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Early Childhood Research Quarterly 28 (2013) 831– 842

Contents lists available at ScienceDirect

Early Childhood Research Quarterly

aising teacher education levels in Head Start: Exploringrogrammatic changes between 1999 and 2011

aphna Bassok ∗

urry School of Education, 405 Emmet Street South, P.O. Box 400277, Charlottesville, VA 22904, United States

r t i c l e i n f o

rticle history:eceived 16 December 2010eceived in revised form 16 July 2013ccepted 17 July 2013

a b s t r a c t

Between 1999 and 2011, the percentage of Head Start teachers nationwide with an Associate’s Degree orhigher more than doubled from 38 to 85%. Over the same period, the percentage of teachers with a BA alsorose rapidly from 23 to 52%. This paper uses within-program fixed-effects models and a 13-year panel

eywords:eacher educationead Starteacher quality

of administrative data on all Head Start programs in the United States to explore whether programs thatexperienced increases in teacher education experienced changes with respect to comprehensive serviceprovision, staffing choices and the racial composition of the staff. I find no evidence that programs thatraised their teachers’ education levels sacrificed health or social services. However, programs with gains inteacher education did see some increases in child–teacher ratios, turnover, and racial divergence betweenchildren and staff, which may be associated negatively with young children’s development.

Over the past decade, more and more states have mandatedigher educational credentials for early childhood educators. The007 reauthorization of the federal Head Start preschool programequired that by 2013, half of all lead teachers in the program hold aaccalaureate degree (BA) in early childhood or a related field. Sim-

larly, 24 states currently require lead teachers in public preschoolso have a BA (Barnett, Carolan, Fitzgerald, & Squires, 2011).

Training, attracting, and retaining more educated teachers isostly. Particularly given constrained budgets, mandates for highereacher qualifications may yield important programmatic changes.o date, the early childhood literature on teacher education hasocused on the direct effects of teacher education on classroomuality and children’s learning (e.g. Are teachers with a degree inarly childhood more sensitive in their interactions with children?o their students learn more?). However, to assess accurately theotential impact of degree mandates, it is necessary to consider notnly the direct effects of employing teachers with higher creden-ials but any unintended consequences and their costs and benefitss well.

This paper leverages a 13-year panel of administrative data fromead Start to explore whether Head Start programs that expe-

ienced changes in teacher education levels also saw meaningfulrogrammatic changes along several other dimensions. The 1998

eauthorization of Head Start mandated that by 2003, 50% of allead Start teachers nationwide have, at minimum, an Associate’segree (AA) in early childhood education or a related field. While

∗ Tel.: +1 434 982 5415; fax: +1 434 924 3866.E-mail address: dbassok@virginia.edu

885-2006/$ – see front matter © 2013 Elsevier Inc. All rights reserved.ttp://dx.doi.org/10.1016/j.ecresq.2013.07.004

© 2013 Elsevier Inc. All rights reserved.

in 1999, only 38% of Head Start teachers had an AA or above,by 2011, this figure had more than doubled to 85%. This changeoccurred during a period largely characterized by stable or declin-ing funding for the Head Start program. It therefore provides aunique opportunity to explore timely questions about efforts tomaintain and improve the quality of early childhood programswhile facing strained budgets. The current study measures to whatextent increases in Head Start teachers’ education levels are asso-ciated with meaningful changes along three other dimensions; (1)the provision of non-academic services such as health and socialservices; (2) staff structure and stability (i.e. child–teacher ratios,teacher turnover) and (3) the racial composition of the teachingforce relative to the student body.

1. Why mandate higher education levels?

As in the K-12 system, there is consensus that “teacher quality,”defined broadly, plays a critical role in early childhood educa-tion. Whitebook, Gomby, Bellm, Sakai, and Kipnis (2009) arguesthat teachers, and the quality of interactions between teachersand children, are key determinants of preschool quality, and pro-vides a summary of the extensive research base that supports thisclaim (Bowman, Donovan, & Burns, 2001; NICHD Early Child CareResearch Network, 2000; Phillipsen, Burchinal, Howes, & Cryer,1997; Vandell & Wolfe, 2000).

However, there is substantial debate over the effect of specific

degrees on teacher quality and student learning in early child-hood settings. Some past research, including studies conducted inHead Start classrooms, report positive associations between tea-chers’ educational attainment and both observed care quality and

8 search Quarterly 28 (2013) 831– 842

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Fig. 1. Shows the overall percentage of Head Start lead teachers nationwide whohave acquired certain degrees (author’s calculation using annual Program Infor-

32 D. Bassok / Early Childhood Re

hild outcomes (Burchinal, Cryer, Clifford, & Howes, 2002; Helburn,995; Honig & Hirallal, 1998; Howes, Phillips, & Whitebook, 1992;ICHD Early Child Care Research Network, 1999; Zill et al., 2001).owever, more recent research does not replicate this earlier pat-

ern. This work has led to more nuanced hypotheses about themportance of pre-service teacher education (Early et al., 2006;

ashburn et al., 2008). To date, Early et al. (2007) provide the mostethodologically rigorous analysis of this topic through their coor-

inated, secondary analysis of seven large, longitudinal datasets.heir findings, which accounted for the nested structure of theata as well as missing data, found little evidence of an associa-ion between teachers’ educational attainment or major and theirtudents’ learning.

These authors as well as other researchers point out, the nullndings raise a number of questions and suggest the need for

broader research agenda to unpack the mechanism by whichegree acquisition may improve quality in early childhood sett-

ngs (Washington, 2008; Whitebook et al., 2009; Zaslow, Tout,alle, Whittaker, & Lavelle, 2010). For instance, it may be that

he effects of degrees vary depending on the specific quality, con-ent, and structure of the degree program (Hyson, Tomlinson,

Morris, 2009). Perhaps the benefits from degree requirementsay come indirectly through their impact on higher wages,

rofessionalization, and reduced turnover (Whitebook & Ryan,011). Another possibility is that the impact of teachers’ degreesn program quality is moderated by other programmatic fea-ures, making it worthwhile to explore whether programs thataise teacher education levels make changes in other impor-ant program characteristics. This is the question this paperddresses.

. Raising teacher education in Head Start

Head Start is a federally funded preschool program servingver 900,000 low-income children through nearly 50,000 class-ooms (Office of Head Start, 2010). Its mission is to promote schooleadiness broadly defined by providing educational, health, nutri-ional, and other services to children and their families. In 1998,ongress reauthorized Head Start with the Community Oppor-unities, Accountability, and Training and Educational ServicesCOATES) Act. The act mandated that 50% of all Head Start teachersationwide have, at minimum, an AA degree in early childhoodducation or a related field by 2003. At that time, Head Start’sequirement for teachers was that they hold a Child Developmentssociate credential which is attained by clocking 120 h of for-al early childhood education training, passing a written and oral

ssessment, and meeting several other requirements (Council forrofessional Recognition, 2012). Many Head Start advocates wor-ied the mandate was not accompanied by sufficient increases inunding (Barnett, 2003; Shaul, 2003).

