Analysis Directory UMM :Data Elmu:jurnal:E:Economics of Education Review:Vol20.Issue2.2001:

111 R.C. Lowry Economics of Education Review 20 2001 105–119 ted to research or public service at campus i, unre- stricted revenues at campus i, other uses for unrestric- ted revenues at campus i, qualitative attributes at campus i affecting the supply of research or public service, demand for public service in state j. My data do not allow me to identify the specific nature of any restrictions on grants and contracts, so I use rev- enues from different public and private sources and endowment income per 100,000 voting-age residents. 99 percent of gross tuition and fee revenues and 92 percent of state government funding at campuses in my data set are not subject to restrictions. In contrast, 85 percent of federal government funding, 85 percent of private gifts, grants and contracts, 77 percent of local government funding, and 63 percent of endowment income carry restrictions. 9 Other uses for unrestricted revenues are measured by student enrollments, with no distinction between resident and nonresident undergraduates. Graduate and pro- fessional student instruction should be a complement to academic research, so I expect the coefficient in the research equation to be positive. Undergraduate instruc- tion should be a substitute for research, so I expect a negative coefficient. Expectations regarding the effects of enrollments on public service spending are uncertain. An important qualitative attribute that should affect spending on research and public service is land-grant status. Land-grant universities are eligible for certain federal programs involving agriculture and the mechan- ical arts, and have a long tradition of emphasizing public service to nonacademic constituencies National Associ- ation of State Universities and Land-Grant Colleges, 1995. I therefore include a dummy variable for land- grant status, and expect that both research and public service spending will be higher at land-grant campuses. The supply of public service to nonacademic constitu- encies may also depend on the political and economic context in each state. Since public service includes agri- cultural extension programs Broyles, 1995, one rel- evant measure is the importance of agriculture in the state economy. I therefore include the fraction of gross state product due to farming in the public service equ- ation only. Finally, 38 of the campuses in my data set do not 9 Other revenue sources that are not included in my model are sales and services of educational activities, auxiliary enterprises, hospitals, independent operations, and miscel- laneous sources. Revenues from sales and services “are inci- dental to the conduct of instruction, research or public service” Broyles, 1995, p. 30, and thus are endogenous. Auxiliary enterprises, hospitals, and independent operations are stand- alone activities that generate both their own revenues and expenditures. I tested for the effects of miscellaneous income, but the coefficient was insignificant in both spending equations. report any separately budgeted spending on research, and 37 do not report any separately budget spending on pub- lic service. While it may be that some campuses do not supply any research or public service, there are others where the reported amounts may be affected by account- ing practices. Getz and Siegfried 1991 note that insti- tutional accounts do not always match the categories used in the Integrated Postsecondary Education Data System, so that anomalies sometimes occur in the reported data. For example, no campus in the California State University system reported any separately budgeted spending on either research or public service in 1993– 94 or 1994–95. Although I lack detailed information on every such case, I include a dummy variable for the 23 campuses that report no separately budgeted spending on either activity. I report the results of alternative specifi- cations below. 3.4. A priori identification Based on the order condition, each of the equations in my model is over-identified. Exogenous variables excluded from the state government funding equation include land-grant status, academic reputation measures, revenues from federal and private sources and endow- ments, and state-level variables affecting net tuition and fee revenues or public service spending. Exogenous vari- ables excluded from the net tuition and fees equation include land-grant status, federal and private revenues and endowment income, and state-level variables affect- ing state government funding or public service spending. Exogenous variables excluded from the research and public service equations include medical school, aca- demic reputation, and all state-level variables except for the fraction of gross state product due to farming.

