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Monetary returns to academic ability in the public teacher labor market
Economics of Education Review 28 (2009) 277–285
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Monetary returns to academic ability in the public teacher labor market Daniel Player ∗ Mathematica Policy Research, Inc., P.O. Box 2393, Princeton, NJ 08543-2393, United States
a r t i c l e
i n f o
Article history: Received 19 October 2006 Accepted 26 June 2008 JEL classification: J31 J45 I20 Keywords: Human capital Salary wage differentials Teacher salaries
a b s t r a c t Previous research has established the returns to academic ability in the general labor market, and this paper investigates such returns in the teacher labor market. Using a nationally representative sample of public school teachers, I find that teachers who graduate from the most selective undergraduate institutions have salaries that are between 7% and 14% higher than those who graduate from the least selective colleges. An empirical investigation of the source of these returns reveals that the majority of this difference is due to highability teachers sorting into higher paying districts, though a non-trivial amount arises from within-district deviations from the salary schedule. © 2008 Elsevier Ltd. All rights reserved.
1. Introduction Some policymakers and researchers have been critical of this rigid pay structure in public school districts, arguing that it does not provide incentives for highly productive teachers. However, the presence of salary schedules alone does necessarily eliminate the possibility that teachers receive premiums; schedules differ from one district to another and highly productive teachers may have an advantage of sorting into higher paying districts. Also, within districts, administrators may have some flexibility to raise salaries above the schedule by giving certain teachers the opportunity to earn extra compensation for additional responsibilities (such as summer teaching or extracurricular assignments) or by crediting them with additional education or experience. Thus, even rigid salary structures without explicit “merit pay” programs may lead to pay differentials for highly skilled teachers. The purpose of this paper is to investigate whether the teacher labor market rewards certain teachers by examining the monetary
∗ Tel.: +1 609 799 3535. E-mail address: [email protected]. 0272-7757/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.econedurev.2008.06.002
returns to one observable teacher characteristic that has been shown to be correlated with student achievement: academic ability. The results of this paper demonstrate that teachers receive premiums for academic ability (as measured by the selectivity of the college from which they graduate) despite the rigid salary structure. Estimates indicate that teachers who graduate from the most selective colleges receive a premium of between 7% and 14% that arises largely from sorting between districts. However, there is also consistent evidence that teachers from more selective colleges also receive within-district premiums. These within-district premiums may account for up to 34% of the total return to academic ability. These findings have important implications for how we view the teacher labor market. They suggest that whether or not a district uses merit pay, teachers with greater academic ability receive premiums in the teacher labor market. Thus, concerns of inequity that often fuel resistance to wage reform are already realized. However, it is notable that the vast majority of these premiums are from sorting between districts. To the degree that the differences in academic ability reflect true differences in teacher quality, the sorting of teachers perpetuates inequities for disadvantaged
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students that would not be observed if all the salary differentials were within, rather than between, districts. 2. Background Public school teachers have come under scrutiny over the last few decades because of an apparent decline in the academic ability of new hires (Corcoran, Evans, & Schwab, 2004). In light of the recent evidence that teachers’ academic proficiency affects student outcomes (Clotfelter, Ladd, & Vigdor, 2007; Goldhaber, 2007), the potential decline in teacher ability has received the attention of policymakers and lawmakers as one of the largest challenges facing the teaching profession (Bacolod, 2007; Lakdawalla, 2001). In a meta-analysis of the effects of school inputs on student achievement, Hanushek (1986) offered that a teacher’s academic proficiency appeared to be the only school input that appeared to be a relatively consistent predictor of student outcomes. Thus, the declining academic ability of the teachers entering the labor market is seen as a decline in the quality of teachers entering the profession. Given that academically talented teachers appear to be more productive, it is intuitively appealing that they have an advantage in the schools and districts into which they are hired. Likewise, teachers have preferences for higher wages and more favorable working conditions, and there is evidence that teachers seek to sort into districts according to these preferences (Hanushek, Kain, & Rivkin, 2004). The connection between teacher salaries and teacher quality has been an important subject for economists and policy researchers. Research has found a positive relationship between salaries and teacher quality (Figlio, 1997). By examining shifts in salary schedules over time and changes in the composition of the teacher labor force, research has found that teacher salaries have a significant, though small, impact on the types of teachers that are hired in a district (Figlio, 2002; Hanushek, Kain, & Rivkin, 1999), providing some empirical evidence that the relationship between salary and teacher quality is causal. No attempts have been made in previous research to quantify the returns to individual teachers either within or across districts. This paper seeks to fill this gap by offering estimates of the degree to which there is separation in teacher salaries that are correlated with a teacher’s academic ability. 3. Methodology and data The existing literature places this paper in an important context: teacher quality makes a significant difference in student outcomes and it appears to be related to the academic ability of a teacher. However, there is reason to doubt whether productive teachers receive positive premiums in the labor market because districts rely on rigid salary schedules and because schools and districts may lack incentives to hire the most qualified applicants (Ballou, 1996; Figlio, 1997; Hanushek, Kain, O’Brien, & Rivkin, 2005). The empirical work of this paper tests whether academically talented teachers receive a premium in the labor market.
3.1. Methodology For a measure of teacher aptitude, I focus on the selectivity of a college from which a teacher graduates. Unlike many papers in the labor economics literature that have examined college selectivity, the purpose of this paper is not to measure the value added of attending a selective college but rather to take college selectivity as a proxy for the teacher’s total academic ability upon entry into the teacher labor market.1 This necessarily includes the teacher’s precollege ability as well as the value that college has added. Therefore, throughout the paper I refer to “college selectivity” as a proxy for the teacher’s total academic ability. The baseline specification will be a typical earnings function, similar to Brewer, Eide, and Ehrenberg (1999). Specifically, I examine whether academic ability is a positive determinant of teacher salaries. This base model is ln Wi = ˇ0 + ˇ1 Xi + ˇ2 Cij + i
(1)
where log of total annual income (Wi ) is regressed on a vector of individual characteristics (Xi ) and the selectivity of college j (Cij ). In this construct, I use a measure of the teacher’s total annual income from the school, which includes base salary as well as any pay for extracurricular assignments, in order to capture the aggregate return. Additionally, the total annual income from school is likely less prone to measurement error since it does not require teachers to categorize the sources of their pay. Another advantage of this aggregated measure is that a potential source of differential compensation may arise through the ability to secure additional summer assignments.2 Thus, the returns to ability are to be interpreted as the total return of school-related income. At the end of the empirical section, the returns in terms of annual base salary are distinguished from returns from additional assignments. Working conditions play an important role in job satisfaction in teaching and non-teaching occupations. Teachers are sensitive to working conditions (Hanushek et al., 2004) and whether or not districts explicitly design their salary schedules to include compensating differentials, teachers in less attractive schools necessarily interpret some portion of their salary as the amount necessary to compensate them for less desirable working conditions. To explore the productivity premiums further, I also examine the extent to which the returns are due to compensating differentials for less desirable working conditions and cost of living adjustments for high cost of living areas by including controls for working conditions and local cost of living. With an aggregate measure of the returns to productivity, I disaggregate the source of the returns: between-district sorting and within-district differentials. As a first step, I isolate the interdistrict return due to
1 This is a proxy for teacher quality that has been used in other research (e.g., Figlio, 1997). 2 Opportunities for moonlighting (such as summer teaching) may be an important benefit offered to high quality teachers. For instance, Chicago Public Schools (CPS) lists “summer teaching opportunities” along with health and dental insurance as some of the benefits available to teachers (http://www.cps-humanresources.org/Careers/benefits.htm).
D. Player / Economics of Education Review 28 (2009) 277–285
sorting into higher paying districts by examining the district’s starting salary. Likewise, I examine whether high-ability teachers are able to sort into districts that have a higher growth rate in salary over time. I also investigate whether teachers from selective colleges are more likely to be matched with districts that offer deviations from the single salary schedule, and I determine whether these deviations explain academic premiums. Though the salary schedule is set at the district level, the possibility remains that teachers receive some premium within the districts where they are employed. The final empirical task is to measure within-district academic ability premiums using district fixed effects models. 3.2. Data
Table 1 Means (standard deviations) of selected variables for subgroups in the SASS 1999–2000.
