Abstract:In China, between 1978 and 1995, energy use per unit of GDP fell by 55%. There has been considerable debate about the major factors responsible for this dramatic decline in the energyoutput ratio. In this paper we use the two most recent input-output tables to decompose the reduction in energy use into technical change and various types of structural change, including changes in the quantity and composition of imports and exports. In performing our analysis we are forced to deal with a number of problems with … Show more
“…7 There is a wide suspicion that the official rate of inflation for producer prices is understated because the official prices might not be the properly weighted average of plan and market prices, might have been misreported, or were not produced using a good sample of firms (Rawski, 1991;Garbaccio et al, 1999). Assuming that the official data for GDP and industrial subsector value added are correct, lowering the annual growth rate of each industrial subsector by 2% is equivalent to raising the annual rate of inflation of all industrial products by the same percentage in terms of the impacts on the energy consumption, although the reasons for the two adjustments are very different from each other.…”
“…7 There is a wide suspicion that the official rate of inflation for producer prices is understated because the official prices might not be the properly weighted average of plan and market prices, might have been misreported, or were not produced using a good sample of firms (Rawski, 1991;Garbaccio et al, 1999). Assuming that the official data for GDP and industrial subsector value added are correct, lowering the annual growth rate of each industrial subsector by 2% is equivalent to raising the annual rate of inflation of all industrial products by the same percentage in terms of the impacts on the energy consumption, although the reasons for the two adjustments are very different from each other.…”
“…Therefore, as has been argued by Fisher-Vanden et al (2004), sectorial changes can be important to explain the decline in energy intensity. However, most previous studies have found sectoral shift to be a relatively small contributor to the decline in China's energy intensity (Garbaccio et al, 1999;Liao et al, 2007, andMa andStern, 2008). 10…”
The main objective of this paper is to investigate whether openness and investment ownership are key factors in explaining the diffusion of energy-saving technologies in China. Compared with previous studies, the novel aspect of this work is the use of a rich dataset at provincial level, which allows the high level of regional heterogeneity to be taken into consideration. The unbalanced regional growth has been translated into differences in the need for energy resources across the vast territory of China. A detailed analysis of these issues may provide new insights into the energy situation in this country. The analysis is also disaggregated by type of energy: coal, electricity and petroleum. We estimate the models by panel-corrected standard errors, developed by Beck and Katz (1995), over the period . Results obtained confirm the hypothesis that both foreign and non-state investments play a leading role in the decline of energy intensity across Chinese regions, whereas there is no evidence of a positive contribution of state investment. The findings also reveal differences in energy intensity across regions, thus confirming the importance of accounting for the regional dimension when analyzing energy consumption in China.
“…The objective of these papers, which include among others Kambara (1992), Garbaccio et al (1999), Chu at al. (2006), is to investigate the explanation for such decline in energy intensity.…”
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.
Terms of use:
Documents in
Industrial Coal Demand in China: A Provincial Analysis SummaryIn recent years, concerns regarding the environmental implications of the rising coal demand have induced considerable efforts to generate long-term forecasts of China's energy requirements. Nevertheless, none of the previous empirical studies on energy demand for China has tackled the issue of modelling coal demand in China at provincial level. The aim of this paper is to fill this gap. In particular, we model and forecast the Chinese demand for coal using time series data disaggregated by provinces. Moreover, not only does our analysis account for heterogeneity among provinces, but also, given the nature of the data, it captures the presence of spatial autocorrelation among provinces using a spatial econometric model. A fixed effects spatial lag model and a fixed effects spatial error model are estimated to describe and forecast industrial coal demand. Our empirical results show that the fixed effect spatial lag model better captures the existing interdependence between provinces. This model forecasts an average annual increase in coal demand to 2010 of 4 percent.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.