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Effect of UPI Adoption on Savings Behaviour of Indian Households: A Difference-in-Differences Analysis

Effect of UPI Adoption on Savings Behaviour of Indian Households: A Difference-in-Differences Analysis

Focus

Development Economics, Digital Finance, Household Financial Behavior

Motivation

Financial Inclusion, Digital Payments, Household Investment Behavior

About the project

This study examines whether the rapid adoption of India’s Unified Payments Interface (UPI) has influenced household investment behaviour, specifically participation in shares and debentures. Using district-level data from the National Sample Survey combined with PhonePe transaction data, the research applies a difference-in-differences framework to compare changes in investment patterns between high- and low-UPI-adoption districts over time. The analysis spans multiple survey years and leverages quasi-experimental variation in digital payment uptake to isolate potential causal effects, while controlling for demographic and structural differences across regions.

The paper finds that increased UPI adoption does not lead to statistically significant changes in household investment in shares and debentures. Although digital payment growth is associated with greater transaction convenience and consumption activity, the results suggest that these benefits do not automatically translate into deeper participation in formal financial markets. The regression explains a moderate share of variation in asset holdings, but high multicollinearity, limited sample size at the district level, and the absence of household income controls constrain statistical precision.

Overall, the study concludes that while UPI has transformed payment behavior, its role in shaping long-term portfolio choices remains limited or difficult to detect with existing data. The findings imply that digital payment infrastructure alone may be insufficient to drive financial deepening without complementary factors such as financial literacy, income growth, and access to investment platforms. The paper highlights the need for richer household-level panel data and more granular identification strategies to better understand how digital finance influences savings and investment decisions in developing economies.

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