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4-1-2004
The Changing Nature of Faculty Employment
Ronald G. Ehrenberg
Cornell University, rge2@cornell.edu
Liang Zhang
Cornell University
Ehrenberg, Ronald G. and Zhang, Liang, "The Changing Nature of Faculty Employment" (2004). Working Papers. Paper 43.
http://digitalcommons.ilr.cornell.edu/workingpapers/43
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Revised Draft
January 16, 2004
Comments Solicited
The Changing Nature of Faculty Employment*
by
Ronald G. Ehrenberg and Liang Zhang*
(To be presented at the TIAA-CREF Institute conference on “Retirement, Retention
and Recruitment”, New York, NY, April 1-2, 2004))
* Ehrenberg is the Irving M. Ives Professor of Industrial and Labor Relations and
Economics at Cornell University and Director of the Cornell Higher Education Research
Institute (CHERI). Zhang is a graduate research assistant at CHERI. Without implicating
them for what remains, we are grateful to the Andrew W. Mellon Foundation and the
Atlantic Philanthropies (USA) Inc. for their financial support of CHERI.
I. Introduction
The last two decades of the twentieth century saw a significant growth in the
shares of faculty members in American colleges and universities that are part-time or are
full-time without tenure-track status (Eugene Anderson 2002, Roger Baldwin and Jay
Chronister 2001, Valerie Conley, David Lesley, and Linda Zimbler 2002). Growing
student enrollments faced by academic institutions during tight financial times and
growing differentials between the salaries of part-time and full-time non-tenure track
faculty on the one hand, and tenured and tenure-track faculty on the other hand are
among the explanations given for these trends. However, there have been few
econometric studies that seek to test these hypotheses.1
Our paper begins by presenting information, broken down by form of control
(public/private) and 1994 Carnegie Category, on how the proportions of full-time faculty
at 4-year American colleges and universities that are tenured and on tenure tracks and
that are not on tenure tracks have changed since 1989, using information for a consistent
sample of institutions from the annual IPEDS Faculty Salary Surveys and the biennial
IPEDS Fall Staff Surveys. The latter source also permits us to present similar estimates of
the proportions of faculty that are employed part-time and the share of new full-time
faculty appointments that are not on tenure tracks.
To analyze the role that economic variables play in causing changes in faculty
employment across categories, we conduct two types of econometric analyses. First, in
section III, we use panel data to estimate demand functions for tenure and tenure-track
faculty on the one hand and full-time non tenure-track faculty on the other hand to learn
1
Ronald G. Ehrenberg and Daniel B. Klaff (2002) provide some preliminary evidence using data from the
State University of New York (SUNY) system.
1
how changes in revenues per student and the average salaries of different types of fulltime faculty influence the distribution of faculty across categories of full-time faculty.
We do this using both equilibrium models that assume instantaneous adjustments to
changes in revenues and faculty salaries and lagged adjustment models that permit partial
adjustments to equilibrium each year.
Second, in section IV, we estimate models that seek to explain the flow of new
hires of each type of faculty member (rather than the levels of faculty employment) using
data on new hires that are available from the IPEDS Fall Staff Surveys. To explain new
hires, in addition to information on changes in revenues per student, changes in
enrollment, and the levels of faculty salaries, we require information on the number of
vacant positions that are available to be potentially filled. We construct information on
the latter using data on the number of continuing full-time faculty members at an
institution each year that the American Association of University Professors (AAUP)
collects (but does not publish) as part of its annual salary survey.
Continuing faculty members in a rank are defined as the number of faculty
members in a rank one year, who also are on the payroll of the institution in the next year,
regardless of their rank in the second year. Summing up an institution’s continuing
faculty members across ranks in a year and subtracting that number from the institution’s
total faculty employment in the previous year provides us with an estimate of the number
of full-time faculty vacancies that an institution could have filled in a year if it had
replaced each of its departing full-time faculty members.
A brief concluding section summarizes our findings and discusses their
implications for American colleges and universities and their students.
2
II. Changes in Faculty Composition
Table 1 provides annual data on the share of full-time faculty members that are
not employed in tenured or tenure-track positions at 4-year colleges and universities in
the United States for the 1989 to 1999 period. The data come from the annual IPEDS
Faculty Salary Surveys and are tabulated separately by form of control and 1994
Carnegie Category. Because a few institutions fail to report survey data each year, we
restrict our attention to a sample of 504 public and 854 private colleges and universities
that responded to the survey each year.
In the aggregate, the ratio of full-time non-tenure track faculty to total full-time
faculty rose from 0.111 to 0.137 at the public institutions in the sample and from 0.142 to
0.197 at the private institutions in the sample. Contrary to what one might have expected,
given the well-known budget problems of public higher education during the period, the
increasing usage of full-time non tenure-track faculty was larger at the privates than at the
publics. Moreover, for almost all Carnegie Categories, the share of full-time faculty that
is not on tenure tracks was higher in 1999 at private institutions than it was at public
institutions.2
Appendix table 1 provides similar tabulations for the 1989 to 2001 period using
data from the biennial IPEDS Fall Staff Surveys.3 There are a number of important
differences in the definition of faculty in the two surveys. One major one is that the
Faculty Salary Survey is restricted to faculty with instructional responsibilities, while the
Fall Staff Survey also includes faculty without any instructional responsibilities who are
2
The one exception is the Doctoral II category in which the public share is slightly higher than the private
share.
3
Data for 2000 and 2001 are currently not available from the Faculty Salary Survey.
3
entirely on research or public service appointments. This definitional difference probably
leads the share of full-time faculty that is on non tenure-track appointments to be higher
in the Staff Survey data.
