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1 THE DETERMINANTS OF AVERAGE FACULTY SALARY By HANNY ALICE LANE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS UNIVERSIT Y OF FLORIDA 2012
2 2012 Hanny Alice Lane
3 To Jamie Lin You are forever first my best friend a wonderful boyfriend the be st encouragement, and have always believed in me. Without you I would not have bee n able to complete any of this.
4 ACKNOWLEDGMENTS I would like to thank the D epartment of Economics at the University of Florida, especially Dr. Lawrence Kenny for being an incredible advisor and for Dr. Slutsky for being a great support. I would also l ike to thank my parents and my brother for also helping and supporting me as I completed this challenging but rewarding journey. I could not have done it without any of you.
5 TABLE OF CONTENTS Page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 A BSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 11 2 SAMPLE AND METHODS ................................ ................................ ...................... 17 Sample ................................ ................................ ................................ .................... 17 Dependent Variable ................................ ................................ ................................ 18 Independent Variables ................................ ................................ ............................ 19 School Quality Variables ................................ ................................ .................. 19 Teaching Characteristic Variables ................................ ................................ .... 22 Funding Variables ................................ ................................ ............................ 23 Demographic Variables ................................ ................................ .................... 25 3 METHODOLOGY ................................ ................................ ................................ ... 32 4 RESULTS ................................ ................................ ................................ ............... 37 School Quality Variables ................................ ................................ ......................... 37 Peer Assessment ................................ ................................ ............................. 37 ................................ ................................ ............................ 38 Teaching Characteristics ................................ ................................ ........................ 41 Less than 20 Students ................................ ................................ ...................... 41 More than 50 Students ................................ ................................ ..................... 42 Percent Full Time Faculty ................................ ................................ ................. 43 Funding Variables ................................ ................................ ................................ ... 44 Federal Appropriations ................................ ................................ ..................... 44 State Appropriations ................................ ................................ ......................... 44 Tuition and Fees ................................ ................................ ............................... 45 Demographic Variables ................................ ................................ ........................... 46 Women ................................ ................................ ................................ ............. 46 Asian, Black, and Hispanic Faculty ................................ ................................ .. 47 5 CONCLUSION ................................ ................................ ................................ ........ 58 LIST OF REFERENCES ................................ ................................ ............................... 60
6 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 62
7 LIST OF TABLES Table page 1 1 Top public and private universities in 1999. ................................ ........................ 15 1 2 Top public and private universities in 2009 ................................ ......................... 16 2 1 Summary of 1999 nominal average faculty salary ................................ .............. 27 2 2 Summary of 2009 nominal average faculty salary ................................ .............. 27 2 3 Cha 1999 and 2009 ................................ ................................ ................................ .... 28 2 4 Nominal mean salary of women faculty compared to men faculty, 1999 ............ 30 2 5 Nominal mean salary of women faculty compared to men faculty, 2009 ............ 30 3 1 Summary statistics, 1999 ................................ ................................ ................... 34 3 2 Summary statistics, 1999 ................................ ................................ ................... 35 3 3 Difference between 2009 and 1999 summary statistics ................................ ..... 36 4 1 Determinants of n ominal average faculty salary in 1999 ................................ .... 49 4 2 Determinants of nominal average faculty salary in 2009 ................................ .... 50 4 3 Difference in determi nants of real average faculty salary, 1999 2009 ................ 51 4 4 Impact of determinants on nominal average faculty salary in 1999 .................... 52 4 5 I mpact of determinants on nominal average faculty salary in 2009 .................... 53 4 6 Impact of determinants on the difference in real average faculty salary, 1999 2009 ................................ ................................ ................................ ................... 54 4 7 ...... 55
8 LIST OF FIGURES Figure page 2 1 Matrix of the average increase in faculty salaries for universities with Most Competitive and Highly Competitive status between 1999 and 2009 ................. 31 4 1 Average faculty salary against peer assessment scores, 1999 .......................... 56 4 2 Average faculty salary against peer assessment scores, 2009 .......................... 56 4 3 Average faculty salary against tuition and fees, 1999 ................................ ......... 57 4 4 Average faculty salary against tuition and fees, 2009 ................................ ......... 57
9 Abstract of Thesis P resented to the G raduate S chool of the U niversity of F lorida in Partial F ulfillment of the R equirements for the Degree of M aster of A rts THE DETERMINA NTS OF AVERAGE FACULTY SALARY By Hanny Alice Lane December 2012 Chair: Lawrence Kenny Major: Economics Most parents and students would consider the best university to be the most recognized a nd most prestigious and accordingly, the most expensive institution. However, universities realize they must focus on building a successful, research in tensive faculty in order to establish qualifie d departments In order to determine whether faculty sal ary can be reflective of more research intensive and better universities, faculty salary will be regressed on measures of school competitiveness, teaching characteristics, government funding, and demo graphic controls over different U.S. universities in two different year cohorts. The school quality variables, in particular Barron's Selector dummy variables, were shown to be influential in average faculty salary offered by universities, proving to have the largest impact when compared to other variables tested. Professors are compensated to teach larger classes and they are willing to receive lower salaries in order to teach smaller classes. Further, the percentage of full time faculty has a significant effect on salaries offered over time, indicating that universities offer higher full time salaries in order to establish strong research programs. There is evidence that state funding allocated to a university and a university's tuition level impact the le vel of
10 salaries offered by universities, and more money in either category of funding allows universities to offer higher salaries for more qualified professors However, to better our understanding of the effects of university quality, teaching characteri stics, funding, and demographic characteristics on average faculty salary, future research must done with other data sets beyond the scope of this paper
11 CHAPTER 1 IN TRODUCTION What situations qualify a university to be the best ? P arents and students c ou ld consider the best to be the most recognized and most prestigious universities, and accordingly, the most expensive institutions. However, universities realize they must focus on building a successful, research intensive faculty in order to establish qua lified departments. As a result, top universities offer the highest salaries to prominent professors in hopes of employing the most qualified research personnel On the other hand, public universities, as compared to private universities, may offer lower s alaries because of the fact that certain state legislatures may not see the benefit to research and thus cut funding to those universities. For instance, t he top 10 public and private universities in 1999 had average faculty salaries of $124,435.18 and $14 2,889.11, respectively 1 Also, the top 10 public and private universities in 2009 had faculty salaries of $133,716.30 and $166,439.20, respectively 2 Regardless the quality of the faculty may indicate the quality of education in that the better research p rograms will consist of the best faculty Accordingly, parents believe that their children benefit from the skilled professors at these universi ties through the superior education they offer Hence, pa rents are willing to pay for higher tuition that is ass ociated with these institutions in order for their children to receive the most elite education. Higher university salaries and excellent education are t hen correlated. Beca use faculty salaries are erminant of u niversity productivity, attorneys, journalists, 1 See Table 1 1. Data is retrieved from 2000 edition of U.S. News & World Report. 2 See Table 1 2. Data is retrieved from 2010 edition of U.S. News & World Report
12 and un iversity administrators have been focused on policies modify ing the framework and distribution of salaries in a cademia (Hearn 1999). In this paper, I cho o se to examine the determinants of f aculty salary as a way of measuring the quality of education a student receives at a university in order to gain further knowledge about this reward system. Previous research has focused on determining the difference in faculty salary as a result of racial and gender discrimination W hen comparing men and women faculty members of the same abilities, w omen tended to be underpaid, with this result seen greatest in research universitie s (Darland et al 1974; Hoffman 1976; Hearn 1999). A motivation behind the d ifference may be that women spend more time with family and raising their family as compared to male professors, so their lower publication rate should lea d to their lower salaries. Other research demonstrated that gender disparity in faculty sala ry relies heavily on the years since faculty attained their highest degree, whether faculty obtained a professional degree, what department they belong to, and the h ours dedicated to teaching versu s administrating (Bellas 1993). However, whether race had a prominen t effect on salary discrimination continues to vary among studies (Darland et al 1 974; Koch and Chizmar 1973 ; Bellas 1993; Webster 1995). As a result, controls for gender and race are included in the model in o rder to improve on these findings and further see how the se factors relate to average faculty salaries. Alternatively, research has focused on looking at specific university requirements to explain the difference in faculty salary. Most of the studies agree that publication rate, administrative exper ience, and rank of the professor affect the salary level (Koch and Chizmar 1973; Siegfried and White 1979 ; Schwab and Dyer 1979). Even though
13 an effective researcher might not always be an effective tea cher, other papers showed that teaching competence, the quality of the department, and the longevity within the institution strongly determines salary differences (Koch and Chizmar 1973; Schwab and Dyer 1979; Katz 1973; Webster 1995). A study conducted by Kenny and Studley (1995) aimed at identifying whether academic salaries captured current productivity and whether they changed quality and the experience of the faculty member affected their salary positively, and therefore professor productivity influences salary offers Because of these previous findings, the more significant question becomes whether the quality of a universit y can be used to explain the dispari ties in faculty salary The more notable and competitive schools may acquire the funding to hire better faculty for stronger research departments offer more courses, and provide better facilities Therefore, studying the det erminants of faculty salary may get closer to answering these questions. This paper differs from previous work by choosing to compare hundreds of universities across the United State s rather than focusing on a single or a few universities or departments. Moreover, most of the previous r esearch has been as late as the mid 1990s to the early 1970 s. T his p aper concentrates on more recent cohorts and focuses on the change in determinants over a 10 year span. Finally, the study attempts to include state funding and tuition as further determin ants of faculty salary because the less state funding offered to the universities limits the salaries offered to hire faculty, requiring higher tuition to maintain the faculty. Previous studies on tuition focused on identifying the determinants of tuition and how
