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The sensitivity of variable measurement in faculty salary studies
THE SENSITIVITY OF VARIABLE MEASUREMENT IN FACULTY SALARY STUDIES
Richard B. Hansen’ This paper concerns the factors which influence salaries at a major Ph.D. granting university. It differs from similar studies in that it employs more than one indicator of performance in the areas of teaching, research and service, determinants which are inherently difficult to measure. Thus, in addition to supplementing the existing body of research on faculty salaries, this investigation provides an indication of the sensitivity of the results of similar research to the measurement of these independent variables. The paper briefly discusses the theoretical and institutional aspects of salary determination in academia and summarizes the methodologies and results of similar studies. The methodology used in the investigation is briefly presented followed by the results of the study. Finally conclusions from the study are drawn. BACKGROUND According to both economic theory and decision makers in higher education, faculty salaries are determined by performance in teaching, research and service. It follows that faculty salary differences should be attributable to differences among professors in these three areas.2 However, there may be other explanatory factors. 1 versity
. Rlchatd of Northern
2 It should but may partly reduced teaching faculty salaries.
B. Hansen Iowa.
is an Assistant
Professor
in the Department
of Economics
at the
be noted that a professor’s remuneration may not be entirely reflected be in forms which further influence performance (e.g., graduate student loads, travel money); this may account for some of the unexplained
Univet-
by salary assistance, variation in
First, neither employers nor empIoyees in academia are homogeneous in regard to nonpecuniary considerations or the relative importance of nonpecuniary vis-a-vis pecuniary job characteristics.3 Second, and following in part from the importance of nonfinancial factors, relative demand differences can exist among disciplines. Next, and also related, employers may practice sex discrimination. Fourth, casual empiricism suggests that professors who serve in administrative positions (e.g., chairpersons) receive higher salaries for doing so and that their salaries are not correspondingly reduced when they return to nonadministrative duties. Finally, and again on the basis of casual empiricism, it appears that seniority qua seniority may be rewarded in academia. Studies of faculty salary determination have broadly been of two types: those that were interdisciplinary and inn-a-institutional4 and those that were intradisciplinary and interinstitutional. Owing to the nature of this research, only studies of the first type will be discussed here. 3 For example, a school might pay one professor more colleague due to the former’s greater collegiability or one faculty than another who is no more productive because of the former’s graphic location; unfommately. measurement of these differences
than it pays an equally productive member might accept a lower salary greater preference for a specific geois not possible.
4 Robert Allen and Craig McPhee, “Teaching, Research, and Rewards,” November, 1974 (mimeographed); Fredricka Brecht, Nancy M. Gordon and Saul Pleeter, “Faculty Productivity and the Distribution of Their Earnings,” paper presented at the Western Economic Association Meetings, January, 1976; Industrial Relations 13 (February 1974): 69-77; Emily P. Hoffman, “An Econometric Study of Massachusetts/Amherst Faculty Salary Differentials,” paper presented at the New Manpower Researchers Conference, October, 1974; David Katz, “Faculty Salaries, Rates Promotion, and Productivity at a Large University,” American Economic Review 63 (June 1973): 469-77; James V. Koch and John F. Chitmar. “The Influence of Teaching and Other Factors Upon Absolute Salaries and Sakuy lncremeots at Illinois State University,“~ournd ofEconomic Education 3 (Fall, 1973): 27-34; Jane Loch and Marianne Ferber, “Sex as Predictive of Salary and Status on a University Faculty,” Journal of Educational Measurement 8 (Winter 1971): 23544.
5 W. Lee Hansen, Burton Weisbrod and Robert P. Strauss. “Modeling the Earnings and Research Productivity of Academic Economists,” /oumal of POlitiCd Economy, 86 (June 1978): 729-41; George Johnson and Frank Stafford, “Lifetime Earnings in a Professional Labor Market: Academic Economists,” Joumd of Po&tic& Economy 82 (May/June 1974): 549-69; N. Arnold Tolles and Emanuel Malichar. Studies of the Stwchwe of Economkts’ Sakwies mad Income, American Economic Review, Sup@mort. December, 1968; Howard Tuckman, Publication, Teaching ad tbe Academic Reward Stnrchrre. (Lexinston. Mass.: D.C. Heath. 1976).