The tabulations in appendix table 1 are for a sample of 319 public and 761 private
4-year colleges and universities that participated in the Staff Survey each year. While the
share of full-time faculty on non tenure tracks is also higher at private institutions than at
public institutions in this sample, the increase was greater during the period at the publics
than at the privates, due primarily to large increases at the public Research I and Research
II institutions. This suggests the growing usage of full-time non tenure-track faculty
positions for full-time researchers at these institutions.
In Table 2, we provide some evidence on the growing usage of part-time faculty
members. Part-time faculty data is available in the Fall Staff Survey but not in the Faculty
Salary Survey. The numbers presented in the table represent the ratio of total part-time
faculty members to total full-time faculty members at a set of institutions that were both
in the sample each year and reported positive numbers of part-time faculty members in
each year.4 The ratios are calculated using a sample of 172 public and 483 private
institutions.
During the 1989 to 2001 period, the ratio of part-time to full-time faculty
members rose from .269 to .377 at the public institutions in the sample and from .499 to
.686 at the private institutions in the sample. In 2001, the share of part-time faculty was
higher for each Carnegie category of institution at private institutions than it was at public
institutions.
4
The latter restriction is necessary because it is impossible to determine whether a blank in the survey data
represents zero or missing data in a year. As a result, the shares of full-time faculty members that are parttime may be overstated in these data.
4
Finally, the Fall Staff Survey also contains information on whether faculty
members who are newly hired during the academic year are on tenured, tenure-track or
non tenure-track appointments. Remembering that these data include visiting faculty
members and faculty members on research or public service appointments who do not
have any instructional responsibilities, Table 3 presents information for the 1989 to 2001
period on the shares of new faculty appointments that are neither tenured nor on tenuretracks. These tabulations are for a set of 177 public and 516 private institutions that
reported data on new faculty hires each year.
Overall, the share of new full-time faculty appointments not on tenure tracks
increased from .460 to .515 at public institutions and from .452 to .573 at private
institutions in the sample during the period. Increasingly, new faculty members at 4-year
colleges and universities in the United States are being appointed to positions that are not
on tenure tracks.5
III.
The Demand for Tenure-Track and Non Tenure-Track Faculty Members
Consider an academic institution, which, for simplicity, hires only two types of
faculty members - tenure and tenure-track (FT) and non tenure-track (FN). The latter
category includes both full-time and part-time faculty members. The institution is
assumed to derive utility from its employment of each category relative to its number of
full-time equivalent enrolled students (E).
(1) U (FT/E, FN/E)
Tenured and tenure-track faculty members are important to the academic institution
because in addition to teaching, they advise students about their courses of study and
5
The Fall Staff Survey also contains information on the usage of graduate teaching and research assistants.
From 1989 to 2001, the usage of graduate assistants, relative to total full-time faculty, increased by about
20% at both private and public research and doctoral universities.
5
provide advice and letters of recommendation for postgraduate education and
employment opportunities, and they conduct research, share governance responsibilities
with the administration and the trustees and provide long-term stability to the institution.
Full-time non tenure-track faculty may be important to the institution because, absent the
responsibility to produce research, they can be assigned higher teaching loads and can
specialize in teaching. Part-time non tenure-track faculty are valuable because in areas in
which there is a large supply of people willing to work in such positions they provide the
institution with an inventory of instructors who can be hired at the last moment to meet
fluctuations in demand. In fields that deal directly with “real world” matters, such as
engineering and business, full-time employed professionals willing to teach part-time
also provide a type of specialized instruction that institutions might otherwise not be able
to offer. In a world in which revenue sources are increasingly uncertain, both types of
non tenure-track faculty members provide the academic institution with flexibility to
meet rapid changes in its financial situation that the tenure system would otherwise
constrain it from having.
Suppose that the average salary per full-time tenured and tenure-track faculty
member to the institution is ST and the average salary per non tenure-track faculty
member is SN. If the funds per full-time equivalent student that the institution has
available to employ faculty are B/E and the institution seeks to maximize its utility from
hiring faculty members subject to the constraint that the employment budget is exhausted,
then the employment demand curves (2) and (3) will result.
(2) FT/E = FT/E (ST, SN, B/E)
(3) FN/E = FN/E (ST, SN, B/E)
6
The employment of each type of faculty per full-time equivalent student will
depend upon the salaries for both types of faculty members and the funds that it has
available to employ faculty members. Other factors held constant, when a faculty type’s
average salary level rises, an institution will hire fewer of that type of faculty member
and, if its demand for that type of faculty members is elastic (with respect to the faculty
type’s average salary), it will also substitute more faculty members of the other type. An
increase in the per full-time equivalent student faculty employment budget will lead to an
increase in both types of faculty members per full-time equivalent student if both types of
faculty members are “normal goods” in the institution’s utility function. One might
conjecture that institutions that do not have a strong research component in their faculty
members’ portfolio of responsibilities would treat both tenured and tenure-track faculty
and non-tenure-track faculty as normal goods. However, institutions that highly value
research might treat non tenure-track faculty as “inferior goods” and employ fewer of
them as their faculty employment budget expands.
In this section, we employ 9 years of institutional level data that span the fall 1989
to fall 1997 period to estimate variants of equations (2) and (3) for a national sample of 4year colleges and universities. Because no information is available to us on the salaries
paid to part-time faculty members, we confine our attention only to the employment of
full-time faculty members. Initially, we treat all professorial level faculty (professors,
associate professors and assistant professors) as tenured and tenure-track faculty, all
lecturers as non tenure-track faculty and exclude instructors from the analyses.6 These
assumptions allow us to easily compute average faculty salary variables for tenured and
6
We exclude instructors initially because nationally over 15% of them at Research I and Research II
institutions and 25 to 30% of them at other institutions are tenured or on tenure-track lines.
