboratory Technicians Family and General Practitioners Surgeons Physician Assistants Dentists Radiologic Technologists and Technicians Internists, General Healthcare Practitioners and Technical Workers, All Other Physical Therapists - 50 100 150 200 250 300 350 400 Bioscience Occupations Section 3CShortfall Analysis ! 22 Georgia Tech researchers conducted a companion study of supply and demand in bioscience occupations. (Drummond and Youtie, 2003) State and national occupational employment forecasts call for long-term shortfalls in medical and clinical laboratory technician and technologist positions. However, current demand measures do not show a great shortage of medical and clinical laboratory technicians and technologists, and executive interviews even suggest that there are plenty of technicians for the number of available bioscience positions in Georgia today. Not all medical and clinical laboratory technicians will work in a bioscience company; most will work in health care services settings. Still, Georgia institutions do not offer programs that produce significant numbers of graduates for these positions. As a result, many of these technician-level positions in Georgia are probably being filled by workers receiving onthe-job training or moving from related occupations. Educators should track the relationship between demand for medical and clinical laboratory technicians and the supply of graduates through 2010 to assess when shortfalls dictate the need for increasing technician training resource allocation. Also significant were concerns about the lack of experience of the state's bioscience graduates. Nine of 10 bioscience openings require industry-relevant experience. This is particularly true of research and management positions, which can require up to five or more years of experience. And although executives interviewed for this study mentioned having needs to fill positions in a diverse range of occupations (e.g., biostatistician, regulatory affairs, quality assurance), the common thread was the need for professionals with specialized experience in these positions. It was recommended that relevant corporate or government experience be incorporated into the existing curriculum in partnership with local industry, and that certificate programs be considered for executives. Information Technology Occupations Shortfalls in the information technology occupations have been significantly reduced since the 2001 study. There are still some shortfalls in certain information technology occupations, especially computer software engineers. Nevertheless, taking all information technology occupations together, the demand for these workers is nearly balanced with the supply. Almost half of all the information technology-related jobs come from in-migration of Section 3CShortfall Analysis ! 23 out-of-state specialists, so it is important for the state to continue to monitor the relationship between supply and demand for these workers given their important role in economic development. Limitations These shortfall results should be interpreted in the context of limitations of the analysis. Demand projections are long-term forecasts, which cannot reflect short-term fluctuations in certain sectors (e.g., layoffs in the high-tech sector) or business changes that may make an occupation seem less attractive (e.g., managed care practices, which may have discouraged workers from taking health care positions). At the same time, these long-term forecasts can be influenced by the economic, demographic, technological, and policy circumstances that exist during the base year, which for this analysis was 2000. The relationship between supply and demand is constrained by the way that postsecondary educational institutions categorize their major programs. For example, shortfalls may appear in a given occupation when in fact Georgia institutions are graduating students that could take jobs in this occupation, but their major area is coded in a category not typically linked to the occupation. Finally, students have the freedom to pursue certain jobs or majors because of reasons unrelated to the education-occupation link--wanting to live in a certain city, desire jobs with certain working conditions (e.g., those that offer telecommuting, casual clothes). For these reasons, common sense and industry review must be used in interpreting the shortfall findings. Section 4 External and Internal Migration Section 4CExternal and Internal Migration ! 25 The Importance of Migration Migration of educated workers to Georgia is vital to the state's economy. The top 12 occupations with shortfalls of more than 100 a year would have had nearly double the shortfalls without in-migration. In many cases, the number of net migrants is a larger source of workers than are the graduates of all Georgia's higher educational institutions combined. This section will examine two types of migration: (1) external migration from other states into Georgia, and (2) internal migration within Georgia. External Migration Approach Will Georgia be able to continue its reliance on educated workers from other state's to fill jobs in critical occupations? The external migration analysis addresses this question by examining migration projections published by the U.S. Census Bureau through 2025. The Census Bureau has two population projection series. Series A bases its forecasts on historic migration. This series has traditionally been the most accurate predictor of state-to-state migration. Series B uses employment projections from the U.S. Bureau of Labor Statistics to drive its migration projections. Both series use the same method to account for births and deaths in the natural population. They differ only in the way they account for migration. Findings Georgia May Not Be Able to Rely on Migration to Fill Employment Needs Even though Georgia is projected to retain its position among the top 10 states with the most in-migration, the state can expect fewer in-migrants in the future. (See Table 4.1.) According to Series A projections, Georgia's 2025 net migration will only be 30 percent of 2000 net migration levels. Series B projections indicate that the state's 2025 net migration will be only 76 percent of 2000 net migration levels. (See Figure 4.1.) In either case, Georgia will have fewer annual net migrants than it has in the past. Section 4CExternal and Internal Migration ! 26 Table 4.1 Interstate Migration Projections, 1995 and 2025: Top 10 States Ranked by Migration Population 1995 Series A&B 2025 Series A (Historic Migration) 2025 Series B (Emp. Migration) Rank State Pop Rank State Pop Rank State Pop 1 California 2 Texas 3 New York 4 Florida 5 Pennsylvania 6 Illinois 7 Ohio 8 Michigan 9 New Jersey 10 Georgia 31.6 1 California 18.7 2 Texas 18.1 3 Florida 14.2 4 New York 12.1 5 Illinois 11.8 6 Pennsylvania 11.2 7 Ohio 9.5 8 Michigan 7.9 9 Georgia 7.2 10 New Jersey 49.3 1 California 41.5 27.2 2 Texas 28.2 20.7 3 Florida 20.1 19.8 4 New York 19.4 13.4 5 Illinois 13.7 12.7 6 Pennsylvania 12.9 11.7 7 Ohio 12.3 10.1 8 Georgia 11.0 9.9 9 Michigan 10.4 9.6 10 North Carolina 9.9 Population in millions and projections are for July 1. Series A and B reflect different interstate migration assumptions. Source: U.S. Bureau of the Census, Population Division, PPL-47, table 1. Section 4CExternal and Internal Migration ! 