The legislation did require that in each year that the real value ofead Start funding appropriation increased, a set proportion of this

ncrease would be used for quality improvements. Further, at leastalf of these quality improvement funds were to be used specifi-ally for salary and benefit increases (Hart & Schumacher, 2005).n fact, between 1999 and 2001, the overall funding for Head Startncreased, which translated to yearly increases in quality improve-

ent funding. However, in 2001, funding peaked at $356 millionnd in the following years the much smaller gains in Head Startppropriations as well as the lower proportion set aside for qualitymprovements led to sharp drops in quality improvement fund-

ng ($80 million in 2002, and $32 million in 2003). Requirementso raise teacher education levels in this context of constrainedesources may have led some Head Start programs to considerhanges in other program areas.

mation Reports). Educational attainment for adults 25–29 comes from the CurrentPopulation Survey (CPS), March and Annual Social and Economic Supplement,1971–2006.

Head Start was once again reauthorized in 2007 with the“Improving Head Start for School Readiness Act” which requiredthat 50% of Head Start teachers nationwide hold a BA degree by2013. According to one analysis, the estimated costs of meetingthe goal would be approximately $2.7 billion over six years (Ewen,2005). As with the prior reauthorization, the education demandswere criticized for being “unfunded mandates” (National Head StartAssociation, 2008).

Nonetheless, the goals set out in each of the reauthorization actswere met (see Fig. 1). While in 1998, 34% of teachers held an AAdegree or more, by 2002 the mandated threshold was exceededwith 52% of teachers meeting the requirement. By 2011, 85% ofteachers had an AA degree or more, and further, 52% of Head Startteachers held a four-year college degree, up from just 23% in 1999.

As shown in Fig. 1, Head Start’s increase in teacher educationlevels outpaced changes in the educational attainment of the U.S.Population age 25–29 nationwide which is somewhat puzzling,given the constrained budget environment. As discussed above,one hypothesis is that Head Start programs that saw increasesin their teacher education levels did so by making programmaticchanges. A survey of 477 Head Start program directors conducted in2008, explored how programs were operating given more stringentquality requirements but no additional resources (Allen & Smith,2008). The findings from that survey support the hypothesis thatprograms adjusted other aspects of their operations in order tomeet requirements. For instance, 78% reported that they eliminatedstaff positions and reassigned job responsibilities, 23% reportedincreasing class sizes, and 36% reported reducing programs forfamilies (e.g. GED assistance, career development). The purpose ofthis paper is to explore the relationship between increased educa-tion levels and programmatic changes more rigorously, leveragingwithin-program fixed-effects models.

3. The current paper

This study adds to a small, related literature investigatingwhether efforts to improve quality in early childhood settingsare associated with unintended consequences or programmaticchanges. Blau (2007) measures the effects of tougher quality reg-

ulations on day care centers and finds that the costs associatedwith meeting these requirements are transferred over to the childcare workers in the form of lower earnings. Hotz and Xiao (2011),show that while child care regulations do lead to improvements

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n care quality, they also lead to closures of centers, particularlyn communities serving low-income children. The current studyontributes to this existing literature by considering this issue ofnintended consequences within the context of Head Start, a large,ublic program. It does so over a period in which quality improve-ents were an explicit priority and budgets were constrained. In

ddition, the study leverages a rich, longitudinal dataset cover-ng programs nationwide and includes more detailed informationbout staff and service provision than is typically available.

I first ask whether programs that experienced gains in theducation levels of their teachers made changes with respect torogram scope. As discussed above, the mission of Head Start iso promote school readiness through the provision of compre-ensive services including education, health, nutrition and familyupport services. Indeed, the program is often distinguished fromther public, early childhood education programs for its broadercope (Gormley, Phillips, Adelstein, & Shaw, 2010). I hypothesizehat given limited resources and a requirement to raise teacherducation, programs may reduce service provision. I use six meas-res of health and social service provision and examine whether

ncreases in the education levels of Head Start teachers are asso-iated with reductions in the provision of these services. Recentesearch shows that the Head Start program had long-term impactsn non-educational outcomes such as health and mortality, anduggests that the elimination of such services may have negativemplications for children (Deming, 2009; Ludwig & Miller, 2007).

Next, I explore whether Head Start programs that increasedeacher education levels made changes with respect to otherspects of their staffing, such as the number of teachers they employr the percentage of staff members that is classified as a teacher.ote that Head Start programs could increase the percentage of

eachers with degrees in a number of ways, for instance, by incen-ivizing or aiding existing teachers to acquire the necessary degreer by replacing existing teachers with teachers who already possesshe degree. They could also increase the percentage of teachers with

BA simply by eliminating positions held by teachers without a BAr by reclassifying these teachers into other (non-teacher) roles.he data used for this study does not allow me to track individ-al teachers over time to parse out the exact mechanism by whichead Start programs changed the composition of their teaching

taff. However, I do observe a number of related program-levelharacteristics including the number of teachers employed, thehild–teacher ratio, the rate of teacher turnover, and the percentagef the staff classified as teachers.

If programs raised teacher education levels by firing or reclassi-ying teachers who lacked the desired degree, we might expect toee a drop in the number of teachers, or a shifting of the staff towardon-teaching positions. The extent to which Head Start programsould pursue such a strategy is constrained because Head Start pro-rams regulate group size and child–teacher ratios. For instance,ead Start allows no more than 20 children in a classroom and

pecifies each classroom must be staffed by a teacher and aide orwo teachers. Nevertheless, the regulations do leave some room forhese types of staffing changes, which are worth examining due toheir hypothesized link to child outcomes.

Child–teacher ratios are a commonly regulated structural fea-ure of child care settings, and a number of advocacy organizationsecommend low ratios as a way to ensure quality interactionsithin classrooms (Barnett et al., 2011). These regulations are sup-orted by research showing child–adult ratios in early childhoodettings are associated with observed classroom quality, with chil-ren’s learning gains, and with longer-term outcomes like the

ikelihood of attending college (Burchinal et al., 2000; Chetty et al.,011; NICHD Early Child Care Research Network, 2002). Simi-

arly, several recent studies show that teacher instability negativelympacts children’s learning both in early childhood and in K-12

Quarterly 28 (2013) 831– 842 833

settings (Ronfeldt, Lankford, Loeb, & Wyckoff, 2011; Tran & Winsler,2011).

Finally, I explore whether raising the educational requirementsof Head Start teachers had the unintended consequence of chang-ing the racial composition of the teacher labor force and whetherit is related to a drop in the employment of current or former HeadStart parents. Fuller, Livas, and Bridges (2005) estimate that 47% ofCalifornia’s center-based care staff were non-Latino White in con-trast to California’s K-12 system where 74% of all teachers werenon-Latino White (Fuller et al., 2005). If this difference is drivenby stricter education requirements in the public school system,increases in the requirements for Head Start teachers may impactthe racial composition of their teaching force.