7
tenure-track and for non tenure-track faculty members at each institution; however,
nationally a small percentage of professorial faculty are actually not on tenure-track lines
and a small percentage of lecturers are tenured or on tenure-track lines. Hence, we relax
these assumptions below and also include instructors in the analyses.
Table 4 provides estimates of four different specifications of models based upon
equations (2) and (3). All are estimated in logarithmic form and include institutional level
fixed effects to control for differences in the nature of the curriculum, the research
intensity of the institution, and other omitted forces that might influence the usage of
different types of faculty members. Inasmuch as the funds available to employ faculty
depends upon the revenues coming into the institution, in each equation we replace the
per full-time equivalent student faculty employment budget of an institution by its
revenues per full-time equivalent student that are available to hire faculty members.7
Panel A provides a baseline estimates. The elasticities of both professorial faculty
and lecturers with respect to revenue per student are both close to unity. Professorial
faculty members’ employment is very sensitive to their own salaries, with an elasticity of
about minus one, but is insensitive to the salary levels of lecturers. In contrast, lecturers’
employment levels are inelastically related to their own salary level and negatively
related to the salary levels of professorial faculty. As we shall show, the latter result does
not continue to hold in models that allow for lagged adjustment of faculty employment
levels to faculty salary levels.
Panel B presents similar estimates for equations that also include year fixedeffects. The latter are included to control for omitted variables that may vary
7
The latter is computed as the total institutional revenue (including tuition and fees, appropriation, grants
and contracts, sales and services, and other sources) minus the funding for Pell grants that the institution
receives from the federal government.
8
systematically over time and influence the demand for faculty members. For example, in
years in which students’ financial need is high, colleges and universities may have to use
more funds for institutional grant aid and thus have fewer resources available to employ
faculty members. While the inclusion of the year fixed-effects marginally reduces the
magnitudes (in absolute value) of the salary elasticities, in the main the results are similar
to those in panel A.
The estimates in panels A and B assume that faculty employment levels adjust
instantaneously to changes in faculty salaries; however, there may be lags in the
adjustment process due to the presence of tenured faculty members and tenure-track and
non tenure-track faculty members who are on multi-year contracts. To allow for lagged
adjustment, panels C and D present estimates of partial adjustment models that included
lagged (one year) values of the logarithm of the faculty category’s employment level as
an additional explanatory variable.8 These models are estimated using dynamic
estimation methods that control for the endogeneity of the lagged dependent variables.9
The coefficient of the lagged dependent variable in the professorial employment
equation is very close to zero, suggesting an almost immediate adjustment of tenure and
tenure track faculty employment levels to changes in their salary levels. This implies that
normal voluntary turnover creates sufficient vacancies each year that adjustment to new
desired employment levels can rapidly occur, even when desired employment levels are
falling. In contrast, there is evidence of somewhat slower adjustment in the demand for
8
Let (FT/E)* be the equilibrium level of tenured and tenure-track faculty per student for an institution in
year t that results from equation (2) in the text. The partial adjustment model specifies that
(FT/E)t – (FT/E)t-1 = k((FT/E)t – (FT/E)t-1), where k is the adjustment coefficient. If k equals one, then full
adjustment occurs in one year. If k is less than one, adjustment to equilibrium is only partial in a year. This
model leads to an equation similar to (2), save that the lagged value of tenured and tenure-track
employment per student also appears on the right-hand side and this variable’s coefficient is equal to one
minus k. A similar equation is specified for non tenure-track faculty.
9
See Manuel Arellano and Stephen Bond (1991).
9
non tenure-track faculty members.10 Moreover, once we allow for lagged adjustment, the
own salary elasticities of demand for both tenure and tenure-track faculty members on the
one hand, and non tenure-track faculty members on the other hand, become inelastic. In
addition, higher salaries for tenured and tenure-track faculty now are seen to lead to an
increase in the employment of non tenure-track faculty.11
The estimated coefficients in Table 4 come from models in which all professorial
faculty are assumed to be tenure or tenure track and all lecturers are assumed to be non
tenure-track. In actuality there is a small percentage of non tenure-track faculty members
in the professorial groups, a small percentage of tenured and tenure-track faculty
members in the lecturer group and instructors, excluded from the analyses in Table 4, are
in both groups. It is straightforward for us to accurately compute the employment of
tenured and tenure-track faculty members at each institution and the employment of non
tenure-track faculty members at each institution from the Faculty Salary Survey data.
However, additional assumptions must be made to enable us to obtain estimates of the
average salaries of the two different types of faculty at each institution. Specifically, we
assume that the average salary of non tenure-track faculty at each rank at an institution is
a multiple of the average salary of tenure and tenure-track faculty at the rank at the
institution. This multiple is allowed to vary across institutions and over time but is
assumed to be constant across ranks at an institution at a point in time. 12
10
For example, the coefficient of about .15 on the lagged value of lecturer employment implies that about
85% of the adjustment to the new equilibrium level of lecturer’s employment occurs within the one-year
period.
11
We experimented with allowing more complex adjustment processes, such as including lagged values of
both faculty employment levels in each faculty employment equation or allowing the speed of adjustment
to equilibrium to depend upon the fraction of faculty with tenure or on tenure-tracks. However, these
extensions did not improve the fits of our models.
12
Appendix A provides details of how the average salaries of tenured and tenure-track faculty, on the one
hand, and non tenure-track faculty, on the other hand, are computed by us.
10
Making these assumptions, Table 5 presents estimate similar to those found in
Table 4 for the more accurately defined measures of tenured and tenure-track and non
tenure-track faculty. The estimated elasticities of both types of faculty employment with
respect to revenue per student are much smaller in panels A and B, than the comparable
estimates in Table 4. The own salary elasticities of demand for tenured and tenure-track
faculty are now inelastic, while those for non tenure-track faculty are unitary elastic.