27 Figure 4.1. In-migration and Out-migration From 1995 to 2025: Series A and Series B Projections 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000 1995 2000 2005 2010 2015 2020 2025 Series A Inmigration Series A Outmigration Series A Netmigration Series B Inmigration Series B Outmigration Series B Netmigration In-migrants and Out-migrants More Educated Than Continuous Residents This potential migration problem is even more serious because in-migrants and outmigrants have higher education levels than do continuous residents of Georgia. Table 4.2 and Figure 4.2 present data from the 2000 census showing education levels for adults over 25 who enter Georgia, leave Georgia, and stay in the state. Fifteen percent of continuous residents have bachelor's degree or higher. But 25 percent of in-migrants and 29 percent of out-migrants hold bachelor's degrees. Both series show out-migration will increase, meaning that Georgia may lose a greater number of workers with higher education. Series A shows in-migration decreasing, so Georgia will have fewer of these highly educated in-migrants. Series B shows in-migration increasing, but not as rapidly as out-migration does. In either case, the net migration decline will have a particularly detrimental effect on the state's ability to fill higher education-related occupations. Section 4CExternal and Internal Migration ! 28 Table 4.2. Levels of Education of Georgia Residents, In-migrants, and Outmigrants Level of Education Continuous Continuous Residents In-migrants Out-migrants Residents In-migrants Out-migrants Less then High School 3,110,905 High School degree 1,535,412 College less than bachelor's 1,323,601 Bachelor's degree 674,882 Graduate work or degree 335,416 413,406 206,422 285,503 208,775 91,704 188,767 111,156 165,222 119,325 55,560 45% 22% 19% 10% 5% 34% 17% 24% 17% 8% 29% 17% 26% 19% 9% Total 6,980,216 1,205,810 640,030 Population figures reflect all adults over 25 years old. Source: Public Use Microdata Sample, 2000 Census. 100% 100% 100% Figure 4.2. Percentage of Georgia's Adult Population by Level of Education of Continuous Residents, In-migrants, and Out-migrants 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Less then HS HS degree College less than bachelorBsachelorsGdreagdrueaete work or degree Outmigrants Inmigrants Continuous Residents Section 4CExternal and Internal Migration ! 29 Internal Migration In addition to migration between states, the USG and its institutions are affected by intrastate migration. Intrastate migration raises questions such as: Are students more likely to go to school in a location near their home county? Are students more likely to work in a location near their home counties? Are students more likely to work in a location near their educational institution? How local is the draw area for different types of USG institutions? By adding a new institution to a new location, or by changing the type of an existing institution, how would the systemwide distribution of students change? By adding a new institution to a new location, how many more graduates would be likely to stay to work in the area? Method One of the best ways to address internal migration is by following graduates of USG institutions into their first jobs. By matching the USG's student database to the Georgia Department of Labor's (DOL) employment database, it is possible to track each individual student from home county, to institution, to work county. The first matching effort involved linking USG graduates during the 1993-1997 academic years to the DOL 1998 employment security database.1 Some 80,000 individual students were located in the employment database, which provides a rich foundation to build models of intra-state migration. The basic statistical-geographical model utilized for this analysis is the gravity model. A gravity model is much like Newton's discovery that gravitation attraction between two bodies is a function of the size of the bodies and distance between them.2 1For the last two years, this research team has worked with the Board of Regents staff to procure an updated version of this dataset that would include employment information for 1998 to 2002. The updated dataset could not be secured in time for inclusion in this study. Thus, the models presented in this section are based upon the original 1998 dataset. Although these models make sense and show much promise, before any policy decisions can be based on them it will be necessary to develop a more robust, multi-year dataset. 2 In a typical social science application of the gravity model, the number of employees working in one location and living in a second location is equal to C * emp * pop / d where C is a constant, emp is the number of employees in the first location, pop is the population at the second location, and d is the distance between the locations. The parameters , , and can be understood as weights, with Section 4CExternal and Internal Migration ! 30 To understand the student migration model, assume a high school student lived in Columbus, attended college at Statesboro, then after graduation worked in Savannah. Figure 4.3 shows the "flow" path of that student. The magnitude of this flow will be larger when the number of students in the home county is larger, the size of the institution is larger, and the size of the workforce in the work county is larger. The flow will decrease the longer the home county-school county distance, and the longer the school countywork county distance. Figure 4.3. Student Flow Path: Home, School, Work There is a third factor. We would expect that the distance between the student's home county and work county would also be important. Because of familiarity and contacts generated through family and friends, a student might be more likely to work in a county near to his or her home county. (See Figure 4.4.) Wages are an important fourth factor. Locations with higher wages are likely to offer an additional attraction to graduates seeking work in certain locations across the state. The model also accounts for instances where home and work counties are identical or adjacent.3 Figure 4.4. Flow Path of Student Working Near Home County larger parameter values giving more weight to that factor, and smaller (nearer to 0) weights giving less weight. 3 The model can be written as Flow = C * hgrads * sgrads * wgrads * hstime * hwtime * swtime Instead of dividing by the distances, researchers rewrite the model in multiplicative terms, and expect that the final three parameters will be negative. For each home county-school county-work county flow, researchers know the hgrads (the number of USG students from a county), the sgrads (the number of students at the school), the wgrads (the number of workers found in the work county), the hstime (home-school travel time in hours), the hwtime (home-work travel time in hours), and the swtime (school-work travel time in hours). By taking the natural log of both sides of the flow equation above, the equation is transformed into lflow = lC + *lhgrads + *lsgrads + *lwgrads + *lhstime + *lhwtime + *lswtime The six parameters (and constant) of this equation can then be estimated by multiple regression. There are seven other control variables added to the equation, including lewage: natural log of the expected wage in the work county hwsame: 1 if the home county and work county are the same, 0 otherwise hwadj2: 1 if the home county and work county are adjacent, 0 otherwise Section 4CExternal and Internal Migration ! 