This is because Black and Latino child care workers, on aver-age, have lower levels of education and are less likely to enroll indegree programs relative to their White counterparts (Ackerman,2005; Early & Winton, 2001; Maxwell, Lim, & Early, 2006). Black andLatino individuals are also particularly under-represented amongfour-year Early Childhood degree completers. For instance, theauthor’s calculations using the Integrated Postsecondary EducationData System show that in 1999, the year that the current anal-ysis begins, 79% of Early Childhood BA completers were white, 8%were Black and 7% were Hispanic. In contrast, among AA completersthese figures were 66%, 15% and 11%, respectively. The figures sug-gest that efforts to either raise existing teachers’ education levels orrecruit new teachers with degrees may lead, unintentionally, to awhitening of the Head Start teaching force, particularly as programsraise the percentage of BA-level teachers.

A shift in the racial and ethnic composition of the Head Start staffmay have important implications if a shared racial or ethnic back-ground between students and teachers impacts students’ learning.The evidence on the importance of racial congruence for children’slearning in early childhood settings is mixed. A number of studiesindicate that early childhood teachers rate their relationships withstudents more positively when they share the child’s ethnicity, andthat teachers also form more attached relationships with childrenwho match their ethnicity (Howes & Shivers, 2006; Murray, Murray,& Waas, 2008; Saft & Pianta, 2001). However, using data from twolarge studies of early childhood care, Burchinal and Cryer (2003),found no evidence that child–teacher ethnic match was associatedwith child outcomes, a finding echoed in other studies (Ewing &Taylor, 2009).

As a final measure, I consider the percentage of current andformer Head Start parents employed on the staff. Head Startprograms have a long history of involving parents in program oper-ations and the program’s performance standards require all HeadStart programs provide parents with opportunities to become vol-unteers or staff at the program (Zigler, Styfco, & Gilman, 1993). Tothe extent that Head Start parents are relatively less likely to holdor attain a degree, efforts to raise teacher education may result inless parents on staff. Like racial and ethnic congruence, the per-centage of Head Start parents on staff can be thought of as a crudeproxy for shared beliefs, expectations, and environments (Shivers,Sanders, Wishard, & Howes, 2007). However, Barbarin, Downer,Odom, and Head (2010) explicitly examine congruence betweenparents and teachers with respect to child-rearing beliefs and findthat shared beliefs do not translate into more effective settings foryoung children.

4. Method

4.1. Participants

Data for this analysis come from Program Information Reports(PIR), which are mandatory, program-level surveys collected from

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34 D. Bassok / Early Childhood Re

ll Head Start programs annually. The terms “Head Start programs”nd “programs” are used to refer to “Head Start delegates.” Headtart is made up of 10 regional offices and two offices that serveigrant populations and Native Americans. These offices award

ederal grants to public or private agencies (grantees) that canirectly operate centers, or can pass some or all of their responsibil-

ty to delegate organizations which are also local agencies. In turn,elegates may operate any number of actual Head Start centers.he delegate-level administrative data utilized for this study arehe finest-grained longitudinal data collected about Head Start pro-rams nationwide. I constructed a 13-year panel covering the fulluniverse” of Head Start programs in each year between 1999 and011. The sample includes programs operating in the 50 U.S. statesnd Washington D.C. Programs that did not serve any childrenhrough center-based care (i.e. those that provided only home-ased care), as well as those who had no funded enrollment oro teachers on staff were eliminated. The analytic sample includes283 programs and 23,832 program-by-year observations. Of thoserograms that remain in the sample, 64% appeared in all thirteenears, and about 93% are in the data for at least two years. Sampleizes for the analyses presented range from 12,700 to 23,800 pri-arily because some outcome variables are not available in every

ear of the panel but also due to a very limited number of observa-ions with missing data.

.2. Measures

.2.1. Teacher educationPIR provide information on the number of teachers with specific

egrees (AA, BA, graduate) in each year. I use AA and BA to refer tossociate and Baccalaureate degrees which have many differentesignations (e.g. AA, AAT, BA, BS, B.Ed). Prior to 1999, data on theercentage of teachers with a BA or above is unavailable as are datan many of the study’s key outcome variables. For this reason, theurrent analysis begins in 1999. I constructed a variable measuringhe percentage of teachers with an AA or above as well as two vari-bles decomposing this group into the percentage with an AA andhe percentage with a BA or above.

.2.2. Health and social service provisionPIR include a detailed section reporting the services Head Start

hildren and their families receive. In the current analysis, I con-idered six outcomes, three that are child-focused and three thatre family focused. Although there are many additional items in theIR measuring child-directed services (e.g. the number of childrenp to date on immunizations or the number of children receiv-

ng preventative dental care), I focus on services directly providedy Head Start programs. Specifically, the child-directed measures

nclude: (1) the percentage of newly-enrolled Head Start childrenho have completed a routine screening for developmental, behav-

or, and sensory concerns; (2) the percentage who have a disabilityefined as the percentage of children with an Individualized Edu-ation Program (IEP) indicating they have been determined eligibley the LEA to receive special education and related services; and (3)he average hours per month a mental health professional spendsn site.

The PIR also include 15 items about an array of services directedoward Head Start families. Programs were asked to report theumber of families who received each of these 15 services since

ast year’s PIR, and separately to report the number of families thateceived at least one of the services. Services include the percentagef families who received English as a second language (ESL) courses,

he percentage who received emergency or crisis intervention andhe percentage who received services for substance abuse, domes-ic violence, or child abuse. The Cronbach’s alpha for these 15 itemss 0.87. I consider as outcomes: (4) the percentage of Head Start

Quarterly 28 (2013) 831– 842

families that received at least one of the family services; (5)the percentage of families that received “parenting education,”which was, throughout the period considered, the most commonfamily-directed service; and (6) a dichotomous variable measuringwhether or not the Head Start program offers programs for fathersand father figures. Data on the enrollment rates of disabled childrenare available for the full panel. Information about mental health ser-vices, parenting education, and programs for fathers are availablefor 2002–2011, for developmental screenings data is available from2002 to 2010 and for participation in at least one family service from2005 to 2011. For all these variables I use the maximum availableyears of data.

4.2.3. StaffingThe first three staffing measures are the number of teachers, the

total enrollment, and the child–teacher ratio. The number of chil-dren enrolled is defined as all children who have been enrolled inthe program and have attended at least one class or, for programswith home-based, options, received at least one home visit. Chil-dren in home-based or family child care are included in the totalenrollment measure but not the child–teacher ratio. Two additionalstaffing outcomes are considered. First, I constructed a variablemeasuring the percentage of Head Start staff that is classified asa teacher, defined as the total number of teachers divided by thetotal number of staff members. This ratio would decrease eitherif teaching positions were fully eliminated or if teaching positionswere converted into other types of staff roles. Second, I definedturnover as the number of teachers who left the program over thepast year divided by the total number of teachers. Turnover dataare only available from 2002 onwards. All other staffing variablesare available for the full panel.

4.2.4. Racial compositionPIR include items that measure the ethnic and racial compo-

sition of Head Starts’ enrollees and their child development staff.Using these data, I examine whether changes in the education lev-els of Head Start teachers over time are associated with changesin both the composition of the staff and the match between theracial background of the children and that of the staff. Each pro-gram is first asked to report the number of Head Start enrollees (orchild development staff members) who are of Hispanic or Latinoorigin, and then asked separately about their racial composition.Respondents are instructed to report each individual in both anethnicity category and a race category. I constructed three vari-ables that measure the percentage of the child development staffthat is classified as Hispanic, Black and White, as well as analogousmeasures for Head Start enrollees. Unfortunately, classroom-leveldata are not available, so racial divergence is defined crudely as thedifference between the percentage of staff members and enrolleeswho are White at the program level.