14 tuition and funding affect enrollment, but not on how the se factors affect salary directly (See McPherson el al 1989; Heller 1998; Hauptman and Merisotis; Freem an and Mumper 2005; Ehrenber and Rizzo 2003). This paper studies the aspect s of faculty salary by analyzing data from three sources: the U.S. News & World Report 2000 and 2010 edition o f Colleges t he 2000 an d the 2010 edition of B and the Integrated Posts econdary Education Data System f i les (IPEDS) from the National Center for Education Statistics. In order to determine whether faculty sal ary can be reflective of research intensive and distinguished universities, faculty salary will be regressed on measures of school competitiveness, teac hing characteristics, government funding, and demographic controls over many U.S. universities in two different year cohorts. In other words, the analysis will potentially determine whether higher salar ies offer ed reflect more qualified professors being hi red to improve research department
15 Table 1 1 Top public and private u niversities in 1999. Name Real Salary 1999 T op 10 Public Universities University of California at Berkley $139503.1 0 Univers ity of Virginia $122599 .00 University of California at Los Angeles $135777.7 0 University of Michigan Ann Arbor $129913.4 0 University of North Carolina Chapel Hill $120802.6 0 College of William and Mary $110914.1 0 University of California at San Diego $127268.3 0 University of Illinois at Urbana Champaign $117923.2 0 University of Wisconsin at Madison $108807.3 0 Georgia Institute of Technology $130843.1 0 Average Salary $124435.18 T op 10 Private Universities California Institute of Technology $152 529.9 0 Harvard University $167412.3 0 Mass. Institute of Technology $143846.7 0 Princeton University $154524.6 0 Yale University $153287.1 0 Stanford University $156006.8 0 Duke University $139074.3 0 Johns Hopkins University $115864.1 0 University of Pen nsylvania $147874.7 0 Columbia University $143023.8 0 Average Salary $142889.11 Note: Real Salary 1999 is in 2009 dollars. The top 10 universities were rated as such by the U S News & World Report
16 T able 1 2. Top public and private u niv ersities in 2009 Name Real Salary 2009 T op 10 Public Universities University of California at Berkley $144569 .00 University of California at Los Angeles $147416 .00 University of Virginia $135702 .00 University of Michigan Ann Arbor $143567 .00 Universi ty of North Carolina Chapel Hill $143048 .00 College of William and Mary $113631 .00 Georgia Institute of Technology $140556 .00 University of California at San Diego $134043 .00 University of Illinois at Urbana Champaign $126656 .00 University of Wisconsi n at Madison $107975 .00 Average Salary $133716.30 T op 10 Private Universities Harvard University $192859 .00 Princeton University $181013 .00 Yale University $174322 .00 California Institute of Technology $171649 .00 Mass. Institute of Technology $15962 0 .00 Stanford University $180225 .00 University of Pennsylvania $169736 .00 Columbia University $167680 .00 University of Chicago $184072 .00 Duke University $160990 .00 Average Salary $166439.20 Note: Real Salary 2009 is in 2009 dollars. The top 10 univ ersities were rated as such by the US News & World Report
17 CHAPTER 2 SAMPLE AND METHODS Sample The sample used in this study comes from the U.S. News & World Report for the 2000 and 2010 editions, which covers the 1998 1999 and 2008 2009 school years respectively (U.S. News 1999 2009). U S News & World Report collects quantitative data from different universities all over the country through surveys. They then rank the colleges in three steps: by categorizing the universities b y their mission and region ; by gather ing data on each college based on 16 indi cators of academic excellence to create a composite weighted score ; and finally by ranking the colleges in each category against their peers based on their composite weighted sc ore. In order to have a wide range of colleges, the sample was drawn from the U.S. News & World Report ranked National Universities and Regional Universities. National Universities consist of universities that offer a full range of undergraduate majors u p to a full range of masters and PhD programs, while the Regional Universities include a wide range of undergraduate and master programs, but hardly offer any PhD programs In the 2000 edition of U.S. News & World Report 228 National Universities and 504 R egional universities were recorded, while the 2010 edition recorded 262 National Universities and 572 Regional U niversities. From these, schools were chosen only if they were available in both years for each category, and thus the sample included a total of 671 universities i n 1999 and 2009, with at least one observation from all 50 states. H owever, due to the fact that some universities did not have data for every variab le analyzed in this study as others, the total number of observations drop s in their r espective regressions even further. The exact number of observations is listed at the
18 bottom of each regression in Tables 4 1, 4 2 and 4 3 but they range from 540 to 543, 615 to 617, and 524 to 526 universities, respectively Dependent Variable Average Fa culty S alary : The average faculty salary is obtained from the System (IPEDS) for the years of 1999 and 2009 survey data. The average faculty salary data utilized consists of full professor status faculty with a 9 month contract. Further, full professor salary is selected because it bet goal for a superior research department because full professors conduct the majority of the research at universities The professors that answered the faculty salary survey provided by IPEDS included instructional/research staff wh ose major assignments were both instruction and time dedicated toward research (U.S. Department 1999 2009). In order to measure the changes i n faculty salary over the 1 0 year span, a salary difference variable is created by taking the difference between the average faculty salaries of the two years 1 In order to know the distribution of salaries across various universitie s in the United States, Table 2 1 and Table 2 2 list the percentiles of the smallest and largest nominal values of average faculty salary. In 1999, the bottom one percent of the univers ities has average f aculty salaries as high as $38,877 with the smallest faculty salary record ed in the data set being $35,505 2 The 50 th percentile has an average faculty salary of $66,25 9.50, and the top one percent have an average faculty salary of 1 In order to create the Salary Difference variable, I first put Average Faculty Salary in 1999 in 2009 dollars. Therefore, Real Average Faculty Salary 1999= Average F aculty Salary 1999 *(214.537/166.600) Thus Salary Difference = Average Faculty Salary 09 Real Average Faculty Salary 99 2 Lincoln Memorial University
19 $114,833, with the largest salary reported being $130,005 3 The mean salary fo r the 66 8 universiti es is $68,444.48 4 In 2009, the salaries were reported for 6 69 available universities 5 The bottom one percent of the universities has an average faculty salary of up to $ 50,384 with the lowest reported salary being $ 30,000 6 The 50 th percentile o f the un iversities have average faculty salaries at $90, 984 and the top one percent of the universities have average faculty salaries up to $171,649, with the largest salary reported being $192,859 7 The mean university av erage faculty salary is $94,601.45 Indep endent Variables School Quality Variables Universities that offer higher salaries to professors may indicate that these universities hire more qualified professionals than others in order to support a strong research depa rtment, aiding in the quality of th e university. Peer Assessment values, which are obtained from the U.S. News & World Report in the 2000, an d the 2010 edition (U.S News 1999 2009 ), a 2000 2010 ) are used in order to try and capture the relationship between the selectivity in admission for a university and the faculty salary offered Peer Assessment: This variable was developed by the U S News & World Report to capture the competitiveness of the various universities surveyed. It was 3 Harvard University 4 Lincoln University and Fresno Pacific University had missing observations for Av erage Faculty Salary. Also, Maharishi University of Management salary observation was dropped because it had an incredibly low salary of $13,502. Thus there were 668 universities with reported salaries. 5 Fresno Pacific University had a missing observation for Average Faculty Salary. Further Maharishi University of Management salary observation was dropped because it had an incredibly low salary of $14,905. 6 Lincoln University 7 Harvard University
20 derived by surveying the pre sidents, provost, and deans of admission at the institutions about other universities within the same category (U S News 1999 2009). This group then rated peer schools academic programs on a five point scale, 1 being marginal in reputation and 5 being di stinguished in reputation. The study uses the average of all the scores of those who rate the particular university on a five point scale as the reported score 8 Because the peer assessment score can categorize undergraduate excellence in a variety of inta ngibles, such as faculty dedication for teaching and research, the higher the peer assessment score, the higher the average teache r salary will be Thus a top institution offer s higher salar ies for m ore qualified faculty and effective research programs. Ba : academic reputation is the college admission selector from American Colleges is an indicator that attempts to describe, in general terms, the situations a prospective student will meet when app lying for admissions ( 1999 2009). The criteria used to develop this indicator were as range o f the SAT an d ACT, if they were in the top of their high school graduating class class rank, GPA and the percent of applicants accepted by the university. Selector, and are converted i nto five dummy variables 9 for this study. The top category is Most Competitive, which includes universities that admitted students with a high 8 if they did not know ho w to evaluate the university they were asked about These responses were not used to calculate the average. 9 graduating from an accredited high school from their admitted students, sometimes require an examination score for placement standards, and accept 98% or more of its applicants.
21 school rank in the top 10% to 20%, average grades of A and B+, SAT score between 655 and 800 on each component of the SAT, and admitted a small percentage of students tha t apply to the university. The second highest category for a university is Highly Competitive, which are universities that admitted 50% of their applicants that had high school grades of B+ to B, wer e in the top 20% to 35% of their high school class, and had SAT scores ranging from 620 to 654 on verbal and math. The next category is Very Competitive, which indicates universities who admitted students with no less than a B rank in the top 30% to 35% of their high school class, had SAT scores ranging from 573 to 619 on verbal and math components, and accept only half of their applicant pool. The 4th category Competitive is one of the largest, and it pertains to universities that admitted students wit h SAT scores ranging from 500 to 572 in the verbal and math sections, a minimum of a C+ high school average, and were in the top 50% to 60% of their graduating class. The final category is Less Competitive, which includes universities that admitted fre shme n with averages below a C and with median score of 500 on the verbal and math sections on the SAT 10 Table 2 3 demonstrates all the universities with Most Competitive and Highly Competitive status between 1999 and 2009 and how real average faculty salary Almost all of the universities witness an increase in real salary regardless of whether the school remains in the same category or changed between Highly Competitive in 1999 to M ost Competitive in 2009 11 Among the larg est 10 However some of these universities accepted students that did not report there SAT scores or the university chose to n ot disclose that information 11 There were no universities that had change d from Most Competitive in 199 9 to Highly Competitive in 2009 Ther e were a few schools such that average faculty s alary in 2009 fell e Selector stayed the same b etween 1999 and 2009.
