E-Money Transactions as Leading Macroeconomic Indicators: A Markov Switching Value Autoregressive (MSVAR) Approach

Abstract

Aims: This study aimed the combination of markov regime switching and vector autoregression (VAR) models using the number of e-money transactions as measured by leading macroeconomic indicators such as interest rates, inflation rates, stock returns and composite stock price indices. Methodology: This study uses a quantitative method, the first with the stationery test can explain the validity and reliability and stability of the data with Dicky-Fuller test. The second one with threshold test and the last one with markov regime switching model to describe the difference between two condition. Results: The results obtained from this study are the perfection of the model using the markov switching value autoregressive (MSVAR) model with the model type M (2), AR (1) with the white noise value met. Based on these results, this model is able to be a catalyst in the value of the use of electronic money against macroeconomic variables, especially the value of interest rates, inflation, stock returns and the value of the composite stock price index. Implication: Implication: the E-money transaction variable can analyze future macroeconomic predictions and help to make decisions about policies related to finance and control of the payment system.