31 Findings Detailed regression results for this model can be found in Appendix 1. Figure 4.5 shows the model parameters (for the systemwide model) superimposed over the Columbus- Statesboro-Savannah example. The red parameters show that the size of the institution and the size of a county's workforce are equal, with less importance for the number of students coming from the home county. The blue numbers show the distance effects. If any of these were zero, it would mean that distance has no effect on the flow of graduates. The home-work distance is the most important distance factor (- Figure 4.5. Model Results: Home, School, Work Flow Path Weights .46), with the home-school the next most important (-.33), and the school-work the least important of the three (-.18). Yet it should be noted that the location of the school does have some influence on USG graduates' work location decisions. The school-work factor is statistically significant and not zero. The county from which a student comes still has more influence on where a student works, however. Overall, we found that the location of a USG institution significantly affects the locational behavior of USG graduates. A 10 percent increase in the size of the home county student population (whose parameter is 0.27) produces a 2.7 percent increase in the flow of students from that county to that institution. A 10 percent increase in institution size produces a 4.4 percent increase in the flow of students to that institution. A 10 percent increase in a county's college graduate workforce generates a 4.4 percent increase in the flow of students to that county. A 10 percent increase in the distance between home and school decreases the flow of students by 3.3 percent. hssame: 1 if the home county and school county are the same, 0 otherwise hsadj2: 1 if the home county and school county are adjacent, 0 otherwise swsame: 1 if the school county and work county are the same, 0 otherwise Section 4CExternal and Internal Migration ! 32 A 10 percent increase in the distance between school and work decreases the flow of students by 1.8 percent. The model also found that a 10 percent increase in wages in a county means that 10.5 percent more graduates would flow to that area. There is an extra likelihood that students will attend an institution in their home (or adjacent) county, return to their home (or adjacent to home) county to work, or work in the same county where they attended college. In addition to the overall model, researchers conducted special analyses of four types of USG institutions: research institutions, other four-year institutions, two-year institutions, and historically black institutions. First, the model indicates that graduates of the research institutions are less sensitive to changes in wages than graduates of the other types of institutions. For research institution graduates, a 10 percent increase in wages produces only a 2.5 percent increase in graduates taking positions. Second, more two-year students come from the school's county and adjacent counties relative to other types of institutions. Third, graduates of historically black institutions have a greater tendency than other types of institutions to stay in the local area after graduation. Finally, an examination of the distance parameters yields several interesting findings. The home-school distance is especially important for the historically black institutions (parameter of -0.81). These students are very sensitive to distance and tend not to travel far from their home counties to attend school. It is not surprising that students at research universities are least sensitive (-0.24) to home-school distance. The home-work distance factor is reversed: it has little effect on students at historically black institutions (-0.01), and the most effect (-0.55) on students at research institutions. The latter may be due to the tendency of research universities to be located in large urban areas, where many students come from and where many jobs exist swadj2: 1 if the school county and work county are adjacent, 0 otherwise Section 4CExternal and Internal Migration ! 33 Conclusions Georgia may not be able to rely on an ever-increasing stream of educated in-migrants to fill important occupational categories in the future. USG should track net migration, especially by education and occupation, to assess if and when decreasing in-migration into the state impacts critical university-related occupations. At the same time, attention must also be paid to intrastate migration. A gravity model found that the location of USG institutions has a significant effect on the internal flow of graduates in the state. The distance between home and school is important, particularly to graduates of two-year and historically black institutions. Graduates are more likely to work in the local area after graduation, especially graduates of research universities. Also the size of the pool of graduates has a significant effect on intrastate migration. The USG should pay attention to the effect of its institutions on the distribution of graduates and potential workers in various regions across the state. Section 5 Economic Value of USG Students: A Wage-Based Analysis Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 35 There are many ways to portray the economic impact of higher education. While educational institutions generate significant value from expenditures and capital projects, higher education's most compelling impact on the state's economy may be its influence on the earnings of its students. This analysis will answer the question: "In economic terms, what is the value of our graduates to the state of Georgia?" There are many personal and social benefits to higher education, but this analysis will be restricted to estimating the economic benefits of USG graduates to the state of Georgia. Method The most accurate way to determine the economic worth of higher education would be to estimate what a person's earnings would have been without higher education. Ideally the analysis would include statistical controls for personal characteristics such as intelligence, energy, and creativity, then estimate the increment of earnings due to additional education, holding the control variables constant. Yet such variables are difficult to measure and extraordinarily expensive to obtain. Instead, this report presents a modification of the U.S. Census Bureau's study "The Big Payoff" (Day and Newburger, 2002). It assumes that the economic value of higher education can be estimated by comparing the earnings of high school graduates to the earnings of those completing, two-year, four-year, and graduate degrees. The (presumably) positive increment of earnings is assumed to be the value of higher education. The basic data source for this analysis is the matched database of 1993-97 USG graduates and 1998 Georgia Department of Labor worker records referenced in the previous section. To estimate wages for full-time workers more accurately, the analysis is restricted to those earning $10,000 or more in 1998, producing a dataset of 83,329 individual graduates. There is one significant difficulty with this approach. The matched graduate-worker dataset only contains information on those completing degrees; there is no information on persons graduating from high school and not completing a USG degree. Fortunately, we can overcome this difficulty by using the recently released PUMS dataset from the U.S. Census Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 36 Bureau. The PUMS data contains a 1 percent sample of the Georgia population, and includes a weight factor that allows data aggregations to reflect the population as a whole. Because it is microdata (individual records without any identifying information), researchers can create any type of cross-tabulation and are not restricted to the tables published by the Census Bureau. Table 5.1 was produced from the PUMS dataset (excluding those earning more than $10,000 per year), and shows the relationship between education and earnings for those aged 2130 (the approximate age range of those included in the graduate-worker matched dataset). Table 5.2 contains similar estimates for the graduate-worker dataset. In Table 5.2, an estimated earnings value of $22,000 for high school graduates produces similar ratios of higher education values, and matches exactly the earnings ratio for bachelor's degrees to high school graduates. Table 5.1: Earnings by Education Level from Census PUMS Data Level of Education Percent of Earnings Due 1999 to Higher Earnings Education No schooling completed Nursery school to 4th grade 5th grade or 6th grade 7th grade or 8th grade 9th grade 10th grade 11th grade 12th grade, no diploma High school graduate Some college, but less than 1 year One or more years of college, no degree Associate's degree Bachelor's degree Master's degree Professional degree Doctoral degree Source: U.S. Census Bureau, Public Use Microdata Sample, 2003. $ 19,960 22,941 18,161 19,280 21,977 21,445 21,522 20,758 24,012 25,354 25,619 28,593 36,429 39,772 48,869 44,412 0% 5% 6% 16% 34% 40% 51% 46% Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 37 Table 5.2 Earnings Due to Higher Education by Education Level Level of Education Percent of Earnings due 1998 to Higher Earnings Education High School Graduate (estimated) Certificate Bachelor's Master's Professional Doctoral $22,000 29,585 33,261 43,567 54,796 53,883 Source: USG-Georgia Department of Labor matched dataset, 1998. 