Genetic Algorithm Calibration of Seasonal BVAR Models

Abstract

In this paper we explore the use of Genetic Algorithms (GA) to calibrate seasonal BVAR models. In this way, the mechanistic use of seasonal adjustment procedures is avoided, since seasonality becomes a structural, basic and explicit part of the BVAR model. At the same time, the use of GA allows calibration to be performed on a diffuse setting, preserving as much as possible the flexible nature of BVAR and revealing interesting features of the data. The well-known U.S. housing data are used to illustrate the procedures outlined in the paper.