Does socioeconomic inequality affect education more in less wealthy municipalities

This study attempts to capture the full picture of educational development in an emerging country that is characterized by both high economic development and high socioeconomic inequality. A two-step model is used in this study. The first step uses the variables that are directly related to education to capture the educational efficiency of each municipality; the second step uses a statistical Tobit model to estimate the influence of the non-discretionary variables on the educational efficiency found in the first step. A previous categorization by clusters is also implemented to ensure a fair comparison among homogeneous municipalities. The results show significant discrepancies in the influence of socioeconomic variables on educational outcome, which depends on the welfare of the cluster. Data EnvElopmEnt analysis – DEa • EDucational EfficiEncy • Basic EDucation • socioEconomic inEqualitiEs 4 7 0 D O E S S O C IO E C O N O M IC I N E Q U A L IT Y A F F E C T E D U C A T IO N M O R E I N L E S S W E A LT H Y M U N IC IP A L IT IE S ? 4 7 2 C a d e r n o s d e P e s q u is a v . 4 7 n . 1 6 4 p . 4 7 0 -4 9 3 a b r. /j u n . 2 0 17 T HE DEVELOPMENT OF A COUNTRY IS MEASURED BY FACTORS SUCH AS ECONOMIC performance, living standards, sustainability and equality. Developing countries exhibit discrepancies regarding these factors; for example, a developing country may have a high Gross Domestic Product – GDP – but a poor position on the Human Development Index – HDI. This discrepancy is the case, for example, in 2014, in Brazil, India and Russia, which are ranked 7th, 9th and 10th respectively in terms of GDP, but 75th, 130th and 50th respectively on the HDI.1 High inequality can also be found within countries. For example, Brazil has the third-highest Gini index in Latin America. However, Brazil includes cities with a low Gini index of 0.28 (similar to Norway, which has a Gini index of 0.25) and cities with a high Gini index of 0.8. These substantial inequalities imply that areas for improvement may differ among cities or regions in a country and, consequently, that educational policies must also differ. Rumberger and Palardy (2005) show, in a study that is based on a sample of 14,199 American high school students, that the policies that are designed to promote school performance in one region may not promote performance and may even lead to worse performance in another region. Thus, within-country discrepancies make developing countries, such as Brazil, interesting to study because, despite high economic development and high socioeconomic inequalities, the different 1 Available at: ; . Access on: 03 May 2017. 4 7 1 M a ia C rstin a G ra m a n i C a d e r n o s d e P e s q u is a . 4 7 n 16 4 p . 4 7 0 -4 9 3 a b r/ju n . 2 0 17 4 7 3 cultures among regions and the large discrepancies within regions can lead to poor performance in key areas such as education. The education performance in developing countries is greatly affected by non-discretionary variables, and it is necessary to use factors in its analysis that are not directly related to education such as schools, teachers and spending. In developing countries with significant inequality, the aspects that are related to basic living conditions, such as access to sewage systems and water treatment, and the factors that are related to social development variables, such as maternal education, illiteracy rates, dropout rates, and others, must be considered in educational performance analysis. A within-country investigation can help government decision-makers to determine which resources will actually affect the performance of education in each region of a country. In a developing country that spans a continent and has large socioeconomic inequalities, such as Brazil, potential improvements must differ from region to region, and the question “Does socioeconomic inequality affect education more in less wealthy municipalities? ” becomes important. The contribution of this paper is threefold. (1) First, because of the within-country discrepancies, we categorize Brazilian municipalities in homogeneous clusters to more equitably make the relative comparison. (2) To consider the link between educational efficiency and socioeconomic indicators, we built a two-step model that in the first step, analyses the differing within-country educational needs. And (3), in the second step, the model shows the different influences of nondiscretionary variables on educational efficiency. In the first step, the Data Envelopment Analysis – DEA – model is used to measure the use of resources to achieve greater performance and, in the second step, a Tobit regression shows the different effects of high-level socioeconomic inequalities on the educational efficiency in municipalities. The remainder of the paper is organized as follows. In the next section, a brief literature review of educational efficiency is presented, which is followed by a specific description of the Brazilian educational system, including its structure, financing and evaluation. Section 4 presents the two-step model, the clustering method and the database for both educational efficiency and the socioeconomic conditions of developing countries. The empirical results of the two-step model are discussed in section 5. Finally, in section 6, we present some concluding