Increases in tenure-track faculty salaries, holding constant non tenure-track faculty
salaries, are associated with higher non tenure-track faculty employment in these models.
Panels C and D of the table again introduce the possibility of lagged adjustment.
Again adjustment of tenured and tenure-track faculty to changes in equilibrium levels is
faster than the adjustment of non tenure-track faculty members. As in the first two panels
of the table, the own salary elasticity of demand is much larger for non tenure-track
faculty than it is for tenure-track faculty and non tenure-track faculty employment levels
are positively related to tenure track faculty salaries.
IV.
New Hire Equations
Each year the AAUP collects (but does not publish) information on the number of
continuing full-time faculty members (by rank) employed at each academic institution
that responds to the AAUP’s annual salary survey.13 Continuing faculty members in a
rank are defined as full-time faculty members who were employed at the university in the
rank in the previous year, who are still employed at the university in the current year,
regardless of their current ranks.
13
The AAUP salary survey builds on the IPEDS Faculty Salary Survey and faculty members are thus
defined in the AAUP survey as faculty members with at least some instructional responsibility.
11
If one subtracts the number of continuing faculty members at an institution in a rank
in a year from the number of faculty members in the rank in the previous year and sums
the differences across ranks, one obtains an estimate of the number of full-time vacant
faculty positions that potentially could have been filled by new faculty hires at the
institution. That is, ignoring changes in the institution’s desired faculty employment level
caused by changes in enrollments, changes in revenues, or changes in average salaries of
faculty members, this vacancy estimate tells us number of full-time faculty new hires that
are required in the year to keep full-time faculty employment at the institution constant.
While the AAUP data does not distinguish between “vacancies” that are due to the
departure of tenured and tenure-track faculty members and those that are due to the
departure of non tenure-track faculty members, it is possible to construct an estimate of
each type of vacancy by assuming that the departures of all professorial ranked faculty
members are departures of tenure and tenure-track faculty members and that the
departures of all instructors are departures of non tenure-track faculty members.14 Data
on the new hires of full-time faculty members for each institution by tenure and tenuretrack status, but not rank, is available every other year from 1989 in the Fall Staff Survey.
As noted above, full-time faculty members are defined differently in this survey than they
are in the AAUP Survey or the Faculty Salary Survey because visiting faculty members
and faculty members without instructional responsibilities are included in the Fall Staff
Survey.
With this proviso in mind, we use the new full-time faculty hire data from the Fall
Staff Survey for 1989 to 1997 to estimate equations in which the number of newly hired
14
Sadly the AAUP began collecting continuing faculty data for lecturers only in 1996, so lecturers
“vacancies” must be excluded from these analyses
12
faculty members at an institution who are on tenure or tenure-tracks on the one hand and
on non-tenure tracks on the other hand are each assumed to depend upon the number of
faculty vacancies at the institution over the period, the increase in revenue per full-time
equivalent student received by the institution, the change in its full-time equivalent
student body, the logarithm of the average salary of its tenured and tenure-track faculty
and the logarithm of the average salary of its non tenure-track faculty members. Models
are estimated that both include and exclude year fixed effects.15
The estimated coefficients from these models appear in Table 6. Turning first to the
results for new hires of tenured and tenure-track faculty members, the models that use
either the number of professorial vacancies at the institution (panels A and B) or those
that use the total number of faculty vacancies (including instructors) (panels C and D)
perform very similarly. Only a small fraction of all vacancies for full-time faculty
members in a year were filled by new hires of tenured and tenure-track faculty members
during the year. Increased revenue per student leads to increased full-time tenured and
tenure-track new hires, as does increases in the number of full-time equivalent students.
However, these variables coefficients are not always statistically significantly different
from zero and, at the margin, each increase of 100 full-time equivalent students leads to
the hiring of only about 0.2 more full-time tenured and tenure-track faculty members.
Higher average salaries for professorial faculty are associated with fewer tenured and
tenure-track faculty new hires, but this relationship is statistical significant only in the
models that exclude year effects.16
15
Institutional fixed effects are required for the reason discussed in appendix A,
As appendix A makes clear, excluding year effects imposes the restriction that the ratio of the average
salary of tenured and tenure-track faculty in a rank to the average salary of non tenure-track faculty in a
rank at an institution does not vary over time. So this is a very restrictive assumption.
16
13
Turning to the results for full-time non tenure-track new hires, non tenure-track new
hires are negatively associated with the number of instructor vacancies at an institution
and unrelated to the total number of full-time vacancies. The former result may reflect
that “vacancies” for instructors are often involuntary in nature; when the demand for
them declines, academic institutions fail to reappoint faculty members in the role, which
creates “vacancies”. Other factors held constant, the greater the number of such vacancies
the fewer the number of non tenure-track faculty appointments. Increases in revenues per
student are associated with increases in non tenure-track new hires, but changes in fulltime equivalent student employment are not. In the models that include year effects,
increases in the average salaries of tenured and tenure-track faculty members are
positively and statistically significantly associated with increases in the hiring of non
tenure-track faculty. Increases in the average salaries of non tenure-track faculty are
negatively associated with fewer full-time non tenure-track faculty hires; however this
latter relationship is never statistically significantly different from zero.
V.
Concluding Remarks
Our paper has presented evidence from a variety of sources that show that during the
decade of the 1990s the usage of full-time non tenure-track faculty and part-time faculty
continued to grow at four-year colleges and universities in the United States. Lacking
data on the salaries of part-time faculty, we could not estimate demand functions for
them. However, models of the demand for full-time faculty and for full-time faculty new
hires that we did estimate suggest, in the main, that as the salaries of full-time non-tenure
14
track faculty decline relative to the salaries of full-time tenure and tenure-track faculty,
the relative usage of full-time non tenure-track faculty will increase.