4. Analysis

My data set consists of all public, four-year insti- tutions in the 50 states for which I was able to obtain complete financial and enrollment data from the Inte- grated Postsecondary Education Data System, and that are classified as national or regional universities by the US News World Report 1994. 10 Table 1 provides 10 The most prominent public universities not in my data set are the University of Connecticut, the University of the District of Columbia, Rutgers University, and the statutory colleges at Cornell University. Faculty compensation data are missing for the University of Connecticut. Rutgers has three separate cam- puses in New Brunswick, Newark, and Camden, New Jersey, but financial data are available only in the aggregate. The statu- tory colleges at Cornell are omitted because of its unique insti- tutional arrangement, while the University of the District of Columbia is omitted due to the unique political status of the District. 112 R.C. Lowry Economics of Education Review 20 2001 105–119 Table 1 Summary statistics a,b Variable Nonzero cases Mean Standard deviation State government funding, 1994–95 428 2.01e6 3.33e6 Net tuition and fee revenues, 1994–95 428 1.04e6 1.98e6 Research spending, 1994–95 390 7.76e5 1.98e6 Public service spending, 1994–95 391 3.51e5 9.27e5 State tax revenues, 1994 428 1.91e8 3.68e7 State per capita income, 1994 428 20958 2753 Number of governing boards, 1994 428 5.49 4.36 State financial autonomy ranking, 1995 428 0.424 0.309 Private college enrollment, 1994 428 1538.6 967.8 Fraction voting-age population 65 and over, 1994 428 0.171 0.024 Fraction adults with a college degree, 1990 428 0.195 0.037 Fraction gross state product due to farming, 1994 428 0.015 0.016 Resident undergraduates, 1993–94 428 209.8 246.7 Nonresident undergraduates, 1993–94 428 48.8 120.1 Graduate and professional students, 1993–94 402 44.2 73.1 Land grant university 91 0.213 0.410 Integrated medical school 48 0.112 0.316 National university reputation, 1994 127 0.141 0.263 Regional university reputation, 1994 301 0.364 0.320 Mean faculty compensation, 1993–94 428 56910 9798 Local government revenues, 1993–94 250 20138 91883 Federal government revenues, 1994–95 428 7.31e5 1.72e6 Private gifts, grants and contracts, 1994–95 412 2.55e5 6.53e5 Endowment income, 1994–95 274 42181 2.11e5 a indicates variable is measured in units divided by 100,000 state voting-age population. b Means and standard deviations are for all 428 cases. summary statistics. Data are for 1994–95, except for local government revenues, faculty compensation, and enrollments, which are potentially affected by state government funding and tuition revenues. These vari- ables are measured using data for 1993–94. The fraction of adults with a college degree is measured for 1990, which is the most recent year for which reliable estimates are available. 11 11 Estimates of educational attainment are available for more recent years, but are based on small samples for individual states. I do not adjust local government revenues and average compensation for inflation because measures of relevant price increases in individual states or campuses are not available. All data for individual campuses are from the Integrated Postsec- ondary Data System National Center for Education Statistics, various years, except for academic reputation and percent non- resident freshman US News World Report, 1994, integrated medical school Research and Education Association, 1994, and land-grant status National Association of State Universities and Land-Grant Colleges, 1995. Data on governing boards are from the Education Commission of the States 1994, and fin- ancial autonomy is from Volkwein and Malik 1997. Min- orities as a fraction of state voting-age population is from US Bureau of the Census 1998. State government tax revenues, personal income, elderly residents, and adults with college For an “average” public university in my sample, state government funding is about US2.01 million per 100,000 voting-age resident, and net tuition and fee rev- enues are just about half that. The average public univer- sity campus spends US776,228 on research per 100,000 voting-age residents, and US350,994 on public service. Average full-time equivalent enrollments are about 210 resident undergraduate, 49 nonresident undergraduate, and 44 graduate and professional students per 100,000 voting-age residents. Table 2 presents the results of two-stage least squares regressions for each of my equations, with absolute t- ratios shown in parentheses. All dependent and inde- pendent variables are measured in natural logs, except for dummy variables and percentile rankings for aca- demic reputation or state financial autonomy. 12 This degrees are from the US Department of Commerce various years. 