22 increase in average salaries were from universities that had remained in the Most Competitive category. Also, the average increase in faculty salary in 2009 for the universities that moved from Highly Competitive to Most Competitive was $14,753.60 ; a g reater increase than those that remained as Highly Competitive in both years 12 Similar to the hypothesis of the Peer Assessment variable, it is predicted that the more competitive the school is categorized, such as Most Competitive, Highly Competitive, and Very Competitive, the higher the average faculty salary will be because the more selective the university the greater the quality of the school. Therefore th ey are more likely to offer competitive and higher salaries to better faculty in order to suppor t a quality research department Teaching Characteristic Variables As mentioned before, previous studies have discussed how research publications and teaching abilities are important in the determinants of the level of faculty salary (Katz 1973; Koch and C hizmar 1973; Shwab and Dyer 1979) T hese specific variables at the university level are not available for the large number of universities sampled However, the variables indicating the percentage of classes with less than 20 students, t he percentage of cl asses with more than 50 students and the percentage of full time faculty are a good proxy. The data o n these variables are obtained from the U S News & World Report to assess a research, as well as the compensating differential to faculty for class size. 12 See Figure 2 1 T here are 12 universities that moved from Highly Competitive to Mos t Competitive, compared to 21 Highly Competitive s tatus. S o the averages may be inflated, but the differences cannot be ignor ed. Even after averaging the 12 largest salaries of the universities that stayed Highly Competitive in both years ( $ 14612.30 ) the average was still less than the average salary for uni versities that changed from Highly Competitive to Most Competitive.
23 Less than 20 Students : In a paper by Kenny and Denslow (1980) the number of that teachers demanded a higher salary as the number of students inc reased in the class for various school districts in six states 13 T eachers may be willing to have a lower salary if it mean s having the ability to teach smaller and more manageable classes. Therefore, a s the number of classes with 20 students or less increa ses, average faculty salaries will fall. More than 50 Students : Different from the Less than 20 Students variable, this variable will have a positive relationship with average faculty salary because teachers require a higher salary to compensate them for i nstructing a larger class. Percent Full Time Faculty : As the percentage of full time faculty increases, the average faculty salary offered to professors rises because full time professors focus on research more than non full time faculty. Full time faculty members are likely to stay with a university department in order to commit to developing and completing better research studies. Thus universities offer higher salaries to full time faculty because they F unding Variables Changes in state government funding levels have significant impacts on tuition expenditures and allocation (Freeman and Mumper 2005). Hence, the variables discussed below are included in order to control for the fact that outsid e sources c an influence professor salaries, and more research intensive universities usually obtain more financial resources T he data for these variables are obtained from the IPEDS 13 1 419 school districts in six states (Florida, Georgia, Virginia, Louisiana, Michigan, and California) we re examined (Kenny and Denslow, 1980).
24 survey that asked universit ies about the salaries they offer to their faculty (IPEDS 1999 2009) Federal Appropriations: All regressions include the Federal Appropriations per student variable which describes the amount of money received from the federal government through direct appropriations of congress, e xcept for grants and contrac ts 14 An increase in Federal appropriations towards universities allows them to afford better facilities, offer more courses, and hire better research faculty Hence, the m ore money a university receives from the federal government, the higher the average f aculty sa lary of the universities offered State Appropriations: In some regressions, State Appropriations per student are used in conjunction with the Federal Appropriations variable to further capture the relationship of funding and teacher salary. Highe r level s of stat e appropriations relate to higher levels of institutional scholarship support and lower levels of tuition and fees at both public and private institutions (Freeman and Mumper 2005). State Appropriations include amounts received from the sta te government through a direct appropriation of its legislative body, except for grants and contracts 15 Similar to federal appropriations, as state appropriations increase, teacher salary will increase because universities can offer a higher salary Also, this may indicate that more research intensive universities receive the greater appropriations, and therefore can hire the more qualified professors Tuition and Fees: Due to the correlation between state funding and tuition, Tuition and F ees of the 1998 1 999 and 2008 2009 school years will be used in place of 14 The data provided by the IPEDS survey is divided by the student population of full time enrolled students in the fall semester of the respective years to put it in per capita terms. 15 The data provided is put into per capita terms as well by dividing state appropriations by the number of full time enrolled students.
25 the State Appropriations variable in some regression s 16 If state funding is limited or decreased, universities may choose to increase tuition and fees in order to offer the same level of salaries for faculty ( Hauptman and Merisotis 1990). Therefore, as tuition charged increase s the more money a university has to go towards hiring better fac ulty and developing a qualified research program, which can indicate a better university program overall Demogra phic Variables Women, Black, Hispanic, and Asian: From the IPEDS survey, the percent of women faculty, percent of Black faculty, percent of Hispanic faculty, and the percent of Asian facul ty is derived. The variables are created by taking the total number of female Black, Hispanic, and Asian full time full professors and dividing each category by the total number of full time full professors employed by the university. As mentioned in the introduction, women have been underpaid as compared to men, and th us as the percent of women increases as compared to men, the average faculty salary at the university will decrease. Accordingly, Table 2 4 and Table 2 5 demonstrate that the 25 th percentile of women professors earn higher salaries as compared to male prof essors in that same percentile but in the larger percentiles, women earn lower salaries as compared to male faculty in both 1999 and 2009. This could be due to not only the fact that female faculty are not publishing as highly as men, but a larger percent age of female faculty may be employed at the lower ranked universities and thus earning lower salaries. Be cause there is some different evidence as to whether there is salary 16 As state appropriations increase, tuition and fee s can decrease because universities can cover some of the cost that tuition and fees were allocated towards with the greater amount of appropriations.
26 discrimination based on race and ethnicity, there is no prediction about the sign of the race coefficient. Regions : Dummy variables were created for 8 of the 9 census regions 17 : New England, Mid Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, and Mountain The more northern state s of the U S have higher costs of living and tougher climate changes, which according to Kenny and Denslow may increase teacher salaries (1980). T hus it is predict ed that universitie s in the more northern regions, such as New England, Mid Atlantic, and Ea st North Central will have higher average faculty salary as compared to the omitted Pacific r egion 17 The 9 th region, Pacific, is used as the residual for the region dummy variables
27 Table 2 1. Summary of 1999 n ominal average f aculty s alary Percentiles Smallest 1% $ 38877 $ 35505 5% $ 48489 $ 35570 10% $ 52258 $ 37665 Obs 668 25% $ 57574.5 0 $ 37876 Sum of Wgt. 668 50% $ 66259.5 0 Mean 68444.48 Largest Std. Dev. 15108.38 75% $ 77304 $ 119036 90% $ 88781 $ 119997 Variance 2.28e+08 95% $ 97383 $ 121148 Skewness .7944465 99% $ 114833 $ 130005 Kurtosis 3.834275 Table 2 2. Summa ry of 2009 n ominal average faculty s alary Percentiles Smallest 1% $ 50384 $ 30000 5% $ 63984 $ 42070 10% $ 69431 $ 44953 Obs 669 25% $ 77771 $ 45859 Sum of Wgt. 669 50% $ 90984 Mean 94601.45 Largest Std. Dev. 23678.84 75% $ 107975 $ 180225 9 0% $ 125631 $ 181013 Variance 5.61e+08 95% $ 140298 $ 184072 Skewness .9171399 99% $ 171649 $ 192859 Kurtosis 4.263808
28 Table 2 3 Changes in r eal faculty s alary per u niversities between 1999 and 2009 Name of Institution Barron's Select or 99 Barron's Selector 09 Change in Real Salary 1999 Most Competitive to 2009 Most Competitive Boston College Most Most $ 15024.1 0 Brown University Most Most $ 26394 California Institute of Technology Most Most $ 19119.1 0 University of California at Be rkley Most Most $ 5065.9 0 University of California at Los Angeles Most Most $ 11638.3 0 Carnegie Mellon University Most Most $ 9067.1 0 University of Chicago Most Most $ 31493.2 0 Columbia University Most Most $ 24656.2 0 Cornell University Most Most $ 1924.99 Dartmouth College Most Most $ 12682.8 0 Duke University Most Most $ 21915.7 0 Emory University Most Most $ 17072.8 0 Georgetown University Most Most $ 23369.6 0 Harvard University Most Most $ 25446.7 0 Johns Hopkins University Most Most $ 30490.9 0 Lehigh Univ ersity Most Most $ 13049.5 0 Mass. Institute of Technology Most Most $ 15773.3 0 New York University Most Most $ 29785.2 0 University of Notre Dame Most Most $ 12184.8 0 Northwestern University Most Most $ 23089.5 0 University of Pennsylvania Most Most $ 21861.3 0 Princeton University Most Most $ 26488.4 0 Rice University Most Most $ 19355.1 0 Stanford University Most Most $ 24218.2 0 Tufts University Most Most $ 11551.3 0 University of Virginia Most Most $ 13103 Wake Forest University Most Most $ 15401.9 0 Washington University St. Louis Most Most $ 28587.2 0 College of William and Mary Most Most $ 2716.9 0 Yale University Most Most $ 21034.9 0 Note: There were no universities that had c hanged from Most Competitive in 19 99 to Highly Competitive in 2009. Most= Most Compet itive, and Highly=Highly Competitive.
29 Table 2 3 Continued Name of Institution Barron's Selector 99 Barron's Selector 09 Change in Real Salary 1999 Highly Competitive to 2009 Highly Competitive Boston University Highly Highly $ 18174.9 0 University of California at Irvine Highly Highly $ 6150.8 0 University of California at San Diego Highly Highly $ 6774.7 0 University of California at Santa Barbara Highly Highly $ 6019.7 0 University of Florida Highly Highly $ 18948.09 University of Georgia Highly Highly $ 892.7 0 Georgia Institute of Technology Highly Highly $ 9712.9 0 University of Illinois at Urbana Champaign Highly Highly $ 8732.8 0 University of Michigan Ann Arbor Highly Highly $ 13653.6 0 North Carolina State University at Raleigh Highly Highly $ 5170.7 0 Pepperdine University Highly Highly $ 7850.4 0 Rutgers New Brunswick Highly Highly $ 12494.8 0 Santa Clara University Highly Highly $ 14894.3 0 Stevens Institute of Technology Highly Highly $ 10235.2 0 SUNY at Binghamton Highly Highly $ 17104.3 0 Syracuse Un iversity Highly Highly $ 16153.16 Texas A&M University at College Station Highly Highly $ 10125.5 0 Trinity University Highly Highly $ 874.4 0 University of Texas Austin Highly Highly $ 18230.7 0 University of Wisconsin at Madison Highly Highly $ 832.3 0 Worc ester Polytechnic Institute Highly Highly $ 15620.2 0 1999 Highly Competitive to 2009 Most Competitive Brandeis University Highly Most $ 18580.9 0 Case Western Reserve University Highly Most $ 8765.5 0 George Washington University Highly Most $ 22641.7 0 Rens selaer Polytechnic Institute Highly Most $ 8374.7 0 University of Miami Highly Most $ 20331.1 0 University of North Carolina Chapel Hill Highly Most $ 22245.4 0 College of New Jersey Highly Most $ 8884.9 0 SUNY Geneseo Highly Most $ 9595.73 Tulane University H ighly Most $ 14031.7 0 University of Rochester Highly Most $ 22119.6 0 Vanderbilt University Highly Most $ 17097.1 0 Villanova University Highly Most $ 4374.9 0 Note: There were no univ ersities that had changed from Most Competitive in 1999 to Highly Competiti ve in 2009. Most= Most Competitive, and Highly=Highly Competitive.
