Bounds on policy relevant parameters with discrete policy variation

When estimating policy parameters, also known as treatment effects, the assignment to treatment mechanism almost always causes endogeneity and thus bias many of these policy parameters estimates. Additionally, heterogeneity in program impacts is more likely to be the norm than the exception for most social programs. In situations where these issues are present, the Marginal Treatment Effect (MTE) parameter estimation makes use of an instrument to avoid assignment bias and simultaneously to account for heterogeneous effects throughout individuals. Although this parameter is point identified in the literature, the assumptions required for identification may be strong. Given that, we use weaker assumptions in order to partially identify the MTE, i.e. to stablish a methodology for MTE bounds estimation, implementing it computationally and showing results from Monte Carlo simulations. The partial identification we perfom requires the MTE to be a monotone function over the propensity score, which is a reasonable assumption on several economics' examples, and the simulation results shows it is possible to get informative even in restricted cases where point identification is lost. Additionally, in situations where estimated bounds are not informative and the traditional point identification is lost, we suggest a more generic method to point estimate MTE using the Moore-Penrose Pseudo-Invese Matrix, achieving better results than traditional methods.

The Brazilian foreign exchange market through the microstructure perspective

The objective of this study is to investigate whether the relationship between order ow and the spot exchange rate stems from the fact that the ow aggregates information on dispersed economic fundamentals in the economy. To perform this test, a database that includes all transactions of the commercial and nancial segments of the Brazilian primary foreign exchange market between January of 1999 and May of 2008 was used. We show that the order ow was partly responsible for variations in in ation expectations over the time period and that this relationship did not remain robust, drawing comparisons with other fundamentals such as GDP and Industrial Production.

Modelamento estocástico da dinâmica do livro de ordens: uma aplicação ao mercado brasileiro

O presente trabalho trata da importância do modelamento da dinâmica do livro de ordens visando a compreensão dessa microestrutura de mercado. Para tanto, objetiva aplicar as técnicas de modelamento do livro de ofertas utilizando o modelo estocástico proposto por Cont, Stoikov e Talreja (2010) ao mercado acionário brasileiro. Uma vez aplicado o modelo, analisamos os resultados obtidos sob a ótica de outros estudos empíricos, como Bouchaud et al. (2002). Após a estimação e análise dos resultados foram realizadas simulações para constatar se os parâmetros encontrados refletem a dinâmica do mercado local, para diferentes cenários de normalização do tamanho das ordens. Por fim, com a análise dos resultados encontrados, foi possível concluir, com algumas ressalvas, que o modelo proposto é válido para o mercado de ações brasileiro, assim como é apresentado o impacto da liquidez dos ativos na comparação aos parâmetros encontrados em outros mercados internacionais.