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Modeling demand for coal in India: vector autoregressive models with cointegrated variables

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  • Kulshreshtha, Mudit
  • Parikh, Jyoti K.

Abstract

In this paper, long-run structural relationships of coal demand with price and income variables have been estimated for the four major coal consuming sectors in India using annual time series data from 1970–1995. Some of the recent developments in multivariate dynamic econometric time series modeling techniques have been used, including the estimation of long-run cointegrating relationships, short-run dynamics and measurement of the effects of shocks and their effect on the evolution of dynamic coal demand system. The models have been estimated using cointegrating VAR framework, which allows for endogeneity of regressors. Results indicate that coal demand is likely to grow more than proportionately with economic growth due to high GDP elasticities and low price elasticities. Further, coal prices are found to be weakly exogenous in all the sectors except cement. Persistence profiles indicate that coal demand systems in the four sectors seem to be stable and converge to equilibrium within a period of around 4–7 years after a typical system-wide shock.

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  • Kulshreshtha, Mudit & Parikh, Jyoti K., 2000. "Modeling demand for coal in India: vector autoregressive models with cointegrated variables," Energy, Elsevier, vol. 25(2), pages 149-168.
    • Handle: RePEc:eee:energy:v:25:y:2000:i:2:p:149-168
    DOI: 10.1016/S0360-5442(99)00059-6
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