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Journal ArticleDOI

Estimating energy conservation potential in China’s energy intensive industries with rebound effect

Boqiang Lin, +1 more
- 10 Jul 2017 - 
- Vol. 156, pp 899-910
TLDR
In this paper, the authors investigated the influential factors of energy consumption in the industries by employing the cointegration method, and estimated the possible energy conservation potential considering energy rebound effect, and showed that GDP and the scale of industries are the deterministic factors increasing energy consumption, while R&D intensity decreases it.
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This article is published in Journal of Cleaner Production.The article was published on 2017-07-10. It has received 65 citations till now. The article focuses on the topics: Energy consumption & Energy intensity.

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Citations
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Journal ArticleDOI

A big data driven analytical framework for energy-intensive manufacturing industries

TL;DR: A big data driven analytical framework is proposed to reduce the energy consumption and emission for energy-intensive manufacturing industries and two key technologies of the proposed framework are utilized to implement energy big data analytics.
Journal ArticleDOI

The impact of industrial structure efficiency on provincial industrial energy efficiency in China

TL;DR: In this article, the slacks-based measure model incorporating undesirable output is applied to evaluate the industrial energy efficiency both at the provincial level and the sectoral level in China for the period 2010 to 2016.
Journal ArticleDOI

Energy intensity and energy conservation potential in China: A regional comparison perspective

TL;DR: In this article, the authors identify the drivers of energy intensity across China's regions, employing a series of econometric techniques allowing for cross-sectional dependence and slope homogeneity.
Journal ArticleDOI

Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives

TL;DR: In this paper, the authors provide an overview of different steel production routes and present the modeling, scheduling and interrelation regarding material and energy flows in the iron and steel industry by thoroughly reviewing the existing literature.
Journal ArticleDOI

Environmental regulation, technological innovation and energy consumption---a cross-region analysis in China

TL;DR: Wang et al. as mentioned in this paper investigated the three types of environmental regulations on energy consumption using feasible generalized least squares method during 1997-2015 in direct and indirect path in China and found that the environmental regulations have a significant negative effect on the energy consumption.
References
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Journal ArticleDOI

Co-integration and Error Correction: Representation, Estimation and Testing

TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI

Distribution of the Estimators for Autoregressive Time Series with a Unit Root

TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
Journal ArticleDOI

Testing for a Unit Root in Time Series Regression

TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
Journal ArticleDOI

Maximum likelihood estimation and inference on cointegration — with applications to the demand for money

TL;DR: In this paper, the estimation and testing of long-run relations in economic modeling are addressed, starting with a vector autoregressive (VAR) model, the hypothesis of cointegration is formulated as a hypothesis of reduced rank of the long run impact matrix.
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