Jerome Freiberg, Chair Alex Ignatiev
William Douglas Ruth Manny
Joseph Eichberg Cary Nathenson
Elizabeth Anderson Fletcher Carlos Pedemonte
Osman Ghazzaly Dale Rude
Wyman Herendeen
Context of the report:
The Faculty Affairs Committee of the Faculty Senate began meeting under
the direction of Jerry Freiberg in February, 1999 to identify issues common
to all faculty on campus. An all day retreat was held to narrow the
number of issues and determine priorities. Faculty compensation was
one issue that was identified. Under the umbrella of faculty compensation
the following areas were studied: retirement (including VMOE, contributions
to retirement programs and benefits upon retirement), and salary compression.
This report on salary compression is the first from the 1999 Faculty Affairs
Committee. Other reports on compensation as well as the institutional
environment for research and institutional priorities are expected to follow.
Acknowledgments:
The analyses were based on data provided by Barbara Fasser and staff
in the Office of the Provost.
Resource person: Steve Werner, College of Business.
Critical Readings of Early Drafts: Jerry Freiberg, College of
Education and Dale Rude, College of Business.
Salary compression is the narrowing of the
pay differentials between people in the same job or between people in different
(usually adjacent) jobs in an organizational hierarchy over time.
This narrowing of the pay differential may be either a perception of inequity
(subjective compression) or a true salary compression (objective compression).
While most faculty at the University of Houston have the perception that
salary compression is present (subjective compression) there has been no
recent systematic investigation of the problem by the faculty to determine
if salary compression (objective compression) is actually present at the
University of Houston.
In this report two different analyses, a modification
of the within class data analysis and the rank ratio method, are used to
explore the possibility that objective salary compression may be present
at the University of Houston. The analyses used data obtained from
the office of the Provost and are based on the monthly salary of tenure
track faculty for fiscal year 2000 current as of September 15, 1999.
Administrative stipends are not included.
Both the within class data analysis and the
rank ratio method show clear indications of salary compression. Salary
compression appears to be widespread affecting most colleges and departments
at the University of Houston. Recommendations to reduce salary compression
include: increasing the recent centrally funded merit increments tied to
promotions; expanding the funds available for merit based equity; continue
with the current policy of exploring counter offers with faculty; appoint
a task force to examine opportunities for progressive employee benefits
and salary stagnation as it relates to the private sector and comparable
universities; and establish a central University wide system/database (which
includes years at a given rank) to monitor salary compression and report
the outcome to the faculty every 3 years.
I. Background
Definitions
Salary compression is "the narrowing over time
of the pay differentials between people in the same job or between people
in different (usually adjacent) jobs in an organizational hierarchy" (Bereman
and Lengnick-Hall, 1994). This narrowing of the pay differential
may be either a perception of inequity (subjective compression) or true
salary compression may be present within the organization (objective compression).
According to Gomez-Mejia and Balkin, (1987) the perception of equity or
the salary one feels they deserve is based on both merit and seniority.
Since there is both an objective and subjective component to salary compression,
Bereman and Lengnick-Hall (1994) propose three different scenarios as these
two components are viewed together. In the first scenario, objective
pay compression is present and the personnel are aware of the compression
and perceive an inequity. This scenario is most likely to occur where
employees have access to salary information as they do at the University
of Houston and other public institutions. It is also possible that
an objective or true compression may be present but the personnel are either
not aware of it or do not view the compression as inequitable. This
case is most often present in organizations where the pay systems are not
available to the employees and hence, they are not aware of any inequity.
In this case, pay compression is not problematic for the personnel within
the organization since there is no perception of inequality. In the
last scenario, the employees believe salary compression is present but
their perception is not supported by the presence of true or objective
salary compression. Based on their access to the budget, most faculty
at the University of Houston probably believe salary compression is present
(subjective compression). However, there has been no recent systematic
investigation of the problem by the faculty to determine if salary compression
(objective compression) is actually present at the University of Houston.
This question will be explored in section II of this report.
An extreme form of salary compression is salary
inversion. Salary inversion refers to the condition where a new junior
person is hired at a salary that exceeds that of a senior person at a higher
rank within the organization (e.g. an assistant professor whose salary
exceeds that of an associate professor). Inversion has been reported
to be as high as 25% in a few high-demand fields in academia (Bereman and
Lengnick-Hall, 1994).
