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Can Public Schools Buy Better-Qualified Teachers?Author(s): David N. FiglioSource: Industrial and Labor Relations Review, Vol. 55, No. 4 (Jul., 2002), pp. 686-699Published by: Cornell University, School of Industrial & Labor RelationsStable URL: http://www.jstor.org/stable/3270629

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CAN PUBLIC SCHOOLS BUY

BETTER-QUALIFIED TEACHERS?

DAVID N. FIGLIO*

Since the early 1980s, real teacher salaries in U.S. public schools haveincreased considerably faster than salaries of other Americans with similar levels

of education and training. Providing an important impetus for this develop-ment were claims that increased salaries would allow the recruitment of better-

qualified teachers. This analysis, which uses panel data on new teachers in 188

public school districts that changed their salaries between 1987-88 and 1993-

94, investigates whether a school district can, by unilaterally increasing teachersalaries, improve the quality of the teachers it hires, as indicated by their having

graduated from selective colleges and majored in the specific subject matter

they teach. For nonunion school districts, the author finds a positive, statisti-

cally significant relationship between a given district's teacher salaries and that

district's probability of hiring well-qualified teachers. Several tests indicate that

this relationship is not found in unionized school districts.

Since the early 1980s, real teacher sala-ries in U.S. public schools have in-

creased at a rate considerably faster thanthose paid to other Americans with similar

levels of education and training (Ballou

*DavidN. Figlio is WalterMatherlyProfessor ofEconomics at the Universityof Florida and FacultyResearchFellow at the National Bureau of EconomicResearch. This research was supported with fundsfrom the National Science Foundation, the U.S. De-

partment of Education, and the University of OregonFoundation. The author thanks Dale Ballou, Bruce

Blonigen, Thomas Buchmueller, Caroline Hoxby,John Matsusaka, Daniel Rees, Joe Stone, Wesley Wil-

son, James Ziliak, seminar participants and other

colleagues at the University of Oregon and Universityof Southern California, and participants at the 1996Association for Public Policy Analysis and Manage-ment and Western Economic Association meetingsfor helpful comments or conversation. The confiden-tial data used in this paper were provided by theNational Center for Education Statistics, U.S. Depart-ment of Education.

and Podgursky 1996). Much of this rapidincrease in teacher salaries was fueled byseveral prominent recommendations, suchas that expressed in the 1983 report of the

National Commission on Excellence in

Education, to increase salaries in order to

recruit better-qualified teachers (Ballou and

Podgursky 1995). The apparentwidespread

acceptance of this recommendation begsthe question: will higher salaries lead a

school district to be able to attract more

qualified teachers?

Several recent papers have demonstrated

that teachers in general are responsive, in

A data appendix with copies of the computerprograms used to generate the results, as well asinstructions and recommendations on how to applyfor access to the confidential data used in this project,are available from the author at the Department of

Economics, University of Florida, Gainesville, FL

32611-7140.

Industrial and Labor Relations Review,Vol. 55, No. 4 (July 2002). ? by Cornell University.0019-7939/00/5504 $01.00

686



CAN PUBLIC SCHOOLS BUY BETTER TEACHERS?

both their entry and exit decisions, to sala-ries. However, these papers do not explic-itly link salaries to the distributionof teacher

hires. Numerous other studies describe apositive cross-sectionalrelationship betweenteacher qualifications (for example, test

scores, the quality of a teacher's college, or

subject-specific knowledge) and teachersalaries. However, there is reason to sus-

pect that these results, however consistent,will not provide much guidance in helpingto determine whether raising teacher sala-ries will result in higher levels of teacher

qualifications.1

Might this positive relationship be dueto factors other than inter-district differ-ences in teacher salaries? One can easilythink of possible omitted variable biases inboth directions. Suppose that teachers (andtheir spouses) who graduated from presti-gious colleges tend to locate in suburbswhere people of similar backgrounds live.Graduates of more prestigious colleges earn

higher incomes (Loury and Garman 1995),and communities with higher incomes tend

to pay higher teacher salaries, all else equal(Hoxby 2000; and Figlio 1997b). If teach-ers prefer to teach in the school districtswhere their children attend school (per-haps to coordinate vacation schedules, orfor numerous other reasons) or simply pre-fer to work closer to home, then better-

qualified teachers may self-select into

higher-paying districts for reasons otherthan salary. Alternatively, the cross-section

regression results may be biased downward

if school districts compensate teachers, say,for dangerous working conditions or towork with lower-quality students. It seems,

1Studies showing how teachers' entry and exitdecisions respond to salaries are Baugh and Stone

(1982); Eberts and Stone (1984); Murnane and Olsen

(1990); Rickman and Parker (1990); and Theobald

(1990).Cross-sectional studies

investigatingthe rela-

tionship between teacher qualifications and salariesare Antos and Rosen (1975); Ballou (1996); Ballouand Podgursky (1996); Chambers (1985); Ehrenbergand Brewer (1994); Ferguson (1991); Figlio (1997a);and Smith and Lee (1990).

