Many theories developed in the social sciences argue that education is of major causal importance for a variety of outcomes. The empirical quantification of education effects, however, is a challenging task. First, education is a choice variable driven by numerous factors, only some of which are observed, and which often have a direct effect on the outcome, too. Second, education is commonly measured by the years of schooling which largely disregards the complexity of a diverse education system. Third, the effects of education are likely heterogeneous over different educational levels and across individuals. As a consequence, if potential confounders and heterogeneity are neglected in a regression-type model, then standard estimators will generally be biased for the true causal effect.
This project aims at the estimation of causal education effects using a unique feature of the Swiss education system. Pupils around the age of 12 had to pass a centrally organized exam (the “Sekundar- or Gymnasialprüfung”). The result of this exam determined the level of secondary school that pupils could attend, and their educational track. Thus, the exam had a large impact on the highest education achieved. For estimation purposes, we can take advantage of a discontinuity in the classification scheme. Pupils below a certain threshold were classified in lower level secondary school, pupils above the threshold in higher level secondary school. Strategic sorting near the treshold can be plausibly ruled out because grading was delegated to external experts. This allows us to analyze the education outcomes of pupils near the discontinuity as if they would come from a randomized experiment.
The project is structured in two parts. The first part is concerned with a large survey of former pupils. In preparatory field work, we have identified several schools that conducted the test and archived the old exam results. We have collected this data and updated the contact details of about 3000 former pupils. As part of the current project, the database will be extended to include even more schools/former pupils. In a next step, we will conduct a large scale survey about demographic aspects (e.g., civil status, fertility, and health related behavior), economic aspects (e.g., employment prospects, earnings, risk preferences, time discounting), political interest (e.g., turnout, party identification, political attitudes), and sociological and psychological aspects (e.g., altruism, discrimination, social capital). This will provide us a unique database worldwide.
The second part tackles the empirical quantification. Using modern regression discontinuity methods, we estimate causal education effects by comparing pupils just below and above the threshold and how they differ in the outcome of interest. These pupils are assumed to be similar, and thus comparable. Given the nature of our data, we expect to obtain significant education effects for a large range of topics. The results of a pre-study are promising and confirm our expectations. From a policy perspective, our results are, among other things, of great relevance in the on-going debate about harmonizing the Swiss education system. Fully understanding the causal effects of education is crucial for a systematic, and well-founded policy discussion, and we will feed this discussion with extensive empirical evidence.