3 Each of the investigations focused on a large university and used multiple regression analysis. However, the models differed with respect to both the general nature of the variables included and, in the case of some of the variables, their measurement. The following is a list of the general variables that were used in most of the studies: teaching, research, service, gender, administrative duties, relative market demand, highest earned degree and years of professional experience. While it is difficult to summarize the findings of these studies, owing to their dissimilarities, what follows is an attempt to do SO.~ Generally, teaching was found to exert either’ no significant effect or a significantly negative effect. Most of the prior studies showed research having a significantly positive influence. Service was also found to have a significantly positive effect on faculty salaries in most studies. Sex discrimination against females was discovered in those investigations which tested for it. Administrative responsibility was typically found to exert a positive and significant influence on salaries. Those studies which used assessed strength of relative market demand as the indicator of market forces showed significant coefficients of the expected sign. It was discovered, in those investigations testing for it, that professors with the Ph.D. earn significantly higher salaries than those without it. Finally, with one exception, years of professional experience was consistently the most significant factor influencing faculty salaries. METHODOLOGY The results of this investigation are based on a random sample of fiftythree professors in eight departments (Chemistry, Economics, English, Mathematics, Physics, Political Science, Psychology and Zoology). These departments are represented in most previous studies and are found at most universities.
6 The
reader
is referred
to the original
studies
for more
information.
4 The general form of the model that was tested is
where AS = academic year salary T = teaching R = research S = service G = gender A = administrative position M = market conditions E = experience u = error term These variables are included both because they are thought to be potentially influential and because they are comparable to those used in similar research. As was indicated above, more than one “yardstick” of teaching, research and service are employed. An elaboration on the variables follows. The dependent variable, salary, was measured all cases salaries were for academic year appointments.
in absolute
terms.7
In
Teaching is perhaps the most difficult of the independent variables to quantify. Department chairmen were asked to rate their professors’ teaching on a scale of one to seven (with the latter being the highest rating) and the ratings were treated as both cardinal numbers and as dummy variables (the latter involved compressing the ratings into three categories: high, medium and low). Additionally, students were asked to rate their professors’ teaching on a scale of one to seven and the mean score was used.
7 variable;
Ocha regression equations, the result was uniformly
not presented lower coefficients
here. used the natural of determination.
log of salary
as the dependent
5 Research was also measured by chairmen ratings treated as both cardinal numbers and dummy variables as above. Additionally, it was indicated by publications which were divided into four broad categories: textbooks, books, articles and “other” publications (the latter included edited books, research reports, notes, communications, revised books and poems); each category was measured in terms of both lifetime totals and standardized averages.8 The remaining variables can be discussed briefly. Gender was indicated by a binary dummy variable. Having been a department chairperson was also treated as a binary dummy variable.9 Disciplinary market conditions were categorized as strong, moderate or weak relative demand based on an assessment made by Brown” and a multiple category dummy variable was employed. The last variable, experience, was measured in number of years since receipt of the Ph.D. degree.’ r RESULTS The results of the estimation of the four specifications of the general model are presented in Table 1. Each of the equations is significant at the .Ol level and the coefficients of determination range from .74 to .82.
8 Averages were used both because they better cause of collinearity between the various publications averages were standardized to allow for the possibility of publishing. 9 No one in the sample was a department had any served in any other administrative capacity. 10 1967).
David p. 13.
11
All
G. Brown.
professors
The Mobile
in the sample
Professors
held
portray the flow measure of productivity and becategories and other independent variables; the of interdisciplinary differences in typical forms
chairperson
at the
(Washington.
D.C.:
the doctorate.