therefore, that in order to address the ques-tion of whether higher salaries attract bet-

ter-qualified teachers, one must attempt to

disentangle the effects of the self-selectionof teachers for non-salary reasons into high-paying districts from the effects of salary asa means of recruiting better-qualified teach-ers. Doing so requires more informationthan a cross-sectional salary regression can

provide.In this study, to isolate how changes over

time in a school district's teacher salariesaffect its probability of recruiting teacherswith high qualifications, I make use of

multiple rounds of the restricted-accessversion of the Schools and Staffing Surveys(SASS), administered by the U.S. Depart-ment of Education, a rich data source that

provides information on individual teacher

qualifications and teacher salaryschedules.I supplement these data with administra-tive information collected in the U.S. De-

partment of Education's Common Core ofData and the Census of Governments. I amable to isolate the effects of salary changes

because in twoyears, 1987-88 and 1993-94,the SASS asked the sampled teachers to

identify their undergraduate institutionsand college major(s). Therefore, I can use

panel data to estimate the effects of changesin a particular public school'ssalary schedulefrom 1987-88 to 1993-94 on that school's

probability of recruiting teachers with par-ticular credentials. Doing so allows me tocontrol for unobservable factors that mayhave been driving earlier evidence of a

relationship between teacher pay andteacher quality.

Teacher Salaries and Teacher Quality

What happens to the probability that aschool district's new teacher will have a

particular qualification when the schooldistrict raises salaries relative to its neigh-bors? An empirical investigation aimed at

answering this question should, ideally,

control for factors that differ systematicallyacross districts over time. Some districtswill naturally be more attractive to teachersfrom selective institutions, independent of

salary, for instance. Controlling for district

687



INDUSTRIAL AND LABOR RELATIONS REVIEW

fixed effects will also hold constant district-

specific factors on the demand side; somedistricts may have more of a taste for gradu-ates of selective colleges, for example.2Since a host of time-varying characteristicsare common to all schools in a communityat the same time, one should also controlfor time-specific, community-specific fixedeffects. Controlling for both types of fixedeffects allows the researcher to ask the ques-tion: what happens when school districts,

holding constant observed time-varying andunobserved time-invariant attributes, raisetheir teacher salaries relative tootherdistricts

in the same community?Put differently, cansalaries explain why district A is preferredto district B by high-quality teachers at onetime but the districts' roles reverse in an-other time period?

My sample consists of 2,672 newly hiredteachers in 188 school districts in 89 coun-ties in the SASS.3 I say that a teacher is

"newlyhired" if that teacher had completedtwo or fewer years of service in his or hercurrent school at the time of the survey.4

Each round of the SASS is designed to beboth nationally representative and state-

representative of the teaching force, andwhile the SASS is not designed to be repre-sentative of the new teacher force or the setof teachers who change schools, the sampleof new teachers in the SASS has attributessimilar to those of the sample of teachingforce entrants found by Figlio and Rueben

(2001) using a very different data set in a

2Ballou (1996) speculated that such differentialtastes might explain his finding that potential teach-ers from selective institutions were no more likely tofind employment as public school teachers than werethose from less selective colleges.

3The present analysis defines teacher labor mar-kets by county. One-quarter of my school districts arein counties with two or more sampled school districts.

When, to allow for even more effective variation, I

repeat the analyses using metropolitan area and con-solidated metropolitan statistical area in place of

county, the results are substantively unchanged.4My results are robust with respect to alternate

reasonable definitions of "newlyhired." For instance,

increasing the duration since hiring to three or four

years, or reducing it to one or zero years, does not

substantively affect the reported results.

different context. My sample includes bothbrand-new teachers and those who have

taught elsewhere prior to joining the cur-

rently observed school. To reduce thechance of one or a few "good draws"or "baddraws" skewing the results, I look only atschool districts with at least four new teach-ers sampled in each round of the SASS.This does lead to over-sampling of largerdistricts; according to tabulations from thefull sample of the 1993-94 round of theSchools and Staffing Survey, 31% of thenation's new teachers were then employedin the 100 largest districts (Corpus Christi,

Texas, or larger), whereas 60% of the newteachers in my sample are employed bythese large districts. Even so, my analysis is

by no means dominated by the largest ur-ban districts: just 14% of the teachers in mysample are employed by the ten largestdistricts, compared to 8% of teachers in the

country as a whole; and a healthy fractionof teachers in my sample-10%-teach inschool districts outside metropolitan areas,so even rural districts are represented.

