Demonetisation, Financial Inclusion and Bank Efficiency

We estimate three efficiencies, namely new profit, new cost and new technical, to examine the impact of demonetisation and financial inclusion on bank performance in India. Bank efficiency for the 2011–2019 period across size and ownership groups is measured using data envelopment analysis (DEA). In the second stage, differences in impact of the event across bank groups and efficiency types, using repeated analysis of variance (ANOVA), are observed. Significant effects across size and ownership, albeit not uniform across groups, events and efficiency types, were found. There was an increase in the number of frontier banks. SBI, the state-owned and largest bank, with the most significant role in those policies, had seen a positive impact on cost and profit efficiency. Our study is perhaps the first of its kind to examine demonetisation and financial inclusion impact on the banking sector and a two-stage estimation that combines DEA with repeated ANOVA. Our study does not lend support to the view that those events have burdened and adversely affected banks. The study carries important managerial and policy implications and provides much-needed scientific evidence to the popular debate on the impact of the events. JEL Codes: G21, G34, D61, M40

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Journal
The Indian Economic Journal
Published
2026-01-26
DOI
https://doi.org/10.1177/00194662251410118
Primary Topic
Efficiency Analysis Using DEA
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article

Demonetisation, Financial Inclusion and Bank Efficiency

Vincent Charles, Keyur Thaker, Abhay Pant
The Indian Economic Journal
Efficiency Analysis Using DEA
article

Demonetisation, Financial Inclusion and Bank Efficiency

Vincent Charles, Keyur Thaker, Abhay Pant
article en

Abstract

We estimate three efficiencies, namely new profit, new cost and new technical, to examine the impact of demonetisation and financial inclusion on bank performance in India. Bank efficiency for the 2011–2019 period across size and ownership groups is measured using data envelopment analysis (DEA). In the second stage, differences in impact of the event across bank groups and efficiency types, using repeated analysis of variance (ANOVA), are observed. Significant effects across size and ownership, albeit not uniform across groups, events and efficiency types, were found. There was an increase in the number of frontier banks. SBI, the state-owned and largest bank, with the most significant role in those policies, had seen a positive impact on cost and profit efficiency. Our study is perhaps the first of its kind to examine demonetisation and financial inclusion impact on the banking sector and a two-stage estimation that combines DEA with repeated ANOVA. Our study does not lend support to the view that those events have burdened and adversely affected banks. The study carries important managerial and policy implications and provides much-needed scientific evidence to the popular debate on the impact of the events. JEL Codes: G21, G34, D61, M40

The Indian Economic Journal
Indian Institute of Technology Guwahati (IN), Indian Institute of Management Indore (IN), Indian Institute of Information Technology Guwahati (IN), Centre of Technology & Entrepreneurship Development (IN), Pontificia Universidad Católica del Perú (PE), Rajiv Gandhi Institute of Petroleum Technology (IN)
Reduced inequalities
Openalex Percentile: Top 78%
Efficiency Analysis Using DEA
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Demonetisation, Financial Inclusion and Bank Efficiency — Vincent Charles, Keyur Thaker, et al. · The Indian Economic Journal (2026) | TGRS Research Map | TGRS