Between 1989 and 1997, the ratio of the average salary of lecturers to the average
salary of all professorial faculty members at four-colleges and universities in the United
States declined from .642 to .607 in the Faculty Salary Survey data. This suggests that
declining relative salaries of full-time non tenure-track faculty members played a role in
their increasing relative usage during the period.17 Four-year American colleges and
universities have been able to attract lecturers at salaries that have been falling relative to
their tenure track colleagues’ salaries because of the large number of PhDs available to
fill such positions in many fields. However, this does not imply that lecturers and other
full-time non tenure-track faculty members are happy in their roles and the growing
salary gap between them and their tenured and tenure-track counterparts is undoubtedly
one of the main forces leading to efforts by various unions to unionize full-time nontenure track faculty members.18 Hence, the relative cost advantage of full-time non-tenure
track faculty members may diminish in the future.
Of course parents of college age students, taxpayers more generally, state
legislators and governors and the trustees of private colleges and universities may
reasonably ask why they should be concerned about the growing use of part-time and
17
As we have discussed above, not all lecturers are non tenure-track, not all professorial faculty are on
tenured or tenure-track lines and instructors (left out of the computation of the ratio) are employed on all
three types of appointments. However, we can not more accurately estimate how the average salary of fulltime non tenure-track faculty members has changed vis-à-vis the average salary of their tenured and tenuretrack counterparts because the method we used to compute relative salaries of the two groups to conduct
the estimation that led to table 5 required us to assume that in a given year the ratio of salaries of the two
groups at an institution were constant across ranks, but varied across institutions. These ratios were treated
as unobserved institutional fixed effects that were subsumed in the more general fixed effects in our model.
18
By way of an example, in May 2003 non-tenure track faculty members at the University of Michigan
voted to create a union to represent the 1300 full-time and part-time non-tenure track faculty at the
university (Smallwood 2003).
15
full-time non tenure track faculty members. Surprisingly, very few studies have
addressed whether the increased substitution of part-time and full-time non tenure-track
faculty for tenure-track faculty at higher education institutions leads to adverse academic
outcomes for undergraduate students, such as less learning in any class, longer times to
degree, lower graduation rates, or a lower proportion of graduates going on to postgraduate study. Analyses of these issues will be essential if public institutions want to
make the case to their state legislators and governors and private academic institutions
want to make the case to their trustees that better funding would enable them to increase
their usage of tenure-track faculty members and that this would enhance undergraduate
students’ educational outcomes. 19
Finally, it is well known that the proportion of PhDs granted by U.S universities that
go to American citizens has been falling over long periods of time. In some science and
engineering fields and in economics, the proportion of PhDs granted to American citizens
is now well under 50%.20 Universities and public policy makers would do well to
contemplate what the likely affect of their increased usage of part-time and full-time non
tenure-track faculty is on the desire of American college graduates to go on to PhD study.
Put more starkly, by increasing their reliance on non tenure-track faculty, American
19
One study of community college students that randomly assigned them to sections of a remedial
mathematics course that were taught by part-time and tenure-track full-time faculty found no differences in
the amounts that student learned (Bolge 1995). Another study of a Midwestern comprehensive institution
found, using four years of data on fall entering freshman, that the greater the proportion of part-time faculty
that students had during their first semester in college, the lower the probability that they would return for
their second semester (Harrington and Schibik 2001). Studies by economists have tended to focus on how
instructor type (including graduate students) influences the amount that students learn in first-year classes
(Finegan and Siegfried 1998, Lynch and Watts, 1989) and the results vary across studies. Bettinger and
Long (2003) are using data from Ohio public 4-year colleges to study the impact of adjunct faculty (as
compared to full-time faculty regardless of tenure or tenure-track status) and their preliminary results
suggest that adjuncts do not have negative effects on undergraduate students.
20
See for example, John Siegfried and Wendy Stock (2004)
16
colleges and universities may be making PhD study a less attractive option than would
otherwise by the case.
17
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Instructional Faculty and Staff: Who They Are, What They Do, and What They Think
(Washington DC: U.S. Department of Education, 2002)
Ronald G. Ehrenberg, Michael J. Rizzo and George H. Jakubson, “Who Bears the
Growing Cost of Science at Universities?”, National Bureau of Economic Research
Working Paper 9627 (Cambridge MA: April 2003)
T. Aldrich Finegan and John J. Siegfried, “Do Introductory Economics Students
Learn More if Their Instructor Has a PhD?”, American Economist 42 (Fall 1998): 34-46
18
Charles Harrington and Timothy Schibik, “Caveat Emptor: Is There a
Relationship Between Part-Time Faculty Utilization and Student Learning Outcomes and
Retention”. Paper presented at the 41st Annual Meeting of the Association for
Institutional Research (Long Beach CA, June 2001
John J. Siegfried and Wendy A. Stock, “The Market for New PhD Economists in
2002” (paper presented at the Allied Social Science Associations Meeting, San Diego
CA, January 2004)
Scott Smallwood, “Non-Tenure-Track Faculty Members Vote to Unionize at U.
