6 resultados para Two-Sided Matching
em Repositório digital da Fundação Getúlio Vargas - FGV
Resumo:
This paper measures the importance of indirect network effects in the adoption by colleges and students of ENEM, a standardized exam for high-school students in Brazil that can be used in college application processes. We estimate network effects and find that they are economically significant. Students are more likely to take ENEM the larger the number of colleges adopting it. Similarly, colleges are more likely to adopt it the larger the number of students taking the exam. Moreover, we find evidence that colleges play strategically and that heterogeneity determines their decisions. A college is less likely to adopt ENEM the larger the number of competitors adopting it. Colleges’ characteristics such as ownership and organization affect adoption decisions. In a counterfactual exercise we compare colleges’ adoption decisions under competition and under joint colleges’ payoffs maximization. Adoption rates are significantly reduced when colleges internalize the competitive effect, i.e., the effect of their decisions on other colleges’ payoffs. On the other hand, they increase when indirect network effects - the effect of students’ response to their decisions on other colleges’ payoffs - are also internalized. Competitive adoption rates are found to exceed joint optimum rates by a small difference. These results suggest that, without considering students’ welfare, adoption rates are excessive, but close to the joint optimum.
Resumo:
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.
Resumo:
No Brasil, a recente reformulação do Exame Nacional de Ensino Médio (ENEM) e a criação do Sistema de Seleção Unificada (SISU), um mecanismo de admissão centralizado que aloca os alunos às instituições, promoveram mudanças relevantes no Ensino Superior. Neste artigo, investigamos os efeitos da introdução do SISU na migração e evasão dos alunos ingressantes a partir dos dados do Censo de Educação Superior. Para tal, exploramos a variação temporal na adesão das instituições ao SISU e encontramos que a adoção do SISU está associada a um aumento da mobilidade entre municípios e entre estados dos alunos ingressantes em 3.8 pontos percentuais (p.p) e 1.6 p.p., respectivamente. Além disso, encontramos um aumento da evasão em 4.5 p.p. Nossos resultados indicam que custos associados à migração e comportamento estratégico são importantes determinantes da evasão dos alunos.
Resumo:
This article is motivated by the prominence of one-sided S,s rules in the literature and by the unrealistic strict conditions necessary for their optimality. It aims to assess whether one-sided pricing rules could be an adequate individual rule for macroeconomic models, despite its suboptimality. It aims to answer two questions. First, since agents are not fully rational, is it plausible that they use such a non-optimal rule? Second, even if the agents adopt optimal rules, is the economist committing a serious mistake by assuming that agents use one-sided Ss rules? Using parameters based on real economy data, we found that since the additional cost involved in adopting the simpler rule is relatively small, it is plausible that one-sided rules are used in practice. We also found that suboptimal one-sided rules and optimal two-sided rules are in practice similar, since one of the bounds is not reached very often. We concluded that the macroeconomic effects when one-sided rules are suboptimal are similar to the results obtained under two-sided optimal rules, when they are close to each other. However, this is true only when one-sided rules are used in the context where they are not optimal.
Resumo:
In a market where past-sales embed information about consumers’ tastes (quality), we analyze the seller’s incentives to invest in a costly advertising campaign to report them under two informational assumptions. In the …rst scenario, a pooling equilibrium with past-sales advertising is derived. Information revelation only occurs when the seller bene…ciates from the herding behaviour that the advertising campaign induces on the part of consumers. In the second informational regime, a separating equilibrium with past-sales advertising is computed. Information revelation always happens, either through prices or through costly advertisements.
Resumo:
This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).