0% 26% 34% 50% 60% 59% The wage analysis estimates incremental earnings due to higher education by applying the percentages in the second table to the earnings reported in the graduate-worker matched dataset. These estimates calculate the economic value of recent graduates (1993-1997) for the 1998 Georgia economy. In general, the incremental percentage of earnings due to higher education increases as educational levels increase. Higher education accounts for only 16 percent of the earnings of an associate's degree graduate, but up to 60 percent of the earnings of a graduate with a professional degree such as law or medicine. Findings: Total Economic Impact of USG in 1998 Nearly $1.25 Billion The USG's total economic impact on the Georgia economy in 1998 was nearly $1.25 billion. The average value of a USG education to its roughly 90,000 graduates was just under $14,000 per graduate. Table 5.3 presents the economic impact of higher education on recent graduates of USG institutions. Based on total impact, the top two institutions are Georgia State University and University of Georgia, each representing a total economic impact from higher education of more than $200 million apiece, followed by the Georgia Institute of Technology with a total economic impact of more than $100 million. On a per graduate basis, Medical College of Georgia, Georgia Institute of Technology, and Georgia State University had the highest economic impacts of more than $18,000 per graduate. Institutional rankings depend on the types of instructional programs offered. Appendix 2 Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 38 presents the 1998 economic impact of higher education on recent graduates for the top 10 most lucrative instructional programs based on total and average values. The top program in terms of total impact is business administration, followed by nursing and teaching. This ranking reflects the large numbers of students who graduate with these majors. The three top programs with the greatest average values are the professional degrees--dentistry, medicine, and law. Table 5.3: 1998 Economic Impact of Higher Education by Institution Institution Georgia State University University of Georgia Georgia Institute of Technology State University of West Georgia Georgia Southern Univ. Kennesaw State University Valdosta State University Georgia College & State Univ. Southern Polytechnic State Universit Medical College of Georgia Columbus State University North Georgia College & State Univ. Georgia Southwestern Univ. Augusta State University Georgia Perimeter College Clayton College & State Univ. Armstrong Atlantic State Univ. Albany State University Fort Valley State Univ. Macon State College Abraham Baldwin Agricultural College Gainesville College Darton College Floyd College Dalton State College Gordon College Savannah State University Coastal Georgia Community College South Georgia College Middle Georgia College Atlanta Metropolitan College Bainbridge College Waycross College East Georgia College Statewide Count Total Wages Educational Value Average Average Educational Wage Value 11767 $ 14383 5472 5250 6550 4198 4287 3139 1912 1517 2254 2076 1724 1603 2155 1829 1668 1034 918 1078 980 937 908 795 828 759 543 596 565 587 320 324 201 172 499,691,357 $ 217,838,198 $ 518,041,561 211,175,465 254,639,260 101,895,959 189,640,420 83,267,303 211,194,146 83,101,150 164,604,740 62,562,811 132,613,463 53,597,070 100,252,797 39,595,895 86,888,370 32,569,378 66,002,953 29,372,187 74,191,454 26,964,491 66,779,215 25,254,200 55,394,110 21,903,950 52,722,323 20,357,182 70,770,481 18,400,325 60,485,718 17,500,668 50,959,709 16,533,367 32,890,689 13,285,723 26,845,393 10,957,098 32,080,474 8,340,923 27,023,427 7,026,091 25,882,630 6,729,484 25,852,419 6,721,629 23,230,795 6,040,007 22,987,175 5,976,666 21,037,987 5,469,877 14,559,252 4,999,921 17,239,011 4,482,143 16,155,240 4,200,362 16,100,461 4,186,120 8,510,189 2,212,649 7,948,270 2,066,550 5,025,167 1,306,543 3,774,976 981,494 42,465 $ 18,513 36,018 14,682 46,535 18,621 36,122 15,860 32,243 12,687 39,210 14,903 30,934 12,502 31,938 12,614 45,444 17,034 43,509 19,362 32,915 11,963 32,167 12,165 32,131 12,705 32,890 12,699 32,840 8,538 33,070 9,568 30,551 9,912 31,809 12,849 29,243 11,936 29,759 7,737 27,575 7,169 27,623 7,182 28,472 7,403 29,221 7,597 27,762 7,218 27,718 7,207 26,813 9,208 28,925 7,520 28,593 7,434 27,428 7,131 26,594 6,915 24,532 6,378 25,001 6,500 21,948 5,706 89,652 $ 3,234,142,486 $ 1,249,963,035 $ 36,074 $ 13,942 Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 39 Table 5.4 Top 10 Programs with the Greatest Total Economic Impact in 1998 Based on Educational Value Description Count Total Wages Educational Value Average Average Educational Wage Value Business Administration & Mgmt., Gen. Nursing (R.N. Training) Pre-Elem/Erly Childhd/KG. Teach Educ Jr High/Intermed/Middle Sch Teach Educ Liberal Arts & Sciences/Liberal Studies Accounting Computer and Information Sciences, Gen. Education Admin. & Supervision, Gen. Law (LL.B., J.D.) Business, General 4,609 $ 205,509,260 $ 6,764 227,611,427 4,518 134,137,737 3,435 113,259,285 6,684 186,231,485 2,892 104,386,812 1,865 92,872,771 1,300 70,044,392 1,000 52,503,545 1,432 69,576,826 83,642,480 $ 68,304,553 55,144,047 49,656,280 48,469,272 37,112,341 36,214,314 35,699,158 31,492,540 31,020,608 44,589 $ 18,148 33,650 10,098 29,690 12,205 32,972 14,456 27,862 7,252 36,095 12,833 49,798 19,418 53,880 27,461 52,504 31,493 48,587 21,662 Table 5.5 Top 10 Programs with the Greatest Average Economic Impact in 1998 Based on Educational Value Description Dentistry (D.D.S., D.M.D.) Medicine (M.D.) Law (LL.B., J.D.) Education Admin. & Supervision, Gen. Health System/Health Services Admin. Taxation Veterinary Medicine (D.V.M.) Enterprise Management & Operation, Gen. Adult and Continuing Teacher Education Nursing, Other Count Total Wages Educational Value Average Average Educational Wage Value 77 $ 5,953,818 $ 321 20,050,938 1,000 52,503,545 1,300 70,044,392 80 4,180,731 132 6,892,631 140 6,006,569 168 8,929,459 172 8,221,165 100 4,831,923 3,572,291 $ 12,030,563 31,492,540 35,699,158 2,090,365 3,446,316 3,603,941 4,252,463 4,297,671 2,473,403 77,322 $ 46,393 62,464 37,478 52,504 31,493 53,880 27,461 52,259 26,130 52,217 26,108 42,904 25,742 53,152 25,312 47,797 24,986 48,319 24,734 Figure 5.1 maps the total economic impact in millions of dollars, and Figure 5.2 maps the average impact per USG graduate. In 93 counties across the state, the USG had a per-county economic impact of more than $1 million in 1998. USG's impact was more than $10 million in 17 counties, mostly in Atlanta and Georgia's mid-sized cities. (See Appendix 3 for a listing of impacts by county.) It is important to remember that this impact is only for one year's worth of benefits (1998) to a single graduate cohort (1993 to 1997 graduates). A more complete cost-benefit analysis would extend these benefits over a full 40-year career. Benefits thus could be as large as 40 times the total impact indicated in this report. Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 40 Figure 5.1: Economic Impact by County (in Millions of Dollars) Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 41 Figure 5.2: Average Economic Impact per Graduate (in Dollars) Conclusion Drawing on the methodology developed by the U.S. Census Bureau in its study, "The Big Payoff," this analysis has shown that graduating from a USG institution pays off. Not only did it pay off to the average graduate in the 1993 to 1997 time period, to the tune of about $14,000 in 1998, but more significantly it paid off to the state as a whole, by nearly $1.25 billion. It also paid off to 93 counties, each of which benefited by more than $1 million from USG graduates. These impacts reflect only a single year (1998) in the careers of a five-year (1993-1997) Section 5CEconomic Value of USG Students: A Wage-Based Analysis ! 42 graduate cohort. The total benefits could be as much as 40 times higher over this cohort's full work-life. Section 6 Future Directions Section 6CFuture Directions ! 44 This report has examined the value of a USG education from three perspectives: (1) filling jobs in high demand occupations, (2) impacting the migration of graduates within the state, and (3) demonstrating the economic impact of USG education on the state's 1998 economy. The demand-based shortfall analysis continues USG's tradition of monitoring needs for talent in high-demand occupations requiring university education. It shows that the state faces significant health care shortfalls, along with shortages of elementary school teaching and selected IT positions, a situation which calls for a central role for the USG. The migration study introduced new techniques for examining critical issues. The migration analysis presented projections of declining in-migration of educated workers from other states into Georgia through 2025. This finding suggests that close attention should be paid to the needs of high-demand occupations and the extent to which the state must step up to fill employment gaps caused by reduced numbers of in-migrants. This report also introduced new techniques for showing the vital role that USG plays in the state's economy based on educational attainment and wages. These analyses should be continued in several future directions. First, the regional shortfall analysis should be updated as new projections become available from the Georgia Department of Labor. Sub-state regional projections are due to be updated in the coming year. Second, the USG should initiate another round of matching of its graduates with Georgia Department of Labor employment security data for multiple years beyond 1998. This larger database would enable an updated tracking of USG graduates and facilitate a more complete understanding of the impact of particular USG institutions on intrastate migration. Third, the wage-based economic analysis presented in this report should be extended to a full wage benefit-cost analysis. This benefit-cost analysis should incorporate resident instruction expenditures and be applied to all graduates (not just the most recent ones). Such an analysis would show the extent to which the full benefits of higher education compare to the costs of providing this education. In tight economic times, such information can be particularly worthwhile in demonstrating the value of higher education. Section 7 References Section 7CReferences ! 46 Day, J. D. and Newburger, E. D, 2002, July. "The Big Payoff: Educational Attainment and Synthetic Estimates of Work-Life Earnings." Current Population Reports. Washington, D.C. U.S. Census Bureau. Drummond, W.J. and Youtie, J.L., 2001, August. "Our Students and Alumni: Where Do They Come From and Where Do They Go?" Atlanta Georgia: Georgia Tech Research Corporation. Drummond, W.J. and Youtie, J.L., 2003, June. "Supply and Demand of Human Capital for the Biosciences Industry." Atlanta Georgia: Georgia Tech Research Corporation. Duhart, S. H., 2002, March. The Economic Impact of University System Institutions on their Regional Economies. Atlanta, Georgia: Intellectual Capital Partnership Program. Humphries, J. M., Clements, D. H., Lowe, J., and Sapp, T. W., (1999, May-June). "Economic Impact of the University of Georgia on the Athens Area," Georgia Business and Economic Conditions. 59 (3): pp. 1-10. Seligman, D, 2002, November 25. "The Story They All Got Wrong," Forbes. Wash, Darrel Patrick. "A New Way to Classify Occupations by Education and Training," Occupational Outlook Quarterly. Winter 1995-1996, Vol. 39, No. 4, pp. 28-41. Watson, N., 2002, October 4. "Generation X: Generation Wrecked," Fortune. Appendix 1 Intrastate Migration Model The following table shows the models estimated for all students at all institutions, then four additional models that separately estimate parameters for four-year institutions, historically black institutions, research institutions, and two-year institutions. The dependent variable is the home county-school county-work county flow of students (with all flows below 5 omitted), weighted by the size of the flow. Variable All USG Institutions Four Year Inst. Hist. Black Inst. Research Inst. Two Year Inst. (Constant) LHGRADS 1 LSGRADS LWGRADS 2 LEWAGE LHWTIME 3 LHSTIME LSWTIME 4 HWSAME HWADJ2 5 HSSAME HSADJ2 SWSAME 6 SWADJ2 -6.10 *** 0.27 *** 0.44 *** 0.44 *** 1.05 *** -0.33 *** -0.46 *** -0.18 *** 1.59 *** 0.58 *** 0.49 *** 0.10 *** 0.27 *** -0.15 *** -5.02 *** 0.14 *** 0.41 *** 0.43 *** 0.79 *** -0.16 *** -0.33 *** -0.39 *** 1.99 *** 0.58 *** 0.85 *** 0.02 0.01 -0.10 *** -10.10 *** 0.22 *** 0.91 *** 0.49 *** 1.02 *** -0.01 *** -0.81 *** 0.29 *** 1.54 *** 0.21 *** -0.03 -0.71 1.84 *** 1.33 *** -14.45 *** 0.55 *** 0.90 *** 0.55 *** 0.25 *** -0.55 *** -0.24 *** -0.23 *** 1.04 *** 0.39 *** 0.28 *** 0.19 *** 0.14 *** -0.23 *** -5.39 *** 0.05 *** 0.51 *** 0.42 *** 0.80 *** -0.26 *** 0.51 *** -0.22 *** 1.41 *** 0.29 *** 2.16 *** 1.14 *** 0.51 *** 0.19 *** Adj R Square N 0.77 80,440 0.79 36,661 0.91 2,089 *** Parameter is significant at the .001 level of significance. 0.86 31,376 0.80 10,321 LFLOW LHGRADS LSGRADS LWGRADS LEWAGE LHWTIME LHSTIME LSWTIME HWSAME HWADJ2 HSSAME HSADJ2 SWSAME SWADJ2 natural log of the flow of students from home county to (number of students flowing over school county to work county this home-school-work path) natural log of the number of USG graduates from the home county (size of sending population from home county) natural log of the number of students at the institution (size of institution) natural log of the number of USG graduates found working in the county (size of employment in work county) natural log of USG graduate wages in the working county (wages) natural log of home county-work county travel time (home-work distance) natural log of home county-school county travel time (home-school distance) natural log of school county-work county travel time (school-work distance) home county and work county are the same (home-work local effect) home county and work county are adjacent (home-work regional effect) home county and school county are the same (home-school local effect) home county and school county are adjacent (home-school regional effect) school county and work county are the same (school-work local effect) school county and work county are adjacent (school-work regional effect) Due to the multiplicative nature of the gravity model, the regression parameters involving natural logarithms can be interpreted as elasticities. An elasticity of 1.0 means that a 10 percent increase in the value of an independent variable produces a 10 percent increase (or decrease, if the parameter sign is negative) in the value of the dependent variable. Appendix 2 Economic Impact of Higher Education by CIP Description Agricultural Business/Agribusiness Oper. Agricultural Economics Horticulture Svcs. Ops. and Mgmt., Gen. Animal Sciences, General Poultry Science Food Sciences and Tech. Agronomy and Crop Science Forest Harvesting and