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E-wallets and stock market participation – a joint copula regression analysis

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  • Debasis Rooj
  • Reshmi Sengupta

Abstract

PurposeThe objective of this study is to examine the role of financial technology on household stock market participation using a nationally representative data set for India. The study also explores the channels through which the adoption of e-wallets can promote stock market participation.Design/methodology/approachWe measure financial technology using household adoption of e-wallets. Stock market participation is captured by households' financial assets held in shares, mutual funds, and bonds. We use a nationally representative 2019 round of the National Sample Survey (NSS) data from India and apply a novel copula estimation strategy that simultaneously addresses endogeneity nonlinear covariate effects and accounts for rare event bias.FindingsWe find that households’ greater adoption of e-wallets increases their likelihood of stock market participation. Our results further suggest a nonlinearity in adopting e-wallets and stock market participation in terms of age and consumption expenditure. We also show that digital payments induce greater social interaction and risky financial decisions, which can translate into stock market participation. Several robustness tests confirm the validity of our results.Originality/valueThis is the first study that explores the impact of financial technology exclusively on stock market participation. We focus on the stock market rather than considering all risky assets, including precious metals. Moreover, we use a novel copula-based regression methodology that can simultaneously address endogeneity due to unobserved covariates, nonlinearity in continuous covariates and account for rare-event bias due to low stock market participation among Indian households. We also explore several channels through which e-wallets can promote stock market participation.

Suggested Citation

  • Debasis Rooj & Reshmi Sengupta, 2025. "E-wallets and stock market participation – a joint copula regression analysis," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 17(4), pages 642-663, May.
  • Handle: RePEc:eme:rbfpps:rbf-09-2024-0255
    DOI: 10.1108/RBF-09-2024-0255
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