Antonio F. Galvao

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This paper develops a uniform test of linearity against thresholds effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We establish the asymptotic null distribution of the test statistic for stationary weakly dependent processes, and propose a simulation(More)
Using the college admissions model of Hickman (2010), I study the implications of Affirmative Action (AA) in US college admissions for student academic achievement (prior to college) and college placement outcomes. I argue that the competition among high-school students for college seats is similar to a multi-object all-pay auction. The link to auctions(More)
This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to investigate the finite sample performance of the proposed method in(More)
Managers often claim that an important source of value in acquisitions is the acquiring firm's ability to finance investments for the target firm. This claim implies that targets are financially constrained prior to being acquired and that these constraints are eased following the acquisition. We evaluate these predictions on a sample of 5,187 European(More)
This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables es-timator are studied for large N and T when N a /T → 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The es-timator is applied to the(More)
This paper studies panel quantile regression models with fixed effects. We formally establish sufficient conditions for consistency and asymptotic normality of the quantile regression estimator when the number of individuals, n, and the number of time periods, T , jointly go to infinity. The estimator is shown to be consistent under similar conditions to(More)
This paper studies the connections among quantile regression, the asymmetric Laplace distribution, and the maximum entropy. We show that the maximum likelihood problem is equivalent to the solution of a maximum entropy problem where we impose moment constraints given by the joint consideration of the mean and median. Using the resulting score functions we(More)