Matteo Manera (University of Milano-Bicocca) Cristina Cattaneo (Fondazione Eni Enrico Mattei, Milan and University of Sussex) Elisa Scarpa (Edison Trading)
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The general concern on the environmental implications of the rising demand for coal registered in China during the last few years has induced considerable research effort to produce accurate forecasts of China’s energy requirements. Nevertheless, no previous study has modelled the coal demand in China at provincial level. The aim of this paper is twofold. First, we estimate and forecast the Chinese demand for coal using panel data disaggregated by provinces and accounting for spatial heterogeneity. Second, given the spatial nature of the data, we explicitly capture the spatial autocorrelation among provinces using spatial econometrics. In particular, we specify the Chinese industrial coal demand at provincial level with a fixed-effect spatial lag model and a fixed-effect spatial error model. The fixedeffect spatial lag model seems to better capture the existing interdependence between provinces. This model forecasts an average annual increase in coal demand to 2010 of 4 percent.
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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number
2008.8.
Find related papers by JEL classification: C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply
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