Growth Divergence between Indian States

., Kaustubh and Ghosh, Taniya (2024): Growth Divergence between Indian States. Forthcoming in: Economic and Political Weekly

Abstract

The paper investigates the causes of rising inequality among Indian states in terms of per capita State Domestic Product (GDP) in recent decades by examining the convergence/divergence between 20 major Indian states from 2000 to 2019. The paper adds to the existing literature by including the newly created states of Jharkhand, Chhattisgarh, and Uttarakhand in the sample. The paper, like previous research, finds 'conditional' convergence between states per capita GDP; however, the literature cannot determine whether this is due solely to different steady states caused by state-specific characteristics or to differences in productivity growth rates. According to our findings, differences in productivity growth rates, as well as different steady states, are the drivers of states' increasing per capita GDP inequality. Factors such as population growth rate, bank credit/GDP ratio, and shares of agriculture and industry in the GDP explain the differences in steady states between states, which drive the disparity in per capita GDP between states. Therefore, to reduce inequality, the states with low per capita GDP may benefit from rebalancing these variables. Furthermore, we must also investigate the causes of variations in productivity growth rates to address growing regional inequality.

• Item Type: MPRA Paper
• Language: English
• Keywords: Solow Model, Conditional Convergence, Beta-convergence, Stochastic convergence, Unit Root, Fixed Effect
• Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O10 - General; O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O47 - Empirical Studies of Economic Growth ; Aggregate Productivity ; Cross-Country Output Convergence

References

• Agrawal, P. (2015). The Role of Exports in India's Economic Growth. The Journal of International Trade & Economic Development, 24(6), 835-859.

• Arellano, M., & Bover, O. (1995). Another Look at the Instrumental Variable Estimation of Error-components Models. Journal of Econometrics, 68(1), 29-51.

• Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo evidence and an Application to Employment Equations. The Review of Economic Studies, 58(2), 277-297.

• Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223-251.

• Barro, R. J. & Sala-i-Martin, X. (1995). Economic Growth. McGraw-Hill, 1995, 539.

• Bernard, A. B., & Durlauf, S. N. (1996). Interpreting Tests of the Convergence Hypothesis. Journal of Econometrics, 71(1-2), 161-173.

• Blundell, R., & Bond, S. (1998). Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics, 87(1), 115-143.

• Cherodian, R., & Thirlwall, A. P. (2015). Regional Disparities in Per Capita Income in India: Convergence or Divergence? Journal of Post Keynesian Economics, 37(3), 384-407.

• Chao, Y. S., & Wu, C. J. (2017). Principal Component-based Weighted Indices and a Framework to Evaluate Indices: Results from the Medical Expenditure Panel Survey 1996 to 2011. PloS One, 12(9), e0183997.

• Ghosh, B., Marjit, S., & Neogi, C. (1998). Economic Growth and Regional Divergence in India, 1960 to 1995. Economic and Political Weekly, 1623-1630.

• Ghosh, M. (2008). Economic Reforms, Growth and Regional Divergence in India. Margin: The Journal of Applied Economic Research, 2(3), 265-285.

• Ghosh, M. (2012). Regional Economic Growth and Inequality in India during the Pre-and Post-reform Periods. Oxford Development Studies, 40(2), 190-212.

• Ghosh, T & Kaustubh (2023) Growth Decomposition of the Indian states using panel data techniques, Applied Economics. DOI: 10.1080/00036846.2023.2212974

• Islam, N. (1995). Growth Empirics: A Panel Data Approach. The Quarterly Journal of Economics, 110(4), 1127-1170.

• Hayashi F. (2000), Econometrics, Princeton University Press, pp. 342-346.

• Kar, S., Jha, D., & Kateja, A. (2011). Club‐convergence and Polarization of States: A Nonparametric Analysis of Post‐reform India. Indian Growth and Development Review, Emerald Group Publishing, vol. 4(1), pages 53-72, April.

• Lessmann, C., & Seidel, A. (2017). Regional Inequality, Convergence, and its Determinants–A View from Outer Space. European Economic Review, 92, 110-132

• Lolayekar, A. P., & Mukhopadhyay, P. (2020). Understanding Growth Convergence in India (1981–2010): Looking beyond the Usual Suspects. PloS one, 15(6), e0233549.

• Mishra, A., & Mishra, V. (2018). Re-examination of Convergence Hypothesis among Indian States in Panel Stationarity Testing Framework with Structural Breaks. Applied Economics, 50(3), 268-286.

• Misra, B.S. (2020), "Determinants of Total Factor Productivity in Indian States", Indian Growth and Development Review, Vol. 13 No. 1, pp. 259-282

• Misra, B. S., Nazlioglu, S., & Kucukkaplan, I. (2022). “Sources of Divergence in Income in Indian States”, 2001–2015. Development Policy Review, 40, e12594. https://doi.org/10.1111/dpr.12594

• Nagaraj, R., Varoudakis, A., & Véganzonès, M. A. (2000). Long‐run Growth Trends and Convergence across Indian States. Journal of International Development: The Journal of the Development Studies Association, 12(1), 45-70.

• NITI Aayog (2020), Export Preparedness Index (EPI) 2020

• Quah, D. (1992). Empirical Cross-section Dynamics in Economic Growth. European Economic Review, Volume 37, Issues 2–3, 1993, Pages 426-434.

• Quah, D. (1993). Galton's Fallacy and Tests of the Convergence Hypothesis. The Scandinavian Journal of Economics, 427-443.

• Sanga, P., & Shaban, A. (2017). Regional Divergence and Inequalities in India. Economic & Political Weekly, 52(1), 103.