Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/240805 
Year of Publication: 
2020
Series/Report no.: 
Texto para Discussão No. 2611
Publisher: 
Instituto de Pesquisa Econômica Aplicada (IPEA), Brasília
Abstract (Translated): 
In this article we investigate the capacity of antecedent variables, among them admissions for aggression, in the prediction of the number of homicides in Brazil. The main objective is to eliminate a gap regarding the large time lag in the dissemination of information about these deaths in the country, allowing updated conjuncture analyzes. For this, through a 'rolling window' scheme and 'Model Confidence Set' approach, we investigate whether multivariate models with leading variables show forecast performance superior to a set of univariate models. In applying the MCS approach, considering different evaluation statistics, loss functions and estimation windows, we find strong evidence of the ability of the leading variables used to provide additional information content in the prediction of the Brazilian criminal dynamics, with models of leading variables systematically surpassing univariate models, especially in extended periods of forecasting. In general, improvements related to the benchmark Random walk model, in terms of RMSE, MAE and MAD, are of the order of 60%.
Subjects: 
forecasting
homicide forecasting
model confidence set
time series
violence
JEL: 
C53
K42
C22
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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