Teacher quality is subjective andunmeasurable. However, there are surelysome measurable factors that could be usedto indicate teacher quality, or perhapsteacher intelligence. One such measure isthe selectivity of a teacher's undergraduateinstitution, which was found by Ehrenbergand Brewer (1994) to be strongly associ-ated with student achievement. The teach-ers in my sample attended 764 undergradu-ate institutions, ranging from open-admis-

sions colleges that accept any applicantwith high school equivalency to extremelyselective schools such as Harvard Univer-

sity, Williams College, and the University of

Chicago. College selectivity is highly corre-

lated, by all measures, with the standard-ized college entrance examinations usedfor admissions purposes. Therefore, I usethe average SAT verbal score (or SAT-

equivalent, using a technique described indetail by Figlio and Rueben [2001], for

colleges in ACT-dominated areas of thecountry) of entering students in theteacher's undergraduate institution as a

proxy for teacher quality.An alternative measure of teacher qual-

688




ity is teacher subject-matter expertise. It isnatural to expect that teachers with specifictraining in the subject they teach will, all

else equal, be better qualified than otherteachers to teach that subject. Therefore,as an alternative quality measure, I also

identifywhether teachers majored (or havea master's degree) in the subjects they teach.

Thus, I explore whether school districtsthat increase their salaries unilaterally aresuccessful in attracting new teachers withmore subject-matter expertise as well as

graduates from more selective colleges.School districts in the SASS report two

points on their salary schedules: startingsalaries for inexperienced teachers, andsalaries for teachers with twenty years of

experience. Since the set of teachers con-sidered in this study includes both brand-new teachers and experienced teachers,and since there is no obvious way to charac-terize the salary stream of a teacher, I usethe average of the starting teacher salaryand the experienced teacher salaryreportedby school districts as my measure of a

district's teacher salary.Manyfactors besides teacher salaries may

affect a teacher's likelihood of being at-tracted to and hired by a particular schooldistrict. Fortunately, a large number ofthese factors (for example, being in a neigh-borhood populated by high-income gradu-ates of selective schools, or a particularschool district's "tastes" for a particulartype of teacher) arguably do not changeappreciably over a six-year period, so I can

make use of the panel attributes of my datato implicitly control for these (approxi-mately) time-invariant attributes of schooldistricts. But several other factors that mayaffect the probability of high-quality teach-ers being hired in a district didchange overtime. For instance, different parts of the

country were differentially affected by therecession of the early 1990s, and there aresome factors that will be common to allschool districts in a teacher labor market at

the same time. To control for all factorsthat affect every school district in an area atthe same time, I control for time-specific,county-specific fixed effects, so that the

only variation that I employ is the deviation

over timein the school district'srelativepositionin the county.

There are still some other factors that

could be associated with the change overtime in a school district's likelihood (rela-tive to others in its county) of hiring teach-ers with a particular credential. Some dis-tricts have been growing over time, whileothers have been shrinking or maintainingrelatively constant enrollments. A schooldistrict may change non-salary attributes ofits schools (for example, the length of theschool day and year, or the racial and in-come composition of the schools) that in-

dependently affect a teacher's probabilityof being hired, or the teacher's probabilityof being attracted to the district. There-

fore, it is important to control for theseother types of factors even when I controlfor time-varying county-level fixed effects.Table 1 presents a list of definitions anddata sources for all variables used in this

analysis.The first two columns of the first row of

Table 2 present estimates of the results of a

regression of the relevant teacher qualityvariable on district teacher salaries in amodel without controls for district-specificfixed effects, county-specific, year-specificfixed effects, or any other covariates. That

is, this is merely a regression of teacher

quality on teacher salaries and ayear dummyvariable for 1993-94. All standard errors

reported, however, are still corrected forwithin-school district, within-year correla-tion in the errors. We observe strong,

positive correlations between teacher sala-ries and both the probability of a newteacher having majored in the subject thathe or she teaches and the selectivity of the

college that he or she attended as an under-

graduate. However, as mentioned above,this is a suspect identification strategy, sincethere exist numerous potentially omittedvariables that could bias the cross-sectional

relationship in either direction.

Therefore, in the second row of Table 2

are estimates of the same relationship in amodel in which both time-invariant districtfixed effects and time-specific, county-spe-cific constants are included. As before, thestandard errors are corrected for within-

689



Table 1. Description of Variables Used in the Regression Analysis.

Mean SpecificationsVariable (Std. Dev.) Used in: Data Source Methodof Con

Average SAT Verbal Score ofTeacher's UndergraduateInstitution (dependent variable)

Teacher Majored in SubjectHe/She Teaches (dependentvariable)

Teacher Salaries

District Enrollment Growth

South

Union District

Size of District

Teacher Workload

Fraction White in School

Fraction Free-Lunch Eligiblein School

451 (51) Table 1: all rows,cols. 1, 3; Table 3:col. 5

0.284 Table 1: all rows,cols. 2, 4; Table 3:col. 6

25,899(3,841)

0.119

(0.173)

0.495

All specifications

Table 4, all cols.

Table 4, all cols.