Prior to 2005, racial composition data were collected using asingle item that asked about both race and ethnicity. This changein item wording makes direct comparisons before and after 2005impossible so I limit the analysis of racial composition to sevenyears (2005–2011). A notable data limitation is that PIR ask forracial breakdowns for all child development staff combined whichincludes teachers, assistant teachers, home visitors, and familychild care teachers. Because the mandates for increased educa-tional attainment have primarily been targeted toward teachersspecifically, it would be ideal to have data on the demographiccharacteristics broken down by job category.

Finally, I construct the percentage of Head Start staff that are

current of former Head Start parents. Note that while the racevariables refer to the child development staff, the percentage ofthe staff who is a current or former Head Start parents refers tostaff more broadly including all administrative, managerial, child

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evelopment, content area, and support staff (such as custodians,us drivers, etc.).

.2.5. CovariatesAll models include time-varying controls for program character-

stics that may be related both to the education levels of teachersnd to the outcomes considered. For instance, Head Start’s programerformance standards often mandate services only for childrenho have been in the program more than 45 days. However, PIRgures about service refer to all children enrolled in the past year,

rrespective of the length of enrollment. The percentage of childrenhat were in class for less than 45 days is likely to be correlatedith a program’s service provision levels, and may also be related

o their ability to recruit and retain degreed teachers. Therefore, allodels in the paper control for this variable. Other time-varyingeasures include program size, racial composition of the enrolled

hildren, percentage of parents that are unemployed, percentagef parents enrolled in school, and percentage receiving public aideTANF, WIC), each included due to its possible correlation both withhe outcome and the explanatory variables. Not all time-varyingovariates are available for the full panel of data. In each model Iaximize the number of covariates available for the years in which

he key outcome and explanatory variable are available.

.3. Analytic strategy

This study used within-program, fixed-effects models to exam-ne associations between changes in teacher education levels overime and changes in three program characteristics (service provi-ion, staffing, and staff racial composition). Ideally, the study couldddress the question: did increases in teacher education cause Headtart programs to make changes in these other areas. However, inhe absence of experimental data, it is difficult to identify a causalelationship. This is because the education levels of teachers in Headtart programs, or changes in their education over time, may beon-random.

Fixed-effects models leverage the longitudinal nature of theead Start data, and substantially reduce the risk of omitted vari-ble bias relative to cross-sectional approaches. A cross-sectionalnalysis measures “level” associations controlling for observableovariates: For instance, do Head Start programs with relativelyigh teacher education levels provide different levels of family ser-ices relative to those with lower education levels? These typesf models have very limited causal warrant because unobservedactors may be driving any observed relationship. In contrast,xed-effects models rely on repeated measures of outcomes andxplanatory variables within programs over time, and thus measuressociations between changes rather than levels. A key advan-age of these models is that they can account for all unobserved,ime-invariant, factors. For instance, the model accounts for anyime-invariant characteristics of the surrounding labor force orime-invariant preferences held within the program.

The model estimated takes the form:

it = ˇ0 + ˇ1 Teacher Educit + ˇ2 Program Charsit + ˇ4 Yeart

+ Fixed Program Effecti + εit

Here Yit is a continuous measure of some characteristic of Headtart program i at time t, such as the percentage of Head Starthildren that receive a developmental screening or the percent-ge of the Head Start staff that is Hispanic. Teacher Educit is the

ey explanatory variable of interest, the percentage of the teacherst program i who hold a particular degree (e.g. an AA or above) inear t. I also control for a set of time-varying program characteristicsescribing the Head Start programs (e.g. enrollment, demographic

Quarterly 28 (2013) 831– 842 835

characteristics). The model includes a set of “year” dummies (omit-ting the initial year) which account for secular trends over time inthe outcome variable. The fixed program effect captures all time-invariant factors that affect the outcome and εit is the residual error.The standard errors in this model are adjusted for clustering atthe program level across years. The key coefficient of interest isˇ1 which measures the association between the education levelsof Head Start teachers and the various Head Start program char-acteristics. Note that time-invariant covariates such as the regionor physical setting in which the program operates are excluded asthey are “fixed” within units.

I present two models for each outcome. In one, the key explana-tory variable of interest is the percentage of teachers with an AA orabove. In the other, this measure is disaggregated into two sub-components: the percentage with an AA and the percentage ofteachers with a BA or above. Presenting the data this way allows meto first measure the overall association between degree attainmentand program outcomes, and then examine whether evidence ofprogrammatic changes differed by degree type. In general, recruit-ing and retaining teachers with a 4-year degree is hypothesized tobe more costly for programs and therefore yield greater associa-tions with programmatic changes.

5. Results

Results are presented in four sections. First, descriptive trendsare discussed to highlight the change in teacher education levelsover time and to describe trends in the outcome variables. Theremaining three sections explore whether these changes in teachereducation levels are associated with changes in: (1) service provi-sion, (2) staffing decisions, and (3) the racial composition of thechild development staff.

5.1. Descriptive trends

Table 1 provides program-level descriptive statistics for teachereducation levels as well as other program characteristics. Duringthe 13 years covered by this panel, the percentage of teachers withan AA or above nearly doubled from 46% in 1999 to 86% in 2011.These figures are averages of program-level data and are thereforeslightly different from the data presented in Fig. 1 which showsthe percentage of teachers at the national level who have acquiredcertain degrees. A substantial portion of this change was driven byincreases in the percentage of teachers with a BA or above whichalso rose, from 30% to 55% over the same period.

The next panel of Table 1 highlights trends in service provision.In all but one case, an increase in service provision is evident. MostHead Start children are screened for developmental and behav-ioral issues, with the percentage rising from 86% in 2002 to 90 in2010 (Comparable data on screenings are not available in the 2011PIR). These high rates are perhaps not surprising given that HeadStart programs are required to screen all children within 45 days ofenrollment. Head Start performance standards also mandate thatat least 10% of each program’s total enrollment be made available tochildren with disabilities. Programs exceed this requirement withdisabled children making up approximately 13 or 14% of enrolledchildren in each year of the panel. There has been a marked increasein the percentage of Head Start families that received parentingeducation up to 54% from 33 in 2002.

The third panel shows that both the number of teachersemployed at Head Start programs and program enrollment have

increased over time. That said, the child–teacher ratio has gradu-ally dropped from 20 to 18. Turnover rates have varied over time,with the highest observed turnover in 2002, and the lowest in 2010(17% versus 12%).

836 D. Bassok / Early Childhood Research Quarterly 28 (2013) 831– 842

Table 1Descriptive statistics, program-level trends in key explanatory and outcome variables.