30 Table 2 4 Nominal mean salary of women f aculty compared to m en f aculty 1999 Quartile Mean Salary for Women Mean Salary for Men 1 $ 73537.8 0 $ 57259.7 0 2 $ 72881.9 0 $ 44170 3 $ 67379.4 0 $ 72168 4 $ 61343 $ 68526.1 0 Note: Quartile 1 corresponds to 25% and less of the sampled women faculty; Quartile 2 corresponds to 25% to 50% of the sampled women faculty; Quartile 3 corresponds to 50% to 75% of the sampled women faculty; and Quartile 4 cor respond s to 75% and more of the sampled women faculty. Table 2 5 Nominal mean salary of w omen faculty compared to men f aculty 2009 Quartile Mean Salary for Women Mean Salary for Men 1 $ 107727 $ 76422 2 $ 101895 $ 75699.5 3 $ 86566.8 0 $ 82554.8 4 $ 833 86.6 0 $ 94879.8 Note: Quartile 1 corresponds to 25% and less of the sampled women faculty; Quartile 2 corresponds to 25% to 50% of the sampled women faculty; Quartile 3 corresponds to 50% to 75% of the sampled women faculty; and Quartile 4 correspond s to 7 5% and more of the sampled women faculty.
31 Highly Comp etitive 2009 Most Competitive 2009 Highly Competitive 1999 21 Universities $ 10332.45 12 Universities $ 14753.60 Most Competitive 1999 N/A 30 Universities $ 18323.73 Note: This is a matrix repres entation of the changes in average faculty salaries of universities as they move or do not move between 1999 and 2009 in the The top line states the number of universities that stayed or us, while the second line shows the average increase in real faculty salary for those schools. N /A means there was no record of universities changing from Most Competitive to Highly C ompet it ive in 2009. Number of universities and the average salaries were calculated from Table 2 3 Figure 2 1 Matrix of the average i ncrease in faculty salaries for u niversities with Most Comp etitive and Highly Competitive s tatus between 1999 and 2009
32 CHAPTER 3 METHODOLOGY In order to look at the determinants of f aculty salary, I will estimate four separate regressions for average faculty salary in the 1999 cohort and 2009 cohort 1 In regression (1) and regression (2), I will use the peer assessment score as a measure of a university quality and in regression (3 ) and r egression (4), I will use Selector dummy variables. All four regressions will include the variables indicating the percentage of classes with less than 20 students, percentage of class es with more than 50 students, percentage of full time facu lty, percent of women, Black, Hispanic, and Asian faculty and the dummy variables that indicate the region the university is in 2 As f or the variables that describe university funding, all four regression s will include the variable for federal appropriati on s per capita, and in regression (1) and regression (3), state appropriations per capita will be used and in regression (2) and regression (4), tuitions and fees will be used. T he regression sequence s in T ables 4 1 and Table 4 4 for 1999 and Table 4 2 an d Table 4 5 for 2009 are as follows: 0 1 *Peer Assessment Score i 2 *Less than 20 Students i + 3 *More than 50 Students i 4 *Full Time Faculty i 5 Federal Appropriations i 6 Tuition and Fees i + 7 W omen i 8 Black i + 9 *Hispanic i 10 *Asian i 11 *Ne w England i 12 *Mid Atlantic i 13 *East North Central i 14 *West North Central i 15 *South Atlantic i 16 *East South Central i 17 *West South Central i 18 *Mountain i 1 Summary statistics f or all variables can be seen in Table 3 1, Table 3 2, and Table 3 3. 2 The correlation coefficient between Less than 20 Students and More than 50 Students is 0 .43, which means that it is unlikely there is any correlation between them. Also the correlation between the class size variables and the school reputation variables had correlation coefficients that were less than 0 .3.
33 0 1 *Peer Assessment Score i 2 *Less than 20 Stud ents i 3 *More than 50 Students i 4 *Full Time Faculty i 5 Federal Appropriations i 6 *State Appropriations i 7 Women i 8 Black i 9 *Hispanic i 10 *Asian i 11 *New England i 12 *Mid Atlantic i + 13 *East North Central i 14 *West North Central i 15 *South Atlantic i + 16 *East South Central i 17 *West South Central i 18 *Mountain i 0 1 *Most Competitive i 2 Highly Competitive i 3 *Very Competitive i 4 Competitive i 5 Less Competitive i 6 *Less than 20 Stu dents i 7 *More than 50 Students i + 8 *Full Time Faculty i 9 Federal Appropriations i 10 Tuition and fees i + 11 Women i 12 Black i 13 *Hispanic i 14 *Asian i 15 *New England i + 16 *Mid Atlantic i 17 *East North Central i 18 *West North Centra l i + 19 *South Atlantic i 20 *East South Central i 21 *West South Central i + 22 *Mountain i 0 1 *Most Competitive i 2 Highly 3 Very Competitive i 4 Competitive i 5 Less Competitive i 6 *Less than 20 St udents i 7 *More than 50 Students i + 8 *Full Time Faculty i 9 Federal Appropriations i 10 State Appropriations i 11 Women i 12 Black i 13 *Hispanic i 14 *Asian i + 15 *New England i 16 *Mid Atlantic i 17 *East North Central i 18 *West North Central i 19 *South Atlantic i 20 *East South Central i 21 *West South Central i 22 *Mountain i To see if different determinan ts of average faculty salary have chan ged over time, I will estimate four regressions of the differences in a verage faculty sal ary from 1999 to 2009, on the same variables as above, but each variable, except for the region s, represents the change in those said variables over time 3 Each regression has the same order of variables as described above. I nstead of each variable represe nting a single year, it repre sents the difference of the values between 1999 and 2009 The results of these regressions are seen in Table 4 3 and Table 4 6. 3 By changes I mean subtracting the values of the independent variables in 1999 from the values of the same independent variables in 2009. In order to create the Salary Difference variable, I first put the Average Faculty Salary in 1999 in 2009 dollars Therefore Real Average Faculty Salary 1999= Average Faculty Salary 1999*[(214.537=CPI 2009/166.600=CPI 1999)]. Thus Salary Difference = Average Faculty Salary 09 Real Average Faculty Salary 99. All other 1999 financial variables (Tuition and Fees, State Appropriations, Federal Appropriations) are derived the same way to put them in real 2009 terms, and create the difference financial v ariables.
