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Cash preference in India: Empirical methods and findings
Journal of Payments Strategy & Systems,
13
(2),
165-176
(2019)
Abstract
This paper proposes an indicator that provides a proxy measure of cash preference in India, based on credit and debit card transactions undertaken at automated teller machines and point-of-sale terminals. This indicator demonstrates that the customers of public and private sector banks show a preference for cash transactions over non-cash transactions, while the customers of foreign banks prefer non-cash transactions over cash transactions. The estimated cash preference ratio shows a declining trend over time, in line with the Reserve Bank of India’s progress towards a less cash-dependent economy. The empirical results reveal a sharp decline in cash preference during the period of demonetisation; however, cash preference marginally increased during the post-demonetisation period. The study also finds that customers of public sector banks have the highest cash preference, followed by the customers of private sector banks. The authors propose the introduction of an oversight mechanism to identify the root causes of high cash preference, and the provision of remedial measures, such as investment in the infrastructure to support non-cash transactions and educating customers about the benefits of a cashless economy.
Keywords: payment system; automated teller machine; point of sale; cash preference; structural change; oversight framework
The full article is available to subscribers to the journal.
Author's Biography
Sasanka Sekhar Maiti is Director of the Department of Statistics and Information Management at the Reserve Bank of India (RBI). He has worked at the RBI for 20 years in areas including information management, statistical data analysis, payment systems and reserve management. His research interests are in the areas of central banking, exploratory data analysis, payment system oversight and regulations, optimisation techniques and the simulation of complex systems.
Nandalaya Hemachandra is a Professor at the Indian Institute of Technology Bombay, where he heads the Department of Industrial Engineering and Operations Research. His research interests include Operations Research methodologies such as Markov decision models, Queuing models and Game Theory, and their application in such areas as Communication networks, Supply chains, Financial engineering, Logistics and Power systems. His research has been published in numerous journals and referred conferences.
Anil Kumar Sharma is an adviser in the Reserve Bank of India’s Department of Statistics & Information Management. He has written numerous research papers in areas related to the external sector and corporate finance, and in 2014 was awarded the UK Foreign and Commonwealth Office’s Chevening Gurukul Fellowship for Leadership and Excellence. Dr Sharma holds a PhD in economics from Mumbai University and an MPhil and master’s degree in statistics from the University of Delhi.