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Number of programs 1859 1832 1846 1874 1882 1879 1854 1864 1819 1786 1778 1787 1772

Teacher educationTeach AA+ 45.6 45.4 48.3 57.7 63.0 70.7 75.0 77.6 79.8 79.8 82.4 83.6 86.0

(34.1) (32.4) (31.4) (30.4) (28.9) (26.5) (24.6) (23.6) (23.0) (23.1) (22.5) (21.7) (20.0)Teach AA 16.0 17.4 19.4 23.4 27.2 31.3 33.8 33.9 34.2 33.8 33.5 32.3 31.4

(21.5) (21.7) (21.6) (23.0) (24.5) (26.0) (26.9) (27.0) (27.2) (26.7) (26.6) (25.9) (25.2)Teach BA+ 29.6 28.0 28.9 34.3 35.9 39.4 41.3 43.7 45.6 46.0 48.9 51.3 54.6

(32.1) (31.5) (31.5) (32.5) (32.6) (32.5) (32.7) (32.8) (32.7) (32.3) (32.2) (31.3) (30.7)

Child and family servicesDevelopmental screening 86.0 85.9 85.6 87.4 88.9 89.9 89.3 90.8 89.8

(25.5) (25.8) (26.5) (24.8) (21.7) (20.0) (19.8) (14.7) (15.6)Disabilities 14.0 13.7 13.8 13.3 13.3 13.5 13.6 13.1 13.2 13.2 12.9 12.6 12.8

(7.1) (7.1) (7.3) (7.4) (7.0) (7.5) (7.8) (7.3) (7.2) (7.3) (7.5) (7.1) (7.0)Mental health hours 48.5 48.2 50.0 48.7 48.7 51.8 54.7 51.8 51.1 52.3

(128.1) (127.5) (94.8) (92.9) (93.7) (94.7) (127.6) (107.2) (106.7) (123.6)Family services 66.8 70.6 71.4 74.0 74.9 76.5 78.7

(29.0) (29.0) (29.3) (27.8) (28.7) (28.1) (26.9)Parenting education 33.3 34.0 34.7 38.6 42.5 43.5 46.8 49.3 52.1 53.9

(34.5) (34.2) (34.6) (35.9) (36.9) (37.6) (37.3) (38.0) (37.7) (37.7)Programs for fathers 74.4 80.9 81.6 85.8 87.1 87.5 87.1 87.6 88.3 88.4(binary) (43.7) (39.3) (38.8) (35.0) (33.5) (33.1) (33.6) (32.9) (32.1) (32.0)

Staffing# of teachers 20.9 21.0 22.3 23.7 25.0 24.8 25.0 25.4 25.5 26.1 26.0 27.0 27.1

(29.2) (28.3) (29.2) (31.8) (34.2) (33.1) (34.8) (36.7) (37.8) (38.9) (39.1) (40.4) (41.3)Enrollment 442.3 452.8 462.6 479.3 494.6 497.5 502.0 510.0 511.9 522.1 518.4 527.0 527.6

(556.0) (561.4) (603.8) (637.5) (661.6) (664.1) (665.1) (683.2) (685.8) (703.5) (682.9) (699.5) (699.9)Child/tchr ratio 19.8 19.7 18.9 18.4 17.8 17.8 17.6 17.4 17.5 17.4 17.5 17.5 17.6

(9.5) (7.5) (6.8) (6.7) (6.2) (6.6) (6.1) (6.1) (6.0) (5.5) (5.5) (5.5) (5.5)% staff, teachers 25.6 25.1 24.6 23.9 24.3 24.3 24.0 23.8 24.2 24.3 24.2 24.6 24.4

(9.4) (8.6) (8.7) (9.1) (9.0) (9.0) (8.7) (8.6) (8.8) (8.7) (8.6) (9.0) (8.7)Turnover 16.8 14.7 15.1 16.1 15.9 15.9 16.6 13.5 11.9 13.2

(19.9) (17.9) (18.3) (18.4) (18.0) (17.9) (17.7) (15.9) (14.7) (15.7)

Racial compositionStaff, white 51.8 53.7 54.3 53.9 56.2 56.3 57.2

(37.4) (37.6) (37.7) (38.0) (37.4) (37.4) (36.9)Enrlmnt,white 40.6 43.5 43.2 43.5 44.3 44.8 45.4

(35.1) (35.6) (35.3) (35.4) (35.4) (35.3) (35.3)Difference 11.2 10.2 11.2 10.4 11.9 11.5 11.9(White staff − white

enrollment)(21.5) (22.1) (21.0) (21.1) (20.0) (21.0) (20.0)

Staff, black 24.6 24.3 23.9 23.4 23.4 23.1 22.6(31.7) (31.7) (31.5) (31.3) (31.4) (31.1) (30.6)

Enrlmnt black 25.8 25.3 24.8 24.4 24.4 23.9 23.4(31.2) (31.0) (30.6) (30.5) (30.4) (29.8) (29.5)

Difference -1.2 -1.0 -0.9 -0.9 -1.0 -0.8 -0.8(Black staff − black

enrollment)(12.4) (12.3) (13.3) (12.7) (12.4) (12.3) (12.6)

Staff hispanic 19.2 19.8 19.6 19.7 19.9 19.8 20.1(27.4) (27.9) (27.8) (27.8) (27.7) (27.4) (27.3)

Enrlmnt hispanic 26.5 28.0 28.2 28.3 28.9 29.2 29.7(30.9) (31.2) (31.1) (31.0) (31.2) (31.1) (31.2)

Difference −7.3 −8.2 −8.7 −8.6 −9.0 −9.4 −9.6(Hispanic staff − hispanic

enrollment)(16.8) (18.1) (17.9) (16.6) (17.4) (16.2) (16.0)

% staff, parents 31.8 32.3 31.1 29.7 29.1 28.8 28.6 28.3 28.3 28.1 28.8 28.4 28.3(19.1) (18.8) (18.6) (18.3) (19.0) (18.4) (18.3) (18.5) (17.8) (17.8) (18.2) (17.7) (17.7)

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otes: Program-level means, standard deviations in parentheses. Children in home-o teacher ratio.

The final panel shows that in 2005, roughly 41% of Head Startnrollees were White and that Black and Hispanic children com-rised just over a quarter of enrollees each. Recall that race andthnicity are separated on the PIRs such that the White andlack categories will include Hispanic individuals and vice versa.etween 2005 and 2011, the percentages of White children enrolled

ncreased from 41 to 45%, as did the percentage of Hispanic stu-

ents, from 27 to 30%. Over the same time period, the percentagef staff that is White also increased from 52 to 57%. The racialivergence variable, which measures the difference between theercentage of staff and the percentage of students that are White,

or family child care are included in the total enrollment measure but not the child

fluctuates between 10% and 12% points in every year, indicating thatat the program level, White staff members are overrepresented rel-ative to White enrollees in every year. The percentage of parentsemployed as staff members has gradually fallen from 32 to 28%.

5.2. Teacher education and service provision

Table 2 shows results from 12 within-program, fixed effectsmodels estimating whether changes in teacher education levels arerelated to changes in service provision. For each of six outcomes,I present results from two models. In the first, the explanatory

D. Bassok / Early Childhood Research Quarterly 28 (2013) 831– 842 837

Table 2Within-program fixed effects models estimating changes in Head Start service provision.

