MULTIVARIATE ARIMA MODELING FOR A REGIONAL MACROECONOMY: EXPERIENCES WITH THE FLORIDA ECONOMY

The first part of this paper presents the background information necessary for determining the direction of the study. The general forms of univariate and multivariate ARIMA models are presented, and time series and econometric models are compared and contrasted. Past work in both univariate and multivariate time series approaches to macroeconomic forecasting are reviewed. The definition of Granger causality is presented, along with Pierce's approach to measuring causality.