Production Tech. Forestry, General Wildlife and Wildlands Management Architecture City/Urban, Community & Reg. Planning Landscape Architecture Fashion Merchandising Gen. Retail & Whlsale Opns. & Skills,Oth Marketing Opns/Market. & Distrib.,Oth Communications, General Advertising Journalism Broadcast Journalism Mass Communications Public Relations & Organizational Comm. Radio and Television Broadcasting Tech. Computer and Information Sciences, Gen. Information Sciences and Systems Education Admin. & Supervision, Gen. Educational Supervision Educational/Instructional Media Design Educ. Assessment, Testing & Measurement Educational Psychology Special Education, General Education of the Deaf & Hearing Impaired Education of the Emotionally Handicapped Education of the Mentally Handicapped Education of the Multiple Handicapped Education of the Physically Handicapped Educ. of the Specific Learning Disabled Education of the Speech Impaired Counselor Educ. Counseling & Guid. Svc. Adult and Continuing Teacher Education Elementary Teacher Education Count Total Wages Average Educational Average Educational Value Wage Value 32 $ 1,144,736 $ 380,444 $ 35,773 $ 11,889 102 3,195,829 1,116,054 31,332 10,942 144 3,732,228 1,117,734 25,918 7,762 75 2,310,407 812,549 30,805 10,834 45 1,433,299 545,653 31,851 12,126 36 1,122,934 493,008 31,193 13,695 29 926,021 373,571 31,932 12,882 60 1,672,422 434,830 27,874 7,247 183 5,870,401 2,239,956 32,079 12,240 69 1,667,671 449,517 24,169 6,515 331 11,774,151 4,776,348 35,571 14,430 60 2,338,792 1,169,396 38,980 19,490 155 4,779,397 1,746,304 30,835 11,266 56 1,555,020 528,707 27,768 9,441 268 10,128,172 3,443,578 37,792 12,849 42 1,192,645 405,499 28,396 9,655 504 16,047,691 5,590,646 31,841 11,093 180 5,640,928 1,917,915 31,338 10,655 476 14,211,295 4,919,586 29,856 10,335 42 1,364,348 455,499 32,484 10,845 44 1,338,011 680,604 30,409 15,468 170 5,066,615 1,722,649 29,804 10,133 146 4,605,523 1,565,878 31,545 10,725 1,865 92,872,771 36,214,314 49,798 19,418 346 15,826,961 5,446,664 45,743 15,742 1,300 70,044,392 35,699,158 53,880 27,461 352 16,863,348 8,482,213 47,907 24,097 433 17,512,253 8,804,345 40,444 20,333 100 3,759,265 1,879,633 37,593 18,796 158 5,216,441 2,389,460 33,015 15,123 1,119 34,305,509 14,635,394 30,657 13,079 61 1,976,960 749,431 32,409 12,286 228 8,433,552 4,231,309 36,989 18,558 414 13,687,896 5,860,177 33,063 14,155 57 2,077,498 1,038,749 36,447 18,224 211 7,747,488 3,873,744 36,718 18,359 205 7,804,915 3,902,457 38,073 19,036 65 1,735,740 764,128 26,704 11,756 1,226 43,860,696 22,010,070 35,775 17,953 172 8,221,165 4,297,671 47,797 24,986 1,894 61,276,872 26,300,006 32,353 13,886 CIP 13.1203 13.1204 13.1205 13.1301 13.1302 13.1303 13.1305 13.1306 13.1307 13.1308 13.1309 13.131 13.1311 13.1312 13.1314 13.1315 13.1316 13.1317 13.1318 13.1319 13.132 13.133 13.1401 13.9999 14.0201 14.0301 14.0701 14.0801 14.0901 14.1001 14.1401 14.1701 14.1801 14.1901 14.2801 15.0101 15.0201 15.0301 15.0303 15.0603 15.0699 Description Count Total Wages Educational Value Average Average Educational Wage Value Jr High/Intermed/Middle Sch Teach Educ Pre-Elem/Erly Childhd/KG. Teach Educ Secondary Teacher Education Agricultural Teacher Educ (Vocational) Art Teacher Education Business Teacher Education (Vocational) English Teacher Education Foreign Languages Teacher Education Health Teacher Education Home Economics Teacher Educ (Vocational) Technology/Industrial Arts Teacher Educ. Mkt. Op./Mkt. & Distrib. Teacher Educ. Mathematics Teacher Education Music Teacher Education Physical Education Teaching and Coaching Reading Teacher Education Science Teacher Education, General Social Science Teacher Education Social Studies Teacher Education Technical Teacher Education (Vocational) Trade & Industrial Teacher Educ. (Voc) Spanish Language Teacher Education Teaching ESL/Foreign Language Education, Other Aerospace, Aeronautical and Astronautic Agricultural Engineering Chemical Engineering Civil Engineering, General Computer Engineering Electrical, Electronics & Communication Environmental/Environmental Health Engin Industrial/Manufacturing Engineering Material Engineering Mechanical Engineering Textile Sciences and Engineering Architectural Engineering Techno/Tech Civil Engineering/Civil Tech./Technician Computer Engineering Tech./Technician Elec., Electronic & Comm. Engin. Tech. Industrial/Manufacturing Tech/Technician Industrial Product. Technol./Techn, Oth. 3,435 4,518 299 67 227 324 474 118 160 86 187 27 577 270 1,141 155 332 380 151 103 98 35 37 117 105 60 182 507 80 810 33 715 27 615 77 62 282 72 441 32 69 113,259,285 134,137,737 9,447,384 2,527,598 6,824,167 11,302,748 16,085,303 3,871,376 4,873,588 2,877,947 7,061,956 1,206,617 21,143,382 8,243,489 36,450,262 6,018,182 12,427,992 11,933,392 5,599,220 4,719,949 5,237,002 1,007,320 1,292,462 4,290,560 5,199,631 2,364,553 7,704,471 21,031,503 4,301,743 42,491,892 1,586,508 34,596,614 1,126,517 28,914,625 3,359,819 2,569,395 10,562,128 2,881,587 20,381,034 1,203,453 2,589,875 49,656,280 55,144,047 4,001,975 1,101,440 2,797,164 5,026,755 7,253,074 1,680,655 1,884,212 1,266,123 2,830,419 465,641 9,912,378 3,369,426 14,752,130 3,036,194 5,987,285 4,909,756 2,516,581 2,476,143 2,416,346 443,950 646,231 2,163,080 2,307,421 825,416 2,791,399 8,562,128 1,462,593 17,313,852 793,254 12,817,671 383,016 11,199,098 1,369,130 873,594 3,591,123 979,740 6,765,493 398,961 880,557 32,972 29,690 31,597 37,725 30,062 34,885 33,935 32,808 30,460 33,465 37,764 44,690 36,644 30,531 31,946 38,827 37,434 31,404 37,081 45,825 53,439 28,781 34,931 36,671 49,520 39,409 42,332 41,482 53,772 52,459 48,076 48,387 41,723 47,016 43,634 41,442 37,454 40,022 46,216 37,608 37,534 14,456 12,205 13,385 16,439 12,322 15,515 15,302 14,243 11,776 14,722 15,136 17,246 17,179 12,479 12,929 19,588 18,034 12,920 16,666 24,040 24,657 12,684 17,466 18,488 21,975 13,757 15,337 16,888 18,282 21,375 24,038 17,927 14,186 18,210 17,781 14,090 12,734 13,607 15,341 12,468 12,762 CIP 15.0805 15.1001 15.1101 16.0501 16.0901 16.0905 19.0402 19.0501 19.0503 19.0601 19.0701 19.0901 22.0101 22.0103 23.0101 23.1001 23.1101 24.0101 24.0199 26.0101 26.0202 26.0501 26.0701 27.0101 27.0302 27.0501 30.0101 30.9999 31.0101 31.0301 31.0501 31.0504 31.0505 38.0101 40.0501 40.0601 40.0699 40.0801 42.0101 42.0901 42.1701 Description Mechanical Engineering/Mechanical Tech. Construction/Building Tech./Technician Engineering-Related Tech/Technician, Gen German Language and Literature French Language and Literature Spanish Language and Literature Consumer Economics and Science Foods and Nutrition Studies, General Dietetics/Human Nutritional Services Housing Studies, General Individual/Family Devel. Studies, Gen. Clothing/Apparel and Textile Studies Law (LL.B., J.D.) Paralegal/Legal Assistant English Language and Literature, General Speech and Rhetorical Studies English Technical and Business Writing Liberal Arts & Sciences/Liberal Studies Lib. Art&Sci., Gen. Studies&Human., Oth Biology, General Biochemistry Microbiology/Bacteriology Zoology, General Mathematics Operations Research Mathematical Statistics Biological and Physical Sciences Multi/Interdisciplinary Studies, Other Parks, Recreation and Leisure Studies Parks, Rec. & Leisure Facilities Mgmt. Health and Physical Education, General Sport and Fitness Administration/Mgmt. Exercise Sciences/Physiology & Movement Philosophy Chemistry, General Geology Geological and Related Sciences, Other Physics, General Psychology, General Industrial and Organizational Psychology School Psychology Count Total Wages Educational Value Average Average Educational Wage Value 273 245 279 35 75 157 77 75 65 72 205 31 1,000 47 1,037 390 64 6,684 301 1,095 45 69 76 436 155 66 38 97 124 113 44 123 37 77 385 102 38 177 1,894 50 95 11,459,492 10,217,067 12,642,996 998,831 2,053,917 4,397,702 2,426,053 2,163,339 1,751,732 2,144,227 4,996,078 937,113 