Developmental screening Disabilities Mental health professional (hours)

(1) (2) (3) (4) (5) (6)

Pr. Tchrs AA+ 0.020 −0.003 0.088*

(0.015) (0.003) (0.040)

Pr. Tchrs AA 0.021 −0.005 0.012(0.017) (0.004) (0.047)

Pr. Tchrs BA+ 0.018 0.001 0.186**

(0.018) (0.005) (0.064)

Observations 16,522 16,522 18,289 18,289 18,231 18,231R-squared 0.268 0.268 0.702 0.702 0.533 0.534Years 2002–2010 2002–2010 2002–2011 2002–2011 2002–2011 2002–2011

Families receiving at least one service Parent education Programs for fathers

(7) (8) (9) (10) (11) (12)

Pr. Tchrs AA+ 0.043 0.068*** 0.041(0.023) (0.020) (0.023)

Pr. Tchrs AA 0.012 0.042 0.039(0.028) (0.023) (0.026)

Pr. Tchrs BA+ 0.076*** 0.102*** 0.043(0.026) (0.024) (0.026)

Observations 12,655 12,655 18,289 18,289 18,287 18,287R-squared 0.581 0.581 0.560 0.560 0.420 0.420Years 2005–2011 2005–2011 2002–2011 2002–2011 2002–2011 2002–2011

Notes: Sample sizes vary across regressions due to changes in item availability in the PIR surveys. All models include program fixed effects as well as controls for availabletime-variant covariates as discussed in the paper. Robust standard errors in parentheses.

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ariable of interest is the percentage of teachers with an AA orbove. The second model shows results when this variable isecomposed into the percentage with an AA and then the percent-ge with a BA or above. A negative coefficient on any of the teacherducation variables indicates that programs in which the percent-ge of teachers with degrees rose also saw declines in servicerovision. None of the models suggest this relationship. For fivef six outcomes, the coefficients are positive, and the negativeoefficients in the model predicting enrollment of children withisabilities are practically small and statistically insignificant.

Contrary to the hypothesized negative relationship, as the per-entage of teachers with a BA increased, certain types of servicerovision rose as well. For instance, a 1 percentage point increase ineachers with a BA is associated with a 0.186 h (or roughly 11 min)ncrease in the reported time a mental health specialist is available

ithin a center. Put another way, a standard deviation increase inhe percentage of teachers with a BA, which is equivalent to anncrease of about 32 percentage points, is associated with aboutix extra hours of mental health services per month (32 × 0.186), aeaningful increase over the baseline level of approximately 49 h.

imilarly, a standard deviation increase in the percentage of tea-hers with a BA is associated with about a 3 percentage pointncrease in the percentage of families who receive at least oneervice and those who receive parental education. Overall then, thisodel suggests that changes in teacher education levels did not

ead to reductions of child and family services. All models yieldedull or positive findings and indicate that increases in teacher edu-ation – particularly teachers with a BA – are at times associatedith increases in several types of service provision.

.3. Teacher education and staffing

Table 3 presents results from similar fixed-effects models exam-ning the relationship between teacher education levels and various

measures of staffing. The top row indicates that programs thatexperienced increases in teacher education also saw statisticallysignificant drops in the number of teachers employed, but nochanges in enrollment levels. Models 5 and 6 show that takentogether, these two trends imply a modest but statistically signif-icant increase in the child–teacher ratio. A one-percentage-pointincrease in the percentage of teachers holding an AA or aboveamounts to a 0.02 percentage point increase in the ratio. This meansthat a standard deviation increase in teachers with AA or above,equivalent to an increase of about 34 percentage points, amounts toan increase of about one child (0.68) per teacher. A similar increasein teacher education levels is also associated with about a 1 per-centage point drop (1.08) in the percentage of staff classified asteachers.

The final two models indicate that increases in teacher educa-tion are also related to increases in turnover. A standard deviationincrease in teachers with an AA or above is associated with abouta 1 percentage point (0.85) increase in turnover, over a baselinelevel of about 17%. Model 10 shows this pattern is driven primaryby the increases in teachers with a BA or above. Taken together,the results in Table 3 show that programs in which teacher educa-tion increased also saw increases in both child–teacher ratio and inteacher turnover.

5.4. Teacher education and racial composition of staff

The top panel of Table 4 shows that increases in the percentageof teachers with a college degree are associated with a “whitening”of the child development staff. Models 2, 4 and 6, which disaggre-gate degree attainment show that this pattern is specifically driven

by the increases in teachers with a BA or above, and not by increasesin teachers with a two-year degree. A standard deviation increasein the percentage of teachers with a BA is associated with about a2 percentage point increase in the percentage of staff classified as

838 D. Bassok / Early Childhood Research Quarterly 28 (2013) 831– 842

Table 3Within-program fixed effects models estimating changes in Head Start staffing.

Number of teachers Enrollment Child/teacher ratio

(1) (2) (3) (4) (5) (6)

Pr. Tchrs AA+ −0.023** 0.125 0.022***

(0.007) (0.099) (0.003)Pr. Tchrs AA −0.032*** 0.091 0.026***

(0.009) (0.107) (0.003)

Pr. Tchrs BA+ −0.013 0.167 0.016***

(0.008) (0.111) (0.004)

Observations 23,825 23,825 23,825 23,825 23,825 23,825R-squared 0.936 0.936 0.965 0.965 0.654 0.655Years 1999–2011 1999–2011 1999–2011 1999–2011 1999–2011 1999–2011

Percent of staff who are teachers Turnover rates

(7) (8) (9) (10)

Pr. Tchrs AA+ −0.032*** 0.025*

(0.004) (0.012)

Pr. Tchrs AA −0.033*** 0.011(0.004) (0.014)

Pr. Tchrs BA+ −0.030*** 0.043**

(0.005) (0.016)−0.032***

Observations 23,825 23,825 18,289 18,289R-squared 0.599 0.599 0.359 0.359Years 1999–2011 1999–2011 2002–2011 2002–2011

Notes: Sample sizes vary across regressions due to changes in item availability in the PIR surveys. All models include program fixed effects as well as controls for availabletime-variant covariates as discussed in the paper. Robust standard errors in parentheses.

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hite, a 1 percentage point drop in the percentage of staff classifieds Hispanic and a slightly smaller (0.67) drop in the percentage oftaff that is Black. Similarly, the findings on racial divergence indi-ate that as programs increased the percentage of teachers with aegree, divergence, defined as the program-level difference in theercentage of staff members and enrollees that are white, broad-ned. In other words, the increase in white workers at these centersas not accompanied by a similar increase in white enrollees.

The final models indicate that increases in teacher educationere also accompanied by drops in the percentage of Head Start

taff members who were current or former parents. Here too theelationship is driven by changes in the percentages of teachersith a BA. A standard deviation increase in the percentage of tea-

hers with a BA is associated with about a 1.6 percentage pointecrease in the percentage of staff that is Head Start parents.

. Discussion

Between 1998, when the Head Start reauthorization took place,nd 2011, the percentage of teachers with an AA or above morehan doubled. The percentage of teachers with a BA or abovelso rose substantially, and in 2011 it surpassed the 50% mark.his study used a rigorous, within-program fixed-effects model toxamine whether programs that experienced changes in teacherducation levels also experienced changes with respect to otherrogrammatic characteristics including child and family servicerovision, staffing, and the racial and ethnic composition of thetaff. Taken together, this study provides suggestive evidence thatfforts to improve quality in Head Start programs through height-ned education requirements for teachers may yield unintended

onsequences, a finding that is consistent with earlier research onhe impacts of quality regulations in the child care industry (Blau,007; Hotz & Xiao, 2011). That said, for the most part, the observedrade-offs were modest in magnitude.