0.649 Table 2, row D;Table 4, all cols.

130,359 Table 2, rows C, D;(218,527) Table 4, all

1,181 Table 2, rows C, D;(126) Table 4, all

0.538 Table 2, rows C, D;

(0.340) Table 4, all

0.301 Table 2, rows C, D;(0.246) Table 4, all

Integrated Data Survey;Postsecondary Education

college guides

SASS teacher file

SASS school district file

Common Core of Data

Census

Census of Governments;SASS district file

Common Core of Data

SASS district file

SASS school file

SASS school file

Use IPEDS da

college identiftest score repo

guides; in ACusing Figlio-R

Match collegepostgraduateteacher reportteaching assig

Average of disdegree and nomaster's degreto 1993 dollarindex

Percentage gr1987-88 to 19

Indicator for

Indicator for

by collective bfrom Census odistrict file

School district

Number of daof instruction

School-reportereported enrol

School-reportestudents, divi




Table 2. Relationship between Teacher Salaries and Teacher Quality.

Quality Indicator

Full Set of TeachersNew to Their Schools

Specification

(A) Cross-Sectional Relationship

(B) Specification with Only County-Year and District Fixed Effects

(C) Specification That Also IncludesTime-Varying Covariates

(Dl) Specification That Includes AllFixed Effects and Time-VaryingCovariates: Nonunion School Effect

(D2) Union Interaction

(1) AverageSAT Verbal

ScoreofUndergraduate

Institution

0.0017

(0.0005)

0.0027

(0.0015)

0.0027(0.0012)

0.0035

(0.0025)

-0.0013

(0.0025)

(2) Teacher

Majoredin

SubjectHe/SheTeaches

0.0004

(0.0002)

0.0045

(0.0013)

0.0046(0.0016)

0.0087

(0.0032)

-0.0060

(0.0034)

OnlyNew TeacherswithPrior Teaching Experience

(3) Average (4) TeacherSAT Verbal Majored

Scoreof in SubjectUndergraduate He/She

Institution Teaches

0.0019

(0.0005)

0.0047

(0.0022)

0.0038(0.0017)

0.0049

(0.0036)

-0.0016

(0.0038)

0.0008

(0.0003)

0.0068

(0.0019)

0.0070(0.0025)

0.0153

(0.0021)

-0.0120

(0.0023)

Notes: Each cell represents a separate regression, except the cells in rows (D1) and (D2), which are estimatedin the same regression specifications. The results above present only the salary coefficients (*100, in the caseof teacher major specifications). Covariates included in some specifications include district size, teacher

workload, fraction white in the school, and fraction free lunch-eligible in the school. An appendix tableincludes the full set of coefficient estimates. Huber standard errors, corrected for the presence of within-year,within-district error

correlation,are in

parenthesesbeneath

parameterestimates.

school district, within-year correlation in

the errors. The results suggest that if a

school district unilaterally raises its salaries

relative to others in its county, it will in-

crease the quality level of the experiencedteachers it hires. The coefficient of interestin each equation is statistically significantat conventional levels, with the coefficient

in the subject matter expertise equationbeing particularly strong in magnitude and

statistical significance.The magnitudes of these estimated ef-

fects are not trivial. Given that the average

within-county standard deviation in experi-enced teacher salaries is $2,525 (for coun-

ties with five or more school districts), an

increase in salaries of this magnitude is

expected to increase average new teacher

quality by about 12 SAT points, the equiva-

lent of a difference in SAT scores between,say, Carnegie Mellon University and Ameri-

can University, or Indiana University and

Northern Illinois University. Since the av-

erage within-county standard deviation in

new teacher quality is 34.6 points, this im-

plies that increasing salaries by one stan-

dard deviation within a county would be

associated with an increase in average new

teacher quality of more than one-third of a

standard deviation. The teacher subjectmatter expertise specification suggests that

a one standard deviation increase in rela-

tive salaries is associated with an 11 per-centage point increase in the probabilitythat a new teacher majored in the subjectthat he or she teaches. Since 28% of teach-ers in the sample have this credential, this

is a rather large change.The third row of Table 2 presents the

estimated effects of increasing teacher sala-

ries in a model that also includes school

district size, the teacher workload (as mea-

sured by the number of hours of instruc-

tion in the school year), the fraction ofstudents in the school who are white, and

the fraction eligible for subsidized lunches

(a measure of relative poverty) in the school.

Levinson (1988) demonstrated that these

691




factors either directly affect or proxy forfactors that affect teacher salary demands.While Table 2 only reports the coefficient

estimates on the salaryvariable, a full set ofcoefficient estimates is presented in the

Appendix.The results are reasonably similar to those

presented in the first row. The salary coef-ficient in the college selectivity equation is

slightly smaller in magnitude but even more

strongly statistically significant than that

presented above, and the salary coefficientin the subject matter expertise equation isalmost exactly the same in magnitude and

statistical significance as when the time-varying covariates are excluded.