12 All estimations were performed using Stata version 5.0. Table 1 shows that there are a number of independent variables for which some campuses have zero values. Multiplying the ratio of each variable to state voting-age residents by 100,000 means that virtually all of the positive values exceed one, so that the natural log is positive. With a few exceptions, I recode 113 R.C. Lowry Economics of Education Review 20 2001 105–119 functional form assumes that the marginal effect of each independent variable is conditional on the values of all independent variables. Table 3 shows estimated marginal effects of different variables evaluated at the sample means. 4.1. State government funding Turning first to state-level variables, state government funding is significantly higher in states with more tax revenues. Given tax revenues, state government funding is lower in states with many elderly residents or large private higher education sectors, and both coefficients are at least 2.35 times their respective standard errors. The coefficient for the number of governing boards is negative and more than three times its standard error, consistent with my expectation that a large number of boards makes it more difficult for public universities to engage in effective lobbying. With respect to campus outputs, state government funding increases with enrollments by all three types of students, and all enrollment coefficients are more than three times their standard errors. The estimated elas- ticities are 0.475 for resident undergraduates, 0.090 for nonresident undergraduates, and 0.072 for professional and graduate students. However, a one percent increase in the number of resident undergraduate students typi- cally represents many more students than a one percent increase in the number of nonresident undergraduates, or graduate and professional students. Table 3 shows that estimated marginal effects at the sample mean are US4,553 for resident undergraduates, US3,703 for nonresident undergraduates, and only US3,281 for graduate and professional students. The order of these point estimates is consistent with my expectations, although the differences are less than their standard errors evaluated at the sample mean. The effects of research and public service are consist- ent with the hypothesis that quasi-public goods targeted toward specific state constituencies are likely to be over- funded, whereas broadly distributed public goods are likely to be underfunded Hoenack, 1983, p. 164. Both coefficients are positive and at least twice their standard cases with zero values as one, so that ln1 = 0. There is only one campus that has less than one dollar in endowment income per 100,000 voting-age residents, and I recode that observation as one. There are 23 campuses with less than one nonresident undergraduate per 100,000 voting-age residents, but only one with zero. I recode that observation as 0.1, which is less than the smallest positive value of 0.38. This approach sacrifices some consistency in order to minimize the number of observations that are recoded. There are also several campuses with less than one graduate or professional student per 100,000 voting-age resident, but these are accounted for by my intercept shift for campuses with no graduate or professional programs. errors, but estimated marginal effects at the sample mean are only US0.162 for research spending, compared to US0.469 for public service spending. The estimated dif- ference is thus US0.307, and its standard error is US0.193 t = 1.59. Additional perspective can be gained by comparing the marginal effects of research and public service to the marginal effects of enrollments. According to the point estimates, it would take about US9,708 worth of public service by an average public university to have the same impact at the margin as one additional resident undergraduate, compared to almost US28,105 worth of research. Public universities with integrated medical schools receive more state government funding than do other- wise comparable campuses, and state government fund- ing also increases with input costs. State government funding is significantly lower at public universities that also receive funding from local governments, and the tra- deoff is approximately one-for-one, based on the esti- mated marginal effect in Table 3. The coefficient on net tuition and fee revenues is positive, and less than its stan- dard error. 