Purpose : Bihar is one of India’s poorest but youngest state economies. As demographic developments took place, the age composition of the state changed. The study aimed to examine the impact of demographic dynamics on Bihar’s growth prospects.

Methodology : The study adopted an analytical and explanatory research design rooted in a deductive approach. Engle–Granger causality, bivariate ARDL–ECM, and vector error correction model (VECM) were employed for the analysis, using data processed in EViews 12.

Findings : The ARDL and VECM analyses revealed that the working-age population had a positive impact on economic growth, while the growing dependency ratio, particularly among children, had a significant negative effect. The old-age population’s growth also negatively affected the economy, though weakly.

Practical Implications : Bihar faced the challenge of an aging population, which required attention to healthcare, social protection, and active aging initiatives. To fully capitalize on its demographic advantage, the state needed to focus on strategic reforms in governance, rural development, and entrepreneurship, while preparing for the socio-economic complexities of an aging society.

Originality : The study’s originality lay in its focus on Bihar, a region often overlooked in macroeconomic and demographic discussions. Employing advanced econometric techniques (ARDL and VECM), it provided an in-depth understanding of how demographic dynamics impacted economic development, highlighting the risk of unexploited demographic advantages becoming future liabilities.

1. Acharjee, C., & Dutta, S. (2013). Relationship between economic development and population ageing: An empirical study on selected states of India. Arthshastra Indian Journal of Economics & Research, 2(3), 23–31. https://doi.org/10.17010/aijer/2013/v2i3/54519
2. Aggarwal, S., & Khanna, A. (2021). Pension finance literacy of Indian government employees with respect to the National Pension Scheme. Arthshastra Indian Journal of Economics & Research, 10(2–3), 41–57. https://doi.org/10.17010/aijer/2021/v10i2-3/167173
3. Alam, I., & Ahmed, S. (2019). India's labour migration to the Kingdom of Saudi Arabia: Issues and challenges. Arthshastra Indian Journal of Economics & Research, 8(3), 32–41. https://doi.org/10.17010/aijer/2019/v8i3/146035
4. Ando, A., & Modigliani, F. (1963). The “life cycle” hypothesis of saving: Aggregate implications and tests. The American Economic Review, 53(1), 55–84. https://www.jstor.org/stable/1817129
5. Bihar. (2023). In Wikipedia. https://en.wikipedia.org/wiki/Bihar
6. Bloom, D. E., Canning, D., Fink, G., & Finlay, J. E. (2009). Fertility, female labor force participation, and the demographic dividend. Journal of Economic Growth, 14(2), 79–101. https://doi.org/10.1007/s10887-009-9039-9
7. Bloom, D., Canning, D., & Sevilla, J. (2003). The demographic dividend: A new perspective on the economic consequences of population change. Rand Corporation. https://www.rand.org/pubs/monograph_reports/MR1274.html
8. Chakraborty, P., Chaudhury, S., & Bandyopadhyay, A. R. (2019). Socioeconomic conditions among the urban oldest-old females: A gerontological study in Medinipur Municipal Town, West Bengal. Arthshastra Indian Journal of Economics & Research, 8(5), 7–15. https://doi.org/10.17010/aijer/2019/v8i5/149678
9. Chandrasekhar, C. P., Ghosh, J., & Roychowdhury, A. (2006). The 'demographic dividend' and young India's economic future. Economic and Political Weekly, 41(49), 5055–5064. https://www.jstor.org/stable/4419004
10. Economic and Political Weekly Research Foundation. (n.d.). India time series (EPWRFITS) [Database]. EPW Research Foundation. https://epwrfits.in
11. Global Data Lab. (n.d.). Subnational Human Development Index (Version 7.0) [Data set]. Institute for Management Research, Radboud University. https://globaldatalab.org
12. Goyal, S., Kovuri, A., & Golait, R. (2022). Has COVID-19 distorted the state-wise convergence in India? An empirical analysis. Arthshastra Indian Journal of Economics & Research, 11(4), 8–25. https://doi.org/10.17010/aijer/2022/v11i4/172740
13. Gupta, S., & Kumar, S. (2018). Influence of demographic determinants on reverse mortgage willingness: An empirical study from India. Arthshastra Indian Journal of Economics & Research, 7(2), 7–20. https://doi.org/10.17010/aijer/2018/v7i2/124537