6.1. Service provision

Encouragingly, the study shows that Head Start programs thatraised their teachers’ education levels did so without sacrificingprogrammatic scope as measured by several service provision indi-cators. Head Start service provision actually increased over thestudy period. The study demonstrates that those programs thatincreased their teacher education levels did not experience a dif-ferential drop in health or social service provision. On the contrary,in some cases, increases in teacher education within programswere positively associated with service provision. For instance, pro-grams that increased the percentage of teachers with a BA also sawincreases in the number of hours a mental health professional wasavailable and the percentage of families that experienced at leastone support service.

This paper hypothesized that given constrained budgets, someprograms that raised their teachers’ educational attainment woulddo so through drops in service provision. There is no evidence ofthis pattern and instead the results raise the possibility that degreedteachers and service provision may act as complements. This unex-pected result is heartening given recent quasi-experimental studieswhich provide compelling evidence that Head Start has substantiallong-term impacts on a number of non-cognitive outcomes suchas health and mortality (Gibbs, Ludwig, & Miller, 2011; Ludwig &Miller, 2007). For instance, Deming (2009) finds that as adults, HeadStart participants are several percentage points less likely to be inpoor health relative to their siblings who did not participate in theprogram. The comprehensive services the Head Start program pro-vides to children and their families are plausible partial explanationfor these effects. It may be that teachers with higher educational

attainment are able to help families access these services.

One caveat worth highlighting is that the available PIR itemsdo not measure the intensity of service provision with muchnuance. The survey indicates, for example, the number of Head Start

D. Bassok / Early Childhood Research Quarterly 28 (2013) 831– 842 839

Table 4Within-program fixed effects models estimating changes in the racial/ethnic composition of Head Start child development staff.

Hispanic staff Black staff White staff

(1) (2) (3) (4) (5) (6)

Pr. Tchrs AA+ −0.017 −0.008 0.036**

(0.011) (0.006) (0.013)

Pr. Tchrs AA −0.002 0.004 0.014(0.013) (0.007) (0.015)

Pr. Tchrs BA+ −0.031** −0.021** 0.059***

(0.012) (0.008) (0.015)

Pr Enr hispanic 0.105** 0.105** −0.005 −0.006 0.029 0.030(0.036) (0.036) (0.009) (0.009) (0.019) (0.020)

Pr Enr black −0.037 −0.037 0.185*** 0.185*** −0.271*** −0.271***

(0.024) (0.024) (0.040) (0.040) (0.039) (0.039)

Observations 12,655 12,655 12,655 12,655 12,655 12,655R-squared 0.925 0.925 0.971 0.971 0.907 0.908Years 2005–2011 2005–2011 2005–2011 2005–2011 2005–2011 2005–2011

Staff/child racial divergence Percentage of parents on staff

(7) (8) (9) (10)

Pr. Tchrs AA+ 0.038* −0.020**

(0.015) (0.007)

Pr. Tchrs AA 0.026 −0.002(0.018) (0.008)

Pr. Tchrs BA+ 0.051** −0.042***

(0.017) (0.008)

Observations 12,655 12,655 23,825 23,825R-squared 0.562 0.563 0.721 0.722Years 2005–2011 2005–2011 1999–2011 1999–2011

Notes: Sample sizes vary across regressions due to changes in item availability in the PIR surveys. Staff racial composition refers to the child development staff, which includesteachers, assistant teachers, home visitors and family child care teachers. Racial divergence is defined as the difference between the percent of the staff and enrollees thatare White. All models include program fixed effects as well as controls for available time-variant covariates as discussed in the paper. Robust standard errors in parentheses.

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*** p < 0.001.

amilies who have participated in parental education programs, butoes not measure the frequency, length, or quality of these ses-ions. If programs made changes along this “intensity” margin, theesults of this study would not capture them. Still, the lack of anverall drop in service provision across a number of outcomes isncouraging.

.2. Staffing

On the other hand, the current results do suggest that programshat increased the percentage of teachers with degrees also sawmall drops in the number of teachers employed, but no changesn the number of children enrolled. As a result, child–teacher ratiosose modestly; a standard deviation increase in the percentage ofeachers with AA or above, which is equivalent to an increase ofbout 34 percentage points in teachers with degrees, was asso-iated with an increase of less than one child (0.68 children) pereacher. Head Start performance standards clearly regulate groupizes and ratios allowing no more than 20 children in a class-oom and specifying each classroom must be staffed by a teachernd aide or two teachers. These regulations limit the extent tohich programs could eliminate teaching positions as a strategy

or raising the percentage of teachers with a degree. Neverthe-ess, the modest but statistically significant negative relationships notable due to the research evidence showing that class sizes

nd child–teacher ratios in preschool and kindergarten are relatedo a number of short and long-term child outcomes includingigh school completion (Burchinal et al., 2000; Chetty et al., 2011;ICHD Early Child Care Research Network, 2002). While the small

change observed in the current study likely had a modest impact forenrolled children, in contexts where ratios and group size are lessstrictly regulated, efforts to raise teacher degrees may have largerimpacts.

The results also show that increases in teacher education, partic-ularly the percentage of teachers with a four-year degree are relatedto increases in turnover. This pattern is not surprising, as efforts toincrease teacher education levels likely rely, in part, on replacingexisting teachers with individuals who hold the required degree.By definition, this process will lead to some turnover. Researchsuggests that increases in turnover have negative implications foryoung children (Ronfeldt et al., 2011; Tran & Winsler, 2011). How-ever, evidence from the existing turnover literature suggests thatthe initial turnover may be short-lived, if the degreed teachers whoare placed in classrooms are more stable than those teachers theyreplace. For instance, Whitebook and Sakai (2003) found that highlytrained early childhood teachers were less likely to turnover in sett-ings in which a higher percentage of the teaching staff held a BA.Future research is warranted to investigate whether Head Start’smove toward more educated teachers ultimately results in lowerrates of turnover and more stability for young children.