The third and fourth columns of Table 2

report the results of this analysis repeatedonly with the set of experienced teachers,that is, teachers who previously taught inanother district. I look at this set of teach-ers separately because it is possible that

experienced teachers have a better knowl-

edge of teaching opportunities in otherdistricts in a community than would brand-

new teachers. The results are qualitativelysimilar, but somewhat stronger in magni-tude and statistical significance, with this

sampling restriction.It is possible that salaries and quality are

simultaneously determined. For instance,schools with lower-quality teachers (or de-

clining teacher quality) may be more in-clined to increase salaries, which wouldlead to a downward bias in the relationshipbetween teacher salaries and teacher qual-

ity. On the other hand, the results could beupward-biased if the improving teacher

quality puts upward pressure on salaries.

Although I include a rich set of fixed ef-fects-both time-invariant effects within adistrict and time-varying effects at the

county level-that should address the omit-ted variables problem to a large extent, the

potential endogeneity of the teacher sala-ries could present problems in the current

specification. Regrettably, since I have not

been able to identify any instrumental vari-ables that are strongly correlated with

within-county changes in a district's salaryschedule but not independently correlatedwith changes in teacher quality measures,

the results reported herein may still be

subject to endogeneity bias. This bias willbe downward if increased salaries are moti-

vated by low teacher quality, but the resultscould be upward-biased if changes in sala-ries over the six-year period are correlatedwith other unobserved characteristics thatwould draw different-quality teachers.

Unions and the Teacher Salary-Teacher Quality Relationship

It is possible that unionized and non-union school districts are not alike in their

ability to improve their probability of at-tracting high-qualification teachers usingincreased salaries. For instance, if gradu-ates from selective colleges and those with

subject matter expertise tend to be more

highly motivated or produce higher-qual-ity output than others, they may be more

likely to want to teach at a school whereindividual motivation, effort, and perfor-mance are more directly rewarded.5 Theavailable evidence from the SASS strongly

suggests that higher-quality teachers aredifferentially rewarded in nonunionschools. For example, nonunion schools inthe SASS are three times as likely as union-ized schools (24% versus 8%) to have aformal merit pay system (a difference thatis statistically significant at any conventionallevel) .6

Moreover, there is evidence to suggestthat unionized schools and nonunionschools reward their high-quality (by my

measures) teachers differentially in non-pecuniary waysaswell.7 For instance, in the

5Savio (1996) made a similar argument in explain-ing why high-quality teachers disproportionately teachat private schools despite lower salaries.

6This comparison is computed from an OLS re-

gression in which the dependent variable is an indica-tor for whether the school has merit pay and the

independent variable is a union school indicator.7The comparisons described in this paragraph are

computed from OLS regressions in which the depen-

dent variable is the characteristic faced by the teacher(for example, class size) and the independent vari-ables are the average SAT score of students at theteacher's undergraduate institution, a union school

dummy, and the interaction between these two vari-ables.

692




SASS the relationship between average classsize for a mathematics, science, or socialstudies teacher and the average SAT score

of entering students at that teacher's un-dergraduate institution is negative, thoughnot statistically significant, across all schools,but it is significantly lessnegative for union-ized schools. The results suggest that innonunion schools, a teacher who attendedStanford University would average .8 fewerstudents per class than a teacher who at-tended the University of California at Ber-

keley and 1.7 fewer students per class thanan attendee of San Jose State University,

compared to differences of .33 and .75students per class, respectively, in union-ized schools. The difference in this rela-

tionship between unionized and nonunionschools is significant at about the 3% level.

Similarly, a non-statistically significant,modestly negative estimated relationshipbetween the SAT score of the teacher's

undergraduate institution and the numberof unique "preparations" required of thatteacher by the school district is, again, less

negative for teachers in unionized schoolsthan for those in nonunion schools: innonunion schools, a teacher who attendeda school with SAT scores like those ofCornell University is predicted to have to

satisfy 0.04 fewer preparations than ateacher who attended a school with theSAT scores of SUNY-Binghamton, and 0.08fewer preparations than a teacher who at-tended a school with scores like those of

SUNY-Cortland, compared to figures of 0.01

and 0.03 fewer preparations, respectively,in unionized schools. The difference inthis relationship between unionized andnonunion schools is statistically significantat about the 11% level. These results con-stitute suggestive evidence that nonunionschools differentially reward higher-quali-fied teachers, in both pecuniary and non-

pecuniary ways, although the magnitudesof these differences, while statistically sig-nificant, are not very large.

