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[1] Legislative Budget Board, Fiscal Size Up: 2000-01 Biennium, Austin, January 2000, pp. 1-8.

[2] Legislative Budget Board, Fiscal Size Up: 1986-87 Biennium and Fiscal Size Up: 2000-01 Biennium. To adjust for inflation, appropriations were divided by the US gross domestic product deflator for state and local government expenditures.

[3] Texas Higher Education Coordinating Board, Statewide and National Perspectives on Higher Education in Texas (

[4] Bureau of Business Research, Graduate School of Business, University of Texas at Austin, Economic Contribution of the University of Texas System: A Study in Three Parts, Summer 1994.

[5] Resources Economics, Inc., Economic Return on Investment in College Degrees at the University of Houston, Austin, December 1998.

[6] Texas Comptroller of Public Accounts, Texas Input-Output Study, 1986 Update, Austin, December 1989.

[7] Bureau of Business Research, Economic Contribution of UT System, pp. 2-4 to 2-5.

[8] Denison, Edward P., Sources of Economic Growth in the United States (New York: Committee for Economic Development, 1962) and Gary S. Becker, Human Capital: A Theoretical and Empirical Analysis with a Special Reference to Higher Education (Chicago: University of Chicago Press, 1993), p. 210.

[9] Bureau of Business Research, Economic Contribution of UT System, pp. 1-25 to 1-27. This report asserts that the economic impact of the training/educational function of higher education is about the same magnitude as that of the knowledge/research function. While this may be true when measuring higher education’s impact for the nation as a whole, equating these national results to the state level is difficult. Regional measures of the level of investment in higher education often contain components of both the knowledge and the training functions so that whatever impacts are measured probably contain both aspects. Moreover, in an open regional economy there are many sources available to provide the societal knowledge function.

[10] Resource Economics uses the “net” number of graduates after eliminating the doubled counting of advanced degrees. According to the study, approximately 8,400 students graduate annually from the UH system.

[11] Another major focus of the Texas Guaranteed Student Loan Association study is on the economic return to Texas from equalizing college attendance rates between minorities and whites. Texas Perspectives calculates that if African-American and Hispanic students attended and graduated college at the same rate as whites, the resulting increase in worker productivity would have added 4 percent to the state economy in 1996. See Texas Guaranteed Student Loan Association, Economic Returns from Higher Education in Texas, Austin, 1997, pp. 12-13.

[12] See Chapter III of this report for a more complete discussion of these issues.

[13] See William Miernyk, The Elements of Input-Output Analysis (New York, Random House, 1965).

[14] Type II multipliers include both the industry output and household expenditures generated by increased demand for regional goods and services from outside the area. Type I multipliers, on the other hand, include only the impact of increased industry output that supply the exporting sector.

[15] To allow for the statutory waiver of out-of-state in lieu of in-state tuition, tuition and fee revenue for five percent of public university students was reduced by the average 66 percent differential between out-of-state and in-state tuition and fees.

[16] Telephone conversation with Dr. Linda Domelsmith, Division of Finance, Campus Planning, and Research, Texas Higher Education Coordinating Board, July 21, 2000.

[17] The Comptroller’s research and development input-output multiplier was originally calculated for the private sector, but it can be applied to public university research as well.

[18] Telephone conversation with Mr. Tom Scott, Interim Vice-Chancellor for Governmental Affairs, University of Texas System, September 11, 2000.

[19] “Economic Impact on the State of Texas,” University of Texas MD Anderson Cancer Center, Houston, Texas, 1994.

[20] Telephone conversation with Mr. Mark Moreno, Director, State Relations, Office of the President-Governmental Affairs, MD Anderson Cancer Center, September 13, 2000.

[21] H.B. 1, 76th Legislature, Regular Session, 1999, Article III, Section 35, No. 3, p. III-240. Specific indirect recovery appropriations are shown in Goal B. for each health-related institution.

[22] See Chapter 145.001 of Education, Vernon’s Texas Codes Annoted.

[23] For each public university, Goal A of H.B. 1 shows the one-half of total indirect recoveries that are reappropriated to each institution.

[24] Charles A. Goodman, T. Williams, David M. Adamson, and Kathy Rosenblatt, Paying for University Research Facilities and Administration, Santa Monica: Rand Corporation, MR-1135-1-OSTP, 2000 (

[25] National Science Foundation, Federal Science and Engineering Support to Universities, Colleges, and Nonprofit Organizations, Fiscal Year 1997, Washington, 1999, Table B-9 (www.nsf,gov/sbe.srs/nsf99331/tables/fssb9.xls).

[26] Jacob Mincer, “Investment in Human Capital and Personal Income Distribution,” Journal of Political Economy 66 (1958), pp. 281-301 and Theodore Schultz, “Capital Formation by Education,” Journal of Political Economy 86 (1960), pp. 571-583.

[27] Larry L. Leslie and Paul Brinkman, The Economic Value of Higher Education (Phoenix: American Council of Education and the Oryx Press, 1993), pp. 43-44.

[28] Over this period, the differential in the median earnings of Texas college graduates or higher versus high school graduates relative to the US has fallen somewhat, while, for average earnings, the Texas-US differential has, in fact, risen. These apparently disparate results indicate that for the typical worker, the earnings differential between high school and college and higher graduates in Texas is, in fact, about the same as in the US as a whole, but for some very high income workers, Texas college-plus graduates earn much more. These results are not atypical of fast-growing economies, such as Texas.

[29] These data were supplied by Mr. Tom Scott, Interim Vice-Chancellor for Governmental Relations, University of Texas System.

