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Does the creation of smaller states lead to higher economic growth? Evidence from state reorganization in India

Author

Listed:
  • Vikash Vaibhav
  • K.V. Ramaswamy

    (Indira Gandhi Institute of Development Research)

Abstract

In the largest territorial reorganization since the 1950s, when the modern state boundaries were demarcated, the Indian union government carved out three new states from three large north Indian states in November 2000. This was accompanied by discussions along political and sociological lines. But the debates along economic lines were muted, owing to a lack of data. Equipped with three and a half decades-long macro panel data, we investigate whether the event had an impact on the per capita income. For comparison, we construct five separate counterfactuals using techniques such as synthetic control and elastic net regularization. The three erstwhile `combined' states do not show any evidence of extraordinary growth. We further investigate the six states separately to see if the `new' states grew at the expense of their `parent' states. The state of Uttarakhand shows `extraordinary' growth in the post-reorganization period. Two other smaller states (Bihar and Chhattisgarh) did grow faster than their counterfactual, but do not qualify for the statistical significance test. Three other states (Jharkhand, Madhya Pradesh, and Uttar Pradesh) also do not show a significant change in their growth path. Overall, we find that the creation of smaller sub-national administrative units may not be a panacea for their economic problems.

Suggested Citation

  • Vikash Vaibhav & K.V. Ramaswamy, 2022. "Does the creation of smaller states lead to higher economic growth? Evidence from state reorganization in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-007, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Handle: RePEc:ind:igiwpp:2022-007
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    References listed on IDEAS

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    1. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    2. Nimah Mazaheri & Edouard Al-Dahdah & Sandeep Poundrik & Soujanya Chodavarapu, 2013. "Leadership and Institutional Change in the Public Provision of Transportation Infrastructure: An Analysis of India's Bihar," Journal of Development Studies, Taylor & Francis Journals, vol. 49(1), pages 19-35, January.
    3. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2011. "Synth: An R Package for Synthetic Control Methods in Comparative Case Studies," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i13).
    4. Akhtar Majeed, 2003. "The Changing Politics of States' Reorganization," Publius: The Journal of Federalism, CSF Associates Inc., vol. 33(4), pages 83-98, Fall.
    5. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2015. "Comparative Politics and the Synthetic Control Method," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 495-510, February.
    6. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    7. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    8. Shenoy, Ajay, 2018. "Regional development through place-based policies: Evidence from a spatial discontinuity," Journal of Development Economics, Elsevier, vol. 130(C), pages 173-189.
    9. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    10. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    11. Bhattacharjee, Govind, 2016. "Special Category States of India," OUP Catalogue, Oxford University Press, number 9780199460830.
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    More about this item

    Keywords

    State reorganization; Economic growth; Impact evaluation; Synthetic Control; Elastic Net;
    All these keywords.

    JEL classification:

    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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