4.2. Net tuition and fee revenues The second column in Tables 2 and 3 shows the results for net tuition and fee revenues. All of the coef- ficients are statistically significant and have the expected signs, except for local government revenues and the frac- tion of adults in each state who are college graduates, which have no independent effect. The coefficient for state government funding is negative and more than 2.7 times its standard error. When combined with the results for the state government funding equation, this implies that differences in state government funding lead to par- tially offsetting differences in net tuition and fee rev- enues, but not the reverse. Net tuition and fee revenues are higher in states where public universities have more autonomy over financial and personnel matters, and the coefficient on percentile autonomy ranking is more than seven times its standard error. This is consistent with the hypothesis that state government officials and university administrators prefer different combinations of prices and outputs. Since my equation controls for state government funding and aca- demic reputation, the tradeoff for lower tuition rates in states where public universities have less autonomy is likely to involve reduced amenities such as student ser- vices, lower administrative expenditures, or less invest- ment in future capacity and reputation. Net tuition and fee revenues increase with enrollments by all categories of students, but estimated marginal effects evaluated at the sample means are US4,120 for resident undergraduates, US3,836 for nonresident undergraduates, and only US2,833 for graduate and professional students. When combined with my results 114 R.C. Lowry Economics of Education Review 20 2001 105–119 Table 2 Revenues and outputs at public university campuses a,b,c State government Net tuition and fees Spending on Spending on public funding research service State-level variables General tax revenues 0.402 4.47 – – – Per capita income – 1.132 5.98 – – Number of governing boards 20.097 5.45 – – – State financial autonomy ranking – 0.390 7.27 – – Fraction of voting-age population age 65 or 20.255 2.35 – – – more Private college enrollmentvoting-age 20.122 3.54 – – – population Fraction adults with a college degree – -0.106 0.91 – – Fraction of gross state product due to farming – – – 0.369 2.46 Campus outputs Resident undergraduate enrollment 0.475 5.58 0.835 14.5 – – Nonresident undergraduate enrollment 0.090 4.42 0.181 11.1 – – Total undergraduate enrollment – – 20.833 2.23 0.219 0.43 Graduate and professional enrollment 0.072 2.87 0.121 5.96 0.586 4.07 20.178 1.09 Dummy for graduate and professional 20.178 2.50 20.138 2.07 1.089 2.47 0.296 0.62 programs Research spending 0.062 3.13 – – – Public service spending 0.082 3.16 – – – Dummy for campuses reporting no research or 1.051 7.22 – 27.50 17.0 28.22 17.1 public spending Campus attributes Land-grant university – – 0.949 3.64 0.354 1.26 Integrated medical school 0.238 4.41 0.169 3.14 – – Academic reputation, national university – 0.519 5.01 – – Academic reputation, regional university – 0.243 3.35 – – Regional university dummy – 20.252 3.49 – – Campus input prices Mean faculty compensation 0.625 4.47 0.251 1.74 – – Campus revenues Net tuition and fee revenue 0.071 0.87 – 0.062 0.18 20.326 0.71 State government funds – 20.194 2.79 0.412 0.98 1.378 2.98 Local government funds 20.011 3.16 0.002 0.49 0.040 1.90 0.045 1.99 Federal government funds – – 0.706 6.68 0.166 1.40 Private gifts, grants and contracts – – 0.193 4.87 0.129 3.00 Endowment income – – 0.029 1.29 0.041 1.69 Constant 24.89 210.77 25.26 27.15 Cases 428 428 428 428 R-squared 0.942 0.948 0.812 0.732 Root mean squared error 0.281 0.268 1.784 1.921 a All equations are estimated with Stata version 5.0, using two-stage least squares. Absolute t-ratios are in parentheses. b All variables except dummy variables, academic reputation, and autonomy ranking are measured in natural logs. c indicates endogenous variable. for state government funding, the point estimates imply that graduate and professional instruction may be subsid- ized by revenues from other sources, or at a minimum contributes less at the margin to covering joint costs than does undergraduate instruction. It must be remembered, however, that estimated marginal revenues depend on the actual values of each independent variable. I summarize the results from some additional analysis below. Turning to students’ willingness to pay, net tuition and fee revenues are higher in states with high per capita income, and higher also at campuses with good academic reputations and integrated medical schools. The coef- ficient for the fraction of adults with a college degree is less than its standard error, but this is due to a high corre- lation between educational attainment and per capita income r = 0.76. If I drop per capita income from the 115 R.C. Lowry Economics of Education Review 20 2001 105–119 Table 3 Estimated marginal effects at sample means a,b,c State government Net tuition and fees Spending on Spending on public funding research service Resident undergraduates 4553 4120 – – Nonresident undergraduates 3703 3836 – – Total undergraduates – – 22500 298 Graduate and professional students 3281 2833 10284 21408 Research spending 0.162 – – – Public service spending 0.469 – – – Net tuition and fees 0.140 – 0.046 20.110 State government funds – 20.100 0.159 0.240 Local government funds 21.104 0.081 1.547 0.792 Federal government funds – – 0.750 0.080 Private gifts, grants and contracts – – 0.590 0.177 Endowment income – – 0.530 0.340 a Estimates are based on sample means shown in Table 1. b indicates coefficient is at least than 1.96 times its standard error p,0.05, two-tailed test. c indicates coefficient is at least 2.56 times its standard error p,0.01, two-tailed test. model, the coefficient for adults with college degrees jumps from 0.106 to 0.560, and the t-ratio jumps from 0.9 to 6.1. 