Are CGE Models still useful in economic policy making?

This paper develops background considerations to help better framing the results of a CGE exercise. Three main criticisms are usually addressed to CGE efforts. First, they are too aggregate, their conclusions failing to shed light on relevant sectors or issues. Second, they imply huge data requirements. Timeliness is frequently jeopardised by out-dated sources, benchmarks referring to realities gone by. Finally, results are meaningless, as they answer wrong or ill-posed questions. Modelling demands end up by creating a rather artificial context, where the original questions lose content. In spite of a positive outlook on the first two, crucial questions lie in the third point. After elaborating such questions, and trying to answer some, the text argues that CGE models can come closer to reality. If their use is still scarce to give way to a fruitful symbiosis between negotiations and simulation results, they remain the only available technique providing a global, inter-related way of capturing economy-wide effects of several different policies. International organisations can play a major role supporting and encouraging improvements. They are also uniquely positioned to enhance information and data sharing, as well as putting people from various origins together, to share their experiences. A serious and complex homework is however required, to correct, at least, the most dangerous present shortcomings of the technique.

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.

Sobre o custo do tempo para a competitividade da indústria brasileira: diagnóstico e síntese dos impactos econômicos da facilitação do comércio no Brasil

Este artigo analisa a importância dos atrasos portuários para a competitividade da indústria de transformação no Brasil. Com base em estimativas recentes sobre o custo diário dos atrasos comerciais e em bases de dados do Banco Mundial e do GTAP (Global Trade Analysis Project), revela a magnitude destas barreiras sob a forma de seus equivalentes ad valorem. Em seguida, por meio de simulações em equilíbrio geral, estima o impacto da melhoria dos processos aduaneiros sobre o desempenho da indústria de transformação no Brasil, sob diferentes cenários. Os resultados obtidos ressaltam o caráter estratégico da facilitação do comércio para o Brasil e da sua inclusão como item relevante para a agenda de crescimento de longo prazo do país