Using machine learning to model technological heterogeneity in carbon emission efficiency evaluation: The case of China's cities
Authors:
- Ailun WangAWAilun Wang
- Shuo HuSHShuo Hu
- Jianglong LiJLJianglong Li
- 10 August 2022
- journal article
- research article
- Published by Elsevier in Energy Economics
- Vol. 114
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- An integrated Data Envelopment Analysis–Artificial Neural Network–Rough Set Algorithm for assessment of personnel efficiencyExpert Systems with Applications, 2011
- The greenness of cities: Carbon dioxide emissions and urban developmentJournal of Urban Economics, 2010
- A metafrontier approach for measuring an environmentally sensitive productivity growth indexEnergy Economics, 2010
- China's Local Political Budget CyclesAmerican Journal of Political Science, 2009
- Foreign Direct Investment, Absorptive Capacity and Regional Innovation Capabilities: Evidence from ChinaOxford Development Studies, 2008
- Gold into Base Metals: Productivity Growth in the People’s Republic of China during the Reform PeriodJournal of Political Economy, 2003
- Productivity and Undesirable Outputs: A Directional Distance Function ApproachJournal of Environmental Management, 1997
- Evaluating public transport efficiency with neural network modelsTransportation Research Part C: Emerging Technologies, 1997
- Formulation and estimation of stochastic frontier production function modelsJournal of Econometrics, 1977
- Sources of Agricultural Productivity Gap Among Selected CountriesAmerican Journal of Agricultural Economics, 1969