INCENTIVES TO TEACH BADLY

INCENTIVES TO TEACH BADLY? AFTER-SCHOOL TUTORING IN DEVLOPING COUNTIRES

S. Jayachandran (2008)

Principal Research Question and Key Result Does the ability of teachers to offer paid tuition outside of the school alter their incentives to deliver the in school service? The results of the analysis indicate that tutoring has a negative effect on test scores which suggests that being able to offer tutoring gives perverse incentives for teachers during the school day.  
Theory There are two theoretical links from tutoring to achievement. Student achievement is a function s(m, t) i.e. a function of material taught in school (m) and tutoring):

  1. Tutoring and School are substitutes then δ2s/(δm/δt) = smt < 0: This just states that the value of tutoring increases when less material is taught during the school day. This implies that a teacher can raise demand for tutoring by decreasing the amount of teaching during the school day.
  2. Tutoring and School are compliments then smt>0: This would  hold if there was some threshold level of achievement that students were trying to reach, and for students just shy of the threshold they could benefit from tutoring. This would incentivize the teacher to teach more material, such that there were more students who were able to get close to the threshold level.

The utility to the teacher depends both on his profit, and on the costs of raising/lowering the amount taught. This implies that a tradeoff between the costs of changing m, and the benefits of higher profits induced by changing m.

Given that the results indicate that tutoring and schooling are substitutes, this implies that policies to restrict the provision of t, may increase the amount of m, and also that increasing the costs of lowering m (for example through stricter supervision) could also be welfare creating.

Another possibility is to increase the number of third party tutors. If such tutors offer a higher valued service (for example through smaller tutoring groups), then the teacher will be incentivized to teach  more during the school day, as if less is taught then some students will be diverted to the higher quality third party tutor. The increased competition will reduce the cost of tutors, and more people will take up tutoring, and everyone enjoys the benefits of being taught more in the school day. The reason this holds is that there is less incentive to manipulate m when only some of the students induced to then purchase tutoring will do so from them.

 

Motivation In the developing world many students attend outside tutoring sessions and it is common for the student’s own teacher to also serve as the tutor. This is not common in the developed world. This could be because there is a lower opportunity cost of time due to income effects in the developing world. It could be that there is smaller supply of educated non-teachers who can serve as tutors. Also, less effective means of monitoring teachers by supervisors and parents may increase the ability to rent seek by teachers thus increasing their interest in providing tutoring – this might incentivize teachers to avoid teaching the curriculum in schools in order to generate demand for their fee-generating tutoring classes. If this is the case then all students are made worse off (by less formal education), but those who are hit the most are those who are unable to afford (or otherwise do not demand) tutoring. As such, rather than making the education sector more efficient (by improving access to education for weaker students/those who demand more education) it may actually create inefficiencies. In this case banning teachers from tutoring, or reducing the barriers of entry for third party tutors could be welfare increasing for all students even for those who do not take up outside tutoring. 
Experiment/ Data Data are from a large nationwide survey of students, schools, teachers and families conducted in Nepal. There are 3850 public schools and 890 private schools in Nepal. Students who have completed year 10 and taken the national exam for which the results are recorded are the focus. A random sample of schools is chosen. There are demographic details of the schools, as well as data on whether the student took tutoring, and subjective measures of the quality of school teaching. 
Strategy

ExamScoreijk = βOffersjk + θTakesijk + λi + ρk + εijk                (1) 

This is a fixed effects  model. i is individual, j is school and k is subject. Offers is a dummy that equals 1 if the school offers tutoring in that subject. Thus it is identified by comparing subjects within a school. Making the estimation within school reduces endogeneity concerns such as schools with more resources/brighter students providing more/less tutoring.

To test the notion that there is negative selection into Offers, a regression with Offers as the dependent variable is regressed on σ(PriorExamScore)ijk . If sigma is negative this implies that selection into offering tutoring is negative, as passing the exam is associated with a reduction in offering of tutoring.                                               (2).

A DID estimation is estimated

ExamScoreijk = βOffersjk + θTakesijk + τ(Public * Offers) + λi + ρk + εijk                  (3) 

Where tau is the differential effect that offering tutoring has in a public school (as opposed to a private school). The assumption is that the unobservable elements that encourage selection into OFFERS are the same across private/public schools. An interaction between Public*Takes is also included.

 

Results The results from (1) are negative for Offers, but not really significant. Takes is negative and significant. This indicates that worse students may be selecting into tutoring classes. Whilst some endogeneity is removed by looking within school, it is still possible that whether the school offers tutoring in a specific subject is driven by individual student/teacher ability in that particular subject. Thus, the negative coefficient on Offers could just be reflecting the negative spillovers from the school having to offer tutoring in the first place (due to low quality students).This is partially rebuffed by the results of the Offers regression (2) which shows no relationship between offering tutoring, and past achievement, although this is analyzed on a non-random subsample of the data.

The results of (3) are that tau is negative and significant indicating that when tutoring is offered students in public schools are differentially more likely to fail the exam (presumably as private school teachers are less able to vary the amount of material that is taught in the school day due to better monitoring/financial incentive). The Takes*Public interaction is positive, indicating that selection is negative (I don’t get this bit).  The effect is larger when the sample is restricted to small towns as the school more likely to behave like a monopolist with control over both schooling and tutoring. In urban areas there is likely to be more competition.

Using whether the teacher completed the in school curriculum as the dependent variable, it is shown that the coefficient on OFFERS is negative, indicating that offering tutoring may be incentivizing teachers to teach less.

Robustness
  • Uses different samples.
  • Test alternative hypotheses: could be mechanical fatigue, but the relationship between teacher effort and offers is only marginally significant and negative.

 

Problems
  • If preventing teachers from tutoring decreases wages in the educational sector sufficiently, this may have the effect of dissuading talented teachers from entering the profession, and in the long run this could damage the education sector and be welfare reducing for all students.
  • The subjective measures were based on post exam reflections which could indicate recall bias/be affected by personal feelings toward the teacher.
  • The DID estimation may estimate the differential effect of tutoring in public schools but it cannot speak to the direction of causation. It is still possible that results are driven by negative spillovers from tutoring provision i.e. negative selection.

 

Implications One reason for poor educational outcomes in developing countries could be that teachers lack strong performance incentives. This could indicated that a partial ban on teacher’s tutoring or encouraging third party entrants could be welfare improving, although this will depend on how people sort into those professions. Additionally there may be political constraints that prevent this course of action, as civil service teachers will tend to be well unionized, and a politically visible component of society. That private schools perform better could be an indication that performance pay, or increased monitoring by parents due to a financial stake in the education provided could be useful for increasing test scores.The results could have implications for other sectors. In particular, health workers with a private practice on the side may be facing very similar incentive structures. In actual fact, the incentives may be even stronger, as only one patient observes the outcome of their effort, whereas in a school, potentially many student/parents etc. observe the outcome. This could mean that the costs of varying m for health workers is much lower (as detection is harder) and hence they are more likely to do so in order to increase extractable rents.
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