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Modelling Seasonal Dynamics in Indian Industrial Production--An Extention of TV-STAR Model

Author

Listed:
  • Pami Dua

    (Department of Economics, Delhi School of Economics, Delhi, India)

  • Lokendra Kumawat

    (Department of Economics, Ramjas College,University of Delhi, Delhi)

Abstract
This paper models the seasonal dynamics in quarterly industrial production for India. For this, we extend the time-varying smooth transition autoregression (TV-STAR) model to allow for independent regime-switching behaviour in the deterministic seasonal and cyclical components. This yields the time-varying seasonal smooth transition (TV-SEASTAR) model. We find evidence of the effect of rainfall growth on seasonal dynamics of industrial production. We also find that the seasonal dynamics have changed over the past decade, one aspect of this being the significant narrowing down of seasonals. The timing of these changes coincides with the changes in the character of the economy as it progressed towards a free-market economy in the post liberalization period.

Suggested Citation

  • Pami Dua & Lokendra Kumawat, 2007. "Modelling Seasonal Dynamics in Indian Industrial Production--An Extention of TV-STAR Model," Working papers 162, Centre for Development Economics, Delhi School of Economics.
    • Handle: RePEc:cde:cdewps:162
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    References listed on IDEAS

    as
    1. Matas-Mir, Antonio & Osborn, Denise R., 2004. "Does seasonality change over the business cycle? An investigation using monthly industrial production series," European Economic Review, Elsevier, vol. 48(6), pages 1309-1332, December.
    2. Cecchetti, Stephen G. & Kashyap, Anil K, 1996. "International cycles," European Economic Review, Elsevier, vol. 40(2), pages 331-360, February.
    3. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    4. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    5. Cecchetti, Stephen G & Kashyap, Anil K & Wilcox, David W, 1997. "Interactions between the Seasonal and Business Cycles in Production and Inventories," American Economic Review, American Economic Association, vol. 87(5), pages 884-892, December.
    6. Franses, Ph.H.B.F. & de Bruin, P. & van Dijk, D.J.C., 2000. "Seasonal smooth transition autoregression," Econometric Institute Research Papers EI 2000-06/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Kanwar, Sunil, 2000. "Does the Dog Wag the Tail or the Tail the Dog? Cointegration of Indian Agriculture with Nonagriculture," Journal of Policy Modeling, Elsevier, vol. 22(5), pages 533-556, September.
    8. Beaulieu, J Joseph & Miron, Jeffrey A, 1992. "A Cross Country Comparison of Seasonal Cycles and Business Cycles," Economic Journal, Royal Economic Society, vol. 102(413), pages 772-788, July.
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    More about this item

    Keywords

    Seasonality; Smooth transition autoregression; Economic reforms.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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