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Estimating Structural Breaks Endogenously in India's Post-Independence Growth Path: An Empirical Critique

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  • Ravindra H Dholakia

    (Indian Institute of Management, Ahmedabad)

  • Amey A Sapre

    (Indian Institute of Management, Ahmedabad)

Abstract

This paper attempts to address empirical and methodological issues with regard to endogenous estimation of break dates in India's GDP and sub-sector series and finds that detection of break dates is sensitive to base year changes, marginal extension of time series and alteration of the length of the partition. The study uses series of Indian GDP and sub-sectors at two different base years to evaluate its effect on variation in break dates. To take into account the effect of marginal increase of time series, break dates are estimated on time series from 1950-51 to 2003-04 and 2008-09. The study also raises the issue about selection of the length of partition, which can affect detection of break dates. These empirical limitations do not lead to any conclusive evidence of break dates and hence cannot help settle the debates over different growth and policy regimes of the Indian economy.

Suggested Citation

  • Ravindra H Dholakia & Amey A Sapre, 2011. "Estimating Structural Breaks Endogenously in India's Post-Independence Growth Path: An Empirical Critique," Journal of Quantitative Economics, The Indian Econometric Society, vol. 9(2), pages 73-87, July.
    • Handle: RePEc:jqe:jqenew:v:9:y:2011:i:2:p:73-87
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    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Dholakia, Ravindra H., 1994. "Spatial Dimension of the Acceleration of Economic Growth in India," IIMA Working Papers WP1994-02-01_01243, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Dufour, Jean-Marie & Ghysels, Eric, 1996. "Editors' introduction recent developments in the econometrics of structural change," Journal of Econometrics, Elsevier, vol. 70(1), pages 1-8, January.
    4. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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    Cited by:

    1. D.K. Srivastava & K.R. Shanmugam, 2012. "Stationarity Test for Aggregate Outputs in the Presence of Structural Breaks," Working Papers 2012-072, Madras School of Economics,Chennai,India.
    2. Devi, P. Indira & Shanmugam, K.R. & Jayasree, M.G., 2012. "Compensating Wages for Occupational Risks of Farm Workers in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 67(2), pages 1-12.
    3. Narayan Sethi & Saileja Mohanty & Sanhita Sucharita & Nanthakumar Loganathan, 2020. "Tax Reform And Economic Growth Nexus In India: Evidence From The Cointegration And Rolling-Window Causality," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1699-1725, December.
    4. Amey Sapre, 2014. "Madhya Pradesh: Does Agriculture Determine the State’s Growth Trajectory?," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 8(1), pages 39-57, February.
    5. Shahbaz, Muhammad & Farhani, Sahbi & Ozturk, Ilhan, 2013. "Coal Consumption, Industrial Production and CO2 Emissions in China and India," MPRA Paper 50618, University Library of Munich, Germany, revised 12 Oct 2013.
    6. Purba Roy Choudhury & Biswajit Chatterjee, 2017. "Growth in India’s Service Sector: Implications of Structural Breaks," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(1), pages 75-99, March.
    7. P Muthuramu & T Uma Maheswari, 2019. "Tests for Structural Breaks in Time Series Analysis: A Review of Recent Development," Shanlax International Journal of Economics, Shanlax Journals, vol. 7(4), pages 66-79, September.

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