Matches in SemOpenAlex for { <https://semopenalex.org/work/W2519572020> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2519572020 endingPage "808" @default.
- W2519572020 startingPage "801" @default.
- W2519572020 abstract "Abstract With the advent of the era of big data, large-dimensional spatial panel data is gradually used to do empirical research in the macroeconomic field. This paper adopts a Data Envelopment Analysis(DEA) approach to calculate regional energy efficiency based on the perspective of total-factor energy efficiency using statistical data of 30 administrative regions in China. On basis of spatial effects, the paper assesses the convergence of regional energy efficiency in China using large-dimensional spatial panel data model. Our results indicate that (1) There is significant spatial autocorrelation and clear spatial effects in China's regional energy efficiency. Thus, spatial effects should not be ignored when assessing the convergence of regional energy efficiency in China; (2) During the period from 2000 to 2014 China's regional energy efficiency not only exhibits absolute β -convergence but also exhibits conditional β -convergence, the convergence rate is higher than the rate of absolute convergence after controlling for the initial conditions of the level of economic development, foreign direct investment and government influence; (3) The convergence rate of China's regional energy efficiency from 2004 to 2014 is higher than the convergence rate for the period of 2000–2004, which indicates that industry transfer has contributed to improvement in the convergence of regional energy efficiency in China since 2004." @default.
- W2519572020 created "2016-09-23" @default.
- W2519572020 creator A5019540226 @default.
- W2519572020 creator A5035367191 @default.
- W2519572020 creator A5077313684 @default.
- W2519572020 date "2017-01-01" @default.
- W2519572020 modified "2023-09-29" @default.
- W2519572020 title "Convergence analysis of regional energy efficiency in china based on large-dimensional panel data model" @default.
- W2519572020 cites W1992305274 @default.
- W2519572020 cites W1993977170 @default.
- W2519572020 cites W2000081835 @default.
- W2519572020 cites W2009317771 @default.
- W2519572020 cites W2022186362 @default.
- W2519572020 cites W2032076993 @default.
- W2519572020 cites W2034793026 @default.
- W2519572020 cites W2059071347 @default.
- W2519572020 cites W2061099708 @default.
- W2519572020 cites W2072537609 @default.
- W2519572020 cites W2081703837 @default.
- W2519572020 cites W2083521762 @default.
- W2519572020 cites W2106998380 @default.
- W2519572020 cites W2146818132 @default.
- W2519572020 cites W2191581545 @default.
- W2519572020 cites W3125128165 @default.
- W2519572020 doi "https://doi.org/10.1016/j.jclepro.2016.09.096" @default.
- W2519572020 hasPublicationYear "2017" @default.
- W2519572020 type Work @default.
- W2519572020 sameAs 2519572020 @default.
- W2519572020 citedByCount "70" @default.
- W2519572020 countsByYear W25195720202017 @default.
- W2519572020 countsByYear W25195720202018 @default.
- W2519572020 countsByYear W25195720202019 @default.
- W2519572020 countsByYear W25195720202020 @default.
- W2519572020 countsByYear W25195720202021 @default.
- W2519572020 countsByYear W25195720202022 @default.
- W2519572020 countsByYear W25195720202023 @default.
- W2519572020 crossrefType "journal-article" @default.
- W2519572020 hasAuthorship W2519572020A5019540226 @default.
- W2519572020 hasAuthorship W2519572020A5035367191 @default.
- W2519572020 hasAuthorship W2519572020A5077313684 @default.
- W2519572020 hasConcept C139719470 @default.
- W2519572020 hasConcept C149782125 @default.
- W2519572020 hasConcept C162324750 @default.
- W2519572020 hasConcept C166957645 @default.
- W2519572020 hasConcept C191935318 @default.
- W2519572020 hasConcept C205649164 @default.
- W2519572020 hasConcept C2777303404 @default.
- W2519572020 hasConcept C39432304 @default.
- W2519572020 hasConcept C6422946 @default.
- W2519572020 hasConceptScore W2519572020C139719470 @default.
- W2519572020 hasConceptScore W2519572020C149782125 @default.
- W2519572020 hasConceptScore W2519572020C162324750 @default.
- W2519572020 hasConceptScore W2519572020C166957645 @default.
- W2519572020 hasConceptScore W2519572020C191935318 @default.
- W2519572020 hasConceptScore W2519572020C205649164 @default.
- W2519572020 hasConceptScore W2519572020C2777303404 @default.
- W2519572020 hasConceptScore W2519572020C39432304 @default.
- W2519572020 hasConceptScore W2519572020C6422946 @default.
- W2519572020 hasFunder F4320327557 @default.
- W2519572020 hasLocation W25195720201 @default.
- W2519572020 hasOpenAccess W2519572020 @default.
- W2519572020 hasPrimaryLocation W25195720201 @default.
- W2519572020 hasRelatedWork W2018248323 @default.
- W2519572020 hasRelatedWork W2058934538 @default.
- W2519572020 hasRelatedWork W2109864193 @default.
- W2519572020 hasRelatedWork W2288037775 @default.
- W2519572020 hasRelatedWork W2362510781 @default.
- W2519572020 hasRelatedWork W2780203579 @default.
- W2519572020 hasRelatedWork W3022413072 @default.
- W2519572020 hasRelatedWork W3123079208 @default.
- W2519572020 hasRelatedWork W3123800140 @default.
- W2519572020 hasRelatedWork W3125239093 @default.
- W2519572020 hasVolume "142" @default.
- W2519572020 isParatext "false" @default.
- W2519572020 isRetracted "false" @default.
- W2519572020 magId "2519572020" @default.
- W2519572020 workType "article" @default.