34 Table 3 1. Summary s tatistics 1999 Variable Obs Mean Std. Dev. Min Max Average Faculty Salary 6 68 68444.48 15108.38 35505 130005 Peer Assessment 671 2.901043 0 .5454962 1.7 4.9 Most Competitive 667 0 .0449775 0 .2074103 0 1 Highly Competitive 667 0 .0569715 0 .2319621 0 1 Very Competitive 667 0 .2128936 0 .4096602 0 1 Competitive 667 0 .4302849 0 .49548 75 0 1 Less Competitive 667 0 .1934033 0 .3952628 0 1 Less than 20 Students 587 0 .4942419 0 .1513046 0 .05 1 More than 50 Students 588 0 .0639949 0 .0611411 0 0 .3 Full Time Faculty 627 0 .8081021 0 .1371867 .06 1 Federal Appropriations 671 117.3127 1503.913 0 34097.59 State Appropriations 671 3055.108 3155.113 0 15666.87 Tuition and Fees 671 8100.492 6407.784 1600 24162 Women 635 0 .220877 0 .127822 0 1 Asian 635 0 .0362417 0 .1061685 0 0 .75 Black 635 0 .0533191 0 .0515026 0 0 .4545455 Hispanic 635 0 .0154591 0 0259986 0 0 .2666667 New England Region 671 0 .0894188 0 .2855601 0 1 Mid Atlantic Region 671 0 .1684054 0 .374505 0 1 East North Central Region 671 0 .1535022 0 .3607398 0 1 West North Central Region 671 0 .0849478 0 .279012 0 1 South Atlantic Region 671 0 .16 09538 0 .3677625 0 1 East South Central Region 671 0 .071535 0 .2579087 0 1 West South Central Region 671 0 .1087928 0 .3116114 0 1 Mount Region 671 0 .04769 0 .2132685 0 1
35 Table 3 2. Summary s tatistics 1999 Variable Obs Mean Std. Dev. Min Max Average Fa culty Salary 669 94601.45 23678.84 30000 192859 Peer Assessment 671 2.81237 0 .5625732 1.6 4.9 Most Competitive 668 0 .0643713 0 .245597 0 1 Highly Competitive 668 0 .0748503 0 .2633468 0 1 Very Competitive 668 0 .2260479 0 .418584 0 1 Competitive 668 0 .5074 85 0 .5003186 0 1 Less Competitive 668 0 .0928144 0 .2903896 0 1 Less than 20 Students 641 0 .4801092 0 .150348 0 .14 0 .94 More than 50 Students 641 0 .0648331 0 .0604069 0 0 .3 Full Time Faculty 644 0 .8047826 0 .1252597 0 .28 1 Federal Appropriations 671 144.72 45 2452.246 0 60207.61 State Appropriations 671 2944.368 3229.691 0 19991.86 Tuition and Fees 671 14831.15 10858 2708 40437 Women 652 0 .2897254 0 .1214086 0 1 Asian 650 0 .072057 0 .0589987 0 0 .4615385 Black 650 0 .0433698 0 .1081046 0 0 .9 Hispanic 650 0 0221432 0 .029756 0 0 .2834225 New England Region 671 0 .0894188 0 .2855601 0 1 Mid Atlantic Region 671 0 .1684054 0 .374505 0 1 East North Central Region 671 0 .1535022 0 .3607398 0 1 West North Central Region 671 0 .0849478 0 .279012 0 1 South Atlantic Region 671 0 .1609538 0 .3677625 0 1 East South Central Region 671 0 .071535 0 .2579087 0 1 West South Central Region 671 0 .1087928 0 .3116114 0 1 Mount Region 671 0 .04769 0 .2132685 0 1
36 Table 3 3. Di fference between 2009 and 1999 summary s tatistics Variable Obs Mean Std. Dev. Min Max Average Faculty Salary 668 6559.667 8447.991 16385.09 55010.13 Peer Assessment 670 0 .088806 0 .2273065 1.3 1 Most Competitive 667 0 .0194903 0 .1383441 0 1 Highly Competitive 667 0 .017991 0 .2621925 1 1 Very Competitive 667 0 .0 134933 0 .4260274 1 1 Competitive 667 0 .077961 0 .556083 1 1 Less Competitive 667 0 .101949 0 .4263602 1 1 Less than 20 Students 571 0 .0114011 0 .1032055 0 .61 .37 More than 50 Students 572 0 .000993 0 .0337049 0 .25 .16 Full Time Faculty 610 0 .00 24918 0 .086522 0 .43 .56 Federal Appropriations 671 6.343453 685.0933 3966.634 16298.88 State Appropriations 671 847.2038 929.302 5752.399 0 Tuition and Fees 671 4399.845 3191.185 284.2969 24284.05 Women 632 0 .0672849 0 .0839462 .3636364 .55 Asian 632 0 .0365976 0 .1036722 .6147186 .3846154 Black 632 0 .009963 0 .0984756 0 .3 .7333333 Hispanic 632 0 .0068388 0 .0239169 .1757576 .2834225
37 CHA P TER 4 RESULTS This investigation proved to have insightful initial findings on the effects of various determinants on average faculty salary offered by universities and how they rel ate to their goal for strong research departments Each of the independent variables is discussed in turn describing the significant effect and the impact it held on faculty s alary as compared to the other variables. School Quality Variables Though the two indicators of university reputation have slightly different effects on average faculty salary, they indicate that after controlling for teaching characteristics funding, ge nder, race, and regions, more prominent and competitive universities offer higher average sal aries. This may explain why prestigiou s private universities offer higher s alaries as compared to large public universities as was shown in Table 1 1 and Table 1 2 University selectivity may also be an attractive factor for well qualified professors because they may prefer working for those universities over others, and less prestigious institutions may suffer in quality. Hence, universities understand how the sala ries they offer affect the quality of faculty they attract. Peer Assessment As predicted, Peer Assessment ha s a positive and significant effect on average faculty salary in regression (1) in 1999 and regression (2) in 2009, as seen in Table 4 1 and Table 4 2 For instan ce, in regression (1) of Table 4 4 a one standard deviation increase in 1999 peer a ssessment score s leads to a $6,678.9 7 increase in average faculty salary W hen controlling for S tate Appropriations instead of Tuition and F ees, a one st andar d deviation increase in 1999 peer a ssessment score s lead s to a $7,924.61
38 increase in average faculty salary at universities 1 In 20 09, P eer Assessment has a large impact on average faculty, where a one s tandard deviation increase in 2009 peer assessment s cores lead s to an $8,937.03 and $11,316.38 increase in average faculty salary in regression (1) and regression (2) respectively 2 As shown in Figure 4 1 and Figure 4 2, it a ppears that the higher scoring peer a ssessment universities in both 1999 and 2009 h ave higher average faculty salary as compared to the lower peer a ssessment scoring universities. This supports the hypoth esis that universities with higher reputation, i.e. higher peer assessment score s offer higher salaries in order to attract qualified research program. When considering how Peer Assessment varied from 1999 to 2009, Table 4 3 indicates that this measu re of university quality remains significant and positive, meaning that faculty salaries continue to in crease more with peer assessment score s in 2009 than in 1999. For in stance, a one standard deviation increase in peer a sse ssment scores lead s to a $790.83 increase in average faculty salary when controlling for Tuition and Fees, and an $871.01 increase in average faculty salary when controlling for State A ppropriations 3 A S electors Most Competitive, Highly Competitive, a n d Very Competitive are positive and significant in regression ( 3 ) and regression ( 4 ) of Table 4 1 and Table 4 2 suggesting that the more selective the university the higher the salaries offered to their faculty. The largest impact a rises when schools move from a 1 As seen in r egression ( 2 ) in Table 4 4. 2 Table 4 5 3 Regression (1) and Regression (2) in Table 4 6
39 N on C ompetitive university status to a Most C ompetitive university status where the change in average faculty salary is around $ 34,358 .91 when controlling for Tuition and F ees and $38,852 .52 when controlling for State A ppropriations 4 Highly Competitive and Very Competitive dummy variables had lower impacts than Most Competitive, as seen in Table 4 4 Compet itive and Less Competitive are insignificant as seen in Table 4 1 meaning there is no differenc e in average faculty salary in Competitive and Less C ompetitiv e categories, as c ompared to universities in the N on C ompetitive category. I n 2009, u niv ersities have an almost $39 355.12 to $ 49,989.30 increase in average faculty salary as universities move from a Non C ompetitive university status to a Most C ompetitive university status 5 The other dummy indicators of Highly Competitive and Ver y Competitive are still significant and positive but have lower impacts tha n Most Competitive 6 Similar to 1999, the rest of the dummy indicators for W variab les between 1999 an d 2009, the Most C ompetitive dummy variable remains significant, which means that th e top and most competitive universities continue to offer higher salaries over time 7 To get a better understanding of electors relate to research at various universities, Table 4 7 demonstrates the number of pages written in the top 50 8 4 Regre ssions (3) and (4) of Table 4 4 5 Regressions ( 3 ) and ( 4 ) of Table 4 5 6 Very Competitive is insignificant in regression ( 3 ) and regression (4) of Table 4 3 7 In Table 4 3, Very Competitive and Competitive are marginally significant but have the incorrect signs 8 Programs by Faculty and Graduate Publications: An Update Using 1994 McPherson (2012). The schools considered were 175 of 262 National Universities recorded by the 20 10 edition of the U.S. News & World Report because no t all the national schools in the sa mple we re listed in he total number of pages reported for each of the schools in the category was
40 The universities with the Most Competitive status were writing the most pages in the top journals, as well as receiving the highest average salaries in 2009 as compared to the lower category schools. The difference in pages written between Most Competitive university professors and Highly Competitive university professors is over 1,000 pages. Accordingly, the difference in average salaries amongst these two categories is well over $20,000. Between the lower categories, such as Competitive and Less Competitive, the difference is considerably less, where each category differs in less than 100 pa ges written and less than $11,000 in average faculty salary. Thus universities with higher publications are offering the highest salaries. Consequently, more competitive universities offer higher salaries for be tter faculty to improve research programs 9 A reason as to why the lower categories became insignificant over time is that universities in those categories were not as research intensive in 2009 as compared to the higher and more competitive universities. dummy variables. The significant ve a larger i mpact than Peer Assessment in every regression, as seen in Table 4 4 and Table 4 5 Fo r instance, when moving from a Non C ompetitive status to a Most C ompetitive status, average faculty salary at those universities increases over $30,000 in 1999 as compared to a one standard deviation divided by the number of schools in each category to obtain the average number of pages. Likewise, the faculty salary of the universities elector category was summed and div id ed by the number of universities in the category. 9 The exact numbers in Table 4 to journal publication by economics department fa culty. However, if this relationship as mentioned above is happening in economics departments, it c an comparably be happing in other faculty publications.
41 increase in peer a ssessment score s in 1999 10 In 2009, a change from a Non Competitive status to a Most C ompetitive status also leads to an increase of over $40,000 to $ 50,000 in average faculty salary, as compared to a one standard deviation increase in peer assessment scores 11 Further the adjusted R squared is higher for all the regression s involving the 12 as compared to the regressions involv ing Peer Assessment 13 difference better than peer assessment scores because allow for a non linear estimation of the model, therefore capturing more information than can the linear structure of Peer Assessment. Teaching Characteristics In all the teaching characteristics variable s indicate that professors are compensated to teach larger classes, and full time sta tus professors have earned higher salaries over time. Thus schools that can offer better salaries will attract faculty th at merit higher salaries as well as attract professors that will work for a lower salary in order to teach smaller courses. When evalu ating the salary of a faculty member and whether it is reflective of the quality of school or not, class size and full time status are factors to be considered Less than 20 Students This variable was insignificant in regression ( 1) of Table 4 1 when contr olling for 1999 peer a ssessment scores 14 However in regression (3) of Table 4 1 when 10 In regression ( 1 ) and ( 2 ) of T able 4 4 a one standard deviation increase i n peer assessment scores lead to an increase of around $7,000 in average faculty salary. 11 In regression (1) and (2) of T able 4 5, a one standard deviation increase in peer assessment scores leads to an increase of around $9,000 and $11,000 respectively i n average faculty salary 12 Regression ( 3 ) and ( 4 ) in Tables 4 1 through 4 3 13 Regression ( 1 ) and ( 2 ) in Tables 4 1 through 4 3 14 It was marginally significant in regression (2) of Table 4 1 but it had the incorrect sign.
