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Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series

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  • Pami Dua

    (Delhi School of Economics)

  • Lokendra Kumawat

    (Delhi School of Economics)

Abstract

This paper models the univariate dynamics of seasonally unadjusted quarterly macroeconomic time series for the Indian economy including industrial production, money supply (broad and narrow measures) and consumer price index. The seasonal integration-cointegration and the periodic models are employed. The `best' model is selected on the basis of a battery of econometric tests including comparison of out-of-sample forecast performance. The results suggest that a periodically integrated process with one unit root best captures the movements in industrial production. The other variables do not exhibit periodically varying dynamics, though narrow money and consumer price index exhibit nonstationary seasonality. For the index of industrial production, the periodic model yields the best out-of-sample forecasts, while for broad money, the model in first differences performs best. On the other hand, for narrow money and the consumer price index, incorporating nonstationary seasonality does not lead to significant gains in forecast accuracy. Finally, we find significant conditional heteroskedasticity in industrial production, with error variance in the first two quarters (highest and lowest economic activity quarters, respectively) almost three times that in the other two quarters.

Suggested Citation

  • 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.
  • Handle: RePEc:cde:cdewps:136
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    Cited by:

    1. Kumawat, Lokendra, 2010. "Effect of Rainfall on Seasonals in Indian Manufacturing Production: Evidence from Sectoral Data," MPRA Paper 25300, University Library of Munich, Germany.
    2. Syed Kalim Hyder Bukhari & Abdul Jalil & Nasir Hamid Rao, 2011. "Detection and Forecasting of Islamic Calendar Effects in Time Series Data: Revisited," SBP Working Paper Series 39, State Bank of Pakistan, Research Department.
    3. Lokendra Kumawat, 2010. "Modelling changes in seasonality in Indian manufacturing production: an application of the STAR model," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 13(4), pages 361-372.
    4. Somesh Kumar Mathur & Surendra Babu, 2014. "Modelling & Forecasting of Re/$ Exchange rate – An empirical analysis," 2nd International Conference on Energy, Regional Integration and Socio-Economic Development 7741, EcoMod.
    5. 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.

    More about this item

    Keywords

    Seasonality; Integration; Periodic Integration; Forecast Performance;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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