SAT of college Female White Black Hispanic Advanced degree Urban district Suburban district
The primary data for the empirical work are from the Schools and Staffing Survey (SASS), a nationally representative survey of teachers, schools and districts throughout the United States. I use the most recent wave of the SASS (1999–2000) that was available at the time of this writing. The SASS teacher questionnaire asks teachers a number of questions about their experience in teaching, including their education and experience as well as their income from school and non-school sources. Among other things, the SASS district questionnaire asks the district to list four steps on the single salary schedule: the starting salary for a teacher with a bachelor’s degree, the salary for a teacher with a bachelor’s degree and 10 years of experience, the starting salary for a teacher with a master’s degree and the salary for a teacher with a master’s degree and 20 years of experience. The SASS samples schools as the primary sampling unit. After selecting the schools, it also surveys the school’s district and a sample of teachers in that school. Using the restricted version of the SASS, I am then able to match the teachers to their schools and districts. The number of teachers in the full teacher sample was 42,086. Restricting my sample to only the teachers who reported working full time reduced the sample to 38,375. I also restricted the sample to teachers who could be matched to their districts, which resulted in a sample consisting of 33,901 teachers. Because salary schedules are typically different for different education levels, and only a very small minority of teachers has either less than a bachelor’s degree or more than a master’s degree, I restricted the sample by eliminating those teachers who reported their highest degree as being less than a bachelor’s or more than a master’s degree (593 observations). As a final restriction, I dropped those teachers from the sample who reported base salaries that appear to be implausible: those reporting less than $15,000 (11 observations)3 or more than $150,000 (12 observations).4 The final sample consists of 33,285 teachers.
3 Incidentally, all teachers who reported salaries less than $15,000 reported a salary of zero. 4 The results are unchanged when including the omitted observations, though it is impossible to include the observations who report earnings of zero in log salary models.
279
Rural district Salary N
Selective
Competitive
Non-competitive
1077.0 (69.81) 63.90% (0.480) 90.63% (0.291) 3.70% (0.189) 4.76% (0.213) 53.00% (0.499) 25.21% (0.434) 50.55% (0.500) 24.23% (0.429) 41,519 (12,645)
948.9 (56.30) 67.04% (0.470) 90.68% (0.291) 3.39% (0.181) 4.06% (0.197) 44.70% (0.497) 24.71% (0.431) 42.84% (0.495) 32.45% (0.468) 39,387 (11,822)
879.4 (84.9) 67.96% (0.467) 83.55% (0.371) 10.54% (0.307) 4.86% (0.215) 39.18% (0.488) 23.57% (0.424) 29.83% (0.458) 46.60% (0.499) 35,620 (10,210)
3970
14,766
14,549
Source: Schools and Staffing Survey 2000. Notes: Standard deviations in parentheses.
The measure of academic ability for teachers is the selectivity of the college from which they received their bachelor’s degree as measured by Barron’s Profiles of American Colleges. Due to the small number of teachers graduating from each of the three most selective categories, I collapse these into a single indicator for a “selective” school, retain the Barron’s “competitive” grouping, and collapse schools from the two least selective categories into the omitted group “less competitive.”5 Because these selectivity indicators are categorical rankings, which may have changed over time, I use the mode ranking over the period 1980–1994 as a measure of the school’s typical selectivity. Because it may be unreasonable to assume that that undergraduate institution information was missing at random, I allowed these teachers (965) to be their own category.6 Table 1 shows descriptive statistics from the final sample. Not surprisingly, given the teacher labor market, most of the teachers in the sample are white and female. It is of note that teachers who graduated from selective colleges have higher salaries than those who graduated from less selective colleges. Similarly, graduates of competitive colleges earn more than graduates of non-selective colleges. A more detailed analysis of the rate of return, controlling for other factors, is described below.
5 The results are substantively unchanged if the two bottom categories are not combined, and in each case the return to the selective and competitive graduates are slightly higher when the “least competitive” category is used as the reference group. 6 In a personal communication with Kerry Gruber, a statistician at the SASS survey program, he stated that college codes are missing if a teacher does not report the college he/she attended, if he/she attended outside the USA, or if the coding staff was unable to read the name or locate the college reported by the respondent. The estimates are unchanged if the teachers with missing selectivity measures are dropped from the sample.
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Table 2 Total returns to ability for public school teachers.
Selective Competitive Secondary teacher Total experience Experience squared Master’s degree Female Black Hispanic
Ln(income)
Ln(income)
Ln(income)
0.1323 (0.0052)** 0.0961 (0.0033)** 0.0144 (0.0037)** 0.0269 (0.0006)** −0.0003 (0.0000)** 0.1316 (0.0037)** −0.0482 (0.0037)** 0.0284 (0.0060)** 0.0653 (0.0069)**
0.0935 (0.0054)** 0.0689 (0.0033)** 0.0185 (0.0035)** 0.0285 (0.0005)** −0.0004 (0.0000)** 0.1227 (0.0034)** −0.0522 (0.0038)** −0.0195 (0.0069)** 0.0208 (0.0069)** 0.1411 (0.0106)** −0.1146 (0.0128)** 0.0300 (0.0049)** −0.1175 (0.0053)**
0.0583 (0.0054)** 0.0450 (0.0030)** 0.0215 (0.0033)** 0.0297 (0.0005)** −0.0004 (0.0000)** 0.1144 (0.0032)** −0.0479 (0.0036)** −0.0074 (0.0068) 0.0189 (0.0066)** 0.0987 (0.0098)** −0.0051 (0.0132) 0.0164 (0.0048)** −0.0749 (0.0058)** 0.1490 (0.0052)**
33,285 0.47
33,285 0.54
33,285 0.58
% minority enrollment % subsidized lunch eligible Suburban district Rural district (log) Median house value Observations R-squared
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
4. Empirical results The returns to a teacher’s academic ability, as proxied by the selectivity of the college from which he or she received a bachelor’s degree, are displayed in Table 2. The graduates of the most selective colleges earn a return of 14.2% and graduates of competitive colleges earning a return of 10.1% above the graduates of less selective colleges.7,8 Based on recent estimates of average teacher salaries, this translates to an average annual premium of between $3300 and $6700.9 The coefficients for experience and education are largely unsurprising. The estimates indicate that an additional year of experience adds around 3% of salary, the returns to experience decrease with experience, and a master’s degree is worth around 14%. It is also worth noting that secondary teachers earn more than elementary teachers. This may indicate an additional premium paid for the specific skills of secondary teachers, explored below. Similarly, consistent
7 Recall that coefficients on dummy variables in semi-log equations cannot be interpreted directly as percentage changes without the appropriate transformation (Halvorsen & Palmquist, 1980). All effect sizes reported in the text have been transformed as 100 × (exp(ˇ) − 1). 8 If the average SAT of the college is used instead of the discrete indicators, an increase of 100 points in the average SAT corresponds to a 2.7% increase in salary. 9 This is based on the average teacher salary of $47,808 reported by the National Education Association in Rankings and Estimates (2005).
with other labor market research, women earn less than men in the teacher labor market. Columns 2 and 3 of Table 2 explore the returns after controlling for working conditions and cost of living. To measure the salary premium for academic ability net of compensating differentials, I introduce controls for the characteristics of the district in which the teacher is employed that may be associated with such differentials including the percent minority enrollment, the percent eligible for subsidized lunch, and the urbanicity of the district. Column 2 displays the coefficients from this regression. The coefficients for college selectivity are reduced in this model, with teachers in the most selective colleges earning a premium of around 10% and those from competitive colleges earning around 7% more. This reduction suggests that some of the return for teachers from selective and competitive colleges may be due to compensating differentials. Also of note, the coefficient for black teachers becomes negative with the inclusion of the percent minority enrollment, implying that the premium for black teachers may be due to the fact that they are more likely to be employed in districts with high minority enrollment.10
10 The coefficient for Hispanic teachers remains positive and statistically significant with the inclusion of the district characteristics. Due to the relatively small number of Hispanic teachers, this may be indicative of state-level demographic patterns of teachers being confounded with state
D. Player / Economics of Education Review 28 (2009) 277–285
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Table 3 Contrasting returns of elementary and secondary teachers.
