The importance of labour market responses, competitiveness impacts, and revenue recycling in determining the political economy costs of broad carbon taxation in the UK-Reference-Cited by-同舟云学术

The importance of labour market responses, competitiveness impacts, and revenue recycling in determining the political economy costs of broad carbon taxation in the UK

Published:2022-12 Issue: Volume:116 Page:106393
ISSN:0140-9883
Container-title:Energy Economics
language:en
Short-container-title:Energy Economics

Author:

Turner Karen,Alabi Oluwafisayo,Katris Antonios,Swales Kim

Funder

Children's Investment Fund Foundation

Engineering and Physical Sciences Research Council

Innovate UK

Publisher

Elsevier BV

Subject

General Energy,Economics and Econometrics

Reference31 articles.

1. The economic and environmental impact of a carbon tax for Scotland: a computable general equilibrium analysis;Allan;Ecol. Econ.,2014

2. A theory of demand for products distinguished by place of production;Armington;IMF Staff. Pap.,1969

3. Carbon pricing in climate policy: seven reasons, complementary instruments, and political economy considerations;Baranzini;Wiley Interdiscip. Rev. Clim. Chang.,2017

4. Carbon pricing efficacy: cross-country evidence;Best;Environ. Resour. Econ.,2020

5. The wage curve;Blanchflower;Europe-Revue Litteraire Mensuelle,2009

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Economic impacts of meeting China's NDC through carbon taxes with alternative schemes for recycling tax revenues;Resources, Conservation and Recycling;2024-08

2. Economic growth and environmental sustainability in developing economies;Research in International Business and Finance;2024-06

3. Industrial carbon capture utilisation and storage in the UK: The importance of wage responses in conditioning the outcomes of a new UK CO2 transport and storage industry emerging in a labour supply constrained economy;Journal of Cleaner Production;2024-01

4. Jobs, Skills and Regional Implications of the Low Carbon Residential Heat Transition in the UK;2024

5. Forecasting China’s GDP Growth Rate: An Analysis Based on R Language and Machine Learning;Modern Management;2024