time
the
American
data
were
Council
gathered
on Education,
nor
6
TABLE
1 Regression
1
_.----.~ Variable
I
Coefficient (F-value)
Teaching Chairman’ Rating (Cardinal) Chairman’s Rating (Dummy) High Medium Student’s Rating (Mean) Research Chairman’s Rating (Cardinal) Chairman’s Rating (Dummy) High Medium Publications (Totals) Textbooks Books Articles Other Publications (Standardized Averages) Textbooks Books Articles Other Service Chairman’s Rating (Cardinal: Chairman’s Rating(Dummy) High Medium Committees (Total) Committees (Average) Gender (l=male) Administrative Position (1 = yes) Market Conditions Strong Demand Moderate Demand Experience Constant RS F a -omitted category is b - omitted category is : -significance at 0.01 l -significance at 0.05
low chairman’s weak relative level level
2 Coefficient (F-value)
3 Coefficient (F-value)
----
4 Coefficient (F-value)
-68.2(0.04) 235.3(0.03) -1295.5(1.14) 438.6c1.66)
323.7cO.72)
:576.0(6.05) :2243.4(6.08) 664.6cO.63) ‘2553.2(4.89) 249.2tO.23) 54.0(0.70) :265.9(14.14
‘1008.4(4.12) 330.8(0.59) 392.2t1.03) :934.6(6.25) 660.4(2.32) 1192.4(0.77) -144.0(0.02) 53.7c2.38) 651.6(0.26)
856.2tO.47)
-373.5(0.12)
361.5(0.74) 365.4cO.09)
‘1738.9(4.09)
‘2253.9(8.81)
‘2092.4(5.42)
‘2094.6(5.36)
‘2194.7(4.30) 470.6(0.18) :347.7(35.5( 4127.5 .741 : 15.766
‘2447.9(4.51) 4~8.0(0.13) :379.3(46.49 7769.2 .783 E13.461
‘1452.7c9.80) 490.7(0.30) :252.0(19.52) ‘497.7 .822 z17.229
‘2008.7(4.32) -342.5(0.12) :387.8(57.34) 6806.1 .774 z12.791
evaluation demand
7
The following is a discussion of the influence of teaching, research and service on faculty salaries and of the sensitivity of the results to different measures. None of the three measures of teaching is significant’* which suggests both that this variable does not affect professors’ salaries and that it is not sensitive to its measurement.* 3 With regard to research the findings show that it is a significant factor in explaining faculty salary differences and the significance is not influenced by the type of yardstick employed14 (although it is curious that neither the books variable nor the articles variable is significant in either the total or standardized average form’ 5 ). The coefficient for each of the four measures of service is insignificant suggesting that service does not affect faculty salaries and that this factor is not sensitive to how it is measured.’ 6
12
The
word
“significant”
as used
13 The results of regressions other measures are: the professor’s to teaching activity: and. the average
in this
paper
refers
to significance
at the .05 level
or better.
using other measures of teaching support these conclusions. The own evaluation of teaching; the average hours per week devoted number of contact hours taught per academic year.
14 The results of regressions using other measures of research tend to support these conclusions albeit this is not uniformly so. Other measures consistent with the findings are: nonstandardized average publications (textbooks and other publications but not books or articles are significant); and the sums of the four publications categories for totals, standardized averages and non-standardized averages. The following measures were not significant: the professor’s own evaluation of research; the average hours per week devoted to research activity. 15 Two observations should be noted here: first, these results are not attributable to collinearity among the publications categories; and second, insignificant coefficients also resulted when the articles were classified as “good” or “other” according to the quality of the journals in which they appeared. 16 Again, the results of regressions using other measures verify these conclusions. The other measures are: the professor’s own evaluation of service; the average hours per week devoted to service activity; the number of department committees served on, both totals and averages; and the sums of department and colltige and university committees served on, both totals and averages.
8
The following comments concern the remaining variables in the study. Sex discrimination does not appear to exist at the university in question inasmuch as the coefficient for the gender variable is not significant in any of the equations. The size, nature and significance of the administrative duties variable implies that professors who become a department chairperson receive about $2000 for doing so and that their salaries are not reduced correspondingly when they step down.’ ’ In all four regressions the coefficient for strong relative market demand was positive and significant suggesting that market forces do operate in academia.’ 8 Finally, years of professional experience exerted a positive and the most significant influence on faculty salaries.’ 9 CONCLUSIONS As noted previously, this study differs from others similar to it in more than one measure of teaching, research and service (factors which inherently difficult to quantify) is used to test for the sensitivity of results to the measurement of these factors. The results suggest that findings are not influenced by the measurement employed.
17 or average
This conclusion is supported by the fact that when years as chairperson the coefficient was insignificant.
this
factor
was measured
by either
that are the the
total
18 When market conditions were indicated by department affiliation the coefficients were usually of the expected sign and sometimes significant; interestingly, the coefficient for Economics Department was positive and significant (Chemistry was the omitted department) in all cases. The insignificance of the moderate demand coefficient may be attributable to there being little difference in relative demand among the departments in this category and in the low demand category inasmuch ss the categorization war based on an ordinal ranking of assessed market conditions.
experience academic experience
19 This variable was also broken into chrec categoreis at other academic institutions and nonacademic experience, at either the school studied or other was not significant.