It is also important to recognize that salary
compression is not the same as salary inequity. Salary compression
and even inversion may occur when a faculty member consistently receives
a less than average raise over the course of many years and the salary
then falls behind his or her colleagues in the same rank or in lower ranks
who receive well above average increments. This form of salary compression
may not be inequitable but a reflection of an average full professor compared
to an outstanding associate professor. In this case subjective compression
may be present but true compression may not be present.
Factors contributing to salary compression
Although salary compression is a multi-faceted
problem, several factors have been identified as contributors to true compression.
When there is low unemployment in the market place, the imbalance between
qualified people available to fill positions and the demand for quality
faculty forces the university to pay high salaries to attract the limited
number of qualified applicants. This factor will have the greatest
impact on those fields most vulnerable to outside offers. The strong
Houston economy and that of the United States has created the potential
for this to be a significant factor in salary compression at the University
of Houston.
Limited funds for faculty salaries can also
impact the salary structure within the University. When funds are
limited, often the scarce resources must be used to attract newly trained
faculty particularly when the University is understaffed. When the
limited funds are used to attract new faculty, compression at the associate
and full professor levels may result, particularly when a demand/supply
imbalance is present. Table 1, complied with the assistance of Barbara
Fasser and her office staff in the Office of the Provost, summarizes the
funds available from the state legislature for faculty increments at the
University of Houston since 1990.
TABLE 1 - Increment Pool Available for Faculty Raises
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Salary compression is also exacerbated by the
university's academic rank structure. Tenured faculty in the higher
academic ranks typically have fewer options and offers (Gomez-Mejia and
Balkin 1987) to move to other universities to overcome salary compression.
Often these faculty wish to retain tenure, may have other personnel working
in their labs which can complicate a move and have greater demands for
space and other institutional resources that prohibit other financially
strapped institutions from attracting these established faculty.
This decreased mobility in the higher ranks can compound the problem of
salary compression across ranks.
There are also several factors at the University
of Houston, which extend across all disciplines and could contribute to
salary compression. Under a previous administration, there was a
policy that no counter offers would be made to faculty at the University
of Houston who received offers from other institutions. While the
actual impact of this policy on salary compression at the University of
Houston is not known, two possible scenarios are presented. A no
counter offer policy would prevent established faculty from receiving significant
salary increments if they remained at the University. These larger
increments in the form of counter offers would have the potential of offsetting
salary compression particularly for quality faculty at the associate and
full professor levels. The no counter offer policy could also result
in a significant exodus of the qualified faculty who would be replaced
by junior faculty hired at high salaries resulting in further compression
of those faculty who remain. This last possibility would be compounded
by the demand/supply imbalance mentioned earlier.
Previously at the University of Houston,
there was no central policy or funds for increments tied to promotions
and/or tenure. Without specific increments tied to promotions, salary
differentials between the academic ranks have an increased potential for
erosion. When faculty are promoted in years when funds from the legislature
are minimal, (for example: 1994 - 0.7 % merit pool or 1995 % - 0.2% merit
pool), the problem is magnified.
Singleton (1990) has pointed out that
traditional merit increases often do not adequately differentiate the contributions
of individual faculty. Frequently merit increases for adequate performers
are just a few percentage points less than those for outstanding performers.
The problem is magnified when the increment pool is small as it has been
for many years at the University of Houston (see Table 1).
Potential problems created by salary compression
Several consequences may occur when salary
compression is present in an organization. Perceived or real pay
inequities can result in poor faculty morale (Bergman, Hills, Priefert
1983; Lawther 1989; Bowen and Schuster as cited by Berman and Lengnick-Hall
1994). Poor morale can lead to a lack of pride in the institution.
This lack of pride can carry over to the community and the community's
perception of the institution when faculty feel they are undervalued.
If this feeling is widespread, it could be particularly troubling for an
urban university such as the University of Houston, wishing to increase
its community-based support.
The hiring of new faculty can increase salary
compression and salary compression can hinder the hiring of qualified new
faculty. Gomez-Mejia and Balkin (1987) reported that the majority
of new faculty hires in business colleges occurs at the assistant professor
level. At the University of Houston about 45% of those faculty hired
within the last 8 years have been at the assistant level (See Table 2).
To counter the labor market, particularly in high demand fields, junior
faculty are often offered salaries above the generally-accepted salary
ranges and in some fields at a level that is above the senior faculty in
the same department (salary inversion) (Bereman and Lengnick-Hall, 1994).
