This paper studies the applicability of time series models as a decision tool of buy and sell orders of live cattle futures contracts in the Brazilian Futures Market (BM&F), on dates close to expiration. The models considered are: ARIMA, Neural Networks and Dynamic Linear Models - DLM (this in...

Este trabalho tem como objetivo avaliar o impacto de políticas fiscais nos ciclos econômicos do Brasil, utilizando modelos de equilíbrio geral dinâmico para uma pequena economia aberta com governo. Os resultados dos modelos calibrados para o caso brasileiro são capazes de replicar a maior...

So far, there are very few papers concerning the problems of non causality and non-fundamentalness in fiscal studies. This is even truer for Brazil. Non causality and non fundamentalness are econometric problems that are specially relevant in fiscal studies, as they are relate to fiscal...

The vector autoregressive and structural vector autoregressive (VAR/SVAR) models are the cornerstone of the contemporaneous empirical macroeconomic research, in particular for measuring the impact of fiscal policy shocks. They may be employed as atheoretical models, as well as a mean to support...

This paper investigates the dependency relations that intertwine the mining activity and the economy of the municipality of Brumadinho (MG). Based on the theoretical framework of the Dependency Theory, the text addresses different socio-economic dimensions such as aggregate production,...

É matéria de pouca controvérsia que as variáveis de investimento são procíclicas em relação ao Produto Nacional Bruto. Este artigo discute uma situação relevante que não corrobora esta certeza: a dos investimentos na agricultura dos Estados Unidos. A variação no estoque da capital...

So far, there are very few papers concerning the problems of non causality and non-fundamentalness in fiscal studies. This is even truer for Brazil. Non causality and non fundamentalness are econometric problems that are specially relevant in fiscal studies, as they are relate to fiscal...