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Home / Current / Vol. 1 No. 1 (2026) / Articles

Economic Incentives and Women Voters: An Empirical Analysis of Electoral Strategy in Bihar State Elections 2025

Satyendra Kumar
PhD Scholar in Management, Amity University Patna, satya72892@gmail.com
ORCID ID: 0009-0002-0157-2142
Ravindra Kumar
Ph.D. Scholar, Rayat Bahra University, Mohali, Punjab, India, ravindra94314@gmail.com
ORCID ID: 0009-0006-9539-8892
DOI: - https://doi.org/10.68892/IJRM.007
Keywords: Economic incentives; Women voters; Electoral strategy; Direct cash transfers; Electoral mobilization; Political behaviour
ABSTRACT
Bihar has never seen this kind of voter turnout gap as seen in the year 2025 State General Assembly Elections. The female turnout of 71.6% and male turnout of 62.8% was significant. The female voters turnout has surpassed males voters turnout by 8.8 percentage points, marking a record for Bihar. This female turnout was primarily influenced by the Mukhyamantri Mahila Rozgar Yojana (MMRY), which offered a cash transfer of 10,000 Rupees to each Jeevika members. Utilizing the official data of the Election Commission of India (ECI), data from Axis My India exit polls (42,031 respondents), data on district-level welfare penetration, and case studies of 52 women beneficiaries in five districts of Bihar, this study identifies the impact of cash transfer welfare schemes on the voting behaviour of women. Among beneficiaries of MMRY, support for the incumbent government coalition was 52%. This is a 14 percentage point increase in support for the incumbent government alliance from women beneficiaries compared to women non-beneficiaries, among whom only 38% supported the incumbent government alliance. This gap is reported here as an association: because beneficiary status was not randomly assigned, it may partly reflect pre-existing differences between beneficiaries and non-beneficiaries rather than a pure effect of the transfer. The incumbent government coalition won 202 out of 243 seats (83.1%) and received 52% of the total votes, which is higher than their pre-poll estimation of 190 seats. Women’s distinctive turnout and voting patterns coincided with the coalition’s overall vote gains; given the observational, cross-sectional design of this study, this association should not be read as evidence that women’s behaviour caused the seat outcome.
REFERENCES
  1. Auyero, J. (2000). The logic of clientelism in Argentina: An ethnographic account. Latin American Research Review, 35(3), 55–81.
  2. Chattopadhyay, R., & Duflo, E. (2004). Women as policy makers: Evidence from a randomized policy experiment in India. Econometrica, 72(5), 1409–1443.
  3. Chaudhary, L. (2021). Women, cash transfers, and political engagement in South Asia. Politics & Gender, 17(1), 42–67.
  4. Deshpande, A. (2021). Gender, social policy, and political behaviour in India. India Review, 20(2), 134–159.
  5. Fiszbein, A., & Schady, N. R. (2009). Conditional cash transfers: Reducing present and future poverty. World Bank Policy Research Report.
  6. Gans-Morse, J., Mazzuca, S., & Nichter, S. (2014). Varieties of clientelism: Machine politics during elections. American Journal of Political Science, 58(2), 415–432.
  7. Huber, E., & Stephens, J. D. (2012). Democracy and the left: Social policy and inequality in Latin America. University of Chicago Press.
  8. Inglehart, R., & Norris, P. (2003). Rising tide: Gender equality and cultural change around the world. Cambridge University Press.
  9. Iversen, T., & Rosenbluth, F. (2010). Women, work, and politics: The political economy of gender inequality. Yale University Press.
  10. Jensenius, F. R., & Chhibber, P. (2021). Voting, gender, and political representation in India. Asian Survey, 61(4), 657–678.
  11. Keefer, P., & Khemani, S. (2005). Democracy, public expenditures, and the poor: Understanding political incentives for providing public services. World Bank Economic Review, 19(2), 163–183.
  12. Kitschelt, H., & Wilkinson, S. I. (Eds.). (2007). Patrons, clients, and policies: Patterns of democratic accountability and political competition. Cambridge University Press.
  13. Manacorda, M., Miguel, E. and Vigorito, A. (2011) 'Government transfers and political support', American Economic Journal: Applied Economics, Vol. 3, No. 3, pp. 1–28.
  14. Stokes, S. C. (2005). Perverse accountability: A formal model of machine politics with evidence from Argentina. American Political Science Review, 99(3), 315–325.
  15. Stokes, S. C., Dunning, T., Nazareno, M., & Brusco, V. (2013). Brokers, voters, and clientelism: The puzzle of distributive politics. Cambridge University Press.
  16. Zucco, C. (2013) 'When payouts pay off: Conditional cash transfers and voting behavior in Brazil 2002–10', American Journal of Political Science, 57(4), pp. 810–822.
APPENDICES
APPENDIX A: Data Quality Verification
All data sources have been verified against official government records:

Election Commission of India Data:

  • Voter turnout figures verified against official ECI press releases
  • Gender-disaggregated data cross-referenced with constituency-level reporting
  • District-level aggregates confirmed against state-level summaries

Exit Poll Data:

  • Axis My India polling methodology met professional standards
  • 42,031 sample size provides ±1.5% margin of error at 95% confidence
  • Demographic representation compared against census benchmarks
  • MMRY beneficiary status and vote choice are respondent self-reports; individual-level matching against government beneficiary records was not performed for this study, and this is noted as a limitation rather than a verified data-quality strength

Government Administrative Data:

  • MMRY beneficiary figures from the Bihar Finance Department
  • Transfer amounts and timing verified against government announcements
  • District-level welfare penetration cross-referenced with state welfare department records
APPENDIX B: Qualitative Interview Coding Scheme
Interview transcripts were coded using 14 thematic categories with reliability testing. Cohen's Kappa coefficients for inter-rater agreement:
  • Tangibility: κ = 0.96 (near-perfect agreement)
  • Implementation vs. Promise: κ = 0.94 (near-perfect agreement)
  • Household Use: κ = 0.92 (strong agreement)
  • Trust in Delivery: κ = 0.90 (strong agreement)
  • Previous Experience: κ = 0.88 (strong agreement)
  • All other themes: κ > 0.75 (substantial agreement minimum threshold)
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