4.3. Supply of research and public service The final two columns in Tables 2 and 3 show the results for separately budgeted spending on research and public service, respectively. Holding revenues constant, research and graduate and professional instruction are complements, whereas research and undergraduate instruction are substitutes. Research spending is also higher at public universities with land-grant status. The estimated marginal effect of local government revenues exceeds one, but federal government funding and private gifts, grants and contracts are the only revenue sources whose coefficients exceed twice their standard errors. Although the coefficients on state government funding and endowment income are also positive, neither of them approach statistical significance at conventional levels. The determinants of public service spending are some- what different. Holding revenues constant, public service spending is not significantly affected by enrollments. Holding enrollments constant, public service spending is not affected by net tuition and fee revenues. The coef- ficient on land-grant status is positive, but only 1.26 times its standard error. The coefficients for local, state and federal governments, private gifts, grants and con- tracts, and endowment income all are at least 1.4 times their standard errors, and there clearly is a reciprocal causation between state government funding and spend- ing on public service to nonacademic constituencies. Spending on public service is also significantly higher in states where farming is a large part of the state economy. 4.4. Additional results As noted above, I include intercept shifts to dis- tinguish the 23 campuses that reported no spending on either research or public service, and the 26 campuses that do not have any graduate or professional students. Interestingly, there is no overlap between these two cat- egories. The positive, significant coefficient in the state government funding equation for campuses with no reported spending on research or public service suggests that these campuses may in fact be supplying at least some of these activities. The intercept shift for campuses that have positive graduate and professional enrollments is negative and significant in the state government fund- ing and tuition and fee equations, and positive and sig- nificant in the research spending equation. The result for research spending is intuitive, as it implies that the mere existence of graduate and professional programs results in greater spending on research. The two revenue equa- tions, however, imply that campuses with small graduate and professional programs actually generate fewer rev- enues than those with no programs. 13 This suggests that there are discontinuities not fully captured by my log– log specification. I re-estimated my equations using only the 357 cases 13 The cutoff points at which the net effect of graduate and professional enrollment becomes positive are 11.93 students per 100,000 voting-age residents for state government funding, and 3.14 for net tuition and fee revenues. These figures would fall in the fortieth and ninth percentiles, respectively, among cam- puses in my data set that have graduate or professional pro- grams. 116 R.C. Lowry Economics of Education Review 20 2001 105–119 in my sample that have positive values for graduate and professional enrollment, research, and public service. The results are reassuring. All of the variables in the state government funding have the expected signs and are at least 2.1 times their standard errors, except for net tuition and fee revenue, which has no effect, and research spending, which has a positive effect but a t-ratio of just 1.84. All of the variables in the tuition and fee equation including the fraction of adults with college degrees have the expected signs and are at least 1.9 times their standard errors except local government revenue, which has no effect. The estimated marginal effects on state government funding evaluated at the subsample mean are US5,065 for resident undergraduates, US3,877 for nonresident undergraduates, US3,636 for graduate and professional students. The estimated marginal effects on net tuition and fee revenues evaluated at the sample means are US3,911 for resident undergraduates, US3702 for nonresident undergraduates, and US2,901 for graduate and professional students. The estimated marginal effect of research spending on state government funding is just 0.134, compared to 0.860 for public ser- vice spending. Results