42 and negative This suppor ts the hypothesis, as well as findings by Kenny and D enslow (1980), that professors teaching smaller class es are being compensated with lower salaries. For instance, a one standard deviation increase in the percentage of classes with less than 20 students leads to a decrease of $1851.97 in average faculty sa lary as seen in regression (3) of Table 4 4 when controlling for Tuition and Fees In 2009, this variable was insignificant in regression (1) and regression (4) of Table 4 2 15 However, ere included, this variable became significant and negative as seen in regression (3) of T able 4 2 Thus a one standard deviation increase in the percentage of smaller classes leads to a $211 0 decrease in average faculty salary 16 When looking at the change in average faculty salary o ver time, small class size coefficients are insignificant So universities continue to maintain the same number of their classes the same size over time. More than 50 Students This variable, as predicted, supports the hypothesis that faculty members are compensated to teach larger classes. In 1999, all four regressions have statistically signi ficant values as seen in Table 4 1 where a one standard deviation increase in the percentage of large classes lea d s to an increase in aver age fac ulty salary ranging from $2,898 74 to $5,3 81.03 amongs t the four regressions 17 Similarly in 2009, the coefficient s for this variable are significant in all four regressions of Table 4 2 where a one standard deviation increase in the percentage of l arge classes lead s to an increase 15 This variable was significant bu t it had the incorrect sign in regression (2) of Table 4 2 16 Regression (3) of Table 4 5 17 All four regressions of Table 4 4
43 in average f aculty salary ranging from $4,630 to $8,1 12.65 18 However, when looking in the regression s of the c hange between 1999 and 2009 19 this variable becomes insignificant. Nevertheless, compared to the Less than 20 St udents variable, this variable had a larger impact in regression ( 3 ) of both Table 4 4 and Table 4 5 w here a one standard deviation increase in the percent of classes with more than 50 students ha s over a $2000 larger increase in average faculty salary, a s compared to the percent of smaller class es So it can be seen that universities o ffer compensating wages for larger class sizes. Percent Full Time Faculty Th is variable was insignificant in both Table 4 1 and Table 4 2 mean ing there was not enough evide nce to suggest that the percent age of faculty that are full time has an effect on average faculty salary offered at those universities 20 However, when considering the difference between 1999 and 2009 this variable beco me s positive and stat istically signif icant, where a one standard deviation increase in the percentage of full time faculty lead s to an increase in average fa c ulty salary ranging from $1, 005.12 to $1, 286.93 21 This means that over time, more universities offer more full time salaries. Hence, no tably qualified professors receive higher full time salaries, indicative of man y foundation for a strong research department. 18 All four regressions of Table 4 5 19 All four regressions of Table 4 3 20 This variable had the correct sign as the hypothesis in regressions (1) to (3) of Table 4 2. 21 As seen in Table 4 6
44 Funding Variables In all, State Appropriations and Tuition and Fees both capture the same effect in that more funds allocated towards universities can be used to hire better faculty to improve research programs at a university. Universities that have larger prestige can receive g reater appropriations and thus have an ability to offer better wages to f aculty. Also, if state appropriations fall, tuition and fees must increase to cover what state appropriations covered in paying for qualified faculty. Federal Appropriations This variable is insignificant in all regressions in 1999 and 2009, as well as the difference between 1999 and 2009. Therefore, there is not enough evidence to support that there is an effect of federal funding on average faculty salaries offered by universities across the United States. State Appropriations State appropriations are sta tistically significant and positive in regression (4) and marginally significant in regression (2) in 1999 as seen in Table 4 1 Therefore, a one standard deviation increase in state appropriations per capita leads to a $1,699.34 increase in average facul ty salary, as seen in Table 4 4. This supports the hypothesis that as state funding increases, universities allocate more of their funds to offer better and more competitive salaries for hiring top research faculty. In 2009, the variable is insignificant, and therefore there was not enough evidence to support that it had an effect on 2009 average faculty salary 22 Further, in the regressions representing the changes in faulty salary as a result of State Appropriations between 1999 and 2009, State Appropriatio ns are statistically insignificant, as shown in Table 4 3. Over the span 22 As seen in Table 4 2
45 of 10 years, there is not enough evidence to support an effect on average faculty salary by State Appropriations. Tuition and Fees This variable also proves to be positive and signifi cant in the 1999 and 2009 regressions, as shown in Table 4 1 and Table 4 2 respectively. According to regress ion (1) of Table 4 4, a one standard deviation increase in Tuition and Fees leads to a $2,795.08 increase in average faculty salary, which has a la rger impact than State Appropriations in regression (2). In regression (3) of Table 4 Se lector indicators, a one standard deviation increase in Tuition and Fees leads to a $1375.11 increase in average faculty salary, which has a smal ler impact than State Appropriations on average faculty salary in regression (4). Nevertheless, this supports the hypothesis that the tuition and fees charged by universities affect faculty salaries by allowing universities to offer higher wages. Further, 2009 Tuition and Fees has a larger impact than 2009 State Appropriations, where a one standard deviation increase in Tuition and Fees leads to a $7,095.70 increase in regression (1) and a $5,430 increase in regression (3) of average faculty salary 23 Simila rly, when looking at the changes between 1999 and 2009, a one standard deviation increase in Tuition and Fees leads to a $2,188.83 increase in average faculty salary in regression (1), and a $1999.92 increase in average faculty salary in regression (3), a lager impact than State Appropriations over time 24 As can be seen in Figure 4 3 and Figure 4 4 higher tuition universities have considerably higher average faculty salaries than universities that offer lower tuition 23 As seen in Table 4 5 24 As seen in Table 4 6
46 between $10,000 and $15,000. Also, the regressions including Tuition and Fees have a higher adjusted R Squared as compared to the regressions that had State Appropriations, once controlling for Federal Appropriations. This means that tuition rates may explain the salary difference among univers ities better than state appropriations. More prestigious schools charge higher tuition, as compared to universities with lower tuition rates, and therefore offer higher salaries to hire qualified professors for better research programs. Demographic Variabl es In all, these variables add further explanation as to why average faculty salaries research programs and faculty 25 Women This variable was statistically significan t, as predicted, in all regressions for 1999 and 2009 26 A one standard deviation increase in the percentage of women faculty members leads to a decrease of $1414.99 to $1670.63 in average faculty salary in 1999 27 and a decrease of $201 0 to $4482.41 in avera ge faculty salary in 2009 28 This supports previous studies that women have had lower salaries as compared to m e n This may be due to outside family requirements than can inhibit their ability to publish or the tendency for female faculty member to be hired by lower ranked 25 The analysis on regions variables was excluded from this chapter In both 1999 and 2009 regressions (Table 4 1 and Table 4 2) the New England and Mid Atlantic regions had significant and positive coefficients, meaning that these regions, due to higher cost of living, offered higher salaries. The other regions were not sign ificant as consistently as the above regions in all regr essions, meaning that compared to the Pacific region there was not much difference in average faculty salary in these other regions 26 Marginally significant in regressions (3) and (4) of Table 4 1 27 Table 4 4 28 Table 4 5
47 universities that offer lower average faculty salaries When looking at the changes in the percentage of women faculty at universities between 1999 and 2009, a one standard deviation inc rease in the percentage of women faculty h a s a decrease of $1206.31 to $1544. 6 1 in average faculty salary 29 This indicates that over time universities offer lower salaries to women faculty, as compared to men, suggesting the possibility that female professors have not been publishing as much as ma le professors or are hired at the lower ranked universities that offer lower salaries Asian, Black, and Hispanic Faculty The Asian faculty variable seems to be biased towards higher salaries because all regressions are statistically significant and posit ive for all tables 30 A one standard deviation increase in Asian faculty leads to an increase of $1,255.46 to $1,854.85 in average faculty salary in 1999 31 In 2009, a one standard deviation increase in the percentage of Asian faculty leads to $3,298.14 to $ 3,710 increase in salary, as compared to White faculty 32 Between 1999 and 2009, the Asian faculty variable was statistically insignificant in all regressions, meaning there was not enough evidence to support the hypothesis that the percentage of Asian facu lty affected the average faculty salary at universities between 1999 and 2009, as compared to White faculty. The Black faculty variable only showed positive and significant results in 1999 33 A one standard deviation increase in the percentage of Black facu lty le a d s to an increase of $648.32 to $1257.07 in average faculty salary, as compared to White 29 As seen in Table 4 6 30 Insigni ficant in regression (4) of Table 4 1 but it is significant otherwise in all other tables 31 As seen in Table 4 4 32 As seen in Table 4 5 33 Regressions (1) to (3) are significant in Table 4 1
48 faculty 34 However, this has a lower impact than the Asian faculty variable in 1999. In 2009 and the regressions of the change in average faculty salary, the Bla ck faculty variable was insignificant, meaning there was not enough evidence to support the hypothesis that the percentage of Black faculty affected average faculty salary at universities, as compared to White faculty. The Hispanic faculty variable was als o positive and significant in all regressions of Table 4 1 and Table 4 2 35 The 1999 Hispanic faculty variable has an increase in average faculty salary of $1082.14 to $1504.20 for a one standard deviation increase of the percentage of Hispanic faculty, as compared to White faculty 36 In 2009 a one standard division increase in the percentage of Hispanic faculty le a d s to an increase of $1970 to $2489.67 in average faculty salary, as compared to White faculty 37 However, when looking at the changes between 199 9 and 2009, the Hispanic variable was only marginally significant 38 in regression (1), regression (3) and regression (4) of Table 4 3, where a one standard deviation increase in the percentage of Hispanic faculty le a d s to an increase of $568.87 to $649.82 i n average faculty salary 39 Thus the overall trend over time is that universities are offering similar competitive salaries to all culturally different professors. 34 As seen in Table 4 4 35 Marginally significant in regression (4 ) of Table 4 1 36 Table 4 4 37 Table 4 5 38 Selector of Table 4 3 39 As seen in Table 4 6
49 Table 4 1. Determinants of n ominal average f aculty s alary in 1999 Average Faculty Salary Average Faculty Salary Average Faculty Salary Average Faculty Salary Peer Assessment 12243.8348*** (987.4494) 14527.3421*** (907.7042) Most Competitive 34358.9142*** (3169.6827) 38852.5167*** (2844.9399) Highly Competitive 16409.0359*** (2760 .5182) 18601.2130*** (2580.2348) Very Competitive 7762.3235*** (2151.5111) 9575.4856*** (2052.6541) Competitive 1838.0394 (2000.9209) 2315.9291 (1976.3281) Less Competitive 2282.8455 (2132.2372) 1810.9730 (2112.8384) Less than 20 Students 3586 .3740 (4015.1314) 7024.1532' (3720.7554) 1.224e+04** (3970.3256) 6443.9621' (3732.2445) More than 50 Students 88009.9753*** (9595.5990) 75950.3617*** (10176.0936) 62166.5135*** (9820.9991) 47410.7771*** (10070.1308) Full Time Faculty 2873.7600 (4289.0 966) 7535.9110 (4459.8239) 1773.8959 (4208.4321) 6573.2797 (4297.9018) Federal Appropriations 0.2172 (0.5539) 0.0861 (0.5638) 0.3607 (0.5362) 0.5485 (0.5347) State Appropriations 0.3314' (0.1885) 0.5386** (0.1820) Tuition and Fees 0.4362*** (0.09 76) 0.2146* (0.1019) Women 1.107e+04* (4326.2318) 1.307e+04** (4377.4630) 7250.6421' (4203.5820) 7748.0021' (4183.5463) Asian 15807.1951* (6657.6248) 11825.1357' (6737.4534) 17386.0215** (6463.3609) 15046.7176* (6422.4675) Black 29436.7560** (1021 9.7539) 24407.9401* (10472.7906) 21116.5219* (9845.5159) 15239.5859 (9891.5545) Hispanic 57857.0395** (19048.0373) 49888.0742* (19429.3694) 41623.1543* (18741.8103) 31968.4983' (18697.0330) Constant 25788.0229*** (4976.0467) 21681.0946*** (5014.5688) 663 37.4621*** (4876.5356) 67899.4956*** (4832.2870) N 543.0000 543.0000 540.0000 540.0000 Adj. R Squared 0.5702 0.5565 0.6015 0.6048 Root MSE 9961.2400 10119.3906 9581.4802 9542.0237 Note: Entries are coefficients from ordinary least squares regressions; standard errors are in parentheses. Dependent variable is the 1999 average full professor faculty salary. Omitt ed (baseline) race category is W hite, non Hispanic, omitted Sel ector i s Non C ompetitive. p<0.05, **p<0.01, *** p<0.01. Coefficients from region variables are excluded.
