Developing Artificial Intelligence-Powered Monetary Policy Communication Indicators for Macroeconomic Inquiries in Ghana

Abstract

Central bank communication is a valuable source of information designed to shape the expectations of economic agents within and outside an economy. In particular, the content of Monetary Policy Committees’ press releases and statements reflect the central banks’ view of current and future macroeconomic developments, making them useful for creating high-frequency indicators as alternatives to traditional but slower-to-publish macroeconomic indicators. In this study, Artificial Intelligence (AI)-powered text-mining techniques were employed to create monetary policy communication-based indicators, namely the Monetary Policy Readability Index (MPRI), the Monetary Policy Sentiment Index (MPSI), and the Monetary Policy Uncertainty Index (MPUI), using press releases from the Bank of Ghana's monetary policy committee spanning January 2003 to December 2022. The findings suggest that while readability and sentiments generally declined over the sample period, uncertainty increased, indicating persistent macroeconomic imbalances and vulnerabilities in the domestic economy. The newly developed time series-based indicators demonstrate Granger causal relationships with key macroeconomic variables, affirming their relevance to the central bank, the Ministry of Finance, researchers, investors, and development partners. Notably, the indicators can serve as an early warning system for monitoring and predicting the country's macroeconomic risks, forecasting lagging indicators, assessing the effectiveness of the Bank’s monetary policy communication, and addressing monetary policy inquiries.