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The role of industrial structure upgrades in eco-efficiency evolution: Spatial correlation and spillover effects

pmid: 31412466
The Chinese government has grown increasingly invested in ecology in recent years. This paper discusses eco-efficiency using data envelopment analysis on 48 cities in Bohai Rim with special focus on the role of industrial structure upgrades. Based on the values from a super undesirable slack-based model, this study investigates eco-efficiency from temporal and spatial perspectives to reveal gaps among Bohai cities but an overall improvement in regional eco-efficiency. Moreover, this study adopts the Global and Local Moran's I to identify positive spatial autocorrelations and shows that most cites in Bohai Rim have high-high, low-low aggregation characteristics. Plus, the economic effects of per capita GDP, industrial structure upgrades on eco-efficiency are determined according to a spatial Durbin model. There appear to be negative spillover effects of industrial structure upgrades on surrounding cities, which reflects an industry transfer phenomenon related to eco-efficiency.
- Tsinghua University China (People's Republic of)
- Keele University United Kingdom
- Keele University United Kingdom
- York University Canada
- Tsinghua–Berkeley Shenzhen Institute China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).154 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
