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Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can potentially diminish rates of adolescent pregnancy, given that educational attainment stands as the foremost risk factor influencing sexual initiation, the use of contraceptive methods during initial sexual encounters and fertility. The aim of this paper is to analyze the impact of the implementation of the public educational policy introducing full-time schools (FTS) for high schools in the state of Ceará, Brazil, on early pregnancy rates.

Using the difference-in-differences method with multiple time periods, we measured the average effect of this staggered treatment on the treated municipalities.

The main result indicates a reduction of 0.849 percentage points in the teenage pregnancy rate. Concerning dynamic effects, the establishment of FTS in treated municipalities results in a 1.183–1.953 percentage point decrease in teenage pregnancy rates, depending on the timing of exposure. We explored heterogeneous effects within socioeconomically vulnerable municipalities, yet discerned no impact on this group. Rigorous tests confirm the robustness of the results.

This paper aims to contribute to: (1) the consolidation of research on the subject, given the absence of such research in Brazil to the best of our knowledge; (2) the advancement and analysis of evidence-based public policy and (3) the utilization of novel longitudinal data and methodology to evaluate adolescent pregnancy rates.

The objective of this work was to analyze the income differential of the rural–urban worker in relation to the rural–rural worker and in relation to the urban–urban worker in the Brazilian labor market. Two databases were used, the 2005 and 2015 PNADs (Pesquisa Nacional Por Amostra de Domicílios).

The methodology is the decomposition approach proposed by Firpo et al. (2007, 2009). This method adopts estimates of unconditional quantile regressions, based on the concepts of influence function and recentered influence function (RIF).

Among the main results, income differentials were shown to benefit the urban–urban worker when compared to the rural–urban worker, and income differences to the benefit of the rural–urban workers, when these were compared to the rural–rural workers. The educational variable was relevant in explaining the income disparity and expressing increasing effects in the higher quantiles.

The methodology used in this work is considered recent in the literature as it is based on the RIF regression (Firpo et al., 2007, 2009). The main advantage of this method is the possibility of assigning a “composition effect” and a “wage structure effect” for each variable that determines the level of income at different points of the income distribution.