52,503,545 1,263,932 29,750,722 14,297,884 2,589,063 186,231,485 9,311,265 31,112,194 1,328,777 2,257,425 2,331,868 14,426,171 8,167,442 3,189,217 1,473,728 3,076,208 3,254,407 2,930,288 1,394,620 3,996,741 1,072,728 2,099,265 13,189,917 3,177,692 1,374,878 7,425,007 52,670,640 2,330,760 3,597,538 3,890,630 3,544,352 4,709,904 358,940 717,998 1,516,808 824,858 807,342 595,589 753,162 1,853,036 334,373 31,492,540 371,528 10,827,428 4,916,434 1,268,426 48,469,272 3,399,056 11,050,004 580,895 830,974 816,904 5,157,473 3,495,532 1,474,445 501,068 1,114,406 1,106,498 1,027,492 474,171 1,680,166 460,131 754,572 4,995,746 1,259,935 688,351 2,994,509 19,497,813 1,089,261 1,821,610 41,976 41,702 45,315 28,538 27,386 28,011 31,507 28,845 26,950 29,781 24,371 30,229 52,504 26,892 28,689 36,661 40,454 27,862 30,934 28,413 29,528 32,716 30,682 33,088 52,693 48,321 38,782 31,713 26,245 25,932 31,696 32,494 28,993 27,263 34,260 31,154 36,181 41,949 27,809 46,615 37,869 14,251 14,467 16,881 10,255 9,573 9,661 10,712 10,765 9,163 10,461 9,039 10,786 31,493 7,905 10,441 12,606 19,819 7,252 11,293 10,091 12,909 12,043 10,749 11,829 22,552 22,340 13,186 11,489 8,923 9,093 10,777 13,660 12,436 9,800 12,976 12,352 18,114 16,918 10,295 21,785 19,175 CIP 43.0103 43.0104 43.0107 43.0199 43.0201 44.0401 44.0701 45.0201 45.0601 45.0701 45.0801 45.0901 45.1001 45.1101 45.1201 45.9999 47.0101 47.0104 47.0303 47.0604 47.0608 48.0102 48.0201 48.9999 50.0101 50.0404 50.0408 50.0501 50.0601 50.0701 50.0703 50.0705 50.0901 50.0903 51.0201 51.0203 51.0301 51.0401 51.0602 51.0701 Description Criminal Justice/Law Enforcement Admin. Criminal Justice Studies Law Enforcement/Police Science Criminal Justice and Corrections, Other Fire Protection and Safety Tech./Technic Public Administration Social Work Anthropology Economics, General Geography History, General International Relations and Affairs Political Science, General Sociology Urban Affairs/Studies Social Sciences and History, Other Electrical and Electronics Equipment Ins Computer Installer and Repairer Industrial Machinery Main. and Repairer Auto/Automotive Mechanic/Technician Aircraft Mechanic/Technician, Powerplant Architectural Drafting Graphic & Printing Equip. Operator, Gen. Precision Production Trades, Other Visual and Performing Arts Industrial Design Interior Design Drama/Theater Arts, General Film/Cinema Studies Art, General Art History, Criticism and Conservation Drawing Music, General Music - General Performance Communication Disorders, General Speech-Language Pathology Community Health Liaison Dentistry (D.D.S., D.M.D.) Dental Hygienist Health System/Health Services Admin. Count Total Wages Educational Value Average Average Educational Wage Value 102 1,343 114 71 80 536 649 106 247 108 701 67 799 674 202 148 58 26 41 31 58 29 68 163 188 51 28 61 68 353 37 177 37 94 158 281 39 77 383 80 2,973,496 37,733,176 3,038,069 1,737,270 3,490,772 18,453,896 17,036,415 2,724,316 9,416,494 3,231,414 20,961,390 2,311,275 25,789,515 17,882,550 7,521,668 5,102,668 2,088,163 1,006,082 1,497,399 967,208 2,098,649 897,578 2,273,872 5,927,990 5,676,952 1,645,070 771,643 1,628,760 2,094,615 9,570,609 1,117,509 5,465,502 1,044,347 2,874,073 4,659,186 8,155,197 759,788 5,953,818 12,540,968 4,180,731 992,794 12,650,821 935,357 590,672 907,601 8,653,454 7,229,601 1,018,815 3,357,356 1,198,072 7,585,428 785,834 8,942,002 6,435,774 2,828,031 2,393,146 542,922 261,581 389,324 251,474 545,649 233,370 773,117 1,541,277 1,930,164 559,324 262,359 620,096 712,169 3,331,379 387,428 1,974,465 425,733 1,164,009 1,949,575 3,478,009 197,545 3,572,291 3,346,090 2,090,365 29,152 28,096 26,650 24,469 43,635 34,429 26,250 25,701 38,123 29,921 29,902 34,497 32,277 26,532 37,236 34,477 36,003 38,695 36,522 31,200 36,184 30,951 33,439 36,368 30,197 32,256 27,559 26,701 30,803 27,112 30,203 30,879 28,226 30,575 29,489 29,022 19,482 77,322 32,744 52,259 9,733 9,420 8,205 8,319 11,345 16,145 11,140 9,611 13,593 11,093 10,821 11,729 11,191 9,549 14,000 16,170 9,361 10,061 9,496 8,112 9,408 8,047 11,369 9,456 10,267 10,967 9,370 10,166 10,473 9,437 10,471 11,155 11,506 12,383 12,339 12,377 5,065 46,393 8,737 26,130 CIP 51.0706 51.0801 51.0803 51.0806 51.0807 51.0904 51.0907 51.0908 51.091 51.1004 51.1005 51.1201 51.1399 51.1502 51.1599 51.1601 51.1602 51.1613 51.1699 51.2001 51.2202 51.2306 51.2308 51.231 51.2401 51.9999 52.0101 52.0201 52.0202 52.0203 52.0204 52.0205 52.0299 52.0301 52.0302 52.0401 52.0408 52.0499 52.0601 52.0701 52.0801 52.0802 52.0805 52.0902 52.1002 52.1101 52.1201 52.1202 52.1301 52.1399 52.1401 52.1501 52.1601 52.9999 Description Count Total Wages Educational Value Average Average Educational Wage Value Medical Records Administration Medical Assistant Occupational Therapy Assistant Physical Therapy Assistant Physician Assistant Emergency Medical Tech./Technician Medical Radiologic Tech./Technician Respiratory Therapy Technician Diagnostic Medical Sonography Medical Laboratory Technician Medical Technology Medicine (M.D.) Basic Medical Sciences, Other Psychiatric/Mental Health Services Tech. Mental Health Services, Other Nursing (R.N. Training) Nursing Administration (Post-R.N.) Practical Nurse (L.P.N. Training) Nursing, Other Pharmacy (B. Pharm., Pharm.D.) Environmental Health Occupational Therapy Physical Therapy Vocational Rehabilitation Counseling Veterinary Medicine (D.V.M.) Health Professions & Rel. Sciences, Oth. Business, General Business Administration & Mgmt., Gen. Purchasing, Procurement & Contracts Mgmt Logistics and Materials Management Office Supervision and Management Operations Management and Supervision Business Administration & Mgmt., Oth. Accounting Accounting Technician Administrative Assistant/Secretarial Sci General Office/Clerical & Typing Serv. Administrative & Secretarial Serv., Oth. Business/Managerial Economics Enterprise Management & Operation, Gen. Finance, General Actuarial Science Insurance and Risk Management Hotel/Motel and Restaurant Management Labor/Personnel Relations and Studies International Business Mgmt. Info. Systems & Bus. Data Process Business Computer Programming/Programmer Management Science Bus. Quantitative Methods & Mgmt.,Oth. Business Marketing/Marketing Management Real Estate Taxation Business Management & Admin. Serv., Oth. 40 81 32 50 60 68 106 182 28 63 117 321 61 26 32 6,764 126 76 100 420 137 87 224 111 140 323 1,432 4,609 60 62 59 39 42 2,892 63 184 106 37 211 168 1,794 71 543 168 78 352 694 37 52 85 1,774 191 132 226 1,390,709 1,599,433 990,652 1,645,048 3,164,931 1,832,693 3,034,803 5,466,676 1,063,699 1,556,203 3,736,378 20,050,938 1,537,303 677,185 918,791 227,611,427 5,153,897 1,604,108 4,831,923 22,254,873 4,053,098 3,076,837 9,722,245 3,554,427 6,006,569 9,851,041 69,576,826 205,509,260 1,939,947 2,080,041 1,581,552 1,514,645 2,271,985 104,386,812 1,503,357 3,886,452 2,395,071 758,390 7,968,208 8,929,459 73,921,879 3,530,735 21,355,916 5,277,682 3,215,103 16,158,678 29,166,370 1,512,787 2,073,271 2,900,015 66,129,808 9,671,210 6,892,631 6,202,650 472,841 415,853 257,569 427,713 1,076,077 476,500 815,225 1,648,176 320,816 404,613 1,284,984 12,030,563 520,660 230,243 459,395 68,304,553 1,752,325 417,068 2,473,403 8,895,704 1,398,488 1,046,125 3,400,735 1,777,213 3,603,941 3,547,225 31,020,608 83,642,480 659,582 816,589 534,141 525,881 913,088 37,112,341 390,873 1,079,958 622,718 197,181 2,911,250 4,252,463 28,245,246 1,609,430 7,846,564 1,794,412 1,416,719 6,631,424 10,023,574 393,325 704,912 986,005 23,550,602 3,959,684 3,446,316 1,612,689 34,768 19,746 30,958 32,901 52,749 26,951 28,630 30,037 37,989 24,702 31,935 62,464 25,202 26,046 28,712 33,650 40,904 21,107 48,319 52,988 29,585 35,366 43,403 32,022 42,904 30,499 48,587 44,589 32,332 33,549 26,806 38,837 54,095 36,095 23,863 21,122 22,595 20,497 37,764 53,152 41,205 49,729 39,330 31,415 41,219 45,905 42,026 40,886 39,871 34,118 37,277 50,635 52,217 