Selective Competitive Secondary teacher Secondary × selective Secondary × competitive
Ln(income)
Ln(income)
Ln(income)
Ln(income)
0.1334 (0.0084)** 0.1024 (0.0054)** 0.0212 (0.0051)** −0.0026 (0.0108) −0.0133 (0.0071)
0.0572 (0.0084)** 0.0508 (0.0048)** 0.0271 (0.0046)** 0.0017 (0.0104) −0.0124 (0.0062)*
0.1326 (0.0052)** 0.0961 (0.0033)** 0.0160 (0.0039)**
0.0585 (0.0054)** 0.0450 (0.0030)** 0.0232 (0.0035)**
−0.0054 (0.0036) 0.0064 (0.0055)
−0.0056 (0.0035) 0.0075 (0.0043)
No 33,285 0.47
Yes 33285 0.58
Math/science teacher Special education teacher District controls Observations R-squared
No 33,285 0.47
Yes 33,285 0.58
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. District controls include percent minority, percent eligible for subsidized lunch, median house value, and a 3-level indicator for urbanicity. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
In the third column of Table 2, the median house value in the school district is included as a control for the cost of living in the area and the estimates of the returns to college selectivity are reduced further. However, attending a selective or a competitive college still has a positive and significant effect for teachers over attending a less competitive institution. There is some debate in the education literature over whether hedonic models accurately capture the presence of compensating differentials (Boyd, Lankford, Loeb, & Wyckoff, 2003). Salaries are set at the district level, but working conditions often vary greatly within a district. Furthermore, teacher preferences may not be homogeneous with respect to different types of working conditions.11 Therefore, it may be conceptually impossible for a district to offer compensating differentials since administrators must try to “hit a moving target.” Thus, the estimates attempting to control for compensating differentials and cost of living may bias the actual returns to college selectivity. For this reason, in the remainder of the empirical work I perform the analyses with and without district characteristics to establish a range of returns. The results from Table 2 indicate a positive return for secondary teachers. As there is evidence that academic ability affects student outcomes differently in elementary versus high school (Clotfelter et al., 2007), this may reflect that the returns to academic ability operate differently for elementary and secondary teachers. To investigate this possibility, Table 3 presents the results from regressions that focus on elementary and secondary teachers.12 The first
salary characteristics. 11 For example, there is evidence that black and white teachers have different responses to working in high-minority schools (Hanushek, Kain, & Rivkin, 2004). 12 For ease of presentation, I display only the regressions that omit district characteristics. The results of the regressions that include district
column introduces interactions of secondary teachers and college selectivity. These results indicate that secondary teachers from selective colleges do not earn a different rate of return than elementary teachers and that those from competitive colleges earn less than elementary teachers from competitive colleges. Teachers in secondary schools often teach in highdemand areas such as math and science and the premium for secondary teachers may reflect returns to these skills. The regression presented in the second column introduces controls for whether the teacher is teaching in an area often associated with shortages—technical subjects (math and science) and special education. Although the coefficient for secondary teachers is diminished, the coefficients on the newly included variables indicate that teaching in shortage areas does not significantly affect teacher salaries. Thus, the premium for secondary teachers is not explained by secondary teachers who possess specifically demanded skills, though secondary teachers as a whole may possess nonacademic skills that have a larger return in the non-teacher labor market and therefore receive premiums from districts for being in such positions. Attrition rates from previous studies suggest that this may be the case (Murnane & Olsen, 1989, 1990). The dependent variable in previous regressions is the total income from school, which includes pay above the base salary for assignments such as coaching or mentor teaching. Another explanation for the presence of secondary teacher premiums is the availability of pay for extracurricular activities. Replicating the above regressions with base salary, rather than total income, leaves the returns to college selectivity unchanged but reduces the premium for secondary teachers to zero.13 Thus, the return
controls are available upon request. 13 The coefficients of these regressions are available upon request.
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D. Player / Economics of Education Review 28 (2009) 277–285
Table 4 Starting salaries and average salary steps of districts, by teacher characteristics. Starting BA
Starting BA
Starting BA
Starting BA
Average step
Average step
0.0828 (0.0033)** 0.0610 (0.0023)** −0.0061 (0.0029)* 0.0253 (0.0024)**
0.0337 (0.0027)** 0.0275 (0.0019)** 0.0001 (0.0027) 0.0149 (0.0021)**
0.0997 (0.0067)** 0.0678 (0.0045)** −0.0227 (0.0046)**
0.0367 (0.0059)** 0.0301 (0.0040)** −0.0051 (0.0038)
0.2829 (0.0087)** 0.1679 (0.0061)** −0.0343 (0.0062)** 0.7876 (0.0058)**
0.1178 (0.0086)** 0.0628 (0.0058)** −0.0205 (0.0058)** 0.7390 (0.0054)**
District controls Observations R-squared
No 32,946 0.09
Yes 32,946 0.36
No 5169 0.12
Yes 5169 0.38
No 32,839 0.04
Yes 32,839 0.16
Sample restriction
None
Selective Competitive Secondary teacher Master’s degree
First year teachers with a BA
None
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. District controls include percent minority, percent eligible for subsidized lunch, median house value, and a 3-level indicator for urbanicity. Sample sizes are smaller because not all districts report steps on the salary schedule. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
for secondary teachers as a whole comes largely through non-base salary pay. This is not to say that the premium for secondary teachers is irrelevant, however, since it indicates that secondary teachers have a greater opportunity to earn additional income than elementary teachers. 4.1. Disaggregating the returns The monetary returns that accrue to teachers can arise due to district sorting, within-district deviations from the salary schedule, or some combination of the two. 4.1.1. District sorting To measure the returns due to district sorting, I begin by using the first step on the salary schedule as a dependent variable to proxy for the total level of the salary schedule. Table 4 presents the results of these regressions. In the first column, the level of the salary schedule is regressed for all teachers on college selectivity and the usual controls. Teachers graduating from selective colleges are in districts with a salary level that is up to 8.6% higher those from less-competitive colleges, while those graduating from competitive colleges are in districts where the levels are 6.3% higher. Secondary teachers are not sorting into higher paying districts, as the coefficient for secondary teachers is negative.14 The return for college selectivity is smaller when using the district’s level of salary rather than the teacher’s reported salary. While some of this discrepancy may be due to the fact that the step on the salary schedule does not denote all school earnings, another potential explanation is that teachers from selective colleges go to districts not only with higher levels of salary but also with higher growth rates along the salary schedule. If this were the case, then the step on the salary schedule would not fully capture the attractiveness of the entire schedule and using experi-
14 This indicates that secondary-only districts do not likely pay higher salaries than combined or elementary-only districts.
enced teachers for the salary step regressions would bias the returns downward.15 To examine this possibility, I restrict the regression to first year teachers to isolate only the teachers subject to that step on the salary schedule, shown in columns 3 and 4. With this restriction, the coefficient on college selectivity increases but is still smaller than the estimates using the teacher’s total salary. This may not be surprising if the growth rates along the salary schedules are different, because it may imply that teachers from selective colleges are able to secure spots in districts with higher salary growth rates and therefore the premiums are smaller in the first year than they are in later years. To investigate further whether teachers from selective colleges are able to secure spots in districts with higher salary growth rates, the final two columns of Table 4 regress the log of the average annual salary step on the usual controls.16 The teachers from selective colleges are able to secure spots in districts with up to 24% higher steps every year than the average. Taking columns 2 and 3 together, the teachers from selective colleges start in districts with up to 8% higher salaries and grow up to 22% faster every year than one who graduates from a non-selective college, implying that a teacher who graduates from a selective college can expect to earn between 13% and 20% more than those who graduate from non-competitive colleges after 10 years.17
15 Also, research suggests that teachers from more selective colleges have shorter stays in teaching (Podgursky, Monroe, & Watson, 2004). With differential attrition rates, the OLS estimates of the return for selective college graduates may understate the true effects since wage growth may be confounded with wage levels (cohort effects). 16 The inclusion of controls such as the cost of living may be inappropriate in these equations, as one would expect the cost of living to affect the level of salaries but not necessarily the growth in salaries. 17 Alternatively, one could interact experience with college selectivity to measure differential growth rates of income in the log(income) equations. Coefficients from these regressions indicate that teachers from selective colleges earn .38% more for every year of experience and those from competitive colleges earn .24% more for every year of experience. Combined with the respective coefficients for college selectivity, these translate to a
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Table 5 Estimates of within-district returns to college selectivity. Ln(income)
Ln(income)
Ln(income)
0.0063 (0.0032) 0.0063 (0.0022)** 0.0166 (0.0023)**
0.0202 (0.0079)* 0.0183 (0.0059)** 0.0192 (0.0049)**
0.0251 (0.0346) 0.0431 (0.0230) 0.0172 (0.0160)
Observations Number of districts R-squared
31,832 3579 0.56
4175 42 0.63
402 1 0.65
Sample restrictions
All districts with at least 3 teachers represented
All districts with at least 50 teachers
Largest district in the sample
Selective Competitive Secondary teacher
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. These estimates are from district fixed effects models. * Significant at 5% level. ** Significant at 1% level.
