The rapid development of digital technology in the era of the Fourth Industrial Revolution has accelerated the transformation of payment systems from cash-based to cashless transactions. During the COVID-19 pandemic, the adoption of digital payment systems increased significantly due to mobility restrictions and reduced physical interactions. To support this transformation, Bank Indonesia introduced the Quick Response Code Indonesian Standard (QRIS) as a standardized digital payment instrument. The growing use of digital payment systems is expected to influence the Velocity of Money (VOM) in Indonesia. In addition, the research aims to explore other determinants that influence the velocity of money in both the short and long term.
This study employs a quantitative approach using monthly secondary data from January 2020 to July 2025. The data were obtained from the Central Statistics Agency (BPS), the Indonesian Payment System Association (ASPI), and Bank Indonesia (BI). The dependent variable is Velocity of Money (VOM), while the independent variables consist of QRIS transaction volume (QRIS), ATM debit card transaction volume (ATM), credit card transaction volume (CC), Electronic Data Capture machines (EDC), interest rates (IR), and inflation (Inf). The study applies the Autoregressive Distributed Lag (ARDL) model to estimate both short-run and long-run relationships among the variables. Several preliminary tests were conducted, including unit root tests, optimal lag selection, cointegration tests, and diagnostic tests to ensure model validity and robustness.
The results indicate that in the short run, QRIS transaction volume (QRIS), ATM debit card transaction volume (ATM), and credit card transaction volume (CC) have positive effects on the Velocity of Money (VOM). Conversely, interest rates (IR) and inflation (Inf) negatively affect VOM. In the long run, ATM debit card transaction volume (ATM) has a significant negative effect on VOM, while inflation (Inf) has a significant positive effect. Meanwhile, QRIS transaction volume (QRIS), credit card transaction volume (CC), Electronic Data Capture machines (EDC), and interest rates (IR) do not significantly affect the velocity of money in the long run. These findings suggest that digital payment innovations contribute to faster money circulation and greater transaction efficiency in the short term; however, their long-term effects depend on the extent of technology adoption, financial literacy, and public transaction behavior.
Author: Atik Purmiyati
Details of the research can be viewed here: https://citeus.um.ac.id/cgi/viewcontent.cgi?article=1129&context=jesp