27,445 11,821 5,134 8,049 8,554 17,935 7,007 7,691 9,056 11,458 6,422 10,983 37,478 8,535 8,856 14,356 10,098 13,907 5,488 24,734 21,180 10,208 12,024 15,182 16,011 25,742 10,982 21,662 18,148 10,993 13,171 9,053 13,484 21,740 12,833 6,204 5,869 5,875 5,329 13,797 25,312 15,744 22,668 14,450 10,681 18,163 18,839 14,443 10,630 13,556 11,600 13,275 20,731 26,108 7,136 Appendix 3 Economic Impact of Higher Education by County County Appling Atkinson Bacon Baker Baldwin Banks Barrow Bartow Ben Hill Berrien Bibb Bleckley Brantley Brooks Bryan Bulloch Burke Butts Calhoun Camden Candler Carroll Catoosa Charlton Chatham Chattahoochee Chattooga Cherokee Clarke Clayton Clinch Cobb Coffee Colquitt Columbia Cook Coweta Crawford Crisp Dade Dawson Count Total Wages Average Educational Average Educational Value Wage Value 6,323 $ 252,126,854 $ 93,090,156 $ 39,875 $ 14,722 20 647,115 238,374 32,356 11,919 68 1,984,167 776,500 29,179 11,419 113 3,355,694 1,284,435 29,696 11,367 29 696,443 259,584 24,015 8,951 423 12,769,301 5,039,343 30,187 11,913 26 782,136 335,704 30,082 12,912 244 7,353,093 2,970,083 30,136 12,172 336 10,683,938 4,305,093 31,797 12,813 188 6,198,741 2,471,622 32,972 13,147 103 2,956,536 1,175,268 28,704 11,410 2,208 73,386,458 26,278,534 33,237 11,902 90 2,536,207 1,006,591 28,180 11,184 129 3,700,262 1,498,976 28,684 11,620 82 2,292,702 968,924 27,960 11,816 16 659,767 287,247 41,235 17,953 767 22,369,354 9,167,471 29,165 11,952 152 4,435,973 1,770,339 29,184 11,647 32 769,086 234,796 24,034 7,337 28 882,907 348,993 31,532 12,464 266 8,530,298 3,479,026 32,069 13,079 75 2,244,472 865,301 29,926 11,537 848 28,908,212 11,674,158 34,090 13,767 178 5,526,088 2,121,752 31,045 11,920 66 2,111,881 901,278 31,998 13,656 2,226 75,409,034 28,478,833 33,876 12,794 12 347,721 138,735 28,977 11,561 42 1,257,090 495,758 29,931 11,804 570 21,083,296 8,708,116 36,988 15,277 1,650 48,783,847 20,415,827 29,566 12,373 1,631 61,247,266 23,600,963 37,552 14,470 52 1,683,659 653,214 32,378 12,562 6,703 259,787,054 102,654,575 38,757 15,315 381 11,963,754 4,425,816 31,401 11,616 342 10,681,106 4,059,096 31,231 11,869 486 16,697,633 6,876,684 34,357 14,150 106 3,191,332 1,215,990 30,107 11,472 450 16,881,569 7,006,210 37,515 15,569 47 1,179,976 458,295 25,106 9,751 237 6,871,356 2,714,003 28,993 11,451 20 859,282 395,060 42,964 19,753 88 2,906,901 1,199,778 33,033 13,634 County De Kalb Decatur Dodge Dooly Dougherty Douglas Early Echols Effingham Elbert Emanuel Evans Fannin Fayette Floyd Forsyth Franklin Fulton Gilmer Glascock Glynn Gordon Grady Greene Gwinnett Habersham Hall Hancock Haralson Harris Hart Heard Henry Houston Irwin Jackson Jasper Jeff Davis Jefferson Jenkins Count Total Wages Educational Value Average Average Educational Wage Value 6,393 242 135 74 1,386 550 65 27 229 73 94 84 94 684 595 460 69 18,234 108 18 775 280 100 81 5,600 166 1,212 31 173 13 48 52 556 1,153 37 291 49 83 39 12 245,300,673 6,601,579 4,251,311 2,244,803 46,846,323 19,979,001 2,206,700 743,936 6,908,027 2,362,628 2,716,871 2,671,545 3,094,734 24,172,648 18,828,864 14,730,552 2,226,662 702,502,314 3,705,472 544,479 25,731,675 8,913,748 3,154,675 2,543,312 212,613,029 5,481,667 40,056,574 849,545 5,244,720 341,928 1,448,130 1,734,942 19,133,619 42,361,611 1,220,189 9,027,148 1,497,616 2,921,820 1,192,286 494,993 95,670,495 2,303,329 1,727,298 884,615 17,300,579 8,384,105 796,581 307,133 2,894,361 998,398 986,523 1,054,738 1,329,920 9,932,441 6,764,739 5,845,374 947,610 276,148,872 1,518,817 244,188 9,318,123 3,128,488 1,214,543 972,494 82,625,120 2,308,984 15,105,490 345,172 2,151,757 126,644 593,895 774,755 7,494,903 16,702,765 371,819 3,444,585 606,573 1,232,414 398,165 159,173 38,370 27,279 31,491 30,335 33,800 36,325 33,949 27,553 30,166 32,365 28,903 31,804 32,923 35,340 31,645 32,023 32,270 38,527 34,310 30,249 33,202 31,835 31,547 31,399 37,967 33,022 33,050 27,405 30,316 26,302 30,169 33,364 34,413 36,740 32,978 31,021 30,564 35,203 30,571 41,249 14,965 9,518 12,795 11,954 12,482 15,244 12,255 11,375 12,639 13,677 10,495 12,556 14,148 14,521 11,369 12,707 13,733 15,145 14,063 13,566 12,023 11,173 12,145 12,006 14,754 13,910 12,463 11,135 12,438 9,742 12,373 14,899 13,480 14,486 10,049 11,837 12,379 14,848 10,209 13,264 County Johnson Jones Lamar Lanier Laurens Lee Liberty Lincoln Long Lowndes Lumpkin Macon Madison Marion McDuffie McIntosh Meriwether Miller Mitchell Monroe Montgomery Morgan Murray Muscogee Newton Oconee Oglethorpe Paulding Peach Pickens Pierce Pike Polk Pulaski Putnam Quitman Rabun Randolph Richmond Rockdale Schley Count 40 87 62 54 445 129 289 25 63 1,015 150 67 96 41 155 71 95 23 163 78 19 136 165 2,062 138 108 46 305 217 126 112 45 189 141 98 1 65 61 1,754 206 22 Total Wages 1,125,179 2,407,480 1,730,467 1,535,307 13,905,645 3,972,889 9,409,630 737,374 1,877,664 30,031,011 4,437,344 2,097,584 2,901,125 1,239,963 4,862,864 2,054,642 2,654,877 591,569 4,563,284 2,308,952 553,749 4,185,370 5,283,008 70,530,863 4,585,871 3,269,398 1,406,267 9,841,231 6,742,114 4,182,539 3,371,277 1,303,644 6,519,632 4,462,684 3,018,545 12,288 1,978,038 1,678,301 59,812,734 6,412,917 707,987 Educational Value Average Average Educational Wage Value 446,018 948,268 718,932 550,422 5,485,058 1,708,242 3,821,479 312,320 795,361 11,466,241 1,895,304 805,538 1,227,926 488,909 1,946,284 781,506 1,094,518 228,706 1,764,454 960,466 266,145 1,698,863 2,149,220 25,782,348 1,583,680 1,424,567 656,510 4,190,020 2,788,518 1,634,410 1,390,208 527,136 2,601,007 1,611,459 1,148,442 4,178 833,915 673,020 23,421,417 2,184,650 291,411 28,129 27,672 27,911 28,432 31,249 30,798 32,559 29,495 29,804 29,587 29,582 31,307 30,220 30,243 31,373 28,939 27,946 25,720 27,996 29,602 29,145 30,775 32,018 34,205 33,231 30,272 30,571 32,266 31,070 33,195 30,101 28,970 34,495 31,650 30,801 12,288 30,431 27,513 34,101 31,131 32,181 11,150 10,900 11,596 10,193 12,326 13,242 13,223 12,493 12,625 11,297 12,635 12,023 12,791 11,925 12,557 11,007 11,521 9,944 10,825 12,314 14,008 12,492 13,026 12,504 11,476 13,190 14,272 13,738 12,850 12,972 12,413 11,714 13,762 11,429 11,719 4,178 12,829 11,033 13,353 10,605 13,246 County Screven Seminole Spalding Stephens Stewart Sumter Talbot Taliaferro Tattnall Taylor Telfair Terrell Thomas Tift Toombs Towns Treutlen Troup Turner Twiggs Union Upson Walker Walton Ware Warren Washington Wayne Webster Wheeler White Whitfield Wilcox Wilkes Wilkinson Worth Unknown Statewide Count Total Wages Educational Value Average Average Educational Wage Value 107 38 393 96 18 434 19 2 107 37 51 58 361 549 151 40 18 443 66 76 74 173 165 320 412 24 182 173 11 26 87 925 27 62 82 140 6,323 3,059,997 925,607 13,285,582 3,148,554 600,355 13,234,120 382,919 83,512 3,267,483 1,110,108 1,443,696 1,735,315 11,293,119 17,094,334 5,626,910 1,542,988 488,984 15,645,923 2,035,911 2,082,256 2,418,087 5,303,474 5,138,852 11,081,391 12,665,740 639,860 5,110,251 5,171,036 308,785 776,422 2,834,472 30,725,744 904,864 1,956,101 2,942,909 4,304,758 252,126,854 1,268,134 288,135 5,058,620 1,169,903 221,165 4,949,844 145,869 34,177 1,359,147 412,376 563,913 730,926 4,155,252 6,067,632 2,207,436 652,462 208,908 6,260,998 865,883 773,956 985,311 1,940,990 1,999,248 4,465,065 4,425,345 253,952 1,984,460 2,027,884 120,352 327,891 1,280,829 10,189,454 418,440 769,296 1,098,861 1,721,211 93,090,156 28,598 24,358 33,806 32,797 33,353 30,493 20,154 41,756 30,537 30,003 28,308 29,919 31,283 31,137 37,264 38,575 27,166 35,318 30,847 27,398 32,677 30,656 31,145 34,629 30,742 26,661 28,078 29,890 28,071 29,862 32,580 33,217 33,513 31,550 35,889 30,748 39,875 11,852 7,582 12,872 12,186 12,287 11,405 7,677 17,089 12,702 11,145 11,057 12,602 11,510 11,052 14,619 16,312 11,606 14,133 13,119 10,184 13,315 11,220 12,117 13,953 10,741 10,581 10,904 11,722 10,941 12,611 14,722 11,016 15,498 12,408 13,401 12,294 14,722 89,652 3,234,142,486 1,249,963,035 36,074 13,942