Financial Innovation and Divisia Money in Taiwan: Comparative Evidence from Neural Network and Vector Error Correction Forecasting Models

Abstract

In this article a Divisia monetary index is constructed for the Taiwan economy, and its inflation forecasting potential is compared with that of its traditional simple sum counterpart. The Divisia index is adjusted in two ways to allow for the financial liberalization that Taiwan has experienced since the 1970s. The powerful artificial intelligence technique of neural networks is used and is found to beat the conventional econometric techniques in a simple inflation forecasting experiment. The preferred inflation forecasting model is achieved using networks that employ a Divisia M2 measure of money that has been adjusted to incorporate a learning mechanism to allow individuals to gradually alter their perceptions of the increased productivity of money. The explanatory power of the two innovation‐adjusted Divisia aggregates dominates that of the simple sum counterpart in the majority of cases