Journal ArticleDOI
Dynamic relationship among environmental regulation, technological innovation and energy efficiency based on large scale provincial panel data in China
TLDR
Based on the large scale provincial panel data on in China from 2006 to 2015, the authors uses the directed acyclic graph (DAG) and structure vector autoregrression (SVAR) to study the internal dynamic relationship among the environmental regulation, technological innovation and energy efficiency.About:
This article is published in Technological Forecasting and Social Change.The article was published on 2017-12-01. It has received 251 citations till now. The article focuses on the topics: Incentive & Efficient energy use.read more
Citations
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How does environmental regulation promote technological innovations in the industrial sector? Evidence from Chinese provincial panel data
TL;DR: Wang et al. as discussed by the authors investigated the effect of environmental regulation on technological innovations based on the provincial panel data of industrial sectors in China during the years 2005-2015, and found that industries with a higher degree of market competition and higher human capital investment tend to have stronger technological innovation capabilities.
Journal ArticleDOI
Technological challenges of green innovation and sustainable resource management with large scale data
TL;DR: In this article, the authors focused on finding effective ways to achieve sustainable development, taking into account the seriousness of environmental pollution, sustainable development papers based on big data are clearly the most important contributions of this special volume.
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Does command-and-control regulation promote green innovation performance? Evidence from China's industrial enterprises.
TL;DR: The results find that the eleventh FYP environmental regulation negatively influences enterprise green innovation efficiency in a short-term through reducing cash flows, and suggests that the government should consider the effect of CCR on economy and focus on the heterogeneity of enterprises during designing environmental policies.
Journal ArticleDOI
Technological innovation, environmental regulation, and green total factor efficiency of industrial water resources
TL;DR: In this paper, the effect of technological innovation, environmental regulation, and the interaction of these two factors on the green total factor efficiency (GTFE) of industrial water resources by applying the Super-Slack Based Measure (SBM) model of non-expected output was analyzed.
Journal ArticleDOI
Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China
TL;DR: Wang et al. as discussed by the authors used the difference-in-differences (DID) method to evaluate the impact of carbon emissions and economic growth following carbon emission trading implementation in China.
References
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Journal ArticleDOI
Testing for unit roots in heterogeneous panels
TL;DR: In this article, a unit root test for dynamic heterogeneous panels based on the mean of individual unit root statistics is proposed, which converges in probability to a standard normal variate sequentially with T (the time series dimension) →∞, followed by N (the cross sectional dimension)→∞.
MonographDOI
Causality: models, reasoning, and inference
TL;DR: The art and science of cause and effect have been studied in the social sciences for a long time as mentioned in this paper, see, e.g., the theory of inferred causation, causal diagrams and the identification of causal effects.
Journal ArticleDOI
Unit root tests in panel data: asymptotic and finite-sample properties
TL;DR: In this article, the authors consider pooling cross-section time series data for testing the unit root hypothesis, and they show that the power of the panel-based unit root test is dramatically higher, compared to performing a separate unit-root test for each individual time series.
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A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test
G. S. Maddala,Shaowen Wu +1 more
TL;DR: The Im-Pesaran-Shin (IPS) test as discussed by the authors relaxes the restrictive assumption of the LL test and is best viewed as a test for summarizing the evidence from independent tests of the sample hypothesis.
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