for research and public service spending are also close to those shown in Table 2, although the effect of land-grant status in the public ser- vice equation is now significant. I also split my sample and estimated separate models for “national” and “regional” universities, using the US News World Report’s classifications. All national uni- versities have positive values for graduate and pro- fessional enrollment, research and public service. For regional universities, the coefficients on the intercept shifts for graduate and professional enrollment in my revenue equations are negative, but not significant. The estimated marginal revenues from state government and net tuition and fees for graduate and professional enrollment evaluated at the subsample means exceed those for undergraduates at national universities, but are below those for undergraduates at regional universities. The coefficient on research spending in the state govern- ment funding equation is less than its standard error for national universities, while the coefficient on net tuition and fee revenues is negative and 1.97 times its standard error. For regional universities, the coefficients on both research spending and net tuition and fee revenues are positive and twice their standard errors. In addition, the negative coefficient for private higher education enrollment is less than its standard error for national campuses but nearly four times its standard error for regional campuses, suggesting that funding for regional campuses is more susceptible to political interests and history. Thus, there may well be differences between “full ser- vice” campuses and those that supply only limited amounts of graduate and professional instruction, research, and public service. It appears that internal sub- sidization of graduate and professional programs is most likely at campuses that are primarily engaged in under- graduate instruction, while any tradeoff between state government funding and tuition and fee revenues is con- fined to the largest, “flagship” campuses. The difference between the marginal effects of public service and research on state government funding is greatest at full service campuses, but this does not necessarily mean that research is being subsidized. In fact, the research spend- ing equations for the full sample and every subsample indicate that research is funded by federal and private grants and contracts rather than state government funds or tuition and fee revenues. In order to further investigate the determinants of tui- tion rates, I replaced the equation for net tuition and fee revenues with two equations for the list prices for resi- dent and nonresident freshman. Resident tuition rates and fees increase with academic reputation, per capita income, and financial autonomy, and they decrease with state government funding. Nonresident tuition rates and fees increase with mean input costs, academic reputation, and the fraction adults with a college degree. However, the coefficients for state government funding and campus financial autonomy are each less than their standard errors. 14 This suggests that nonresident tuition rates are driven by cost and demand factors only, whereas resident tuition rates also depend on the identity of relevant decision makers and the level of state government fund- ing. Finally, I experimented with several variations on my basic specification. If I add intercept shifts for campuses that have positive revenues from private gifts, grants and contracts, local governments, or endowment funds, none of their coefficients are significant and my main results are not affected. I also tested further for the effects of qualitative campus attributes, as well as a variety of state-level variables that other researchers have found to have significant effects on state government funding. None of these alternatives improved the model in Table 2. 15 14 The equations are the same as the equation for net tuition and fee revenues in Table 2, except that I omit resident under- graduates and divide nonresident undergraduates, graduate and professional enrollment, and state and local government funding by full-time equivalent enrollment rather than voting-age popu- lation. The effects of per capita income and education attain- ment in the resident tuition rate equation are again affected by multicollinearity. 15 Neither land-grant status nor academic reputation has a sig- nificant effect on state government funding, independent of campus outputs. The presence of an integrated medical school does not affect either research or public service, and the pres- ence of a law school on campus does not have a statistically significant effect on any of my dependent variables, once I con- trol for graduate and professional enrollment. State-level vari- ables tested include the rate of net in-migration, the number of 117 R.C. Lowry Economics of Education Review 20 2001 105–119

5. Discussion