In order to determine whether the rela-tionship between teacher salaries and thelikelihood of recruiting and hiring high-qualification teachers differs by school dis-trict union status, I estimate the baseline

models from Table 2, but also interact theteacher salary variable with a dichotomousvariable representing whether teachers in

the school district were covered by a collec-tive bargaining agreement over this time

period. Every school district in my samplehad the same union status in both 1987 and1993 (the 1987 data come from the Censusof Governments, and the 1993 data fromthe SASS), so a union status dummy vari-able is subsumed into the district fixedeffect and is therefore obviously not sepa-rately reported. These results are reportedin the fourth and fifth rows of Table 2.

I find limited evidence that the relation-ship between salaries and the likelihood of

recruiting high-quality teachers differs be-tween union and nonunion school districts.For both brand-new teachers and experi-enced teachers who are new to a school, the

positive relationship between salary andthe selectivity of the college the teacherattended is higher for nonunion schooldistricts (though only statistically signifi-cant at the 18% level) than for unionized

school districts, although the interactionterm is extremely imprecisely estimated.8

Specifically, in nonunion school districts, aone within-county standard-deviation in-crease in salaries predicts a 12-point incre-ment in the SAT verbal scores of newlyhired teachers' undergraduate institutions,

compared to a predicted improvement of

only 8 points in unionized school districts.

Again, this particular difference is impre-cisely estimated. Results of substantially

larger magnitude and with statistical sig-nificance at conventional levels areobservedfor the positive association between salaryand teacher subject matter expertise.9 TheOLS results suggest that a one within-countystandard-deviation increase in salaries

8Because of the larger sample size of unionized

districts, these smaller estimated salary effects forunionized schools are still statistically significant.

The salary effect in unionized schools is .0023 (stan-dard error of .0009) in column 1 and .0033 (standarderror of .0013) in column 3.

9The estimated effect of salaries in unionizedschools is .0027 (standard error of .0019) in column2 and .0033 (standard error of .0015) in column 4.

693




boosts the likelihood of hiring a teacherwho majored in his or her subject matter byabout 22 percentage points in a nonunion

school district, compared to only 7 percent-age points in a unionized school district.The magnitudes of the effects, as well as theestimated gaps between union and non-union schools, are larger when we look

only at the set of experienced teachers.

Therefore, while there is little or no evi-dence that the relationship between sala-ries and the probability of hiring a teacherfrom a selective institution varies with schoolunion status, there is relatively strong evi-

dence that union status affects the relation-ship between salaries and the probability of

hiring a teacher with subject matter exper-tise.10

Why might the results hold more stronglyfor nonunion districts than for union dis-tricts? There are a number of possiblereasons, none of which is complete or fullyconvincing. Besides the possible supplyside arguments mentioned above, one pos-sible additional reason is that unionized

public schools may simply not be interestedin hiring better-quality candidates. That is,it is possible that higher salaries draw bet-

ter-quality applicants, but that administra-tors of unionized public schools, for what-ever reason, prefer to hire lower-qualityteachers. Ballou (1996) cited that possibil-ity in trying to explain his finding that

potential teachers from selective collegeswere no more likely to find teachingjobs inthe public sector than were potential teach-

ers from less selective colleges. (Of course,a lack of interest in hiring the best teachersis not the only possible way to explainBallou's finding, since demands for differ-

'1In other specification checks, I experimentedwith interacting the other covariates with school unionstatus. In only one case was such an interaction

statistically significant at even the 30% level: the

interaction between district size and union status inthe college selectivity specification. These results

suggest that larger districts fare better in attractinggraduates of selective colleges if the district is union-ized. This interaction term, however, is not statisti-

cally significant in other specifications.

ent kinds of teachers may naturally be dif-

ferent.) I am unable to evaluate this possi-bility because, lacking data on the pool of

applicants for specific teaching positions, Ihave no way to gauge administrator prefer-ences.

Alternatively, perhaps teacher unions

impose additional constraints on hiring (forexample, requiring a certain amount ofeducation coursework) that tend to favor

graduates from less selective institutions orcandidates without specific subject matter

expertise. Such a filtering process mightattenuate the relationship between teacher

salaries and teacher qualifications even ifadministrators desire to improve teacher

qualifications and more teachers from se-lective colleges apply to the school district.

Spurious Correlation?

The preceding discussion suggests thatwhile nonunion public schools attract bet-

ter-quality teachers as they increase their

salaries, these results tend not to be as

strong for unionized public schools. Arethe differences due to unionizationperse,oram I merely picking up the effects of factorscorrelated with unionization? Forinstance,southern school districts are much less likelyto be unionized than are school districtsoutside the South, and it may be that non-union districts are younger and faster-grow-ing than are unionized districts. As such,the reported results may be due merely toNorth-South differences.

Table 3 presents union-nonunion differ-ences for a host of school characteristics.As noted, nonunion schools are dispropor-tionately clustered in the southern UnitedStates: while 29% of unionized teachers inthe SASS teach in the South, 88% of non-union teachers in the SASS are in the South.Unionized school districts also apparentlyare growing somewhat more slowly thanare nonunion districts: the mean growthfrom 1987 to 1993 in unionized districts in

the SASS was 11%, compared to 13% innonunion districts. Unionized schools tendto have teachers who are slightly more ex-

perienced and have slightly more educa-tion-the average teacher experience in

694




Table 3. Differences between Union and Nonunion Schools in the SASS.

