Earnings Inequalities and Educational Mobility in Brazil over Two Decades

This paper studies the impact of changes in educational opportunities on various definitions of labour market inequalities in Brazil over two decades (1976-96). Using four editions of the nationally representative PNAD survey, we analyze the evolution of overall inequalities and inequalities of opportunity in 40-49 year old males’ earnings. We design and implement semiparametric decompositions of the respective effects of (i) schooling expansion, (ii) changes in the structure of earnings, and (iii) changes in intergenerational educational mobility. Earnings inequalities varied little over the period, with a peak in the late 1980s that can be imputed to hyperinflation. First of all, the decompositions show that changes in the distribution of education contributed to the increase in both overall earnings inequalities and inequalities of opportunity among the oldest generations, before sharply reducing them among the post-WWII cohorts. Secondly, the decrease in returns to education also contributed to equalizing labour market opportunities in the 1988-96 period. Thirdly and lastly, the changes in educational mobility were not large enough to significantly affect earnings inequalities, whereas it is shown that they should play a prominent role in equalizing opportunities in the future.Equality of opportunities, Labour market, Inequality decomposition, Brazil

The Measurement of Educational Inequality: Achievement and Opportunity

This paper proposes two related measures of educational inequality: one for educational achievement and another for educational opportunity. The former is the simple variance (or standard deviation) of test scores. Its selection is informed by consideration of two measurement issues that have typically been overlooked in the literature: the implications of the standardization of test scores for inequality indices, and the possible sample selection biases arising from the Program of International Student Assessment (PISA) sampling frame. The measure of inequality of educational opportunity is given by the share of the variance in test scores that is explained by pre-determined circumstances. Both measures are computed for the 57 countries in which PISA surveys were conducted in 2006. Inequality of opportunity accounts for up to 35 percent of all disparities in educational achievement. It is greater in (most of) continental Europe and Latin America than in Asia, Scandinavia, and North America. It is uncorrelated with average educational achievement and only weakly negatively correlated with per capita gross domestic product. It correlates negatively with the share of spending in primary schooling, and positively with tracking in secondary schools.educational inequality, educational achievement, inequality of opportunity

The measurement of educational inequality: Achievement and opportunity

This paper proposes two related measures of educational inequality: one for educational achievement and another for educational opportunity. The former is the simple variance (or standard deviation) of test scores. Its selection is informed by consideration of two measurement issues that have typically been overlooked in the literature: the implications of the standardization of test scores for inequality indices, and the possible sample selection biases arising from the Program of International Student Assessment (PISA) sampling frame. The measure of inequality of educational opportunity is given by the share of the variance in test scores that is explained by pre-determined circumstances. Both measures are computed for the 57 countries in which PISA surveys were conducted in 2006. Inequality of opportunity accounts for up to 35 percent of all disparities in educational achievement. It is greater in (most of) continental Europe and Latin America than in Asia, Scandinavia, and North America. It is uncorrelated with average educational achievement and only weakly negatively correlated with per capita gross domestic product. It correlates negatively with the share of spending in primary schooling, and positively with tracking in secondary schools.Educational inequality, educational achievement, inequality of opportunity.

Neighborhood effects and take-up of transfers in integrated social policies: Evidence from Progresa

When potential beneficiaries share knowledge and attitudes about a policy intervention, that can influence their decisions to participate and, in turn, change the effectiveness of both the policy and its evaluation. This matters notably in integrated social policies with several components. We examine neighborhood effects on the take-up of the schooling subsidy component of the Progresa-Oportunidades program in Mexico.We exploit random variations in the local densities of program beneficiaries generated by the randomized evaluation. Higher program densities in areas of 5 km radius increase the take-up of scholarships and enrollment at the junior-secondary level. These neighborhood effects exclusively operate on households receiving another component of the program, and do not carry over larger distances. While several tests reject heterogeneities in impacts due to spatial variations in implementation, we find suggestive evidence that neighborhood effects stem partly from the sharing of information about the program among eligible households