In some cases, districts that deviate from the traditional salary schedule by offering merit-based awards or bonuses for teachers willing to work in hard-to-staff schools or shortage field areas.18 A possible explanation for the selectivity returns is that teachers who graduate from selective colleges may be more likely to be employed by districts that offer alternative compensation schemes. If high-ability teachers are found disproportionately in these districts and they pay higher average salaries (Goldhaber, DeArmond, Player, and Choi, 2008), this could explain some portion of interdistrict returns. Probability models (not shown) indicate that teachers from selective colleges are more likely to be in districts with these arrangements, but accounting for this increased likelihood in Eq. (1) does not explain the overall premium. Another explanation that might give rise to the college selectivity premium for teachers is the fact that, because of employment connections made during student teaching, teachers may be more likely to be hired into districts near the schools from which they graduated, and districts near selective colleges may pay more than areas near less selective colleges. The data do not permit a detailed investigation of this hypothesis. However, as an investigative test I calculated the average teacher salary near each college19 and introduced it as a regressor in Eq. (1). The purpose of this is to detect whether there would still be premiums associated with attending a more selective college in the hypothetical case where all teachers remain local to the college. With the inclusion of this variable the coefficients are reduced by approximately half, and teachers from selective and competitive colleges receive premiums of approximately 7.5% and 6%, respectively. Thus, there is some evidence that the
12.7% premium for selective colleges and an 8.3% premium for competitive colleges after 10 years. Full results are available upon request. 18 Interestingly, nearly all districts that offer these bonuses also report using a single salary schedule. In the SASS, 8.2% of teachers are in a district that uses location pay, 18.2% of teachers are in districts that use some form of subject shortage pay, and 10.4% of teachers are in districts that offer excellence pay. 19 Average salaries were calculated as the average of the per-teacher instruction expenditure in each district with at least one school in the same county as the college. These data were available from the School District Finance Survey, part of the CCD.
labor conditions near the college explain some, but not all, of the premium. 4.1.2. Within-district premiums Beyond the fact that teachers from more selective colleges are in districts with higher salary levels and growth rates, an alternative explanation for the discrepancy between the returns using reported salaries and using district salary schedule information is that teachers from more selective colleges are rewarded within districts as well. Although the salary schedule is rigid for teachers of a given experience and education level, there may be some opportunities for teachers to earn income (such as new teacher mentoring) above the salary schedule. Similarly, there is some anecdotal evidence that principals or district administrators may have some flexibility to “bump” a teacher up the salary schedule by crediting them with extra experience if that teacher is perceived to be especially productive. If teachers graduating from selective colleges had a greater ability to receive such benefits, there may be returns to selectivity within districts. To calculate the within-district returns to ability, I employ district fixed effects ¯ k ) = ˇ0 + ˇ1 (Xi − X¯ k ) + ˇ2 (Ci − C¯ k ) + i (Wi − W
(2)
where the difference in teacher i’s salary from the average salary in district k is a function of how different that teacher is from the other teachers in the district and the difference in selectivity of the college from the average selectivity. The coefficients in ˇ2 capture the within-district college selectivity premium. As a caveat, districts only have, on average, 8 teachers represented in the SASS. Such small district-specific samples may weaken the findings, as the within-district estimates rely on sufficient variation in the experience levels and academic abilities of teachers within districts. Nonetheless, it is instructive to look within districts to see whether there appears to be a premium for college selectivity. The first column of Table 5 shows district fixed effects for every district that has at least three teachers in the sample. The within-district premium to college selectivity in this case is around 0.8%. To provide some robustness to these
284
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results and ensure sufficient within-district variation, the next column restricts the sample to districts with at least 50 teachers sampled by the SASS (a total of 41 districts). With this restriction in place, the within-district premium for attending a selective or competitive college is around 2.0%, significantly larger than the premiums calculated in the first column of the table. The final column restricts the analysis to the single largest district represented in the SASS.20 The size of the coefficient for selectivity for this largest district is similar to the estimate using the largest 41 districts but is not statistically significant. Those attending a competitive college, however, appear to receive a large and statistically significant within-district premium. Because the data were not designed to be used in a fixed effects framework, I tested the robustness of these findings of intra-district returns by including the district’s starting salary as an independent variable in Eq. (1). Results from these regressions (not shown) are consistent with the fixed effects models and indicate a premium for those from the most selective colleges of approximately 2%. Taken together, these results suggest that teachers from the most selective colleges receive a premium of up to 2 percentage points of their total return. While this increase may appear small, it translates to up to 35% of the total return, based on the results from Table 2. Thus, despite the rigid salary structure in public education, teachers from the most selective colleges have an advantage beyond being able to sort into the highest paying districts and receive pay above what would be expected given their education and experience levels. All results from this paper use the teacher’s total income from school as the dependent variable in order to capture the total returns in base salary and additional compensation. As a final investigation of within-district returns, I use the teacher’s reported base salary and contrast that with total school income in an effort to discern whether high-ability teachers are “bumped up” the schedule or whether the within-district premiums are from extracurricular assignments. The coefficients from these regressions (not shown) are substantively unchanged from those using total salary, implying that the within-district premium for attending a more selective college is largely captured in the teacher’s base salary. 5. Conclusion Despite the rigid salary structure for public school teachers, the findings from this paper provide evidence of positive returns to ability in the teacher labor market. The estimates of the size of this return indicate that teachers who graduate from more selective colleges earn between 7% and 14% more than those who graduate from noncompetitive schools. Based on recent estimates of average teacher salaries, this translates to an annual premium of
20 The largest district in the sample reported that it relies on a single salary schedule. This district was not drawn at random and thus one cannot expect the results to be generalized to all districts. This example serves merely as an illustration that there are returns to ability even within a district that reports using a salary schedule.
between $3300 and $6700. Thus, given prior evidence that teachers’ cognitive ability affects student outcomes, the public teacher labor market appears to reward productivity. An investigation of the source of the premium sheds an important light onto how the teacher labor market functions. Much of the premium is due to the fact that highability teachers sort into districts that pay more. However, the premium for academic ability does not appear to be entirely captured by the steps on the salary schedule and evidence suggests that there are within-district returns. An investigation of these returns shows that high-ability teachers receive higher salaries than one would predict given their education and experience. Models attempting to control for the salary schedule reveal that up to 2 percentage points, or up to 34% of the premium, is found within districts. These results are important in understanding the way that the teacher labor market rewards teacher ability. As evidence mounts about the importance of teacher quality, policymakers face the task of determining how to attract high quality teachers. These results suggest that high quality teachers are rewarded in teaching, but these rewards arise primarily from their sorting into higher paying states and districts. Thus, any effort to expose these high-ability teachers to the most disadvantaged students would need to address the mechanism by which teacher ability is currently rewarded in the teacher labor market. Acknowledgements I am grateful for valuable mentoring and feedback that Dan Goldhaber provided during the early work on this paper. I am also very grateful for helpful comments from Shelly Lundberg, Eugene Silberberg, two anonymous referees, and numerous participants during presentations at the University of Washington, Mathematica Policy Research, and the 2007 meeting of the American Education Finance Association. References Bacolod, M. (2007). Do alternative opportunities matter? The role of female labor markets in the decline of teacher quality 1960–1990. Review of Economics and Statistics, 89(4), 737–751. Ballou, D. (1996). Do public schools hire the best applicants? Quarterly Journal of Economics, 111(1), 97–133. Barron. (1995). Barron’s profiles of American colleges 1994. Hauppauge, NY: Barron’s Educational Series. Boyd, D., Lankford, H., Loeb, S., & Wyckoff, J. (2003). Analyzing the determinants of the matching public school teachers to jobs: Estimating compensating differentials in imperfect labor market. NBER Working Paper 9878, National Bureau of Economic Research. Brewer, D. J., Eide, E. R., & Ehrenberg, R. G. (1999). Does it pay to attend an elite private college? Cross-cohort evidence on the effects of college type on earnings. Journal of Human Resources, 34(1), 104–123. Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2007). Teacher credentials and student achievement in high school: A cross-subject analysis with student fixed effects. NBER Working Paper 13617, National Bureau of Economic Research. Corcoran, S. P., Evans, W. N., & Schwab, R. M. (2004). Women, the labor market, and the declining relative quality of teachers. Journal of Policy Analysis and Management, 23(3), 449–470. Figlio, D. N. (1997). Teacher salaries and teacher quality. Economics Letters, 55(2), 267–271. Figlio, D. N. (2002). Can public schools buy better-qualified teachers? Industrial and Labor Relations Review, 55(4), 686–699.
D. Player / Economics of Education Review 28 (2009) 277–285 Goldhaber, D. D. (2007). Everybody’s doing it, but what does teacher testing tell us about teacher effectiveness? Journal of Human Resources, 42(4), 765–794. Goldhaber, D. D., DeArmond, M., Player, D. W., & Choi, H. J. (2008). Why do so few public school districts use merit pay? Journal of Education Finance, 33(3), 262–289. Halvorsen, R., & Palmquist, R. (1980). The interpretation of dummy variables in semilogarithmic equations. American Economic Review, 70(3), 474–475. Hanushek, E. A. (1986). The Economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24(3), 1141–1177. Hanushek, E. A., Kain, J. F., O’Brien, D. M., & Rivkin, S. G. (2005). The market for teacher quality. NBER Working Paper 11154, National Bureau of Economic Research. Hanushek, E. A., Kain, J. F., & Rivkin, S. G. (1999). Do higher salaries buy better teachers? NBER Working Paper 7082, National Bureau of Economic Research.