50 Table 4 2. Determinants of n ominal average faculty s alary in 2009 Average Faculty Salary Average Faculty Salary Average Faculty Salary Average Faculty Salary Peer Assessment 15885.9801*** (1290.6641) 20115.3869*** (1259.8980) Most Competitive 39355.1160*** (4643.7276) 49989.3027*** (4513.9326) Highly Competitive 16462.4349*** (4172.3473) 22721.3236*** (4176.0475) Very Competitive 5240.4785 (3611.7358) 95 48.2452** (3671.3770) Competitive 1860.6095 (3417.6603) 110.7721 (3517.8965) Less Competitive 5432.4848 (3787.9946) 4907.7602 (3905.6255) Less than 20 Students 3052.9038 (5460.0497) 23490.9062*** (5198.1015) 1.406e+04* (5549.4509) 2779.4938 (5 449.0725) More than 50 Students 1.343e+05*** (13780.5617) 1.135e+05*** (15276.6051) 1.035e+05*** (14243.1158) 76721.9929*** (15089.5126) Full Time Faculty 8114.5473 (6615.9190) 1298.3188 (7071.5695) 6355.3357 (6529.4720) 941.8277 (6811.1393) Federal Ap propriations 0.1657 (0.7279) 0.0370 (0.7700) 1.0423 (0.7134) 1.1491 (0.7371) State Appropriations 0.1345 (0.2470) 0.0908 (0.2407) Tuition and Fees 0.6535*** (0.0784) 0.5004*** (0.0815) Women 2.649e+04*** (6079.2273) 3.692e+04*** (6305.1125) 1.65 7e+04** (6045.8561) 2.142e+04*** (6203.5324) Asian 62383.0809*** (12125.6292) 55901.8317*** (12832.2991) 62840.0684*** (11900.4900) 57907.7836*** (12308.1303) Black 517.0988 (7939.9922) 645.2941 (8414.6968) 1.110e+04 (7796.1332) 1.358e+04 (8060.2705) Hispanic 83669.8066*** (20747.8456) 81032.3237*** (21914.0679) 69260.8306*** (20564.0858) 66209.1335** (21199.5835) Constant 21291.3235** (7097.1457) 21065.0555** (7501.4966) 77589.1766*** (7941.0658) 87114.8156*** (8069.4592) N 617.0000 617.0000 615.0 000 615.0000 Adj. R Squared 0.6402 0.5986 0.6566 0.6349 Root MSE 14075.6276 14868.0127 13762.4717 14191.9094 Note: Entries are coefficients from ordinary least squares regressions; standard errors are in parentheses. Dependent variable is the 2009 aver age full professor faculty salary. Omitt ed (baseline) race category is W hite, non Hispanic, omitted (baseline) region category is Pacific and the omitted ( C ompetitive. p<0.05, **p<0.01, *** p<0.01. Coefficients from region variables are excluded.
51 Table 4 3. Difference in determinants of real average faculty salary, 1999 2009 Salary Difference Salary Difference Salary Difference Salary Difference Peer Asses sment 3479.1160* (1665.9903) 3831.8557* (1719.9831) Most Competitive 4374.8020 (3357.7925) 6222.9560' (3424.8216) Highly Competitive 275.1866 (2487.4947) 294.0650 (2551.5166) Very Competitive 1941.6444 (2030.0501) 2684.4282 (2076.6104) Comp etitive 2660.9210 (1852.6295) 3629.2311' (1890.3021) Less Competitive 2149.6149 (1888.8438) 2982.3868 (1930.0231) Less than 20 Students 1790.6435 (3936.7156) 4457.9180 (4043.1182) 927.2235 (3950.9562) 2931.6725 (4042.9682) More than 50 Students 5608.3107 (11795.1255) 3670.0966 (12232.9941) 395.8871 (11803.3380) 2237.5023 (12149.9952) Full Time Faculty 11616.9659** (4427.2735) 13759.4384** (4551.7400) 12778.9595** (4482.2949) 14874.0271** (4577.5656) Federal Appropriations 1.7469 (1.1919) 1.7 061 (1.2510) 1.7514 (1.1901) 1.7338 (1.2420) State Appropriations 0.5708 (0.3947) 0.5489 (0.3914) Tuition and Fees 0.6859*** (0.1160) 0.6267*** (0.1184) Women 1.437e+04** (4764.2365) 1.816e+04*** (4871.9222) 1.507e+04** (4757.0318) 1.840e+04** (4835.4626) Asian 11549.0311 (6790.9710) 10721.9797 (7015.5921) 10387.5707 (6777.1391) 9939.1555 (6958.4873) Black 1.207e+04 (7555.7898) 1.374e+04 (7800.3489) 1.209e+04 (7571.6530) 1.302e+04 (7771.6836) Hispanic 23785.1470' (14778.2755) 21779.6946 (15244.2953) (14782.3453) 25403.7033' (15157.1094) Constant 3376.7629* (1308.4992) 7526.1895*** (1212.8796) 3256.2162* (1306.4682) 6941.0588*** (1210.9307) N 526.0000 526.0000 524.0000 524.0000 Adj. R Squared 0.1503 0.0954 0.1582 0.1146 Ro ot MSE 7856.3413 8106.0376 7819.8681 8019.8884 Note: Entries are coefficients from ordinary least squares regressions; standard errors are in parentheses. Dependent variable is the difference in average full professor faculty salary from 1999 to 2009. Omi tted (baseline) race category is W hite, non Hispanic, omitted (baseline) region category is Pacific and the omitted ( C ompetitive. p<0.05, **p<0.01, *** p<0.01. Coefficients from region variables are excluded.
52 Table 4 4. Impact of d e terminants on n ominal average faculty s alary in 1999 Average Faculty Salary Average Faculty Salary Average Faculty Salary Average Faculty Salary Peer Assessment 6678.97 7924.61 Most Competitive 34358.9142 38852.52 Highly Competitive 16409.04 18601.21 Very Competitive 7762.3235 9575.486 Competitive N/A N/A Less Competitive N/A N/A Less than 20 Students N/A 1062.79 1851.97 975.001 More than 50 Students 5381.03 4643.69 3800.93 2898.747 Full Time Faculty N/A N/A N/A N/A Federal Appropriations N/A N/A N/A N/A State Appropriations 1045.60 1699.344 Tuition and Fees 2795.08 1375.11 Women 1414.99 1670.63 926.79 990.3 65 Asian 1678.23 1255.46 1845.85 1597.487 Black 648.32 1257.07 1087.56 N/A Hispanic 1504.20 1297.02 1082.14 831.1362 Note: The impact is calculated by multiplying the significant coefficients from Table 4 1 with the standard deviation for that variable from T able 3 the change from moving from a Non C ompetitive category to another category. Therefore, the impact is just the coefficient of the variable calculated in Table 4 1. N/A means the variable wa s insignificant in Table 4 1 so no impact was calculated.
53 Table 4 5. Impact of determinants on n ominal average f aculty s alary in 2009 Average Faculty Salary Average Faculty Salary Average Faculty Salary Average Faculty Salary Peer Assessment 8937.0266 6 11316.37758 Most Competitive 39355.116 49989.3027 Highly Competitive 16462.439 22721.3236 Very Competitive N/A 9548.2542 Competitive N/A N/A Less Competitive N/A N/A Less than 20 Students N/A 3531.810765 2.11E+03 N/A More than 50 Stud ents 8112.64667 6856.18315 6.25E+03 4.63E+03 Full Time Faculty N/A N/A N/A N/A Federal Appropriations N/A N/A N/A N/A State Appropriations N/A N/A Tuition and Fees 7095.703 5.43E+03 Women 3216.113814 4482.405512 2.01E+03 2.60E+03 Asian 3680.5 20675 3298.135398 3.71E+03 3.42E+03 Black N/A N/A N/A N/A Hispanic 2489.678765 2411.197824 2.06E+03 1.97E+03 Note: The impact is calculated by multiplying the significant coefficient s from Table 4 2 with the standard de viation for that variable from T ab le 3 from moving from a Non C ompetitive category to another category. Therefore, the impact is just the coefficient of the variable calculated in Table 4 2. N/A means the variable was insigni ficant in Table 4 2 so no impact was calculated.
