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Can More Environmental Information Disclosure Lead to Higher Eco-Efficiency? Evidence from China

Yantuan Yu (), Jianhuan Huang () and Nengsheng Luo ()
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Yantuan Yu: School of Economics and Trade, Hunan University, 109 Road Shijiachong, Yuelu District, Changsha 410079, China
Jianhuan Huang: School of Economics and Trade, Hunan University, 109 Road Shijiachong, Yuelu District, Changsha 410079, China
Nengsheng Luo: School of Economics and Trade, Hunan University, 109 Road Shijiachong, Yuelu District, Changsha 410079, China

Sustainability, 2018, vol. 10, issue 2, 1-20

Abstract: The present paper investigates the impact of pollution information transparency index (PITI) on eco-efficiency using a novel panel dataset covering 109 key environmental protection prefecture-level cities in China over the period 2008–2015. We apply an extended data envelopment analysis (DEA) model, simultaneously incorporating metafrontier, undesirable outputs and super efficiency into slack-based measure (Meta-US-SBM) to estimate eco-efficiency. Then, the bootstrap Granger causality approach is utilized to test the unidirectional Granger causal relationship running from PITI to eco-efficiency. Results of DEA model show that there exist significant spatiotemporal disparities of eco-efficiency, on average, the eco-efficiency in eastern region is relative higher than those of central/western region. Estimates of ordinary least square (OLS) method, quantile regression, and spatial Durbin model document that the evidence of an inverted-U-shaped relation between PITI and eco-efficiency is supported, and the turning points vary from 0.3370 to 0.4540 with different model specifications. Finally, supplementary analysis of panel threshold model also supports the robust findings. Policy implications are presented based on the empirical results.

Keywords: environmental information disclosure; eco-efficiency; Meta-US-SBM; quantile regression; spatial Durbin model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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