[30] Texas Higher Education Coordinating Board, Cost of Education in Texas, 1999-2000 (

[31] Leslie and Brinkman, The Economic Value of Higher Education, pp. 45-48, 71-75;

[32] Leslie and Brinkman, The Economic Value of Higher Education, pp. 52-53.

[33] Using the 45-year working-life period of analysis utilized in this study, the Standard and Poor’s composite stock index increased approximately 8.5 percent per year from 1954 through 1999. According to Global Financial Data (, this gain would had risen to 12.5 percent annually with reinvested dividends. Thus, the average stock market return over the past 45 years has been slightly over 10 percent per year.

[34] US employment to population ratio’s for 16 to 24 year old former college students and college graduates were obtained from the US Bureau of Labor Statistics, “College Enrollment and Work Activity of 1999 High School Graduates,” New Release, Washington, May17, 2000.

[35] According to data supplied by WEFA Associates, over the past 45 years the 30-year treasury rate has generally followed inflation, ranging from a low of 2.6 percent in 1954 to a high of 13.4 percent in 1981. After excluding inflation, the real rate of return from 1954 through 1999 has averaged 2.8 percent. Adding today’s predictions of roughly 3 percent inflation annually over the next several years brings us back to the 6 percent rate used in these calculations.

[36] See Alan B. Krueger, “Measuring Labor’s Share,” AEA Papers and Proceedings, May 1999, pp. 45-51.

[37] According to the BEA (, compensation of employees accounted for $320 billion of the $602 billion in Texas gross state product in 1997. During the same year, property-type income ($231 billion) and indirect business taxes ($50 billion) accounted for the remaining state economic output.

[38] The seminal reference to the neoclassical model of economic growth is Robert M. Solow, “A Contribution to the Theory of Economic Growth,” Quarterly Journal of Economics 70 (Feb. 1956) pp. 65-94.

[39] Gary S. Becker, Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, 3rd ed. Chicago: University of Chicago Press, 1993.

[40] Some of these studies, for example, have used survey-based ratings based on questions such as “on a scale of 1 to 4, how has your productivity changed over the past year.” See John Barron, Dan Black, Mark Loewenstein, “Employer Size: The implications for Seach, Training, Capital Investment, Starting Wages, and Wage Growth,” Journal of Labor Economics, January 1987, pp. 76-89 and John Bishop, “The Impact of Previous Training on Productivity and Wages,” in Lisa M. Lynch, ed., Training and the Private Sector: International Comparisons. Chicago: University of Chicago Press, 1994), pp. 61–99.

[41] This study used firm-level Compustat data on productivity and financial performance. See Ann Bartel, Formal Employee Training Programs and their Impact on Labor Productivity: Evidence from a Human Resource Survey, Working Paper No. 3026, National Bureau of Economic Research, (Cambridge, Massachusetts), 1989.

[42] Sandra E. Black and Lisa M. Lynch, “Human-Capital Investments and Productivity,” AEA Papers and Proceedings, Vol. 86, No. 2, May 1996, pp. 263-267.

[43] For the both manufacturing and non-manufacturing sectors, these higher estimates were the result of unconstrained Cobb-Douglas regression of (the log of) firm sales on (the logs of) capital stock, labor-hours, cost of materials, and average educational level of the workers. The lower estimates were based on the imposition of constant returns of scale and equal coefficients on the labor quantity and quality variables in the regressions. Both of these restrictions were supported by the data.

[44] Lisa M.Lynch and Sandra E. Black, Beyond the Incidence of Training: Evidence from a National Employers Survey, Working Paper No. 5231, National Bureau of Economic Research (Cambridge, Massachusetts), 1995, Appendix D.

[45] Evidence that there is a declining marginal effect of education is strong. On page 52, Larry Leslie and Paul Brinkman, The Economic Value of Higher Education, note that traditionally calculated private rates of return for bachelor’s degrees are estimated at 11.8 - 13.4 percent; eight percent for for one year of graduate work; 7.2 percent for a master’s degree; and 6.6 percent for a Ph.D.

[46] The employment-population percentages used by age group were calculated from the Texas sample of the Current Population Survey for March 1999. The somewhat high figure for the over-65 population reflects a greater predominance of less-than full time workers in this age group when compared to the population 45 to 64.

[47] This estimated all-funds, state and local appropriation is based on 1998-99 state higher education funding (including benefits) of $12.255 billion less Texas A&M University noneducational services ($521 million), the Higher Education Coordinating Board ($484 million), and patient care at state health-related institutions ($1,560 million), plus the $979 million community college property tax levy during the two years. The resulting net state and local direct higher education appropriation of $10,670 million then was divided by a combined full-time enrollment of 1.216 million during both years to obtain a per-capita appropriation of $8,771. See Legislative Budget Board, Fiscal Size Up: 2000-01 Biennium, Austin, January 2000, pp. 1, 123 and 278-280. The community college property tax levy was obtained from the Comptroller’s Property Tax Division.

[48] In some cases it is impossible to detangle the effects the university system has on human capital from those on knowledge capital. For example, a company may relocate to tap the expertise of some academic department such as engineering or computer science. However, it is hard to envision a case in which such a company would benefit solely from the expertise of the faculty and not also from the availability of students trained by that faculty. So measuring the effects of the increased human capital simultaneously captures some of the attractive benefits of knowledge capital. For a discussion of some of the literature on the higher education’s role in the knowledge function, patent generation, technology transfer and spin-off commercialization, see Walter W. McMahon, “The Contribution of Higher Education to R&D and Productivity Growth,” in William E. Becker and Darrell R. Lewis, eds. Higher Education and Economic Growth, (Boston: Kluwer Academic Publishers, 1993), pp. 105–127.