of Michigan”, Chronicle of Higher Education 49 (May 9, 2003): A15
Michael Watts and Gerald J. Lynch, “The Principles Courses Revisited”,
American Economic Review 79 (May 1989): 236 - 241
19
Table 1
Full time non-tenure track faculty / Total full time faculty
PUBLIC (sample size)
89
90
91
92
93
94
95
96
97
98
99a
Research I (59)
Research II (26)
Doctoral I (28)
Doctoral II (38)
Comprehensive I (246)
Comprehensive II (25)
Liberal Arts I (7)
Liberal Arts II (75)
Total
0.099
0.109
0.117
0.121
0.111
0.148
0.213
0.134
0.110
0.100
0.105
0.117
0.126
0.117
0.138
0.220
0.131
0.112
0.099
0.100
0.114
0.129
0.108
0.129
0.203
0.134
0.108
0.099
0.095
0.110
0.125
0.111
0.153
0.180
0.140
0.108
0.097
0.094
0.116
0.121
0.107
0.133
0.157
0.147
0.107
0.101
0.096
0.119
0.128
0.109
0.129
0.116
0.138
0.109
0.099
0.096
0.121
0.121
0.111
0.129
0.120
0.139
0.109
0.102
0.102
0.124
0.132
0.114
0.127
0.125
0.135
0.112
0.112
0.112
0.128
0.133
0.124
0.135
0.103
0.141
0.121
0.121
0.120
0.149
0.139
0.128
0.131
0.092
0.153
0.128
0.128
0.123
0.160
0.149
0.138
0.160
0.103
0.165
0.137
89
90
91
92
93
94
95
96
97
98
99a
0.124
0.065
0.092
0.123
0.146
0.186
0.109
0.226
0.142
0.173
0.083
0.105
0.096
0.171
0.258
0.102
0.244
0.165
0.148
0.078
0.107
0.107
0.165
0.253
0.095
0.250
0.158
0.171
0.089
0.102
0.102
0.182
0.265
0.097
0.259
0.169
0.167
0.095
0.088
0.141
0.190
0.260
0.098
0.275
0.175
0.159
0.108
0.161
0.123
0.181
0.215
0.099
0.284
0.176
0.166
0.113
0.141
0.090
0.189
0.223
0.102
0.275
0.176
0.172
0.118
0.154
0.107
0.193
0.223
0.109
0.277
0.182
0.151
0.121
0.163
0.115
0.203
0.225
0.115
0.288
0.184
0.156
0.128
0.180
0.132
0.193
0.233
0.119
0.295
0.187
0.154
0.127
0.194
0.141
0.221
0.226
0.130
0.306
0.197
PRIVATE (sample size)
Research I (29)
Research II (11)
Doctoral I (23)
Doctoral II (22)
Comprehensive I (180)
Comprehensive II (65)
Liberal Arts I (156)
Liberal Arts II (368)
Total
Source: National Center for Educational Statistics (NCES) IPEDS Faculty Salary Survey (available at WEBCaspar, http://caspar.nsf.gov)
a
The estimates for 1999 are based on preliminary data released by NCES
20
Table 2
Part-time faculty / Total full time faculty
PUBLIC (sample size)
Research I (50)
Research II (22)
Doctoral I (23)
Doctoral II (34)
Comprehensive I (174)
Comprehensive II (10)
Liberal Arts I (2)
Liberal Arts II (37)
Total
89
0.211
0.153
0.304
0.335
0.350
0.372
*
0.484
0.269
91
0.195
0.214
0.316
0.234
0.352
0.387
*
0.558
0.263
93
0.229
0.175
0.364
0.329
0.397
0.383
*
0.611
0.298
95
0.222
0.197
0.358
0.380
0.415
0.373
*
0.658
0.306
97
0.285
0.201
0.348
0.407
0.454
0.456
*
0.674
0.347
99a
0.268
0.224
0.394
0.455
0.478
0.557
*
0.667
0.365
01a
0.260
0.219
0.352
0.503
0.541
0.484
*
0.631
0.377
PRIVATE (sample size)
Research I (22) b
Research II (8) c
Doctoral I (12)
Doctoral II (13)
Comprehensive I (109)
Comprehensive II (36)
Liberal Arts I (111)
Liberal Arts II (172)
Total
89
0.215
0.430
0.792
0.551
0.909
0.708
0.309
0.685
0.499
91
0.300
0.351
0.631
0.634
0.882
0.745
0.330
0.766
0.532
93
0.387
0.410
0.694
0.633
0.945
1.083
0.367
0.852
0.599
95
0.440
0.418
0.702
0.780
1.032
1.116
0.349
0.887
0.643
97
0.494
0.406
1.043
0.816
1.016
1.239
0.391
0.947
0.697
99a
0.329
0.464
1.127
0.643
1.045
0.903
0.320
0.788
0.622
01a
0.416
0.420
0.923
0.643
1.186
0.949
0.358
0.885
0.686
Source: National Center for Educational Statistics, IPEDS Fall Staff Survey
a
The numbers for 1999 and 2001 are from preliminary data released by the NCES
* Proportions not reported because of the small sample size
21
Table 3
Non-tenured new hires / Total new hires
PUBLIC (sample size)
Research I (53)
Research II (25)
Doctoral I (22)
Doctoral II (31)
Comprehensive I (191)
Comprehensive II (17)
Liberal Arts I (3)
Liberal Arts II (41)
Total
PRIVATE (sample size)
Research I (25)
Research II (10)
Doctoral I (16)
Doctoral II (13)
Comprehensive I (117)
Comprehensive II (39)
Liberal Arts I (119)
Liberal Arts II (177)
Total
89
91
93
95
97
0.543
0.411
0.481
0.377
0.395
0.410
0.449
0.404
0.546
0.372
0.565
0.418
0.382
0.357
0.577
0.398
0.575
0.501
0.495
0.509
0.410
0.385
0.559
0.393
0.558
0.475
0.461
0.516
0.410
0.314
0.382
0.450
0.622
0.545
0.495
0.536
0.429
0.415