When a university's tight budget is directed towards attracting new junior
faculty, resources to prevent salary compression in the higher academic
ranks are just not available. The limited merit increases are not
sufficient to keep pace with the supply and demand imbalances in many of
the disciplines. If the University of Houston implements plans to
increase the number of faculty over the next several years, salary compression
is likely to increase if salaries higher than those of qualified high performing
current faculty are necessary to attract the best new faculty. If
these higher salaries are not offered in an effort to keep salary compression
in check, the hiring may fall short of projected goals or the ability to
attract the most qualified faculty could be compromised.
Another reported outcome of salary compression
is a reduction in the performance level (Lawther 1989, Singleton 1990).
Lowered performance occurs as faculty seek to restore perceptions of equity
by lowering work inputs (effort, time spent on the job, etc.). According
to Singleton (1989), the fact that pay decisions affect productivity, cost
containment, employee turnover, and even employee skills development has
gained increased recognition. It might be interesting to review the
outcome of the post-tenure review process in light of salary compression
to determine if reduced performance is associated with salary compression.
Methods used to detect salary compression
According to Lawther (1989) pay compression
is identified by examining trends in salary inequities that may be present
within various classes or ranges. There have been several methods
used to examine a pay structure for salary compression. In the merit
based system present at the University of Houston and other academic institutions
a modification of the within class analysis (Lawther, 1989) and the rank
ratio method (Bereman, Lengnick-Hall 1994) appear to be the most appropriate.
The within class data analysis examines the
personnel within selected departments. In this analysis, a matrix
is constructed with years of service placed in the rows (ascending order)
and salary ranges in the columns (ascending order). If no salary
compression is present then the majority of employees should fall on the
major diagonal of the matrix. A large number of faculty to the right
of the major diagonal could suggest a shift in the demand/supply with higher
salaries needed to attract the best candidates and faculty on the diagonal
on that same row could be casualties of salary compression. A large
number of faculty falling to the left of the major diagonal could also
suggest salary compression or salary stagnation. However, those faculty
to the left of the diagonal could also be among the poorest performers
and may not be victims of salary compression. Thus, poor performance
may confound the interpretation of faculty falling to the left of the diagonal.
A modification of this method is used to examine salary compression at
the University of Houston in Table 2 (section IIA, pages 8 & 9).
The rank ratio method (Bereman, Lengnick-Hall
1994) compares the salary differential between the various academic ranks
within a discipline. By calculating the rank ratio for each discipline,
college or department, comparisons across disciplines may be made without
comparing absolute dollar amounts. The rank ratio expresses each
rank's average salary as a percentage of the average salary of full professors
(Bereman, Lengnick-Hall 1994). For example "a ratio of 100:75:62:59
indicates that associate professors are earning 75% of professor salaries,
assistant professors are earning 62%, and newly hired assistants are earning
59% of professor salaries" (Bereman, and Lengnick-Hall 1994). Since
salary compression has both an objective and subjective component, the
ideal ratio between ranks or the ratio that would be viewed as equitable
is subject to debate. Thomas Mahoney as cited by Gomes-Mejia, and
Balkin (1987, p47) has argued that in academia compensation differentials
require about a 33% difference between the ranks, a ratio of 100:67:33,
to be viewed as equitable. In section IIB of this report (pages 9-15),
the rank ratio method is used to examine the pay scales at University of
Houston for salary compression. Since the ideal ratio is subject
to debate, Table 3 presents data from the University of Houston, and Table
4 presents data from other universities located in the 10 most populated
states for comparison.
II. Analysis of Salaries at the University of Houston
The Office of the Provost supplied the data
for the analyses. Specifically Barbara Fasser and her office staff
compiled the salary information from data supplied by the MIS Department
from the Human Resources System (HRS) and data from a CB8 report on faculty
rank from the Office of Planning and Policy Analysis. The data consisted
of a list of faculty by college, department and rank that included the
number of years employed at the University of Houston, their monthly salary
and the average monthly salary of all other faculty at that rank within
the same college department. This information was then analyzed using
two of the models discussed above.
