An Event-Based Predictive Modelling Approach: An Application in Macroeconomics

摘要

This paper applies the Behavior Pattern Learning (BPL) approach to automatically discover the conditions previous to specific macroeconomic events from the historical evolution of macroeconomic variables, as well as historical events. Every time the target macroeconomic event (e.g. Consumer Price Index (CPI) inflation greater than 5.5%) takes place, BPL constructs several snapshots at specific previous times. Each snapshot, called a behavior summary, includes information about its present, past, and future. The set of behavior summaries is used by a regression tree approach to discover the conditions for the target event to take place. In this paper, we used BPL to automatically discover the conditions for the occurrence of specific events associated with the CPI inflation and Gross domestic product (GDP) deflactor using macroeconomic data, and war and political events. Comparisons with other prediction models on the same problem show that the BPL provides automatic forecasts that are similar in performance as those forecasts done by models assisted by experts.