Inequality of Educational Opportunities in Egypt

This paper documents inequalities in access to education and educational achievements at basic and secondary education levels in Egypt. Examination of three cohorts suggests that, although basic education has democratized, some inequities in access to general secondary and college education have persisted over the past two decades. The analysis of test-scores from TIMSS and national examinations over time shows that more than a quarter of learning outcome inequality is attributable to circumstances beyond the control of a student, such as socioeconomic background and birthplace. The high level of overall achievement inequality observed makes inequities in learning opportunities between Egyptian youth high compared to other countries in absolute levels. Moreover learning gaps among pupils from different backgrounds appear at early grades. High and unequal levels of expenditures in private tutoring and tracking into vocational and general secondary schools that depends on a high stakes examination substantially contribute to unequal learning outcomes

Benefit in the wake of disaster: Long-run effects of earthquakes on welfare in rural Indonesia

We examine the long-term effects on individual economic outcomes of a set of earthquakes - numerous, large, but mostly not extreme - that occurred in rural Indonesia since 1985. Using longitudinal individual-level data from large-scale household surveys, together with precise measures of local ground tremors obtained from a US Geological Survey database, we identify the effects of earthquakes, exploiting the quasi-random spatial and temporal nature of their distribution. Affected individuals experience short-term economic losses but recover in the medium-run (after two to five years), and even exhibit income and welfare gains in the long term (six to 12 years). The stocks of productive assets, notably in farms, get reconstituted and public infrastructures are reconstructed with some improvements, seemingly partly through external aid, allowing productivity to recover. These findings tend to discount the presence of poverty traps, and exhibit the potential long-term benefits from post-disaster interventions in context where disasters primarily affect physical assets

Benefits to elite schools and the formation of expected returns to education: Evidence from Mexico City

We study the effects of admission into elite public high schools in Mexico City on students' expected earnings, arguing these effects provide an indication of the value-added those schools produce. Using data for the centralized and exam-based allocation of students into schools and an adapted regression discontinuity design strategy, we find that admission substantially increases learning achievement, and also the future earnings and returns students expect from a college education, but no effect on the earnings expected with high school education alone. This suggests that students believe that the benefits from their elite education are complements to a college education

Policy-induced Social Interactions and Schooling Decisions

This paper considers a conditional cash transfer program targeting poor households in small rural villages and studies the effects of the geographic proximity between villages on individual enrollment decisions. Exploiting variations in the treatment status across contiguous villages generated by the randomized evaluation design, the paper finds that the additional effect stemming from the local density of neighboring recipients amounts to roughly one third of the direct effect of program receipt. Importantly, these spatial externalities are concentrated among children from beneficiary households. This suggests that the intervention has enhanced educational aspirations by triggering social interactions among the targeted population

The Measurement of Educational Inequality: Achievement and Opportunity

This paper proposes two related measures of educational inequality: one for educational achievement and another for educational opportunity. The former is the simple variance (or standard deviation) of test scores. It is selected after careful consideration of two measurement issues that have typically been overlooked in the literature: the implications of the standardization of test scores for inequality indices, and the possible sample selection biases arising from the PISA sampling frame. The measure of inequality of educational opportunity is given by the share of the variance in test scores which is explained by pre-determined circumstances. Both measures are computed for the 57 countries in which PISA surveys were conducted in 2006. Inequality of opportunity accounts for up to 35% of all disparities in educational achievement. It is greater in (most of) continental Europe and Latin America than in Asia, Scandinavia and North America. It is uncorrelated with average educational achievement and only weakly negatively correlated with per capita GDP. It correlates negatively with the share of spending in primary schooling, and positively with tracking in secondary schools

The Measurement of Educational Inequality: Achievement and Opportunity

This paper proposes two related measures of educational inequality: one for educational achievement and another for educational opportunity. The former is the simple variance (or standard deviation) of test scores. It is selected after careful consideration of two measurement issues that have typically been overlooked in the literature: the implications of the standardization of test scores for inequality indices, and the possible sample selection biases arising from the PISA sampling frame. The measure of inequality of educational opportunity is given by the share of the variance in test scores which is explained by pre-determined circumstances. Both measures are computed for the 57 countries in which PISA surveys were conducted in 2006. Inequality of opportunity accounts for up to 35% of all disparities in educational achievement. It is greater in (most of) continental Europe and Latin America than in Asia, Scandinavia and North America. It is uncorrelated with average educational achievement and only weakly negatively correlated with per capita GDP. It correlates negatively with the share of spending in primary schooling, and positively with tracking in secondary schools.Educational inequality ; Educational achievement ; Inequality of opportunity