The goal of this paper is to develop a forecasting model of the hourly electricity load demand in the area covered by an utility company located in the southeast of Brazil. A di®erent model is constructed for each hour of day, thus there are 24 di®erent models. Each model is based on a...

This study aims to analyze price discovery in the foreign exchange market in Brazil and indicate which market (spot or futures) adjusts more quickly to the arrival of new information. Using high frequency data from January/2008 to June/2013, we estimate the following price discovery metrics:...

The goal of this paper is to test for and model nonlinearities in several monthly exchange rates time series. We apply two different nonlinear alternatives, namely: the artificial neural network time series model estimated with Bayesian regularization and a flexible smooth transition...

We consider a new method to estimate causal effects when a treated unit suffers a shock or an intervention, such as a policy change, but there is not a readily available control group or counterfactual. We propose a two-step approach where in the first stage an artificial counterfactual is...

Recently, there has been a growing interest in developing econometric tools to conduct counterfactual analysis with aggregate data when a “treated” unit suffers an intervention, such as a policy change, and there is no obvious control group. Usually, the proposed methods are based on the...