To put this information in context the following
issues should be recognized:
1. Salaries for fiscal year 2000 were requested. The salary information is reported to be currentIn an effort to make comparisons more similar and avoid problems which are created by contracts of different length (9- versus 12-month contracts) the analysis was based on monthly salaries.
as of September 15, 1999. Changes made in the database after September 15, 1999 are not
reflected in the data. Salaries of 736 tenure track faculty were provided.2. Information regarding faculty rank prior to the Fall 1989 is not available. Therefore faculty
with more than 10 years at a given rank were listed as 10 years in the information received
from the Office of the Provost. This limitation prohibits an accurate and detailed analysis
of professors and associate professors by years of service within these ranks. However,
the total number of years of employment at the University of Houston was available and
used in the analysis.3. The analyses are based only on tenure track faculty. Information on faculty in non-tenure
track positions was not included. Some colleges have a large number of faculty in
non-tenure track positions which could significantly alter the picture presented within
these colleges.
a. The full-time equivalent for the College of Architecture is 0.75.A. Within Class Analysisb. The 11 month salaries within the College of Pharmacy are paid over a 12 month period.
c. Most faculty in the College of Optometry have 12 month appointments.
d. Some faculty with administrative assignments are paid over a 12 month period.
e. Administrative stipends were not included in the monthly salaries.
f. The figures supplied by the Office of the Provost were not verified except in one case
that appeared to be an outlier. The salary in the report was twice the actual salary due
to a split appointment between two colleges or departments. There may be other errors
in the data that were not detected.g. Summaries by years of service provided by the Office of the Provost did not always
match the overall composite. Therefore these summaries were not used and data used
for this report was taken only from the overall composite.
Tenure track faculty with less than 9
years of service were divided into 4 categories based on their years of
service at the University of Houston. The salary for each faculty
was compared to all other faculty within the same college at the same rank
(professor, associate professor, assistant professor, instructor) and placed
in one of four quartiles. There were 2 cases where the highest paid faculty
within a rank containing faculty with less than 9 years of employment,
earned more than twice the next highest paid faculty within that same rank.
In these two cases the highest salary was taken as the second highest within
that rank when the quartiles were calculated under the assumption that
the highest paid in that rank was an exceptional performer or outlier.
Table 2 displays the percentage of faculty within each years of service
category falling within each salary quartile. When there were less
than three faculty within the college at a given rank none were included.
Applying this exclusion criteria 31 faculty employed 8 years or less were
omitted from analysis. It should be emphasized that Table 2 includes
faculty at all ranks and that only 83 of the185 faculty (44.9%) represented
in Table 2 are at the assistant professor rank. Salaries of 551 faculty
employed more than 8 years are not included in this analysis.
TABLE 2 - Modified Within Class Analysis
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B. Rank Ratio Analysis
As described by Bereman, Lengnick-Hall (1994), the
rank ratio expresses each rank's average salary as a percentage of the
average salary of full professors within the same department. Using
this analysis, each department within a college can be examined to determine
the extent of salary difference present between the academic ranks.
A small difference between the ranks is suggestive of salary compression.
Table 3 displays the rank ratio calculated for each department at the University
of Houston. For each department the mean salary of the full professors
was set to 100. The mean salary for associate professors, assistant
professors and instructors was then expressed as a percentage of the full
professor's salary within the same department. Setting the mean full
professor's salary to 100 permits comparisons across departments and ranks
but does not imply this is the ideal salary for that department and rank.
Of the 736 salaries supplied, 33 were omitted from this analysis.
Omissions include faculty listed in institutes, honors colleges and other
faculty with no comparisons at neighboring ranks.