14. Jasmin. (2020). Distribution of income in India: The story of divergence since 1991. Arthshastra Indian Journal of Economics & Research, 9(1), 37–51. https://doi.org/10.17010/aijer/2020/v9i1/151355
15. Jindal, Y. (2020). Quantifying demographic dividend in India and its impact on economic growth: A state-level study. Arthshastra Indian Journal of Economics & Research, 9(1), 7–24. https://doi.org/10.17010/aijer/2020/v9i1/151353
16. Lakshmanasamy, T. (2021). The differential effects of the determinants of household education expenditure in India: Quantile regression estimation. Arthshastra Indian Journal of Economics & Research, 10(1), 8–26. https://doi.org/10.17010/aijer/2021/v10i1/159883
17. Lee, R. (2003). The demographic transition: Three centuries of fundamental change. Journal of Economic Perspectives, 17(4), 167–190. https://doi.org/10.1257/089533003772034943
18. Lutz, W., & Samir, K. C. (2011). Global human capital: Integrating education and population. Science, 333(6042), 587–592. https://doi.org/10.1126/science.1206964
19. Mason, A. (2005). Demographic transition and demographic dividends in developed and developing countries. In United Nations expert group meeting on social and economic implications of changing population age structures. United Nations. https://www.researchgate.net/publication/252403184
20. Mason, A., Lee, R., & Jiang, J. X. (2016). Demographic dividends, human capital, and saving. The Journal of the Economics of Ageing, 7, 106–122. https://doi.org/10.1016/j.jeoa.2015.04.004
21. Ministry of Home Affairs, Government of India. (2011). A book on Census of India since 1981. Office of the Registrar General & Census Commissioner of India. https://censusindia.gov.in/
22. Mody, A., & Aiyar, S. (2011). The demographic dividend: Evidence from the Indian states (IMF Working Paper No. 2011/038). International Monetary Fund. https://doi.org/10.5089/9781455217885.001
23. Pesaran, M. H., & Pesaran, B. (1997). Working with Microfit 4.0: Interactive econometric analysis. Oxford University Press.
24. Pesaran, M. H., & Shin, Y. (1999). An autoregressive distributed-lag modelling approach to cointegration analysis. In S. Strom, A. Holly, & P. Diamond (eds.), Econometrics and economic theory in the 20th century: The Ragnar Frisch Centennial Symposium (pp. 371–413). Cambridge University Press. https://doi.org/10.1017/CCOL521633230.011
25. Quarteroni, A., Sacco, R., & Saleri, F. (2007). Numerical mathematics (2nd ed.). Springer. https://doi.org/10.1007/b98885
26. Reserve Bank of India. (2022). Handbook of statistics on Indian states 2021–22. RBI. https://www.tnpscthervupettagam.com/currentaffairs-detail/handbook-of-statistics-on-indian-states-2021-22
27. Ross, J. (2004). Understanding the demographic dividend. POLICY Project Note, 13, 1–4.
28. Subramaniam, D., & Ben, J. B. (2018). The relevance of skill development in the Indian context. Arthshastra Indian Journal of Economics & Research, 7(1), 25–36. https://doi.org/10.17010/aijer/2018/v7i1/122135
29. Tiwari, A. K., & Srivastava, M. K. (2015). Population and standard of living in states formed in 2000. Arthshastra Indian Journal of Economics & Research, 4(4), 52–61. https://doi.org/10.17010/aijer/2015/v4i4/77676
30. Toma, S.-G. (2019). Learning from the Asian tigers: Lessons in economic growth. Annals – Economy Series, 3(1), 63–69. https://ideas.repec.org/a/cbu/jrnlec/y2019v3p63-69.html
31. United Nations Development Programme. (2019). Human development report 2019: Beyond income, beyond averages, beyond today: Inequalities in human development in the 21st century. United Nations. https://hdr.undp.org/content/human-development-report-2019
32. United Nations Population Fund. (2012). Building a knowledge base on population ageing in India: Report on the status of elderly in select states of India, 2011. UNFPA. https://india.unfpa.org/sites/default/files/pub-pdf/AgeingReport_2012_F.pdf
33. United Nations, Department of Economic and Social Affairs, Population Division. (2019). World population prospects 2019: Highlights. United Nations. https://population.un.org/wpp/assets/Files/WPP2019_Highlights.pdf