0.531
0.411
0.460
0.460
0.494
0.485
0.529
89
91
93
95
97
0.636
0.409
0.528
0.328
0.351
0.310
0.427
0.281
0.452
0.594
0.511
0.466
0.324
0.476
0.351
0.447
0.302
0.473
0.630
0.536
0.562
0.456
0.416
0.477
0.494
0.386
0.503
0.602
0.459
0.568
0.588
0.507
0.451
0.508
0.360
0.518
0.708
0.460
0.528
0.416
0.418
0.359
0.556
0.405
0.526
Source: National Center for Education Statistics, IPEDS Fall Staff Survey
a
The numbers for 1999 and 2001 are from preliminary data released by NCES
22
99a
0.684
0.524
0.564
0.505
0.435
0.488
0.339
0.435
0.565
01a
0.573
0.523
0.514
0.502
0.429
0.532
0.451
0.566
0.515
99a
0.656
0.457
0.413
0.452
0.526
0.441
0.563
0.448
0.542
01a
0.700
0.423
0.641
0.499
0.461
0.443
0.583
0.547
0.573
Table 4
Logarithmic Faculty Demand Functions Estimates: Instructors Excludeda
(t statistics in parentheses)
Log (All Professorial
Faculty per Student)
Log (Lecturers per
Student)
A) Without year effects
Log (Ave. All Prof. Faculty Salary)
Log (Ave. Lecturer Salary)
Log (Revenue Per Student)
R2
N
-1.0667 (-27.27)
0.0154 (0.64)
0.8216 (58.55)
0.9428
2019
-0.7244 (-5.65)
-0.1933 (-2.48)
0.8375 (18.23)
0.9109
2019
B) With year effects
Log (Ave. All Prof. Faculty Salary)
Log (Ave. Lecturer Salary)
Log (Revenue Per Student)
R2
N
-0.9645 (-22.89)
0.0157 (0.67)
0.8409 (59.6)
0.9449
2019
-0.5435 (-3.88)
-0.1853 (-2.38)
0.8586 (18.32)
0.9117
2019
C) Without year effects
Lagged Dependent Variable
Log (Ave. All Prof. Faculty Salary)
Log (Ave. Lecturer Salary)
Log (Revenue Per Student)
Wald chi2
N
0.0430
-0.2291
-0.0041
0.6659
459
1326
(2.23)
(-3.08)
(-0.20)
(21.09)
0.1461
0.6330
-0.1911
0.5510
43
1291
(4.07)
(1.99)
(-2.21)
(4.09)
D) With year effects
Lagged Dependent Variable
Log (Ave. All Prof. Faculty Salary)
Log (Ave. Lecturer Salary)
Log (Revenue Per Student)
Wald chi2
N
0.0079
-0.2986
-0.0011
0.6561
480
1326
(0.46)
(-4.08)
(-0.06)
(21.27)
0.1527
0.6437
-0.1856
0.5670
51
1291
(4.31)
(2.00)
(-2.15)
(4.19)
a
All professorial faculty are considered tenured and tenure-track faculty and all lecturers are
considered non tenure-track faculty. Instructors are excluded from the analyses
23
Table 5
Logarithmic Faculty Demand Functions: Tenure-Track Status Correctly Assigned
(t statistics are in parentheses)
Log (Tenure & tenure
track per Student)
Log (non-tenured per
Student)
A) Without year effects
Log (Ave.Ten and Ten-Track Fac. Sal.)
Log (Ave Non Ten-Track Fac. Sal.)
Log (Revenue Per Student.
R2
N
-0.1791 (-5.26)
0.0198 (0.75)
0.2482 (17.48)
0.9166
7654
0.9869 (11.12)
-1.0508 (-15.24)
0.3157 (8.52)
0.8012
7654
B) With year effects
Log (Ave.Ten and Ten-Track Fac. Sal.)
Log (Ave. Non Ten-Track Fac. Sal.)
Log (Revenue Per Student)
R2
N
-0.0748 (-2.1)
0.0222 (0.85)
0.2921 (19.63)
0.9179
7654
1.1071 (11.86)
-1.0438 (-15.17)
0.3620 (9.28)
0.8024
7654
C) Without year effects
Lagged Dependent Variable
Log (Ave.Ten. and Ten-Track Fac. Sal)
Log (Ave. Non Ten-Track Fac. Sal.)
Log (Revenue Per Student)
Wald chi2
N
0.0809
-0.0797
-0.0416
0.3831
227
5224
(2.00)
(-1.48)
(-1.53)
(14.89)
0.3314
2.0236
-0.8309
0.3157
311
5061
(12.57)
(11.21)
(-8.92)
(3.76)
D) With year effects
Lagged Dependent Variable
Log (Ave.Ten and Ten-Track. Fac. Sal)
Log (Ave.Non. Ten-Track Fac. Sal.)
Log (Revenue Per Student)
Wald chi2
N
0.1280
-0.0979
-0.0415
0.3920
248
5224
(3.27)
(-1.79)
(-1.50)
(14.99)
0.3317
2.0331
-0.8373
0.3299
347
5061
(12.82)
(11.27)
(-9.01)
(3.92)
24
Table 6
Full-Time Faculty New Hire Equationsa
(t statistics are in parentheses)
New hire tenure & tenure New hire non-tenure track
track faculty
faculty
A) without year effects
Professorial vacancies
Instructor vacancies
Revenue change per FTE in 1,000
FTE change in 100
Log (Ave Ten. and Ten-Track Fac. Sal.)
Log (Ave. Non Tenure-Track Fac. Sal.)
R2
N
a
0.0440 (2.32)
0.2322
0.2126
-14.6044
2.1517
0.8436
1868
(1.35)
(2.13)
(-2.75)
(0.58)
-0.2814
0.4921
0.0523
6.4247
-2.1235
0.8365
1868
(-2.6)
(2.06)
(0.38)
(0.87)
(-0.41)
-0.2923
0.5162
0.0461
32.8974
-1.3754
0.8375
1868
(-2.7)
(2.14)
(0.33)
(2.42)
(-0.27)
B) with year effects
Professorial vacancies
Instructor vacancies
Revenue change per FTE in 1,000
FTE change in 100
Log (Ave Ten. and Ten-Track Fac. Sal.)
