Purpose: This paper empirically investigates the association between technological progress and the demand for real cash balances in Iran. Amid a global shift towards digital payments, understanding the quantitative substitution effect of financial technology on cash is crucial for effective monetary policy and currency management.

Methodology: The study employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration, a method well-suited for analyzing long-run and short-run dynamics with variables of mixed integration orders. Using quarterly time-series data, the model specifies real cash demand as a function of real GDP (transaction motive), bank deposit rates (opportunity cost), and the number of Point of Sale (POS) terminals as a proxy for technological advancement. Post-estimation diagnostic and stability tests are conducted to ensure the model's robustness.

Findings: The ARDL bounds test confirms the existence of a stable, long-run equilibrium relationship between the variables. The long-run estimates reveal that technological progress has a statistically significant and negative association with the demand for real cash in Iran. The coefficient for POS terminals indicates a powerful substitution effect. The Error Correction Model (ECM) results show a significant speed of adjustment, indicating that approximately 35% of any short-term disequilibrium is corrected within one quarter.

Originality/Value: This study provides the first robust, ARDL-based analysis of the technology-cash demand nexus in Iran using recent data. It quantifies the substitution effect, offering empirical evidence that moves beyond descriptive analysis.

Implications: The findings have significant implications for the Central Bank of Iran. They underscore the need to refine cash demand forecasting models, optimize currency management logistics, and strategically advance the development of a Central Bank Digital Currency (CBDC) to navigate the country’s transition towards a less-cash society.