TABLE 3 - Rank Ratio Method
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| ARCHITECTURE | 100:80:75:53 | |
| BUSINESS ADMINISTRATION | ||
| Accounting & Taxation | 100:83:81 | |
| Finance | 100:76:78 | Only 1 Assoc. Professor |
| Management | 100:71:65 | |
| Marketing | 100:XX:63 | XX = no Assoc. Prof. listed |
| Decision and Information | 100:79:63 | Only 1 Asst. Professor |
| EDUCATION | ||
| Educational Leadership & Cul | 100:82:81 | |
| Curriculum & Instruction | 100:62:55 | |
| Educational Psychology | 100:60:54 | |
| Health & Human Performance | 100:57:51:38 | Only 1 instructor |
| ENGINEERING | ||
| Chemical | 100:79:64 | Only 1 Asst. Professor |
| Civil | 100:62:61 | |
| Electrical | 100:82:78 | |
| Industrial | 100:108:98 | Small #'s: 2 Prof., 3 Assoc.,
1 Asst. Prof. |
| Mechanical | 100:71:XX | XX = no Assist. Prof. listed |
| HOTEL & RESTAURANT MNG | 100:69:56 | |
| HUMANITIES & FINE ARTS | ||
| Art | 100:75:63 | |
| Communication | 100:75:67 | |
| Theatre | 100:35:34 | Small #s: 2 Prof. |
| English | 100:63:45:43 | Only 1 instructor |
| Communications Disorders | 100:XX:43 | XX = no Assoc. Prof. |
| Modern & Classical Lang | 100:59:51 | |
| LAW | 100:84:84:46 | |
| NATURAL SCIENCES & MATH | ||
| Biology | 100:71:66:28 | Only 1 instructor |
| Chemistry | 100:68:61 | |
| Computer Science | 100:70:75 | |
| Geology | 100:57:XX | XX = no Assist. Prof. listed |
| Mathematics | 100:73:61 | |
| Physics | 100:70:68 | Only 1 Assist. Prof. listed |
| OPTOMETRY | 100:58:47 | |
| PHARMACY | 100:72:73 | |
| SOCIAL SCIENCE | ||
| Anthropology | XX:100:72 | Small #s: 1 Assist Prof.
XX = no Prof. listed |
| Economics | 100:77:77 | |
| Political Science | 100:71:75 | Only 1 Assist Prof. listed |
| Psychology | 100:72:49 | |
| Sociology | 100:75:66 | |
| SOCIAL WORK | 100:92:69 | |
| TECHNOLOGY | ||
| Industrial | 100:69:58 | Small #s: 1 Prof., 4 Assoc. Prof.,
2 Assist. Prof. |
| Civil/Mech/Related | 100:99:73 | Small #s: 1 Prof., 7 Assoc. Prof.,
1 Assist. Prof. |
| Electrical-Electronic | 100:59:XX | XX = no Assist. Prof.
Small #s: 1 Prof. 5 Assoc. Prof. |
| Human Development | 100:68:XX | XX = no Assist. Prof.
Small #s: 1 Prof., 3 Assoc. Prof. |
This same information is may be obtained in graphical form by contacting the author (email: rmanny@uh.edu).
Using this method of analysis, there are 5 departments (3 with small numbers) where the average salary of a lower rank exceeds the average salary of a higher rank, a salary inversion. These departments are indicated in bold. There are also 12 other departments where the average salaries of the next nearest rank are either the same or within 4 percentage points of each other. These departments are shown in italics. Of the 44 departments/colleges listed above 33 or 75% have neighboring ranks separated by 15% or less. Although the ideal ratio between neighboring ranks is debatable, Table 3 demonstrates that a significant number of colleges and departments have small differences between neighboring ranks suggesting a salary compression problem at the University of Houston.
Table 4 shows the rank ratios present at other Universities
derived from data available from the Chronicle of Higher Education (April
23, 1999 and August 27, 1999). The salaries used to calculate the
rank ratio were reported in thousands of dollars and were rounded to the
nearest hundred. The figures cover full-time members of each institution's
instructional staff, except those in medical schools for the 1998-1999
academic year. The American Association of University Professors
compiled the salaries reported in the Chronicle of Higher Education.
In the data reported by the Chronicle of Higher Education, the University
of Houston was rated as category I, doctoral institution. Universities
in the 10 most populated states with the same rating (category I) were
selected for comparison (California, Illinois, Michigan, New York, North
Carolina, New Jersey, Ohio, Florida, Pennsylvania and Texas). The
overall rank ratio for the University of Houston was calculated from these
figures and is shown in Table 4 for comparison.