Unionized Nonunion p-ValueCharacteristic Schools Schools

of DifferenceSouth 0.289 0.875 0.000

District Enrollment Growth from 1987 to 1993 0.114 0.130 0.023

Teacher Experience (years) 12.55 11.62 0.000

Percent with Master's Degrees 0.453 0.409 0.002

State Certification Required for Employment 0.765 0.745 0.247

Passage of Test Required for Employment 0.735 0.789 0.001

Passage of Subject Knowledge Test Required for Employment 0.624 0.696 0.000

Education School Attendance Required for Employment 0.670 0.544 0.000

Subject Matter Major/Minor Required for Employment 0.480 0.511 0.112

unionized schools in the SASS is 12.6 years,compared with 11.6 years in nonunion

schools, and 45% of teachers in unionizedschools have master's degrees, comparedto 41% in nonunion schools. All four ofthese differences are significantly differentfrom zero.

To determine whether my results are

really "South" effects or "fast growing dis-trict" effects rather than union status ef-

fects, I estimate the specification that in-

cludes all fixed effects and time-varyingcovariates once again, but this time also

interacting all salary variables both with aSouth region dummy and with the district

growth rate, measured by the percentageincrease in district enrollment from 1987to 1993. The results of this exercise are

reported in Table 4. The reported specifi-

cation is for all teachers new to a district,regardless of experience, but the pattern ofresults remains the same when only teach-ers with previous teaching experience are

sampled.Because of the richly interacted specifi-

cation, it is difficult to read the estimatedeffects of teacher salaries on teacher qual-ity, or the differential effects of teacherunions on this relationship, directly off ofTable 4. Therefore, in the bottom portion

of the table I present the implied differ-ence between union and nonunion schoolsin their relationship between teacher sala-ries and teacher quality in a number of

settings. Specifically, I present that esti-

mated difference in southern versus non-southern locales, and, within each of those

two geographic groups, for school districts

with 25th percentile growth rates, median

growth rates, and 75th percentile growthrates.

The estimated union-nonunion differ-ence tends to hold up across these different

groups: in the non-South, the estimateddifference is negative (meaning that union-ized schools have a more negative-or less

positive-relationship) and statistically sig-nificant across the various ranges of growthrates, for both measures of teacher quality.The results for the South are less clear-cut.While the union-nonunion difference is

uniformly estimated to be negative in thecase of subject matter expertise (and statis-

tically significant for faster-growing school

districts), the estimated union-nonuniondifference is positive, though not statisti-

cally significant, for college selectivity.

Notwithstanding these somewhat equivo-cal results for the South, the estimates for

the non-South, which unambiguously showa union-nonunion difference, demonstratethat the estimated relationships are not

merely driven by North-South differences.One might also question the conclusion

regarding differences between unionized

and nonunion schools by calling into ques-tion the adequacy of the specific set ofteacher quality indicators used in this study.That is, although the link between salaryincreases and increased hiring of teachers

695




Table 4. Results by Region and District Student Enrollment Growth Rate.

Quality Indicator

Variable

Teacher Salaries

Teacher Salaries *

Union

Teacher Salaries *

South

Teacher Salaries *

Union * South

Teacher Salaries *District Growth Rate

Teacher Salaries * Union *

District Growth Rate

(5) AverageSAT VerbalScoreofUndergraduateInstitution

(Salary Coefficient)

-0.00

(0.0050)

-0.0068

(0.0031)

0.0099

(0.0036)

0.0135

(0.0071)

0.0023(0.0171)

-0.0014

(0.0169)

(6) TeacherMajoredin SubjectHe/She Teaches

(Salary Coefficient* 00)

-0.0023

(0.0041)

-0.0053

(0.0032)

0.0054

(0.0044)

-0.0049

(0.0076)

0.0188(0.0183)

-0.0180

(0.0181)

Estimated Union-Nonunion Relationship Difference, in Different Circumstances:

Non-South South Non-South South

District Growth at 25thPercentile -0.0068 0.0067 -0.0054 -0.0103

(0.07% over 6 Years) (0.0031) (0.0082) (0.0032) (0.0089)

District Growth at Median -0.0069 0.0066 -0.0068 -0.0118

(8.3% over 6 Years) (0.0031) (0.0074) (0.0030) (0.0079)

District Growth at 75thPercentile -0.0070 0.0065 -0.0082 -0.0132(15.9% over 6 Years) (0.0036) (0.0069) (0.0035) (0.0070)

Notes: All specifications include school district-specific fixed effects and county-year fixed effects. Huberstandard errors, corrected for within-district, within-year correlation in the errors, are in parentheses beneath

parameter estimates.

possessing the qualifications specificallytracked in this study appears to be stron-

ger in nonunion schools than in union-ized schools, it could be that new esti-

mates using a different set of teacherquality indicators would reveal a differ-ent pattern, since unionized and non-union schools may differ significantly incredential requirements.