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Hanushek, E. A., Kain, J. F., & Rivkin, S. G. (2004). Why public schools lose teachers. Journal of Human Resources, 39(2), 326–354. Lakdawalla, D. (2001). The declining quality of teachers. NBER Working Paper 8263, National Bureau of Economic Research. Murnane, R. J., & Olsen, R. J. (1989). The effect of salaries and opportunity costs on duration in teaching: Evidence from Michigan. Review of Economics and Statistics, 71(2), 347–352. Murnane, R. J., & Olsen, R. J. (1990). The effects of salaries and opportunity costs on length of stay in teaching: Evidence from North Carolina. Journal of Human Resources, 25(1), 106–124. National Education Association (2005). Rankings and estimates: Rankings of the states 2004 and estimates of school statistics 2005. Available from http://www.nea.org/edstats/images/05rankings.pdf. Podgursky, M., Monroe, R., & Watson, D. (2004). The academic quality of public school teachers: An analysis of entry and exit behavior. Economics of Education Review, 23(5), 507–518.
Contents lists available at ScienceDirect
Economics of Education Review journal homepage: www.elsevier.com/locate/econedurev
Monetary returns to academic ability in the public teacher labor market Daniel Player ∗ Mathematica Policy Research, Inc., P.O. Box 2393, Princeton, NJ 08543-2393, United States
a r t i c l e
i n f o
Article history: Received 19 October 2006 Accepted 26 June 2008 JEL classification: J31 J45 I20 Keywords: Human capital Salary wage differentials Teacher salaries
a b s t r a c t Previous research has established the returns to academic ability in the general labor market, and this paper investigates such returns in the teacher labor market. Using a nationally representative sample of public school teachers, I find that teachers who graduate from the most selective undergraduate institutions have salaries that are between 7% and 14% higher than those who graduate from the least selective colleges. An empirical investigation of the source of these returns reveals that the majority of this difference is due to highability teachers sorting into higher paying districts, though a non-trivial amount arises from within-district deviations from the salary schedule. © 2008 Elsevier Ltd. All rights reserved.
1. Introduction Some policymakers and researchers have been critical of this rigid pay structure in public school districts, arguing that it does not provide incentives for highly productive teachers. However, the presence of salary schedules alone does necessarily eliminate the possibility that teachers receive premiums; schedules differ from one district to another and highly productive teachers may have an advantage of sorting into higher paying districts. Also, within districts, administrators may have some flexibility to raise salaries above the schedule by giving certain teachers the opportunity to earn extra compensation for additional responsibilities (such as summer teaching or extracurricular assignments) or by crediting them with additional education or experience. Thus, even rigid salary structures without explicit “merit pay” programs may lead to pay differentials for highly skilled teachers. The purpose of this paper is to investigate whether the teacher labor market rewards certain teachers by examining the monetary
∗ Tel.: +1 609 799 3535. E-mail address: [email protected]. 0272-7757/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.econedurev.2008.06.002
returns to one observable teacher characteristic that has been shown to be correlated with student achievement: academic ability. The results of this paper demonstrate that teachers receive premiums for academic ability (as measured by the selectivity of the college from which they graduate) despite the rigid salary structure. Estimates indicate that teachers who graduate from the most selective colleges receive a premium of between 7% and 14% that arises largely from sorting between districts. However, there is also consistent evidence that teachers from more selective colleges also receive within-district premiums. These within-district premiums may account for up to 34% of the total return to academic ability. These findings have important implications for how we view the teacher labor market. They suggest that whether or not a district uses merit pay, teachers with greater academic ability receive premiums in the teacher labor market. Thus, concerns of inequity that often fuel resistance to wage reform are already realized. However, it is notable that the vast majority of these premiums are from sorting between districts. To the degree that the differences in academic ability reflect true differences in teacher quality, the sorting of teachers perpetuates inequities for disadvantaged
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students that would not be observed if all the salary differentials were within, rather than between, districts. 2. Background Public school teachers have come under scrutiny over the last few decades because of an apparent decline in the academic ability of new hires (Corcoran, Evans, & Schwab, 2004). In light of the recent evidence that teachers’ academic proficiency affects student outcomes (Clotfelter, Ladd, & Vigdor, 2007; Goldhaber, 2007), the potential decline in teacher ability has received the attention of policymakers and lawmakers as one of the largest challenges facing the teaching profession (Bacolod, 2007; Lakdawalla, 2001). In a meta-analysis of the effects of school inputs on student achievement, Hanushek (1986) offered that a teacher’s academic proficiency appeared to be the only school input that appeared to be a relatively consistent predictor of student outcomes. Thus, the declining academic ability of the teachers entering the labor market is seen as a decline in the quality of teachers entering the profession. Given that academically talented teachers appear to be more productive, it is intuitively appealing that they have an advantage in the schools and districts into which they are hired. Likewise, teachers have preferences for higher wages and more favorable working conditions, and there is evidence that teachers seek to sort into districts according to these preferences (Hanushek, Kain, & Rivkin, 2004). The connection between teacher salaries and teacher quality has been an important subject for economists and policy researchers. Research has found a positive relationship between salaries and teacher quality (Figlio, 1997). By examining shifts in salary schedules over time and changes in the composition of the teacher labor force, research has found that teacher salaries have a significant, though small, impact on the types of teachers that are hired in a district (Figlio, 2002; Hanushek, Kain, & Rivkin, 1999), providing some empirical evidence that the relationship between salary and teacher quality is causal. No attempts have been made in previous research to quantify the returns to individual teachers either within or across districts. This paper seeks to fill this gap by offering estimates of the degree to which there is separation in teacher salaries that are correlated with a teacher’s academic ability. 3. Methodology and data The existing literature places this paper in an important context: teacher quality makes a significant difference in student outcomes and it appears to be related to the academic ability of a teacher. However, there is reason to doubt whether productive teachers receive positive premiums in the labor market because districts rely on rigid salary schedules and because schools and districts may lack incentives to hire the most qualified applicants (Ballou, 1996; Figlio, 1997; Hanushek, Kain, O’Brien, & Rivkin, 2005). The empirical work of this paper tests whether academically talented teachers receive a premium in the labor market.
3.1. Methodology For a measure of teacher aptitude, I focus on the selectivity of a college from which a teacher graduates. Unlike many papers in the labor economics literature that have examined college selectivity, the purpose of this paper is not to measure the value added of attending a selective college but rather to take college selectivity as a proxy for the teacher’s total academic ability upon entry into the teacher labor market.1 This necessarily includes the teacher’s precollege ability as well as the value that college has added. Therefore, throughout the paper I refer to “college selectivity” as a proxy for the teacher’s total academic ability. The baseline specification will be a typical earnings function, similar to Brewer, Eide, and Ehrenberg (1999). Specifically, I examine whether academic ability is a positive determinant of teacher salaries. This base model is ln Wi = ˇ0 + ˇ1 Xi + ˇ2 Cij + i
(1)
where log of total annual income (Wi ) is regressed on a vector of individual characteristics (Xi ) and the selectivity of college j (Cij ). In this construct, I use a measure of the teacher’s total annual income from the school, which includes base salary as well as any pay for extracurricular assignments, in order to capture the aggregate return. Additionally, the total annual income from school is likely less prone to measurement error since it does not require teachers to categorize the sources of their pay. Another advantage of this aggregated measure is that a potential source of differential compensation may arise through the ability to secure additional summer assignments.2 Thus, the returns to ability are to be interpreted as the total return of school-related income. At the end of the empirical section, the returns in terms of annual base salary are distinguished from returns from additional assignments. Working conditions play an important role in job satisfaction in teaching and non-teaching occupations. Teachers are sensitive to working conditions (Hanushek et al., 2004) and whether or not districts explicitly design their salary schedules to include compensating differentials, teachers in less attractive schools necessarily interpret some portion of their salary as the amount necessary to compensate them for less desirable working conditions. To explore the productivity premiums further, I also examine the extent to which the returns are due to compensating differentials for less desirable working conditions and cost of living adjustments for high cost of living areas by including controls for working conditions and local cost of living. With an aggregate measure of the returns to productivity, I disaggregate the source of the returns: between-district sorting and within-district differentials. As a first step, I isolate the interdistrict return due to
1 This is a proxy for teacher quality that has been used in other research (e.g., Figlio, 1997). 2 Opportunities for moonlighting (such as summer teaching) may be an important benefit offered to high quality teachers. For instance, Chicago Public Schools (CPS) lists “summer teaching opportunities” along with health and dental insurance as some of the benefits available to teachers (http://www.cps-humanresources.org/Careers/benefits.htm).
