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Reducing Schooling Inequality in Brazil: Demographic Opportunities and Inter-cohort Differentials

Author

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  • Carlos Eduardo Velez
  • Sergei Soares
  • Marcelo Medeiros

Abstract

The objective of this paper is to explore the interplay between schooling and demographics in Brazil. We would like to provide a preliminary answer to the question of how long will improvements in schooling of younger cohorts take o change the distribution of educational endowments of the total labor force. This answer depends on two factors. The first is the demographic composition of the working age population — the weight each cohort has in the 16 to 70 year old population. The second is the distribution of schooling within each cohort — its average educational level and the inequality within each cohort. These two factors — demography and education by cohort — define the average educational level and the distribution of education for the working age population in any given year. This paper takes a standard demographic projection and makes various hypotheses about the evolution of education — both the mean and inequality. According to these hypotheses, we will calculate how long improvements in the schooling of successive cohorts take to translate into significant improvements in the schooling of the working age population. Our results are somewhat pessimistic. We calculate that even very strong departures from the observed trend will take many years or decades to translate into significantly different educational endowments for the working age population. In other words, we show that demographic inertia is a strong factor preventing changes in educational endowments in periods shorter than a few decades. O objetivo deste trabalho é a exploração das relações entre escolaridade e demografia no Brasil. Gostaríamos de apresentar uma investigação preliminar sobre quanto tempo melhorias no sistema educacional vão demorar para se refletir na distribuição educacional da população em idade ativa (PIA). Este tempo de resposta depende de dois fatores. O primeiro é a composição etária da população em idade ativa — o peso de cada coorte na população de 16 a 70 anos. O segundo fator é a distribuição da instrução formal dentro de cada coorte — a média e a desigualdade de anos de estudo completados com sucesso. Estes dois fatores — demografia e educação por coorte — definem tanto o nível educacional médio como a distribuição da educação dentro da PIA para um ano qualquer. Neste texto, usamos uma projeção demográfica padrão e fazemos várias hipóteses sobre a evolução tanto da média como da desigualdade educacional. De acordo com essas hipóteses, é possível calcular quanto tempo melhorias no nível educacional de coortes sucessivas vão levar para se traduzir em melhorias significativas na distribuição da escolaridade da PIA. Os resultados, infelizmente, são um tanto pessimistas. Calculamos que até melhorias fortes com relação à tendência observada vão demorar anos ou até décadas para se transformar em dotações educacionais significativamente maiores e melhor distribuídas para a PIA. Em outras palavras, a inércia demográfica é um fator forte impedindo transformações dramáticas na distribuição da educação em períodos menores que algumas poucas décadas.

Suggested Citation

  • Carlos Eduardo Velez & Sergei Soares & Marcelo Medeiros, 2015. "Reducing Schooling Inequality in Brazil: Demographic Opportunities and Inter-cohort Differentials," Discussion Papers 0109, Instituto de Pesquisa Econômica Aplicada - IPEA.
  • Handle: RePEc:ipe:ipetds:0109
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    References listed on IDEAS

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    1. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    2. Angus Deaton & Christina Paxson, 1997. "The effects of economic and population growth on national saving and inequality," Demography, Springer;Population Association of America (PAA), vol. 34(1), pages 97-114, February.
    3. Bourguignon, Francois, 1979. "Decomposable Income Inequality Measures," Econometrica, Econometric Society, vol. 47(4), pages 901-920, July.
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