54 Table 4 6. Impact of determinants on the d ifference in r eal average f aculty s alary, 1999 2009 Salary Difference Salary Difference Salary Difference Salary Difference Peer Assessment 790.83 871.01 Most Competitive N/A 6222.96 Highly Competitive N/A N/A Very Competitive N/A N/A Competitive N/A 3629.23 Less Competitive N/A N/A Less than 20 Students N/A N/A N/A N/A More than 50 Students N/A N/A N/A N/A Full Time Faculty 1005.12 1190.49 11 05.66 1286.931 Federal Appropriations N/A N/A N/A N/A State Appropriations N/A N/A Tuition and Fees 2188.83 1999.92 Women 1206.31 1524.46 1265.07 1544.61 Asian N/A N/A N/A N/A Black N/A N/A N/A N/A Hispanic 568.87 N/A 649.8221 607.5778 Note : The impact is calculated by multiplying the signi ficant coefficients from Table 4 3 with the standard de viation for that variable from T able 3 the change from moving from a Non C ompetitive category to another category. Therefore, the impact is just the coefficient of the variable calculated in Table 4 3. N/A means the variable was insignificant in Table 4 3 so no impact was calculated.
55 Table 4 7. elector s in the top 50 journals in 2009 Barron's Selector 2009 Number of Universities Average Number of Pages Average Salary in 2009 Most Competitive 40 2442.2 $147617.30 Highly Competitive 34 1127.0 $125783.91 Very Competitive 47 442.8 $112401.79 Competitive 47 288.8 $1 04198.23 Less Competitive 4 228.0 $93334.75 Non Competitive 3 107.5 $106631.67 Programs by Faculty and Graduate Publications: An Update Using 1994 by Michael A. McPherson (2012). The schools considered were 175 of 262 National Universities recorded by the 2010 edition of the U.S. News & World Report because not all the national schools in my sample were listed in f pages reported for each of the schools in the category was divided by the number of schools in each category to obtain the average number of pages. Likewise, the faculty salary of the univer elector category was summed and dived b y the number of universities in the category
56 Figure 4 1. Average faculty s alar y against peer assessment s cores 1999 Figure 4 2. Average faculty salary against peer a ss essment s cores 2009
57 Figure 4 3. Average faculty salary against tuition and f ees 1999 Fig ure 4 4. Aver age faculty salary against tuition and f ees 2009
58 CHAPTER 5 CONCLUSION This investigation proved to have insightful initial findings on the effects of various determinants on average faculty salary offered by universities and how they rel ate to their goal for strong research departments. The school quality variables, in particular Barron's Selector dummy variables, were shown to be influential in average faculty salary offered by universities, proving to have the largest i mpact when compared to other variables Professors are compensated to teach larger classes and they are willing to receive lower salaries in order to teach smaller classes. Further, the per centage of full time faculty has a significant effect on salaries o ffered over time, presenting evidence that universities offer higher full time salaries in order to establish str ong research programs. There is evidence that state funding allocated to a university and a university's tuition rate influences the level of s alaries offered by universitie s, and more money in either category of funding allows universities to offer higher salaries for more qualified pro fessors. Also, women professors receive lower salary offers as compared to male professors, indicating that thi s difference could be due to a larger percentage of women faculty not being able to publish as much as men due to outside fa mily responsibilities. T he overall trend over time is that universities are offering similar competitive salaries to all culturally different professors, regardless of race However, to better our understanding of the effects of university reputation, teaching characteristics, funding, and demographic characteristics on average faculty salary, future research must done with other data sets beyond the scope of this paper. It would be beneficial to exam faculty level data for all of the variables discussed in the
59 paper, especially if average faculty salaries were at the individual level. There are some limitations with the paper in that i t was not possible to find such specific data for all the variables in the university sample. Nevertheless, to further answer the question of whether average faculty salary is reflective of school quality, the scope of the data mu st become more faculty foc used. Further, incorporating departmental data that disc usses the publication tendencies for different departments, like economics, science s or mathematics, for multiple universities would support whether faculty salary offered is associated to a universi ties research program. Figure 4 7 showed preliminary results that average salary and economics depart ment publications are indeed correlated but it would be beneficial to include data from other departments into the model. Also, including faculty level da ta for the department could create a more representative sample of universities and their faculty. The effects of u niversity quality and teacher characteristics on salaries might also be estimated more accurately since there would be more variability in th e types of teachers sample d Most importantly, using data that can distinguish which departments get the most funding for research and salaries would be essential to the model. Funding is an issue for universities, and being able to use data that can ident ify how the funds are allocated would be necessary to evaluate whether average faculty salary is determ ined by school competitiveness and teaching characteristics, or the quality of the faculty. In all, to find a better method of evaluating teacher quality at differing universities as well as the factors that determine university quality, r esearch on fac ulty teaching, publication, university quality, and funding must be continued
60 LIST OF REFERENCES Barron's Educational Series, Inc., College Division 2000 2010 Barron's Profiles of College Division of Barron's Educational Series, Barron's Educational Series, Inc. Hauppauge, N.Y Bellas, Marcia L 1993."Faculty Salaries: Still a C ost of being Female?" Social Science Quarterly (University of Texas Press) 74 (1): 62 75. Darland, M.G. ,and S. M. Pawkins, J.L. Lovaeich, E.L. Scott, M.E. Sherman, and J. L. Whipple. 1974. te Regression Studies of Salary Difference Retrieved from the ERIC database. ( ED089638 ). Ehrenberg, Ronald G., and Michael Rizzo. esident and Nonresident Tuition and Enrollment at Flagshi Working Paper 10103 Freeman, Melissa and Michael Mumper The Causes and Consequences of Higher Education: Handbook of Theory and Research, edited by John S mart, 307 361. Great Britain: Springer Hauptman, Arthur M., and Jamie P. Merisotis 1990. The College Tuition Spiral: An Examination of Why Charges are Increasing: A Report to the College Board and the American Council on Education. Washington, D.C.: New York: The Council; The Board: Available from Macmillan Hearn, James C. : An Examination of F The Review of Higher Education 22 (4): 391 410. Heller, DE. 1998. "Rising Public Tuition Prices and Enrollment in Community Colleges and Four Year Institutions." Retr ie ved from the ERIC database. ( ED402837 ). Hoffman, Emily P 1976. "Faculty Salaries: Is there Discrimination by Sex, Race, and Discipline? Additional Evidence." The American Economic Review 66 (1): 196 198. Kenny, Lawrence W., and David A Denslow Jr Journal of Urban Economics 7 (2): 198 207. Kenny, Lawrence W ., and Roger E. Studley nd Lifetime Southern Economic Journal 62 (2): 382 393. Katz, David A 1973. "Faculty Salaries, Promotions, and Productivity at a Large University." The American Economic Review 63 (3): 469 477.
61 Koch, James V., and John F. Chizmar 1973. "T he Influence of Teaching and Other Factors upon Absolute Salaries and Salary Increments at Illinois State University." Journal of Economic Education (pre 1986) 5 (1): 27 35 McPherson, Michael A 2012. "Ranking U.S. Economics Programs by Faculty and Gradua te Publications: An Update Using 1994 2009 Data," Southern Economic Journal 79 (1): 71 89. McPherson, Michael S., Morton Owen Schapiro, and Gordon C. Winston 1989. "Recent Trends in U.S. Higher Education Costs and Prices: The Role of Government Funding." The American Economic Review 79 (2) : 253 257 P apers and Proceedings of the Hundred and First Annual Meeting of the American Economic Association Moore, Nelle. Research in Higher Educa tion 34 (1): 107 126. Schwab, Donald P., and Lee Dyer 1979. "Correlates of Faculty Salary Levels." Industrial Relations 18 (2): 210 219. Siegfried, John J., and Kenneth J White 1973. "Teaching and Publishing as Determinants of Academic Salaries." The J ournal of Economic Education (pre 1986) 4 (2): 90 99 Siegfried, John J., and Kenneth J. White. 1973. "Financial Rewards to Research and Teaching: A Case Study of Academic Economists." The American Economic Review 63 (2 ) : 309 315 Papers and Proceedings of the Eighty fifth Annual Meeting of the American Economic Association. U.S. Department of Education. 1999 2009. "Integrated Postsecondary Education Data System (IPEDS) Files." Institute of Education Sciences : National Center for Education Statistics Retrie ved from h ttp://nces.ed.gov/ipeds/datacenter/Default.aspx. U S News & World Report 1999 2009 Best Colleges 2000 2010 U.S. News & World Report : Washington, D.C: U.S. Webste r, Allen L 1995. "Demographic Factors Affecting Faculty Salary." Educational and Psychological Measurement 55 (5): 728 7 35.
62 BIOGRAPHICAL SKETCH Hanny Lane graduated with a BA in both economics and m athematics from the University of Florida in May of 2011 She was admitted into the graduate program in economics at the University of F lorida in the summer of 2011 and graduate d with a MA in economics in December of 2011 She grew up in Cocoa, F lorida and has lived there her whole life befo re coming to Gainesv ille in August 2007 to begin her undergraduate career. Her parents have both lived in Coc oa, FL for over 30 years, but her mother is originally fr om the Dominican Republic and a nanny. H er father is from Tampa, Florida and has been working with CSR at Cape Canaveral Air Force base for over 40 years. She has a brother who is 12 years her senior and works for Healthfirst. Some of her interests include reading, doing archery, and playing music. She learn ed how to play piano when she was 10 years old. She has b een playing flute since she was 11 years old, and had the privilege of being in the University of Florida Marching band during her sophomore, junior, and senior years of undergraduate college. Her previous work experience has been as a graduate assistant f or the Department of E conomics at the University of Florida, as well as a student assistant at the Department of Health Outcomes at the Institute of Child Health Policy at University of Florida's College of Medicine. She has also participated in the NSF 20 10 Summer Research Progr am at the University of Miami. She hope s to be a successful economist working for Walt Disney World as well as raising and being a part of a wonderful family.