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dc.contributor.authorCattaneo, Cristinaen_US
dc.contributor.authorManera, Matteoen_US
dc.contributor.authorScarpa, Elisaen_US
dc.date.accessioned2010-09-01en_US
dc.date.accessioned2010-09-29T08:56:53Z-
dc.date.available2010-09-29T08:56:53Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10419/40686-
dc.description.abstractThe 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.en_US
dc.language.isoengen_US
dc.publisherFondazione Eni Enrico Matteien_US
dc.relation.ispartofseriesNota di lavoro // Fondazione Eni Enrico Mattei: IEM, International energy markets 2008,8en_US
dc.subject.jelC23en_US
dc.subject.jelE6en_US
dc.subject.jelQ31en_US
dc.subject.jelQ41en_US
dc.subject.ddc330en_US
dc.subject.keywordEnergy demanden_US
dc.subject.keywordCoal demanden_US
dc.subject.keywordChinaen_US
dc.subject.keywordSpatial econometricsen_US
dc.subject.keywordPanel dataen_US
dc.subject.keywordForecastingen_US
dc.titleIndustrial coal demand in China: A provincial analysisen_US
dc.typeWorking Paperen_US
dc.identifier.ppn560338392en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:FEEM Working Papers, Fondazione Eni Enrico Mattei

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