D. Player / Economics of Education Review 28 (2009) 277–285
sorting into higher paying districts by examining the district’s starting salary. Likewise, I examine whether high-ability teachers are able to sort into districts that have a higher growth rate in salary over time. I also investigate whether teachers from selective colleges are more likely to be matched with districts that offer deviations from the single salary schedule, and I determine whether these deviations explain academic premiums. Though the salary schedule is set at the district level, the possibility remains that teachers receive some premium within the districts where they are employed. The final empirical task is to measure within-district academic ability premiums using district fixed effects models. 3.2. Data
Table 1 Means (standard deviations) of selected variables for subgroups in the SASS 1999–2000.
SAT of college Female White Black Hispanic Advanced degree Urban district Suburban district
The primary data for the empirical work are from the Schools and Staffing Survey (SASS), a nationally representative survey of teachers, schools and districts throughout the United States. I use the most recent wave of the SASS (1999–2000) that was available at the time of this writing. The SASS teacher questionnaire asks teachers a number of questions about their experience in teaching, including their education and experience as well as their income from school and non-school sources. Among other things, the SASS district questionnaire asks the district to list four steps on the single salary schedule: the starting salary for a teacher with a bachelor’s degree, the salary for a teacher with a bachelor’s degree and 10 years of experience, the starting salary for a teacher with a master’s degree and the salary for a teacher with a master’s degree and 20 years of experience. The SASS samples schools as the primary sampling unit. After selecting the schools, it also surveys the school’s district and a sample of teachers in that school. Using the restricted version of the SASS, I am then able to match the teachers to their schools and districts. The number of teachers in the full teacher sample was 42,086. Restricting my sample to only the teachers who reported working full time reduced the sample to 38,375. I also restricted the sample to teachers who could be matched to their districts, which resulted in a sample consisting of 33,901 teachers. Because salary schedules are typically different for different education levels, and only a very small minority of teachers has either less than a bachelor’s degree or more than a master’s degree, I restricted the sample by eliminating those teachers who reported their highest degree as being less than a bachelor’s or more than a master’s degree (593 observations). As a final restriction, I dropped those teachers from the sample who reported base salaries that appear to be implausible: those reporting less than $15,000 (11 observations)3 or more than $150,000 (12 observations).4 The final sample consists of 33,285 teachers.
3 Incidentally, all teachers who reported salaries less than $15,000 reported a salary of zero. 4 The results are unchanged when including the omitted observations, though it is impossible to include the observations who report earnings of zero in log salary models.
279
Rural district Salary N
Selective
Competitive
Non-competitive
1077.0 (69.81) 63.90% (0.480) 90.63% (0.291) 3.70% (0.189) 4.76% (0.213) 53.00% (0.499) 25.21% (0.434) 50.55% (0.500) 24.23% (0.429) 41,519 (12,645)
948.9 (56.30) 67.04% (0.470) 90.68% (0.291) 3.39% (0.181) 4.06% (0.197) 44.70% (0.497) 24.71% (0.431) 42.84% (0.495) 32.45% (0.468) 39,387 (11,822)
879.4 (84.9) 67.96% (0.467) 83.55% (0.371) 10.54% (0.307) 4.86% (0.215) 39.18% (0.488) 23.57% (0.424) 29.83% (0.458) 46.60% (0.499) 35,620 (10,210)
3970
14,766
14,549
Source: Schools and Staffing Survey 2000. Notes: Standard deviations in parentheses.
The measure of academic ability for teachers is the selectivity of the college from which they received their bachelor’s degree as measured by Barron’s Profiles of American Colleges. Due to the small number of teachers graduating from each of the three most selective categories, I collapse these into a single indicator for a “selective” school, retain the Barron’s “competitive” grouping, and collapse schools from the two least selective categories into the omitted group “less competitive.”5 Because these selectivity indicators are categorical rankings, which may have changed over time, I use the mode ranking over the period 1980–1994 as a measure of the school’s typical selectivity. Because it may be unreasonable to assume that that undergraduate institution information was missing at random, I allowed these teachers (965) to be their own category.6 Table 1 shows descriptive statistics from the final sample. Not surprisingly, given the teacher labor market, most of the teachers in the sample are white and female. It is of note that teachers who graduated from selective colleges have higher salaries than those who graduated from less selective colleges. Similarly, graduates of competitive colleges earn more than graduates of non-selective colleges. A more detailed analysis of the rate of return, controlling for other factors, is described below.
5 The results are substantively unchanged if the two bottom categories are not combined, and in each case the return to the selective and competitive graduates are slightly higher when the “least competitive” category is used as the reference group. 6 In a personal communication with Kerry Gruber, a statistician at the SASS survey program, he stated that college codes are missing if a teacher does not report the college he/she attended, if he/she attended outside the USA, or if the coding staff was unable to read the name or locate the college reported by the respondent. The estimates are unchanged if the teachers with missing selectivity measures are dropped from the sample.
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Table 2 Total returns to ability for public school teachers.
Selective Competitive Secondary teacher Total experience Experience squared Master’s degree Female Black Hispanic
Ln(income)
Ln(income)
Ln(income)
0.1323 (0.0052)** 0.0961 (0.0033)** 0.0144 (0.0037)** 0.0269 (0.0006)** −0.0003 (0.0000)** 0.1316 (0.0037)** −0.0482 (0.0037)** 0.0284 (0.0060)** 0.0653 (0.0069)**
0.0935 (0.0054)** 0.0689 (0.0033)** 0.0185 (0.0035)** 0.0285 (0.0005)** −0.0004 (0.0000)** 0.1227 (0.0034)** −0.0522 (0.0038)** −0.0195 (0.0069)** 0.0208 (0.0069)** 0.1411 (0.0106)** −0.1146 (0.0128)** 0.0300 (0.0049)** −0.1175 (0.0053)**
0.0583 (0.0054)** 0.0450 (0.0030)** 0.0215 (0.0033)** 0.0297 (0.0005)** −0.0004 (0.0000)** 0.1144 (0.0032)** −0.0479 (0.0036)** −0.0074 (0.0068) 0.0189 (0.0066)** 0.0987 (0.0098)** −0.0051 (0.0132) 0.0164 (0.0048)** −0.0749 (0.0058)** 0.1490 (0.0052)**
33,285 0.47
33,285 0.54
33,285 0.58
% minority enrollment % subsidized lunch eligible Suburban district Rural district (log) Median house value Observations R-squared
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
4. Empirical results The returns to a teacher’s academic ability, as proxied by the selectivity of the college from which he or she received a bachelor’s degree, are displayed in Table 2. The graduates of the most selective colleges earn a return of 14.2% and graduates of competitive colleges earning a return of 10.1% above the graduates of less selective colleges.7,8 Based on recent estimates of average teacher salaries, this translates to an average annual premium of between $3300 and $6700.9 The coefficients for experience and education are largely unsurprising. The estimates indicate that an additional year of experience adds around 3% of salary, the returns to experience decrease with experience, and a master’s degree is worth around 14%. It is also worth noting that secondary teachers earn more than elementary teachers. This may indicate an additional premium paid for the specific skills of secondary teachers, explored below. Similarly, consistent
7 Recall that coefficients on dummy variables in semi-log equations cannot be interpreted directly as percentage changes without the appropriate transformation (Halvorsen & Palmquist, 1980). All effect sizes reported in the text have been transformed as 100 × (exp(ˇ) − 1). 8 If the average SAT of the college is used instead of the discrete indicators, an increase of 100 points in the average SAT corresponds to a 2.7% increase in salary. 9 This is based on the average teacher salary of $47,808 reported by the National Education Association in Rankings and Estimates (2005).
with other labor market research, women earn less than men in the teacher labor market. Columns 2 and 3 of Table 2 explore the returns after controlling for working conditions and cost of living. To measure the salary premium for academic ability net of compensating differentials, I introduce controls for the characteristics of the district in which the teacher is employed that may be associated with such differentials including the percent minority enrollment, the percent eligible for subsidized lunch, and the urbanicity of the district. Column 2 displays the coefficients from this regression. The coefficients for college selectivity are reduced in this model, with teachers in the most selective colleges earning a premium of around 10% and those from competitive colleges earning around 7% more. This reduction suggests that some of the return for teachers from selective and competitive colleges may be due to compensating differentials. Also of note, the coefficient for black teachers becomes negative with the inclusion of the percent minority enrollment, implying that the premium for black teachers may be due to the fact that they are more likely to be employed in districts with high minority enrollment.10
10 The coefficient for Hispanic teachers remains positive and statistically significant with the inclusion of the district characteristics. Due to the relatively small number of Hispanic teachers, this may be indicative of state-level demographic patterns of teachers being confounded with state
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281
Table 3 Contrasting returns of elementary and secondary teachers.
