4 resultados para Eaves Dropping

em Repositório digital da Fundação Getúlio Vargas - FGV


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Este trabalho teve como interesse principal verificar quais as principais causas para a evasão, apresentadas pelos cursos a distância, oferecidos pelas instituições brasileiras. O estudo foi realizado a partir de revisões bibliográficas e pesquisa de campo. Na revisão bibliográfica, observa-se que a sociedade brasileira se depara, desde há muito tempo, com a questão da qualidade da educação. É possível acompanhar a mudança de foco das políticas públicas na área da educação: de uma abordagem quantitativa para uma abordagem qualitativa. O estudo apresenta a EAD como uma modalidade de ensino capaz de somar forças para que seja minimizada a questão da oferta de uma educação de qualidade. São mostrados seu surgimento, desenvolvimento e peculiaridades e como o advento da Internet favoreceu o aumento da comunicação digital, aumentando a procura pela EAD. Cada vez mais, a EAD está ganhando força no processo educativo brasileiro. Porém, assim como a educação tradicional, precisa enfrentar inúmeros problemas. Um deles, foco deste trabalho, é o (ainda) alto índice de evasão. Pesquisando as principais causas para o fato, este trabalho conclui que fatores como qualidade da interação entre alunos e professores bem como o reconhecimento da qualidade dos cursos oferecidos devem ser trabalhados por todas as instituições, públicas e privadas que desejem trabalhar com essa modalidade de ensino.

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This paper evaluates the long-run effects of economic instability. In particular, we study the impact of idiosyncratic shocks to father’s income on children’s human capital accumulation variables such as school drop-outs, repetition rates and domestic and non-domestic labor. Although, the problem of child labor in Brazil has declined greatly during the last decade, the number of children working is still substantial. The low levels of educational attainment in Brazil are also a main cause for concern. The large rotating panel data set used allows for the estimation of the impacts of changes in occupational and income status of fathers on changes in his child’s time allocation circumstances. The empirical analysis is restricted to families with fathers, mothers and at least one child between 10 and 15 years of age in the main Brazilian metropolitan areas during the 1982-1999 period. We perform logistic regressions controlling for child characteristics (gender, age, if he/she is behind in school for age), parents characteristics (grade attainment and income) and time and location variables. The main variables analyzed are dynamic proxies of impulses and responses, namely: shocks to household head’s income and unemployment status, on the one hand and child’s probability of dropping out of school, of repeating a grade and of start working, on the other. The findings suggest that father’s income has a significant positive correlation with child’s dropping out of school and of repeating a grade. The findings do not suggest a significant relationship between a father’s becoming unemployed and a child entering the non-domestic labor market. However, the results demonstrate a significant positive relationship between a father becoming unemployed and a child beginning to work in domestic labor. There was also a positive correlation between father becoming unemployed and a child dropping out and repeating a grade. Both gender and age were highly significant with boys and older children being more likely to work, drop-out and repeat grades.

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This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

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This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.