What is it about?

Evidence on educational returns and the factors that determine the demand for schooling in developing countries is extremely scarce. Building on previous studies that show individuals underestimating the returns to schooling, we use two surveys from Tanzania to estimate both the actual and perceived schooling returns and subsequently examine what factors drive individual misperceptions regarding actual returns. Using ordinary least squares and instrumental variable methods, we find that each additional year of schooling in Tanzania increases earnings, on average, by 9 to 11 percent. We find that on average individuals underestimate returns to schooling by 74 to 79 percent and three factors are associated with these misperceptions: income, asset poverty, and educational attainment.

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Why is it important?

Shedding light on what factors relate to individual beliefs about educational returns can inform policy on how to structure effective interventions in order to correct individual misperceptions. There are numerous supply and demand side factors that likely influence and constrain an individual in a developing country from obtaining more schooling. Supply-side factors, for example, include distance to school, teacher training and the availability of textbooks and physical facilities. Demand-side factors comprise enrolment fees, uniforms, the quality of the educational experience and the opportunity cost of one’s time spent in school. Because schooling generates important monetary benefits, in some settings, it may be more appropriate to examine the role individual perceptions of these monetary benefits play and their interaction with one’s perceived opportunity cost of schooling, if any, in influencing one’s educational demand. If individuals misperceive the future monetary benefits from obtaining more schooling, correcting such misperceptions may be a very cost-effective approach towards increasing school participation We show that individuals substantially underestimate the returns to primary and secondary schooling and we point to those demographic groups that underestimate the educational returns the most. This kind of information can be an important input to policymakers in designing effective information targeting interventions. However, such approach merits an important caution for policy makers. Although information targeting may be a relatively inexpensive approach to boost the demand for schooling in the short run, it is important to consider the potential general equilibrium effects of such a policy and its dynamic impact on the returns to education, especially for the segments of the labour market that become more abundant. We find three powerful predictors that drive the gap between the subjectively perceived average earnings and the actual average measured earnings: the respondent’s age, whether one has a secondary school or university-level education and one’s poverty status (based asset poverty and earnings). Perhaps most policy-relevant is the fact that the largest effects, in terms of the estimated coefficient magnitudes, driving the discrepancy between measured earnings and subjective beliefs about earnings are associated with one’s own earnings and one’s own educational attainment. The lowest earners, as well as the lowest decile in asset poverty, are the two groups of individuals who underestimate the average earnings the most. Surprisingly, secondary school degree holders (relative to primary school degree holders or no degree holders) also, underestimate educational returns. Although our measure of the returns may still be biased, the individuals’ implied estimates of the returns are so low -- about 3-4 percent per year of secondary schooling -- that unless we believe our estimates of the actual educational returns are highly biased such that the true returns in Tanzania are dramatically lower than the returns we estimate in this paper, it seems likely that individuals do in fact underestimate the true returns to schooling.

Perspectives

We find three powerful predictors that drive the gap between the subjectively perceived average earnings and the actual average measured earnings: the respondent’s age, whether one has a secondary school or university-level education and one’s poverty status (based asset poverty and earnings). Perhaps most policy-relevant is the fact that the largest effects, in terms of the estimated coefficient magnitudes, driving the discrepancy between measured earnings and subjective beliefs about earnings are associated with one’s own earnings and one’s own educational attainment. The lowest earners, as well as the lowest decile in asset poverty, are the two groups of individuals who underestimate the average earnings the most. Surprisingly, secondary school degree holders (relative to primary school degree holders or no degree holders) also, underestimate educational returns. Although our measure of the returns may still be biased, the individuals’ implied estimates of the returns are so low -- about 3-4 percent per year of secondary schooling -- that unless we believe our estimates of the actual educational returns are highly biased such that the true returns in Tanzania are dramatically lower than the returns we estimate in this paper, it seems likely that individuals do in fact underestimate the true returns to schooling.

Dr. Plamen Nikolov
Harvard Institute for Quantitative Social Science

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This page is a summary of: What factors drive individual misperceptions of the returns to schooling in Tanzania? Some lessons for education policy, Applied Economics, June 2018, Taylor & Francis,
DOI: 10.1080/00036846.2018.1466991.
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