Selective Competitive Secondary teacher Secondary × selective Secondary × competitive
Ln(income)
Ln(income)
Ln(income)
Ln(income)
0.1334 (0.0084)** 0.1024 (0.0054)** 0.0212 (0.0051)** −0.0026 (0.0108) −0.0133 (0.0071)
0.0572 (0.0084)** 0.0508 (0.0048)** 0.0271 (0.0046)** 0.0017 (0.0104) −0.0124 (0.0062)*
0.1326 (0.0052)** 0.0961 (0.0033)** 0.0160 (0.0039)**
0.0585 (0.0054)** 0.0450 (0.0030)** 0.0232 (0.0035)**
−0.0054 (0.0036) 0.0064 (0.0055)
−0.0056 (0.0035) 0.0075 (0.0043)
No 33,285 0.47
Yes 33285 0.58
Math/science teacher Special education teacher District controls Observations R-squared
No 33,285 0.47
Yes 33,285 0.58
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. District controls include percent minority, percent eligible for subsidized lunch, median house value, and a 3-level indicator for urbanicity. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
In the third column of Table 2, the median house value in the school district is included as a control for the cost of living in the area and the estimates of the returns to college selectivity are reduced further. However, attending a selective or a competitive college still has a positive and significant effect for teachers over attending a less competitive institution. There is some debate in the education literature over whether hedonic models accurately capture the presence of compensating differentials (Boyd, Lankford, Loeb, & Wyckoff, 2003). Salaries are set at the district level, but working conditions often vary greatly within a district. Furthermore, teacher preferences may not be homogeneous with respect to different types of working conditions.11 Therefore, it may be conceptually impossible for a district to offer compensating differentials since administrators must try to “hit a moving target.” Thus, the estimates attempting to control for compensating differentials and cost of living may bias the actual returns to college selectivity. For this reason, in the remainder of the empirical work I perform the analyses with and without district characteristics to establish a range of returns. The results from Table 2 indicate a positive return for secondary teachers. As there is evidence that academic ability affects student outcomes differently in elementary versus high school (Clotfelter et al., 2007), this may reflect that the returns to academic ability operate differently for elementary and secondary teachers. To investigate this possibility, Table 3 presents the results from regressions that focus on elementary and secondary teachers.12 The first
salary characteristics. 11 For example, there is evidence that black and white teachers have different responses to working in high-minority schools (Hanushek, Kain, & Rivkin, 2004). 12 For ease of presentation, I display only the regressions that omit district characteristics. The results of the regressions that include district
column introduces interactions of secondary teachers and college selectivity. These results indicate that secondary teachers from selective colleges do not earn a different rate of return than elementary teachers and that those from competitive colleges earn less than elementary teachers from competitive colleges. Teachers in secondary schools often teach in highdemand areas such as math and science and the premium for secondary teachers may reflect returns to these skills. The regression presented in the second column introduces controls for whether the teacher is teaching in an area often associated with shortages—technical subjects (math and science) and special education. Although the coefficient for secondary teachers is diminished, the coefficients on the newly included variables indicate that teaching in shortage areas does not significantly affect teacher salaries. Thus, the premium for secondary teachers is not explained by secondary teachers who possess specifically demanded skills, though secondary teachers as a whole may possess nonacademic skills that have a larger return in the non-teacher labor market and therefore receive premiums from districts for being in such positions. Attrition rates from previous studies suggest that this may be the case (Murnane & Olsen, 1989, 1990). The dependent variable in previous regressions is the total income from school, which includes pay above the base salary for assignments such as coaching or mentor teaching. Another explanation for the presence of secondary teacher premiums is the availability of pay for extracurricular activities. Replicating the above regressions with base salary, rather than total income, leaves the returns to college selectivity unchanged but reduces the premium for secondary teachers to zero.13 Thus, the return
controls are available upon request. 13 The coefficients of these regressions are available upon request.
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D. Player / Economics of Education Review 28 (2009) 277–285
Table 4 Starting salaries and average salary steps of districts, by teacher characteristics. Starting BA
Starting BA
Starting BA
Starting BA
Average step
Average step
0.0828 (0.0033)** 0.0610 (0.0023)** −0.0061 (0.0029)* 0.0253 (0.0024)**
0.0337 (0.0027)** 0.0275 (0.0019)** 0.0001 (0.0027) 0.0149 (0.0021)**
0.0997 (0.0067)** 0.0678 (0.0045)** −0.0227 (0.0046)**
0.0367 (0.0059)** 0.0301 (0.0040)** −0.0051 (0.0038)
0.2829 (0.0087)** 0.1679 (0.0061)** −0.0343 (0.0062)** 0.7876 (0.0058)**
0.1178 (0.0086)** 0.0628 (0.0058)** −0.0205 (0.0058)** 0.7390 (0.0054)**
District controls Observations R-squared
No 32,946 0.09
Yes 32,946 0.36
No 5169 0.12
Yes 5169 0.38
No 32,839 0.04
Yes 32,839 0.16
Sample restriction
None
Selective Competitive Secondary teacher Master’s degree
First year teachers with a BA
None
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. District controls include percent minority, percent eligible for subsidized lunch, median house value, and a 3-level indicator for urbanicity. Sample sizes are smaller because not all districts report steps on the salary schedule. Standard errors were calculated based on the replicate weights provided in SASS. * Significant at 5% level. ** Significant at 1% level.
for secondary teachers as a whole comes largely through non-base salary pay. This is not to say that the premium for secondary teachers is irrelevant, however, since it indicates that secondary teachers have a greater opportunity to earn additional income than elementary teachers. 4.1. Disaggregating the returns The monetary returns that accrue to teachers can arise due to district sorting, within-district deviations from the salary schedule, or some combination of the two. 4.1.1. District sorting To measure the returns due to district sorting, I begin by using the first step on the salary schedule as a dependent variable to proxy for the total level of the salary schedule. Table 4 presents the results of these regressions. In the first column, the level of the salary schedule is regressed for all teachers on college selectivity and the usual controls. Teachers graduating from selective colleges are in districts with a salary level that is up to 8.6% higher those from less-competitive colleges, while those graduating from competitive colleges are in districts where the levels are 6.3% higher. Secondary teachers are not sorting into higher paying districts, as the coefficient for secondary teachers is negative.14 The return for college selectivity is smaller when using the district’s level of salary rather than the teacher’s reported salary. While some of this discrepancy may be due to the fact that the step on the salary schedule does not denote all school earnings, another potential explanation is that teachers from selective colleges go to districts not only with higher levels of salary but also with higher growth rates along the salary schedule. If this were the case, then the step on the salary schedule would not fully capture the attractiveness of the entire schedule and using experi-
14 This indicates that secondary-only districts do not likely pay higher salaries than combined or elementary-only districts.
enced teachers for the salary step regressions would bias the returns downward.15 To examine this possibility, I restrict the regression to first year teachers to isolate only the teachers subject to that step on the salary schedule, shown in columns 3 and 4. With this restriction, the coefficient on college selectivity increases but is still smaller than the estimates using the teacher’s total salary. This may not be surprising if the growth rates along the salary schedules are different, because it may imply that teachers from selective colleges are able to secure spots in districts with higher salary growth rates and therefore the premiums are smaller in the first year than they are in later years. To investigate further whether teachers from selective colleges are able to secure spots in districts with higher salary growth rates, the final two columns of Table 4 regress the log of the average annual salary step on the usual controls.16 The teachers from selective colleges are able to secure spots in districts with up to 24% higher steps every year than the average. Taking columns 2 and 3 together, the teachers from selective colleges start in districts with up to 8% higher salaries and grow up to 22% faster every year than one who graduates from a non-selective college, implying that a teacher who graduates from a selective college can expect to earn between 13% and 20% more than those who graduate from non-competitive colleges after 10 years.17
15 Also, research suggests that teachers from more selective colleges have shorter stays in teaching (Podgursky, Monroe, & Watson, 2004). With differential attrition rates, the OLS estimates of the return for selective college graduates may understate the true effects since wage growth may be confounded with wage levels (cohort effects). 16 The inclusion of controls such as the cost of living may be inappropriate in these equations, as one would expect the cost of living to affect the level of salaries but not necessarily the growth in salaries. 17 Alternatively, one could interact experience with college selectivity to measure differential growth rates of income in the log(income) equations. Coefficients from these regressions indicate that teachers from selective colleges earn .38% more for every year of experience and those from competitive colleges earn .24% more for every year of experience. Combined with the respective coefficients for college selectivity, these translate to a
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Table 5 Estimates of within-district returns to college selectivity. Ln(income)
Ln(income)
Ln(income)
0.0063 (0.0032) 0.0063 (0.0022)** 0.0166 (0.0023)**
0.0202 (0.0079)* 0.0183 (0.0059)** 0.0192 (0.0049)**
0.0251 (0.0346) 0.0431 (0.0230) 0.0172 (0.0160)
Observations Number of districts R-squared
31,832 3579 0.56
4175 42 0.63
402 1 0.65
Sample restrictions
All districts with at least 3 teachers represented
All districts with at least 50 teachers
Largest district in the sample
Selective Competitive Secondary teacher
Notes: Standard errors in parentheses. Omitted category is less selective/non-selective. Other regressors included are a quadratic in experience and indicators for female, black, and Hispanic teachers. These estimates are from district fixed effects models. * Significant at 5% level. ** Significant at 1% level.
