Analisis Tren Ekonomi Digital terhadap Kebijakan Moneter di Indonesia

This study aims to determine the effect of fintech, the amount of money in circulation, interest rates and economic growth on the analysis of digital economic trends on monetary policy in Indonesia. There are four variables in this study, namely fintech, the amount of money in circulation, interest rates and economic growth. The analysis method used is Vector Autoregression with the Impluse Response Function test or abbreviated as IRF and the Forecast Error Variance Decomposition test commonly abbreviated as FEVD, stationarity test, cointegration test, lag structure stability test and optimal lag length test. There is a contribution from each variable to the variable itself and other variables, according to the results of the Vector Autoregression study with a lag basis of 2. In addition, the results of the Vector Autoregression analysis show that the past variable (t-1) contributes to the current variable both to the variable itself and to other variables. The results of the analysis show that there is a reciprocal relationship between the variables. By using response function analysis, we can see if there is a response from other variables to changes in one variable in the short, medium, or long term. In addition, we know that the stability of all variables is formed in the short, medium, and long term. According to the Variance Decomposition Analysis, factors such as Fintech and Money Supply contribute the most to the variable itself. However, other variables that have the greatest influence on the variable itself and are supported by other variables in the short, medium, and long term are economic growth and interest rates are most influenced by Fintech.