Incentives and Teacher Effort: Further Evidence from a Developing Country
Hai-Anh H. Dang and Elizabeth M. King 1 Forthcoming at Economics of Transition
Few would contest that teachers are a very important determinant of how much students learn in school, and how to improve teacher performance has been the focus of lively policy debate in rich and poor countries.two problems can get in the way. One is that teachers may not be adequately prepared to teach, and, second, even when teachers are well-trained, they may not be motivated to do their best because good performance is not aptly rewarded, salaries being determined primarily by seniority, not performance, and performance being neither monitored nor measured. To improve performance, some countries have linked at least a portion of teacher pay to criteria related to performance, usually to how well students do on tests.
Furthermore, after-school work hours can better represent teacher effort for different reasons. One, since these hours are (largely) chosen by teachers, by design, they are better measures of teacher effort than the official, fixed in-class teaching time. Two, if teacher effort were regarded as a continuous and unobserved (latent) index variable that is manifested in terms of both absence and number of work hours (or tutoring activities), then teacher work hours would approximate this variable better since work hours are a continuous variable with multiple values.
One limitation of our study, however, is that since only a single cross-section of school survey data is available, we assume that all the (observed or unobserved) school-level characteristics are time-invariant and exogenous. This assumption is reasonable in the Lao context for various reasons. On the one hand, teachers in Lao PDR mostly have little choice about their location assignment, suggesting that our model can provide causal impacts of incentives on teacher effort. On the other hand, the specific educational context in Lao PDR that we will discuss later suggests that this assumption is not unreasonable. Moreover, our simultaneous OLS-probit model at the teacher level effectively functions as a teacher random effects model that can add an additional layer of identifying information to the traditional school random effects model that can provide more accurate estimates. Still, despite the favorable evidence for the assumption on these school characteristics and our econometric modelling, for extra precaution, we present estimation resulrt.
Teacher effort is difficult to measure in part because it happens behind classroom doors, away from the eyes of school inspectors, parents and even school principals, and in part because effort has several dimensions. Absenteeism has been used as a proxy measure of effort in previous studies, but it is typically an unreliable indicator when data are self-reported; self-interest and possible collusion among teachers and other school actors tend to underestimate absence rates. To overcome this measurement problem, a survey of schools conducted in Bangladesh, Ecuador, India, Indonesia, Peru, and Uganda used unannounced school visits and checks of teachers present against a roster of teachers who were supposed to be in classrooms (Chaudhury et al., 2006).
Various incentives to improve teacher effort and performance have been evaluated, but largely with mixed results. In a randomized study in India, Muralidharan and Sundarraman (2011) find that performance pay incentives do not reduce teacher absence but do increase their teaching effort (conditional on their presence)..
