Institutional and historical inequalities can have a sizable impact on the disadvantages that some populations face until this day. Particularly, it is often the case that children born in remote and rural communities face more difficulties in accumulating human capital than their peers in urban areas. In Barcelona School of Economics Working Paper 1273, “Teacher Compensation and Structural Inequality: Evidence from Centralized Teacher School Choice in Peru,” authors Matteo Bobba, Tim Ederer, Gianmarco León-Ciliotta, Christopher A. Neilson, and Marco Nieddu study how increasing teacher compensation in hard-to-staff schools in rural areas can reduce inequality in access to qualified teachers by studying a policy conducted in Peru.
Not willing to move that far away
The importance of a good teacher cannot be understated. Having a better one can play an important role in improving students’ performance. The problem is that some localities may have more difficulties in attracting talent. They might be too far away, or present less attractive amenities for prospective teachers to choose to work there.
This has some dire consequences. In this paper, the authors study the case of Peru and find that teachers at rural schools tend to be less competent and more likely to lack the appropriate teaching certifications. In turn, approximately one in four students in these schools perform below the basic curricular requirements in Spanish and math in standardized national tests. The data shows a high correlation between concentration of competent teachers and higher students’ achievement outcomes. (See Figure 1)
Paying for your troubles
The allocation of accredited and qualified teachers into public schools takes place through a centralized deferred acceptance mechanism. In this process, teachers are ranked based on the grades obtained in a standardized knowledge test. The highest ranked teacher is then allocated to her preferred position. The process continues with the second ranked teacher choosing her preferred option, and so on, until there are no more teachers or positions available. In a second stage all remaining positions are filled through a decentralized secondary market that includes teachers without accreditation. Many positions in the more rural and poorest parts of the country are filled through the latter, with the result that teachers assigned to rural schools have competency scores that are lower than those assigned to urban schools.
A wage compensation policy first implemented in 2014 and targeted to rural schools sought to correct this. According to their population and distance to the provincial capital, schools were divided in different categories that dictated the amount of the wage bonus a teacher could receive. This bonus could represent as much as 30% of a teacher’s monthly earnings.
The authors find causal evidence supporting the fact that these higher wages increased the number of teachers that were interested in those positions. The increased competition for places lead to a higher average competency of newly hired teachers in rural schools. Having on average a better pool of teachers in those schools is an important factor in explaining the large improvements that test scores showed for students in those targeted schools. Importantly, this result comes from new (and better prepared) teachers coming to high-paying schools and not by the increasing effort of the incumbents.
How extensive are these effects?
Then, the authors seek to extend the analysis by modeling the choices of teachers by means of using their revealed preferences in the data. This is done to test different alternative scenarios.
They find that wages are a more important factor for attracting teachers in rural schools than in urban ones. It is noticeable that more competent teachers seem to be particularly sensitive to school-level characteristics. This could mean that a complementary policy that enhances school infrastructure can make the policy even more effective in attracting qualified teachers.
Importantly, the model shows that although an important part of the positive effect of the policy is concentrated in those schools that are just below the cut-offs separating high-paying rural schools from others, it is true as well that these gains spread over to most rural schools. This is particularly true when looking at the effects on the share of filled vacancies. (See Panel A of Figure 2)
Can we make this policy even more effective?
The authors suggest we can. Although the policy has been able to reduce some of the pre-existing inequalities, it is inefficient and not large enough to effectively undo the inequality of initial conditions that hard-to-staff schools and their communities face. The authors then characterize alternative wage schedules that are consistent with two independent objectives: To fill every vacancy with a teacher, irrespectively of her/his quality, and to assign in each school with an open vacancy one teacher, which is at least as competent as the average one in urban schools. This can be done using a slight modification of the deferred acceptance mechanism that allows schools to post wages until the policy objectives are achieved.
A simulation of such a mechanism shows that the current way in which teachers are allocated has some room for improvement. If differences in school infrastructure were completely eliminated, the share of filled vacancies and the share of schools with higher quality teachers would rise at constant wage bills by an additional six and seven percentage points, respectively. Larger increments in equity can also be achieved if, instead of equalising school infrastructure, the number of teachers from rural locations were to increase by just 3% with respect to the actual number of applicants. This targeted teacher training policy would lead to significant cost savings for policies that seek to eliminate inequality. Filling every job vacancy would cost 30% less and providing equal access to high quality teachers would cost 35% less than the optimal policy with the existing stock of teachers.