(via., experience at the university studied, experience); the results were that years of schools, was significant while nonacademic
9 Additionally, this study can be compared to others like it. With two exceptions the results are the same in terms of variable significance. The two differences pertain to sex discrimination and the influence of service performance; the former was not found at the university studied while it was discovered at other schools and the latter was not significant in this study while it often was in others.
REFERENCES
1.
Allen,
Robert F. and Craig R. McPhee. “Teaching, wards,” Lincoln, Neb., 1974. (mimeographed)
2.
Brecht, Fredricka, Nancy M. Gordon and Saul Pleeter. “Faculty Productivity and the Distribution of Their Earnings.” Paper presented at the 51st annual conference of the Western Economic Association, San Francisco, 24-27 June 1976.
3.
Brown, David G. The Market for CoZlege Teachers. Chapel Hill, N.C.: North Caroline Press, 1965.
4. U.S. Department 5. American
. Academic Labor Markets. of Labor, 1965.
. The Mobile Professors. Council on Education, 1967.
Research and Re-
Washington,
D.C.:
Washington,
D.C.:
6.
Doering, Peter B. and Michael J. Piore. Zntemal Labor Markets Manpower Analysis. Lexington, Mass.: D.C. Heath, 1971.
7.
Ferber, Marianne. “Professors, Performance Relations 13 (February 1974): 69-77.
8.
Freeman, Richard H. “Demand for Labor in a Nonprofit Market: University Faculty.” In Labor in the Public and Nonprofit Sector, pp. 85-129. Edited by Daniel Hammermesh. Princeton, N.J.: Princeton University Press, 1975.
9.
Gordon, Nancy, Thomas Morton and I. C. Braden. “Faculty Salaries: Is There Dis-rimination by Sex, Race, and Discipline?” American Economic Review 64 (June 1974): 419-27.
and Rewards.”
and
Industrial
11 10. Hansen, W. Lee, Burton A. Weisbrod and Robert P. Strauss. “Modeling the Earnings and Research Productivity of Academic Economist,” Journal of Political Economy 86 (June 1978): 72941. 11.
Heckman, James J. and Solomon Polachek. “Empirical Evidence on the Functional Form of the Earnings-Schooling Relationship,“JoumaZ of the American Statistical Association 69 (June 1974): 350-54.
12.
Hoffman, Emily P. “An Econometric Study of Massachusetts/Amherst Faculty Salary Differentials.” Paper presented at the New Manpower Researchers Conference, Washington, D.C., October 1974.
13. Johnson, George and Fred Stafford. “Life Labor Market: Academic Economists,” omy 83 (May/June 1974): 549-69.
Earnings
Journal
in a Professional of Political Econ-
of Faculty Salaries and Rates of Promo14. Katz, David A. “Determinants tion at a Large University.” Ph.D. dissertation, University of Illinois, 1971. 15.
. “Faculty Salaries, and Productivity at a Large University.” Review 63 (June 1973): 469-77.
Rates
of Promotion,
American
Economic
16. Koch, James and John Chizmar. “The Influence of Teaching and Other Factors Upon Absolute Salaries and Salary Increments at Illinois State University.” Journal of Economic Education 3 (Fall 1973): 27-34. 17. Loeb, Jane and Marianne Ferber. “Sex as Predictive of Salary and Status on a University Faculty.” Journal of EducationalMeasurement 8 (Winter 1971): 23544.
12 18. Siegfried, John and Kenneth White. “Teaching and Publishing as Determinants of Faculty Salaries.” Journal of Economic Education 3 (Spring 1973): 90-99. 19. TolIes, N. Arnold and Emanuel Malichar. “Studies in the Structure of Economists’ Salaries and Income.” American Economic Review: Supplement (December 1968). 20. Tuckman, Howard P. Publications, Teaching and the Academic Reward StrucEure. Lexington, Mass.: D.C. Heath, 1976.