Table 4 - Rank Ratio Method of Universities located in 10 Most Populated
States
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| California | |
| California Inst of Tech | 100:70:58 |
| Stanford | 100:68:54 |
| U of Calif @ Berkeley | 100:66:55 |
| U of Calif @ Davis | 100:72:60 |
| U of Calif @ San Diego | 100:66:56 |
| U of Calif @ Santa Barbara | 100:65:54 |
| U of San Diego | 100:69:60:50 |
| U of Southern Calif | 100:70:61:51 |
| Illinois | |
| DePaul U | 100:73:55:52 |
| Illinois Inst of Tech | 100:79:70:50 |
| Illinois State U | 100:79:66:49 |
| Loyola U of Chicago | 100:68:54 |
| Northern Illinois U | 100:73:62:37 |
| Southern Illinois U - Carbondale | 100:74:61:42 |
| Trinity International U - Liberal Arts | 100:85:66 |
| U of Illinois @ Chicago | 100:73:60:49 |
| Urbana-Champaign | 100:70:60 |
| Michigan | |
| Michigan State U | 100:75:60:54 |
| Michigan Tech U | 100:73:64:45 |
| U of Michigan - Ann Arbor | 100:71:56:46 |
| Wayne State | 100:76:60:54 |
| Western Michigan U | 100:80:65:52 |
| New York | |
| State U of NY - Albany | 100:72/56 |
| State U of NY - Buffalo | 100:72:57 |
| Cornell U | 100:78:65:42 |
| Syracuse U | 100:76:62:70 |
| U of Rochester | 100:66:63 |
| North Carolina | |
| Duke U | 100:66:55 |
| North Carolina State U | 100:72:63 |
| Chapel Hill | 100:74:58:51 |
| Greensboro | 100:72:58 |
| New Jersey | |
| Princeton U | 100:60:47:39 |
| New Brunswick | 100:72:53:45 |
| Ohio | |
| Kent State U | 100:74:59 |
| Ohio State Main Campus | 100:68:57:45 |
| U of Cincinnati Main Campus | 100:74:61:47 |
| Florida | |
| Florida Atlantic U | 100:77:64:53 |
| Florida International U | 100:77:65:55 |
| Florida State U | 100:75:66:34 |
| U of Central Florida | 100:78:63:43 |
| U of Florida | 100:73:63:58 |
| U of South Florida | 100:74:63:52 |
| U of Miami | 100:68:59:46 |
| Pennsylvania | |
| Carnegie Mellon | 100:69:61 |
| Drexel U | 100:76:74:46 |
| Lehigh U | 100:71:57 |
| Pennsylvania State Main Campus | 100:67:55:38 |
| Indiana U of PA | 100:81:62:46 |
| Temple U | 100:75:53:52 |
| U of Pennsylvania | 100:67:60 |
| U of Pittsburgh Main Campus | 100:71:58:45 |
| Texas | |
| Texas A&M U | 100:71:62 |
| Texas Tech U | 100:71:56:40 |
| University of Houston | 100:69:63:48 |
| University of Texas - Austin | 100:65:60 |
| PUBLIC Doctoral Institutions (Chronicle of Higher
Education - August 27, 1999) |
100:71:59:42 |
Based on the within class analysis (Table 2)
and rank ratio analysis (Table 3), it is apparent that true salary compression
is present at the University of Houston. Salary compression is present
at all academic levels in most, if not all, colleges. It is also
apparent that salary compression is not a unique problem to the University
of Houston but is a national issue, affecting many other Universities (Table
4).
It should also be recognized that neither
of the analyses reflects salary differentials present between the University
of Houston and the private sector or other comparable Universities.
This is a very significant issue in many fields but is beyond the scope
of this report.
III. Possible solutions to a salary compression problem
Several models to remedy true salary compression have been proposed. However, Lawther, (1989) has cautioned that "if pay compression exists on a large scale, attempting to deal with it on a piece-meal basis may only aggravate the problem." This statement suggests that the solution to the salary compression present at the University of Houston may require action centrally rather than at the college level. Four different approaches to solving salary compression are presented. The solutions are not meant to be exhaustive or exclusive, but are presented to provide a sampling of the possible solutions that have been proposed to solve salary compression.
b. Salary stagnation as it relates to the private sector and comparable
universities
Bereman, NA, Lengnick-Hall, ML. (1994) Pay compression at public universities: the business school experience. Public Personnel Management. 23(3): 469-480.
Bergman TJ, Hills FS, Priefert L. (1983) Pay compression: Causes results and possible solutions. Compensation Review 15:17-26
Gomez-Mejia, LR, Balkin DB. (1987) Pay Compression in Business Schools: Causes and Consequences. Compensation & Benefits Review 19(5): 43-55.
Lawther WC. (1989) Ways to monitor (and solve) the pay-compression problem. Personnel 66(3): 84-87.
Singleton CA (1990) Maximizing the productivity boost from your merit increase dollars. Compensation & Benefits Management 7(1): 34-39.
The Chronicle of Higher Education (1999) Facts and Figures 1998-99 AAUP Faculty Salaries. April 23, 1999.
The Chronicle of Higher Education (1999) Average faculty Salaries
of Full-Time Faculty Members. 46(1):36 August 27, 1999.