Fundação Getúlio Vargas

About: Fundação Getúlio Vargas is a education organization based out in Rio de Janeiro, Brazil. It is known for research contribution in the topics: Corporate governance & Context (language use). The organization has 2559 authors who have published 5612 publications receiving 74007 citations.

Research design: qualitative, quantitative, and mixed methods approaches

Abstract: Nova edicao do conhecido livro sobre metodologia de pesquisa de Creswell. Originalmente pensado no campo da Educacao, o autor ficou muito conhecido tambem em Administracao. Nesta nova edicao, ele procura sair da dicotomia metodos quantitativos x qualitativos, com uma otima discussao adicional sobre metodos mistos. Como um todo, e uma obra excelente de referencia para cursos introdutorios de metodologia de pesquisa em programas de pos-graduacao.

The theory of communicative action

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A Theory of Friendly Boards

Abstract: We analyze the consequences of the board's dual role as advisor as well as monitor of management. Given this dual role, the CEO faces a trade-off in disclosing information to the board: If he reveals his information, he receives better advice; however, an informed board will also monitor him more intensively. Since an independent board is a tougher monitor, the CEO may be reluctant to share information with it. Thus, management-friendly boards can be optimal. Using the insights from the model, we analyze the differences between sole and dual board systems. We highlight several policy implications of our analysis.

Unconditional Quantile Regressions

Abstract: We propose a new regression method to evaluate the impact of changes in the distribution of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered) influence function (RIF) of the unconditional quantile on the explanatory variables. The influence function, a widely used tool in robust estimation, is easily computed for quantiles, as well as for other distributional statistics. Our approach, thus, can be readily generalized to other distributional statistics.