Richard B. Hansen’ This paper concerns the factors which influence salaries at a major Ph.D. granting university. It differs from similar studies in that it employs more than one indicator of performance in the areas of teaching, research and service, determinants which are inherently difficult to measure. Thus, in addition to supplementing the existing body of research on faculty salaries, this investigation provides an indication of the sensitivity of the results of similar research to the measurement of these independent variables. The paper briefly discusses the theoretical and institutional aspects of salary determination in academia and summarizes the methodologies and results of similar studies. The methodology used in the investigation is briefly presented followed by the results of the study. Finally conclusions from the study are drawn. BACKGROUND According to both economic theory and decision makers in higher education, faculty salaries are determined by performance in teaching, research and service. It follows that faculty salary differences should be attributable to differences among professors in these three areas.2 However, there may be other explanatory factors. 1 versity
. Rlchatd of Northern
2 It should but may partly reduced teaching faculty salaries.
B. Hansen Iowa.
is an Assistant
Professor
in the Department
of Economics
at the
be noted that a professor’s remuneration may not be entirely reflected be in forms which further influence performance (e.g., graduate student loads, travel money); this may account for some of the unexplained
Univet-
by salary assistance, variation in
First, neither employers nor empIoyees in academia are homogeneous in regard to nonpecuniary considerations or the relative importance of nonpecuniary vis-a-vis pecuniary job characteristics.3 Second, and following in part from the importance of nonfinancial factors, relative demand differences can exist among disciplines. Next, and also related, employers may practice sex discrimination. Fourth, casual empiricism suggests that professors who serve in administrative positions (e.g., chairpersons) receive higher salaries for doing so and that their salaries are not correspondingly reduced when they return to nonadministrative duties. Finally, and again on the basis of casual empiricism, it appears that seniority qua seniority may be rewarded in academia. Studies of faculty salary determination have broadly been of two types: those that were interdisciplinary and inn-a-institutional4 and those that were intradisciplinary and interinstitutional. Owing to the nature of this research, only studies of the first type will be discussed here. 3 For example, a school might pay one professor more colleague due to the former’s greater collegiability or one faculty than another who is no more productive because of the former’s graphic location; unfommately. measurement of these differences
than it pays an equally productive member might accept a lower salary greater preference for a specific geois not possible.
4 Robert Allen and Craig McPhee, “Teaching, Research, and Rewards,” November, 1974 (mimeographed); Fredricka Brecht, Nancy M. Gordon and Saul Pleeter, “Faculty Productivity and the Distribution of Their Earnings,” paper presented at the Western Economic Association Meetings, January, 1976; Industrial Relations 13 (February 1974): 69-77; Emily P. Hoffman, “An Econometric Study of Massachusetts/Amherst Faculty Salary Differentials,” paper presented at the New Manpower Researchers Conference, October, 1974; David Katz, “Faculty Salaries, Rates Promotion, and Productivity at a Large University,” American Economic Review 63 (June 1973): 469-77; James V. Koch and John F. Chitmar. “The Influence of Teaching and Other Factors Upon Absolute Salaries and Sakuy lncremeots at Illinois State University,“~ournd ofEconomic Education 3 (Fall, 1973): 27-34; Jane Loch and Marianne Ferber, “Sex as Predictive of Salary and Status on a University Faculty,” Journal of Educational Measurement 8 (Winter 1971): 23544.
5 W. Lee Hansen, Burton Weisbrod and Robert P. Strauss. “Modeling the Earnings and Research Productivity of Academic Economists,” /oumal of POlitiCd Economy, 86 (June 1978): 729-41; George Johnson and Frank Stafford, “Lifetime Earnings in a Professional Labor Market: Academic Economists,” Joumd of Po&tic& Economy 82 (May/June 1974): 549-69; N. Arnold Tolles and Emanuel Malichar. Studies of the Stwchwe of Economkts’ Sakwies mad Income, American Economic Review, Sup@mort. December, 1968; Howard Tuckman, Publication, Teaching ad tbe Academic Reward Stnrchrre. (Lexinston. Mass.: D.C. Heath. 1976).