In some cases, districts that deviate from the traditional salary schedule by offering merit-based awards or bonuses for teachers willing to work in hard-to-staff schools or shortage field areas.18 A possible explanation for the selectivity returns is that teachers who graduate from selective colleges may be more likely to be employed by districts that offer alternative compensation schemes. If high-ability teachers are found disproportionately in these districts and they pay higher average salaries (Goldhaber, DeArmond, Player, and Choi, 2008), this could explain some portion of interdistrict returns. Probability models (not shown) indicate that teachers from selective colleges are more likely to be in districts with these arrangements, but accounting for this increased likelihood in Eq. (1) does not explain the overall premium. Another explanation that might give rise to the college selectivity premium for teachers is the fact that, because of employment connections made during student teaching, teachers may be more likely to be hired into districts near the schools from which they graduated, and districts near selective colleges may pay more than areas near less selective colleges. The data do not permit a detailed investigation of this hypothesis. However, as an investigative test I calculated the average teacher salary near each college19 and introduced it as a regressor in Eq. (1). The purpose of this is to detect whether there would still be premiums associated with attending a more selective college in the hypothetical case where all teachers remain local to the college. With the inclusion of this variable the coefficients are reduced by approximately half, and teachers from selective and competitive colleges receive premiums of approximately 7.5% and 6%, respectively. Thus, there is some evidence that the
12.7% premium for selective colleges and an 8.3% premium for competitive colleges after 10 years. Full results are available upon request. 18 Interestingly, nearly all districts that offer these bonuses also report using a single salary schedule. In the SASS, 8.2% of teachers are in a district that uses location pay, 18.2% of teachers are in districts that use some form of subject shortage pay, and 10.4% of teachers are in districts that offer excellence pay. 19 Average salaries were calculated as the average of the per-teacher instruction expenditure in each district with at least one school in the same county as the college. These data were available from the School District Finance Survey, part of the CCD.
labor conditions near the college explain some, but not all, of the premium. 4.1.2. Within-district premiums Beyond the fact that teachers from more selective colleges are in districts with higher salary levels and growth rates, an alternative explanation for the discrepancy between the returns using reported salaries and using district salary schedule information is that teachers from more selective colleges are rewarded within districts as well. Although the salary schedule is rigid for teachers of a given experience and education level, there may be some opportunities for teachers to earn income (such as new teacher mentoring) above the salary schedule. Similarly, there is some anecdotal evidence that principals or district administrators may have some flexibility to “bump” a teacher up the salary schedule by crediting them with extra experience if that teacher is perceived to be especially productive. If teachers graduating from selective colleges had a greater ability to receive such benefits, there may be returns to selectivity within districts. To calculate the within-district returns to ability, I employ district fixed effects ¯ k ) = ˇ0 + ˇ1 (Xi − X¯ k ) + ˇ2 (Ci − C¯ k ) + i (Wi − W
(2)
where the difference in teacher i’s salary from the average salary in district k is a function of how different that teacher is from the other teachers in the district and the difference in selectivity of the college from the average selectivity. The coefficients in ˇ2 capture the within-district college selectivity premium. As a caveat, districts only have, on average, 8 teachers represented in the SASS. Such small district-specific samples may weaken the findings, as the within-district estimates rely on sufficient variation in the experience levels and academic abilities of teachers within districts. Nonetheless, it is instructive to look within districts to see whether there appears to be a premium for college selectivity. The first column of Table 5 shows district fixed effects for every district that has at least three teachers in the sample. The within-district premium to college selectivity in this case is around 0.8%. To provide some robustness to these
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results and ensure sufficient within-district variation, the next column restricts the sample to districts with at least 50 teachers sampled by the SASS (a total of 41 districts). With this restriction in place, the within-district premium for attending a selective or competitive college is around 2.0%, significantly larger than the premiums calculated in the first column of the table. The final column restricts the analysis to the single largest district represented in the SASS.20 The size of the coefficient for selectivity for this largest district is similar to the estimate using the largest 41 districts but is not statistically significant. Those attending a competitive college, however, appear to receive a large and statistically significant within-district premium. Because the data were not designed to be used in a fixed effects framework, I tested the robustness of these findings of intra-district returns by including the district’s starting salary as an independent variable in Eq. (1). Results from these regressions (not shown) are consistent with the fixed effects models and indicate a premium for those from the most selective colleges of approximately 2%. Taken together, these results suggest that teachers from the most selective colleges receive a premium of up to 2 percentage points of their total return. While this increase may appear small, it translates to up to 35% of the total return, based on the results from Table 2. Thus, despite the rigid salary structure in public education, teachers from the most selective colleges have an advantage beyond being able to sort into the highest paying districts and receive pay above what would be expected given their education and experience levels. All results from this paper use the teacher’s total income from school as the dependent variable in order to capture the total returns in base salary and additional compensation. As a final investigation of within-district returns, I use the teacher’s reported base salary and contrast that with total school income in an effort to discern whether high-ability teachers are “bumped up” the schedule or whether the within-district premiums are from extracurricular assignments. The coefficients from these regressions (not shown) are substantively unchanged from those using total salary, implying that the within-district premium for attending a more selective college is largely captured in the teacher’s base salary. 5. Conclusion Despite the rigid salary structure for public school teachers, the findings from this paper provide evidence of positive returns to ability in the teacher labor market. The estimates of the size of this return indicate that teachers who graduate from more selective colleges earn between 7% and 14% more than those who graduate from noncompetitive schools. Based on recent estimates of average teacher salaries, this translates to an annual premium of
20 The largest district in the sample reported that it relies on a single salary schedule. This district was not drawn at random and thus one cannot expect the results to be generalized to all districts. This example serves merely as an illustration that there are returns to ability even within a district that reports using a salary schedule.
between $3300 and $6700. Thus, given prior evidence that teachers’ cognitive ability affects student outcomes, the public teacher labor market appears to reward productivity. An investigation of the source of the premium sheds an important light onto how the teacher labor market functions. Much of the premium is due to the fact that highability teachers sort into districts that pay more. However, the premium for academic ability does not appear to be entirely captured by the steps on the salary schedule and evidence suggests that there are within-district returns. An investigation of these returns shows that high-ability teachers receive higher salaries than one would predict given their education and experience. Models attempting to control for the salary schedule reveal that up to 2 percentage points, or up to 34% of the premium, is found within districts. These results are important in understanding the way that the teacher labor market rewards teacher ability. As evidence mounts about the importance of teacher quality, policymakers face the task of determining how to attract high quality teachers. These results suggest that high quality teachers are rewarded in teaching, but these rewards arise primarily from their sorting into higher paying states and districts. Thus, any effort to expose these high-ability teachers to the most disadvantaged students would need to address the mechanism by which teacher ability is currently rewarded in the teacher labor market. Acknowledgements I am grateful for valuable mentoring and feedback that Dan Goldhaber provided during the early work on this paper. I am also very grateful for helpful comments from Shelly Lundberg, Eugene Silberberg, two anonymous referees, and numerous participants during presentations at the University of Washington, Mathematica Policy Research, and the 2007 meeting of the American Education Finance Association. References Bacolod, M. (2007). Do alternative opportunities matter? The role of female labor markets in the decline of teacher quality 1960–1990. Review of Economics and Statistics, 89(4), 737–751. Ballou, D. (1996). Do public schools hire the best applicants? Quarterly Journal of Economics, 111(1), 97–133. Barron. (1995). Barron’s profiles of American colleges 1994. Hauppauge, NY: Barron’s Educational Series. Boyd, D., Lankford, H., Loeb, S., & Wyckoff, J. (2003). Analyzing the determinants of the matching public school teachers to jobs: Estimating compensating differentials in imperfect labor market. NBER Working Paper 9878, National Bureau of Economic Research. Brewer, D. J., Eide, E. R., & Ehrenberg, R. G. (1999). Does it pay to attend an elite private college? Cross-cohort evidence on the effects of college type on earnings. Journal of Human Resources, 34(1), 104–123. Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2007). Teacher credentials and student achievement in high school: A cross-subject analysis with student fixed effects. NBER Working Paper 13617, National Bureau of Economic Research. Corcoran, S. P., Evans, W. N., & Schwab, R. M. (2004). Women, the labor market, and the declining relative quality of teachers. Journal of Policy Analysis and Management, 23(3), 449–470. Figlio, D. N. (1997). Teacher salaries and teacher quality. Economics Letters, 55(2), 267–271. Figlio, D. N. (2002). Can public schools buy better-qualified teachers? Industrial and Labor Relations Review, 55(4), 686–699.
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