Scripts and data for "The impact of financing cost differences on global energy and industry decarbonization"

The zip file in this record contains code and data to create the figures and tables and to replicate the underlying analysis in the following publication: Waidelich et al. (2026). The impact of financing cost differences on global energy and industry decarbonization. Nature Climate Change (forthcoming), DOI: https://doi.org/10.1038/s41558-026-02756-0 For more information on the repository's content and how to replicate the paper content, see the README document included in the replication package. Source Data for the main figures in the paper are provided with the publication itself.For more details on how to access the third-party input data used here, see the Data and Code Availability Statements in the publication itself and the README document in this repository. For questions, please contact the corresponding author as indicated in the underlying publication. Data files for the CoC estimates:If you want to use the cost of capital estimates, country-level and IMAGE region-level files are included in the zip file as WaidelichEtAl2026_CostOfCapital_ByCountry.csv and WaidelichEtAl2026_CostOfCapital_ByIMAGERegion.csv. Variables included in these files:- country, region and sector identifiers (names and, for countries, ISO codes)- wacc_aftertax_nominal: our main WACC estimates- wacc_aftertax_nominal_aaa: our main estimates but setting the country risk premium to zero (i.e., assuming that the country is AAA-rated)- wacc_derivative_...: partial derivatives of our main estimates with respect to different input parameters (country risk premium, equity risk premium, beta, debt spread and risk-free rate). These allow users to modify our estimates ceteris paribus (e.g., by changing the risk-free rate assumption) without having to rerun the entire replication package- flag_imputation_corporatetax: indicates countries for which the corporate tax rate is imputed (see Methods and SI of the underlying publication)- gdp_ppp_real_bn and year_of_gdp_value: GDP data that can be used to aggregate country-level estimates to regions- key input variables that vary by country or sector (crp_debt_defaultspread_average_20162025, corporate_tax_rate, debt_spread_damodaran_global, relevered_beta) Note that these files, and the repository more broadly, also cover climate-relevant sectors not included in the paper (e.g., vehicle or heat pump manufacturing), applying the paper's methodology to support modelers interested in other sectors. If you have any questions about these data files and how to use them for your own research, reach out to the corresponding author.Data sources and usage terms:- Damodaran data: Aswath Damodaran, Stern School of Business, New York University (https://pages.stern.nyu.edu/~adamodar/). Use and redistribution permitted subject to Damodaran's usage rules; commercial resale of the data is not permitted.- World Bank data: World Bank, World Development Indicators, CC BY 4.0.- Individual PwC corporate tax rates: PwC, Worldwide Tax Summaries (https://taxsummaries.pwc.com), © PwC. All rights reserved.- OECD government bond yield data: OECD, Main Economic Indicators, accessed via FRED, Federal Reserve Bank of St. Louis. Redistribution permitted subject to OECD attribution requirements.