3 Each of the investigations focused on a large university and used multiple regression analysis. However, the models differed with respect to both the general nature of the variables included and, in the case of some of the variables, their measurement. The following is a list of the general variables that were used in most of the studies: teaching, research, service, gender, administrative duties, relative market demand, highest earned degree and years of professional experience. While it is difficult to summarize the findings of these studies, owing to their dissimilarities, what follows is an attempt to do SO.~ Generally, teaching was found to exert either’ no significant effect or a significantly negative effect. Most of the prior studies showed research having a significantly positive influence. Service was also found to have a significantly positive effect on faculty salaries in most studies. Sex discrimination against females was discovered in those investigations which tested for it. Administrative responsibility was typically found to exert a positive and significant influence on salaries. Those studies which used assessed strength of relative market demand as the indicator of market forces showed significant coefficients of the expected sign. It was discovered, in those investigations testing for it, that professors with the Ph.D. earn significantly higher salaries than those without it. Finally, with one exception, years of professional experience was consistently the most significant factor influencing faculty salaries. METHODOLOGY The results of this investigation are based on a random sample of fiftythree professors in eight departments (Chemistry, Economics, English, Mathematics, Physics, Political Science, Psychology and Zoology). These departments are represented in most previous studies and are found at most universities.
6 The
reader
is referred
to the original
studies
for more
information.
4 The general form of the model that was tested is
where AS = academic year salary T = teaching R = research S = service G = gender A = administrative position M = market conditions E = experience u = error term These variables are included both because they are thought to be potentially influential and because they are comparable to those used in similar research. As was indicated above, more than one “yardstick” of teaching, research and service are employed. An elaboration on the variables follows. The dependent variable, salary, was measured all cases salaries were for academic year appointments.
in absolute
terms.7
In
Teaching is perhaps the most difficult of the independent variables to quantify. Department chairmen were asked to rate their professors’ teaching on a scale of one to seven (with the latter being the highest rating) and the ratings were treated as both cardinal numbers and as dummy variables (the latter involved compressing the ratings into three categories: high, medium and low). Additionally, students were asked to rate their professors’ teaching on a scale of one to seven and the mean score was used.
7 variable;
Ocha regression equations, the result was uniformly
not presented lower coefficients
here. used the natural of determination.
log of salary
as the dependent
5 Research was also measured by chairmen ratings treated as both cardinal numbers and dummy variables as above. Additionally, it was indicated by publications which were divided into four broad categories: textbooks, books, articles and “other” publications (the latter included edited books, research reports, notes, communications, revised books and poems); each category was measured in terms of both lifetime totals and standardized averages.8 The remaining variables can be discussed briefly. Gender was indicated by a binary dummy variable. Having been a department chairperson was also treated as a binary dummy variable.9 Disciplinary market conditions were categorized as strong, moderate or weak relative demand based on an assessment made by Brown” and a multiple category dummy variable was employed. The last variable, experience, was measured in number of years since receipt of the Ph.D. degree.’ r RESULTS The results of the estimation of the four specifications of the general model are presented in Table 1. Each of the equations is significant at the .Ol level and the coefficients of determination range from .74 to .82.
8 Averages were used both because they better cause of collinearity between the various publications averages were standardized to allow for the possibility of publishing. 9 No one in the sample was a department had any served in any other administrative capacity. 10 1967).
David p. 13.
11
All
G. Brown.
professors
The Mobile
in the sample
Professors
held
portray the flow measure of productivity and becategories and other independent variables; the of interdisciplinary differences in typical forms
chairperson
at the
(Washington.
D.C.:
the doctorate.
time
the
American
data
were
Council
gathered
on Education,
nor
6
TABLE
1 Regression
1
_.----.~ Variable
I
Coefficient (F-value)
Teaching Chairman’ Rating (Cardinal) Chairman’s Rating (Dummy) High Medium Student’s Rating (Mean) Research Chairman’s Rating (Cardinal) Chairman’s Rating (Dummy) High Medium Publications (Totals) Textbooks Books Articles Other Publications (Standardized Averages) Textbooks Books Articles Other Service Chairman’s Rating (Cardinal: Chairman’s Rating(Dummy) High Medium Committees (Total) Committees (Average) Gender (l=male) Administrative Position (1 = yes) Market Conditions Strong Demand Moderate Demand Experience Constant RS F a -omitted category is b - omitted category is : -significance at 0.01 l -significance at 0.05
low chairman’s weak relative level level
2 Coefficient (F-value)
3 Coefficient (F-value)
----
4 Coefficient (F-value)
