Data for: Do vehicle efficiency improvements lead to energy savings? The Rebound Effect in Great Britain

This folder contains the main python codes used to conduct the analysis of this paper. These read in the raw data, clean and sample the data, before joining on additional datasets and running panel data regressions. Data on fuel prices, GDP and weather are included in the Research data folder. These are listed by the year and month of the first test in a driving period and the number of months covered in the driving period. For example a driving period between two MOT tests that begins on Jan 2006 and ends in Mar 2006 would cover a ‘delta’ of 3 months and the fuel price value would be the average fuel price over this time period. The programs to replicate the empirical work carried out in this paper are uploaded via the submission system to aid transparency in line with the journal’s replication policy. However, the main dataset used in this study is too large to upload to the site (>30 Gigabytes), this data is publicly available and a link is included in the programs where interested readers can freely download the data and run the programs. Similarly, the fuel consumption data used in section 4.3 is also publicly available but is proprietary meaning it cannot be uploaded, but can be freely accessed by the interested reader, links are also included in the python files for the sources of this data. All other data is uploaded with the article submission. Please contact [e-mail] if there are queries.本文件夹包含用于开展本论文分析的核心Python代码。这些代码可读取原始数据、对数据进行清洗与抽样，随后关联额外数据集并开展面板数据回归分析。燃油价格、国内生产总值（GDP）与气象数据已收录于研究数据文件夹中，这些数据按照行驶周期内首次检测的年、月，以及该行驶周期覆盖的总月数进行排序。例如，两次MOT检测之间的行驶周期若始于2006年1月、结束于2006年3月，则其时间差（delta）为3个月，对应的燃油价格取值为该时段内的平均燃油价格。为契合期刊的可复现政策以保障研究透明度，本论文实证工作的复现程序已通过投稿系统上传。但本研究使用的核心数据集体量过大（超过30吉字节（Gigabytes）），无法直接上传至投稿平台。该数据已公开发布，程序中已附带下载链接，感兴趣的读者可自行下载数据并运行代码。同理，本文4.3小节使用的燃油消耗量数据同样为公开发布的数据，但因属于专有数据无法直接上传，不过感兴趣的读者可免费获取；相关数据来源链接已包含在Python代码文件中。其余所有数据均已随论文投稿一并上传。如有任何疑问，请联系邮箱[e-mail]。