6.3. Staff racial and ethnic composition

In the final analysis of the paper, I examine whether changes

in the education levels of teachers are related to increases in thepercentage of child development staff that is white, the racial diver-gence between children and their teachers, and the percentageof parents employed as staff. I find evidence of all three of these

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40 D. Bassok / Early Childhood Re

atterns. In most, though not all, cases, the change is driven byncreases in the percentage of teachers with a BA or above, ratherhan those with a two-year degree. Again, this pattern is not sur-rising, given that white early childhood educators tend to haveore years of education than their Black or Hispanic peers, and

hat white individuals are overrepresented among individuals whoither enroll in or complete a four year degree program (Ackerman,005; Early & Winton, 2001; Maxwell et al., 2006). Nevertheless,his paper is the first to empirically document that moving toward

more degreed teaching staff is associated with a whitening ofhe teaching force, a concern that is voiced in the early childhoodommunity. For instance, Washington (2008) describes a sensef ambivalence among the early childhood workforce about theeightened focus on degree requirements and indicates there is aerceived tension between degree acquisition and the fields’ com-itment to diversity.Earlier research provides insights regarding the implications

f these changes for children enrolled in Head Start. In partic-lar, Burchinal and Cryer (2003) and others find no evidencehat a racial or ethnic match is positively related to childutcomes in early childhood settings, and demonstrate that stim-lating, sensitive teachers effectively teach children, irrespectivef racial congruence (Ewing & Taylor, 2009). However, a num-er of studies do find that teachers rate their relationships withhildren more highly when they share racial or ethnic back-round (Howes & Shivers, 2006; Murray et al., 2008; Saft &ianta, 2001), and suggest that these relationships are impor-ant in shaping children’s learning trajectories. Shivers et al.2007) argue that racial and ethnic match are proxies for “culturalontinuity” which they suggest meaningfully impacts children’sevelopment.

There is also evidence from the K-12 sector that racial matchetween children and teachers impacts children’s learning tra-

ectories. It is important to note that the K-12 setting is distinctrom the early childhood one in notable ways including the higherducational requirements for K-12 teachers. That said, Dee (2004)everages random-assignment data from the Project Star classize experiment and finds that kindergarteners who are randomlyssigned to an “own-race” teacher meaningfully outperform theireers with respect to math and reading achievement. Other stud-

es tackled this question using datasets in which the same childs observed with two teachers, one who matches them raciallynd one who does not. These studies again show that school-agedhildren benefit when assigned to teachers who share their racialackground (Dee, 2005; Hanushek, Kain, O’Brien, & Rivkin, 2005).iven the mixed evidence, further research on the impacts of the

acial changes observed among Head Start’s staff on children’searning is worth pursuing.

Finally, the impact of the observed drop in parental employ-ent on staff on child outcomes is ambiguous. No study that I am

ware of has explored this issue. A decline in parental involvementn staff may lead to a loss of shared culture or belief congru-nce between staff and enrolled children and families. However,he existing empirical research suggests that belief congruence, ateast with respect to child-rearing attitudes- is not related to childutcomes (Barbarin et al., 2010). It may be that drops in parentalmployment on staff may impact children indirectly, if the wageshese positions provide are used, in part, to support children. Unfor-unately, in the current study I have no way of testing whetherrops in parental employment were related to changes in families’

ncome.More research is necessary to understand the impact of each

f the programmatic changes observed on child outcomes, ando assess how any potential costs or benefits compare to theenefits of increases in degreed teachers. That said, the cur-ent study provides a novel, preliminary look at the effects of a

Quarterly 28 (2013) 831– 842

teacher education mandate on program characteristics in HeadStart.

7. Limitations

While this paper adds to our understanding of programmaticchanges associated with increasing teacher education levels inearly childhood settings, the PIR data have several important limi-tations detailed below. As discussed above, the PIR data provide along, nationally-representative, program-level dataset with whichto study how early childhood programs change over time. How-ever, the data is self-reported by programs, and the accuracy of thereports is not verified (Levinson, 2007; Government AccountabilityOffice, 2008). If programs tend to report overly optimistic informa-tion, this would bias the results of the current study, particularly ifthe likelihood of misreporting has changed over time.

In addition, some of the items are relatively crude and do notprovide the desired specificity. For instance, the data on racialmatch is available at the program rather than classroom level,and therefore serves only as a proxy for the racial match childrenactually experience. Similarly, information about race and parentalinvolvement is reported for the child development staff and for thefull staff respectively. Ideally, this information would be availablespecifically for teachers, since they are the group of workers whowere targeted with the education mandates. Despite these limita-tions, the analysis expands our understanding of efforts to changethe early childhood labor force, as detailed below.

8. Conclusions & directions for future research

The current study provides the first large-scale, empirical exam-ination of potential program-level trade-offs associated with effortsto raise teacher education in Head Start. The findings from thispaper provide evidence of changes both with respect to staffing pat-terns (child–teacher ratios, turnover) and with respect to the staff’sracial composition, though notably not with respect to service pro-vision. In many cases, changes were primarily related to increases inthe percentage of teachers with four rather than two year degrees.Recruiting teachers with a BA or supporting current teachers as theypursue this degree seems to pose a greater challenge for Head Startprograms, a finding that is not surprising given the more limitedaccess to four year degree programs in early childhood educationor related topics (Bassok, 2010).

While the analysis focused specifically on the Head Start pro-gram, some of the overarching findings may inform a broaderconversation. In the 2013, President Obama released his plan fora preschool expansion and called for, “well-trained teachers, whoare paid comparably to K-12 staff” (White House, Office of thePress Secretary, 2013). The current study suggests that in thinkingthrough efforts to substantially change the composition of the earlychildhood labor force, it may be important to consider both directand indirect effects, including the potential for unintended conse-quences. The study is a first step toward understanding how policyinitiatives requiring higher education for early childhood educatorsmay impact programs and in turn children.

Moving forward, additional research is essential to assess howthe changes that occurred in Head Start programs, both withrespect to higher levels of teacher education and with respect to therelated staffing changes, impacted the quality of experiences youngchildren experienced and the overall effectiveness of the program.The composition of the teaching force at Head Start has changedsubstantially over the past 15 years, and studying the effects of

these changes on children will provide important lessons. Suchanalysis would also add to the existing literature on the effects ofteacher education in early childhood settings which to date haslargely leveraged cross-sectional variation in teacher education.

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The main hurdle for pursuing this work is the lack of high-uality data longitudinally tracking both the early childhood labororce and child outcomes. For instance, no large-scale dataset existsracking early childhood teacher career trajectories and the devel-pment trajectories of the children they teach. In recent years,here have been proactive efforts to improve data availabilityCommittee on Early Childhood Care & Education Workforce, 2012;overnment Accountability Office, 2012). In the meantime, how-ver, researchers and policy makers must make due with imperfectata. The PIR, even with their limitations, allow us a new win-ow into a timely research question that cannot be addressed withther existing datasets about programmatic changes that occurreds Head Start raised teacher education.

Though not longitudinal, existing data such as the Head Startamily and Child Experiences Survey, which includes five repeatedross-sectional analyses of Head Start children and programs from999 to 2009, may provide some insights about the relationshipetween changes in teacher characteristics and child outcomes,articularly if these data could be linked to the rich PIR data. Inddition, more qualitative work including structured interviewsith program directors could help validate and contextualize thendings of the current study. This type of work would help answerome of the process questions that the current study leaves unan-wered about the specific strategies used to raise teacher education,he roadblocks encountered, etc.

The current study demonstrates that efforts to raise the edu-ational attainment of Head Start teachers are associated withhanges in other programmatic features. The results are policy-elevant both because of the potential for direct implications fromhese changes for children and because they raise the possibil-ty that the unintended consequences associated with efforts toaise teacher attainment at Head Start may moderate the rela-ionship between teacher degrees and child outcomes. Futurefforts to measure the benefits of policies aimed at a moreducated early childhood labor force should account for the pos-ible costs associated with recruiting and retaining teachers withegrees.

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