-68.2(0.04) 235.3(0.03) -1295.5(1.14) 438.6c1.66)
323.7cO.72)
:576.0(6.05) :2243.4(6.08) 664.6cO.63) ‘2553.2(4.89) 249.2tO.23) 54.0(0.70) :265.9(14.14
‘1008.4(4.12) 330.8(0.59) 392.2t1.03) :934.6(6.25) 660.4(2.32) 1192.4(0.77) -144.0(0.02) 53.7c2.38) 651.6(0.26)
856.2tO.47)
-373.5(0.12)
361.5(0.74) 365.4cO.09)
‘1738.9(4.09)
‘2253.9(8.81)
‘2092.4(5.42)
‘2094.6(5.36)
‘2194.7(4.30) 470.6(0.18) :347.7(35.5( 4127.5 .741 : 15.766
‘2447.9(4.51) 4~8.0(0.13) :379.3(46.49 7769.2 .783 E13.461
‘1452.7c9.80) 490.7(0.30) :252.0(19.52) ‘497.7 .822 z17.229
‘2008.7(4.32) -342.5(0.12) :387.8(57.34) 6806.1 .774 z12.791
evaluation demand
7
The following is a discussion of the influence of teaching, research and service on faculty salaries and of the sensitivity of the results to different measures. None of the three measures of teaching is significant’* which suggests both that this variable does not affect professors’ salaries and that it is not sensitive to its measurement.* 3 With regard to research the findings show that it is a significant factor in explaining faculty salary differences and the significance is not influenced by the type of yardstick employed14 (although it is curious that neither the books variable nor the articles variable is significant in either the total or standardized average form’ 5 ). The coefficient for each of the four measures of service is insignificant suggesting that service does not affect faculty salaries and that this factor is not sensitive to how it is measured.’ 6
12
The
word
“significant”
as used
13 The results of regressions other measures are: the professor’s to teaching activity: and. the average
in this
paper
refers
to significance
at the .05 level
or better.
using other measures of teaching support these conclusions. The own evaluation of teaching; the average hours per week devoted number of contact hours taught per academic year.
14 The results of regressions using other measures of research tend to support these conclusions albeit this is not uniformly so. Other measures consistent with the findings are: nonstandardized average publications (textbooks and other publications but not books or articles are significant); and the sums of the four publications categories for totals, standardized averages and non-standardized averages. The following measures were not significant: the professor’s own evaluation of research; the average hours per week devoted to research activity. 15 Two observations should be noted here: first, these results are not attributable to collinearity among the publications categories; and second, insignificant coefficients also resulted when the articles were classified as “good” or “other” according to the quality of the journals in which they appeared. 16 Again, the results of regressions using other measures verify these conclusions. The other measures are: the professor’s own evaluation of service; the average hours per week devoted to service activity; the number of department committees served on, both totals and averages; and the sums of department and colltige and university committees served on, both totals and averages.
8
The following comments concern the remaining variables in the study. Sex discrimination does not appear to exist at the university in question inasmuch as the coefficient for the gender variable is not significant in any of the equations. The size, nature and significance of the administrative duties variable implies that professors who become a department chairperson receive about $2000 for doing so and that their salaries are not reduced correspondingly when they step down.’ ’ In all four regressions the coefficient for strong relative market demand was positive and significant suggesting that market forces do operate in academia.’ 8 Finally, years of professional experience exerted a positive and the most significant influence on faculty salaries.’ 9 CONCLUSIONS As noted previously, this study differs from others similar to it in more than one measure of teaching, research and service (factors which inherently difficult to quantify) is used to test for the sensitivity of results to the measurement of these factors. The results suggest that findings are not influenced by the measurement employed.
17 or average
This conclusion is supported by the fact that when years as chairperson the coefficient was insignificant.
this
factor
was measured
by either
that are the the
total
18 When market conditions were indicated by department affiliation the coefficients were usually of the expected sign and sometimes significant; interestingly, the coefficient for Economics Department was positive and significant (Chemistry was the omitted department) in all cases. The insignificance of the moderate demand coefficient may be attributable to there being little difference in relative demand among the departments in this category and in the low demand category inasmuch ss the categorization war based on an ordinal ranking of assessed market conditions.
experience academic experience
19 This variable was also broken into chrec categoreis at other academic institutions and nonacademic experience, at either the school studied or other was not significant.
(via., experience at the university studied, experience); the results were that years of schools, was significant while nonacademic
9 Additionally, this study can be compared to others like it. With two exceptions the results are the same in terms of variable significance. The two differences pertain to sex discrimination and the influence of service performance; the former was not found at the university studied while it was discovered at other schools and the latter was not significant in this study while it often was in others.
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