Log (Ave. Non Tenure-Track Fac. Sal.)
R2
N
0.1901
0.1744
-1.3842
2.6754
0.8443
1868
(1.09)
(1.72)
(-0.14)
(0.72)
C) Without year effects
Total vacancies
Revenue change per FTE in 1,000
FTE change in 100
Log (Ave Ten. and Ten-Track Fac. Sal)
Log (Ave. Non Tenure-Track Fac. Sal)
R2
N
0.0315
0.2242
0.2155
-14.4818
2.2026
0.8432
1868
(1.8)
(1.3)
(2.16)
(-2.73)
(0.6)
-0.0098
0.4744
0.0722
7.8810
-2.0518
0.8354
1868
(-0.4)
(1.98)
(0.52)
(1.07)
(-0.4)
D) With year effects
Total vacancies
Revenue change per FTE in 1,000
FTE change in 100
Log (Ave Ten. and Ten-Track Fac. Sal)
Log (Ave Non tenure Track Fac. Sal.)
R2
N
0.0275
0.1808
0.1762
-1.3129
2.7293
0.8440
1868
(1.57)
(1.04)
(1.73)
(-0.13)
(0.74)
-0.0091
0.5025
0.0712
32.5641
-1.3725
0.8363
1868
(-0.37)
(2.08)
(0.5)
(2.39)
(-0.27)
0.0403 (2.11)
Institutional Fixed Effects are included in each equation
25
Appendix Table 1
Full time non-tenure track faculty / Total full time faculty,
PUBLIC (sample size)
89
91
93
95
97
99a
01a
Research I (53)
Research II (25)
Doctoral I (27)
Doctoral II (34)
Comprehensive I (229)
Comprehensive II (21)
Liberal Arts I (4)
Liberal Arts II (61)
Total
0.245
0.183
0.160
0.176
0.133
0.181
0.134
0.213
0.191
0.253
0.171
0.193
0.176
0.133
0.141
0.110
0.211
0.194
0.263
0.179
0.191
0.200
0.132
0.132
0.140
0.187
0.201
0.286
0.192
0.202
0.206
0.129
0.119
0.125
0.202
0.212
0.332
0.233
0.213
0.212
0.141
0.146
0.117
0.195
0.241
0.356
0.244
0.235
0.226
0.153
0.182
0.109
0.223
0.260
0.375
0.274
0.237
0.240
0.179
0.199
0.121
0.242
0.281
89
91
93
95
97
99a
01a
0.312
0.173
0.233
0.132
0.188
0.207
0.155
0.287
0.235
0.358
0.165
0.193
0.122
0.197
0.199
0.158
0.294
0.248
0.344
0.186
0.231
0.153
0.195
0.216
0.149
0.297
0.250
0.335
0.180
0.212
0.137
0.207
0.227
0.149
0.292
0.248
0.410
0.196
0.234
0.144
0.212
0.220
0.154
0.286
0.275
0.432
0.222
0.256
0.159
0.242
0.239
0.173
0.321
0.301
0.434
0.230
0.274
0.191
0.254
0.230
0.183
0.328
0.309
PRIVATE (sample size)
Research I (26)
Research II (11)
Doctoral I (19)
Doctoral II (15)
Comprehensive I (164)
Comprehensive II (58)
Liberal Arts I (149)
Liberal Arts II (319)
Total
Source: National Center for Education Statistics, IPEDS Fall Staff Survey
a
The numbers for 1999 and 2001 are from the preliminary data released by NCES.
26
Appendix A
Let Fijt be the number of faculty members of rank i at institution j in year t. Let
fijt be the fraction of faculty members of rank i at institution j in year t that have tenured
or tenure-track appointments. Finally, let Sijt be the average salary of faculty members of
rank i at institution j in year t. Then the number of faculty members at institution j with
tenured or tenure track appointments in year t is simply the sum over all ranks (i) of Fijtfijt
and the number of faculty members on non tenure-track appointments is simply the sum
over all ranks (i) of Fijt(1-fijt). Each of these sums can be directly calculated from the
Faculty Salary Survey data. Put another way, we know from the data the number of
tenured and tenure-track and the number of non tenure-track faculty members at each
institution in each year.
We know the average salary of faculty members of each rank at each institution in
each year. We do not have information on the average salary of faculty members at each
rank in each year by tenure-track status. However, if an estimate of these numbers can be
obtained if one is willing to assume that the average salary of tenured and tenure track
faculty at a rank is a constant multiple of the average salary of non tenure-track faculty at
the rank. This multiple is assumed to be constant across ranks at a given institution over
time but is allowed to vary over time. That is, letting the subscript T represent tenured
and tenure-track faculty and the subscript N non tenure-track faculty, we assume
(A1) SijtT = mjtSitjN
and
(A2) mjt= bidt.
27
It immediately follows that the average salary of tenure and tenure track faculty
members across all ranks at institution i at time t (SitT) is given by the sum across all
ranks of SijtbidtFijtfijt divided by total tenured and tenure track faculty employment at the
institution. The average salary of non tenure-track faculty members at the institutions is
similarly calculated by replacing the fijt by (1 – fijt) in the expression above All of the
variables in each of these two expressions are known numbers save for bi and dt which are
treated as parameters that vary across institutions and over years. When one takes the
logarithm of each average salary expression, as is done when we estimate logarithmic
demand equations (table 5) and new hire equations (table 6), the logarithm of each
average salary is equal to the sum of the logarithm of a known number and the logarithms
of an institutional and a year effect. Hence the bi and dt are subsumed in the institutional
and time fixed effects.
28
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