The bottom panel of Table 3 reports themeans across unionized and nonunionschools in district-reported teacher

credentialing requirements. There is nodiscernible difference between union andnonunion schools in the fraction requiring

state certification. Unionized schools aresignificantly more likely than nonunionschools to require education school atten-dance. In contrast, they are marginallysignificantly less likely than nonunion

schools to require teachers to have ma-

jored or minored in their subject of choice

(p < .11); significantly less likely than non-union schools to require teachers to pass

the National Teachers' Examination or astate test of basic or subject-specific skills;and highlysignificantly less likely than non-union schools to require passage of a stateor national subject-specific test. There-

fore, if anything, it appears that nonunionschool districts tend to have higher basicstandards than unionized schools alongseveral lines of required credentials.

Conclusions

Can public schools attract better-quali-fied teachers by raising teacher salaries?The evidence presented in this paper sug-gests they can. Using an empirical ap-

696




proach that avoids many of the most likelyomitted variables problems associated withcross-sectional analysis of this issue, I find a

positive, statistically significant relationshipbetween changes in a school district'steacher salaries and its likelihood of re-

cruiting higher-qualified teachers, mea-sured in terms of college selectivity as wellas subject matter expertise. However, this

relationship holds only for nonunion schooldistricts, not, in general, for unionizedschool districts. Although this union/non-union difference could conceivably be

sample-specific-reflecting, for instance,

the over-representation of larger schooldistricts in the sample-it is strongly con-firmed within the framework of the study.It is, moreover, consistent with Hoxby's(1996) finding that unionized schools payhigher teacher salaries than nonunionschools and yet have lower academic per-formance (measured by a higher dropoutrate).

The results of the study suggest thatschools-at least nonunion schools-can

succeed in luring high-quality, predomi-nantly already established teachers away fromother districts by unilaterally raising sala-ries. I have not addressed whether theoverall quality of new teachers hired can be

improved through more broadly coordi-

nated salary increases across a large number

of schools. My finding that teachers in mysample of nonunion schools were respon-sive to salaries certainly is not inconsistentwith the efficacy of, say, public policy-gen-

erated pay increases across the teachingprofession, but further analysis with differ-ent data would be needed to address that

issue directly.It is important to note that raising teacher

salaries to recruit better-quality new teach-ers could come at a significant cost. Ameri-can public school systems pay teachers, in

general, according to a salary schedule

whereby all teachers with a certain combi-nation of education level and experienceearn the same salary. Increasing salaries toattract new teachers would involve raisingthe salaries of existing teachers of lower

quality. Therefore, such a policy, thoughpossibly effective, may be prohibitivelycostly.

The union-nonunion differences re-

ported in this paper, however, suggest the

potential viability of an alternative policy:instituting merit pay or pay-for-perfor-mance. Such a policy, though apparently atodds with the emphases of teacher unions,may provide opportunities to differentiallyattract high-quality teachers with higher

pay, while not shifting up the salary distri-bution to all teachers. A central problemwith merit pay, of course, is that it would

require schools to measure the basicallyunmeasurable-teacher quality. How to goabout doing that is a matter beyond the

scope of the current paper. This paperdoes, however, provide evidence that one

precondition for merit pay to be effective-

high-quality teachers' responsiveness tosalaries-is present.

697




Appendix

Full Set of Coefficients from Third-Row (C) Specifications in Table 2

Credential(Columns):Full Set of

TeachersNew to Their SchoolsOnlyNew Teachers

with Prior Teaching Experience

(1) AverageSAT

VerbalScoreof

UndergraduateVariable Institution

Teacher Salaries

Size of District

Teacher Workload

Fraction of Students in School Who Are White

Fraction Free Lunch-Eligible in School

0.0027

(0.0012)

-0.0000(0.0011)

-0.0021

(0.0145)

0.0836

(0.0750)

-0.0124

(0.0736)

(2) Teacher

Majoredin


(Coefficients*100)

0.0046

(0.0016)

-0.0006(0.0008)

-0.0066

(0.0129)

(3) AverageSAT

VerbalScoreof

UndergraduateInstitution

0.0038

(0.0017)

-0.0012(0.0015)

-0.0059

(0.0176)

-0.0201 0.1354 -0.0246

(0.0585) (0.0970) (0.0832)

-0.1071 -0.0896 -0.1160

(0.0616) (0.0759) (0.0793)

Note: All specifications include school district-specific fixed effects and county-year fixed effects. Huber

standard errors, corrected for within-district, within-year correlation in the errors, are in parentheses beneath

parameter estimates.

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