Research and analysis

Executive Summary: Methodological Paper: Climate Change Levy and related Climate Change Agreement Scheme

Published 25 June 2025

Prepared by Ipsos for HM Revenue and Customs. The views in this report are the authors’ own and do not necessarily reflect those of HM Revenue and Customs

HMRC Research Report 828

1. Executive Summary

HM Revenue and Customs (HMRC) commissioned Ipsos and UCL Consultants (UCLC) to undertake an evaluation study on the environmental impact of taxes (rates and reliefs). As part of this research it was decided to undertake the empirical evaluation of two taxes, the Landfill Tax and the Climate Change Levy (CCL). This report outlines a methodology for evaluating the impact of CCL and its related Climate Change Agreement (CCA) scheme, designed to promote energy efficiency in UK businesses. It also provides an overview of the steps taken to empirically evaluate this tax as well as the reasons why this work could not be undertaken at this time.

The Climate Change Levy (CCL) is an environmental tax applied to energy usage by businesses in various sectors, including industrial, commercial, agricultural, and public administration. Introduced in 2001, the CCL aims to encourage energy efficiency. Businesses operating in specified energy-intensive sectors can qualify for a reduced CCL rate by participating in the Climate Change Agreement (CCA) scheme. By meeting their agreed-upon targets, businesses can benefit from significant discounts on their CCL liability, thereby reducing their energy costs and enhancing their competitiveness.

The evaluation of CCL could not be completed due to several data-related challenges, primarily concerning the availability and linking of essential datasets. Accessing comprehensive gas and electricity consumption data through the Non-Domestic National Energy Efficiency Framework Database (ND-NEED) was not possible as gas data was not available.   Alternative data sources such as the Quarterly Fuel Inquiry (QFI) data, while containing relevant information, could not be linked with other datasets due to a lack of common identifiers, rendering it unsuitable for the evaluation. Delays in data access further complicated the process, impacting the feasibility assessment and the construction of control groups.

For future evaluations, the report recommends using a Synthetic Difference in Differences (SDiD) approach with an instrumental variable by Martin et. al (2014). This method aims to mitigate biases stemming from the self-selection of businesses into the CCA scheme. The proposed methodology involves comparing businesses eligible for the CCA scheme which chose not to participate with those that did. It is also suggests to split the analysis in two periods 2013 to 2016 to cover the period of the second CCA scheme until the discount rate change in 2016 and 2016 to 2020 to asses the impact of CCL discount rate change, until the latest available data.

Future evaluations would require a comprehensive dataset encompassing treatment and control variables, energy consumption data sourced from the ND-NEED framework, business performance indicators such as turnover and employment, and information on whether firms have participated in other relevant policies (such as the CRC and the ESOS schemes).

For future evaluations, the report highlights the importance of early data access, suggesting a period of at least six months dedicated to ensure all the necessary datasets can be accessed.