Replication materials for: Beyond tariff adjustment: Fuel-price shocks and utility financial recovery in Korea
Description
Korean electricity prices, sales, settlement statistics and utility financial records for 2011-2024, with Python scripts that reproduce Tables 1-5, Supplementary Tables S1-S13 and Figs. 1-4 of the related article. The data cover Korea Electric Power Corporation (KEPCO) on a separate and a consolidated basis, Korea Hydro & Nuclear Power (KHNP) and the five thermal generation subsidiaries (KOEN, KOMIPO, KOSPO, KOWEPO and EWP). Version 2 adds the inputs and code for the revised analysis: KEPCO parent and group financing measures for 2017-2024 from the financial statements filed through DART; monthly SMP and KEPCO's average purchase and sales prices for 2020-2024; annual settlement prices, traded volumes and trading amounts by generation company and settlement prices by fuel type from KPX EPSIS; the tariff decisions of 2021-2024 and the quarterly fuel-cost adjustment charges, formula-implied and applied, from KEPCO's notices and releases. Version 1 remains available as the record of the initial submission. Values are taken from official publications and databases: KEPCO's Statistics of Electric Power in Korea and Monthly Electric Power Statistics; annual business reports, including amended reports, filed with the Financial Supervisory Service through the DART electronic disclosure system; the Korea Power Exchange (KPX) Electric Power Statistics Information System (EPSIS) and KPX's official annual system marginal price; KEPCO tariff notices and press releases and the Ministry of Trade, Industry and Energy's tariff-reform release of December 2020; Korea Gas Corporation (KOGAS) gas tariffs for power generation; the Korea Energy Economics Institute (KEEI) Yearbook of Energy Statistics; the Bank of Korea Economic Statistics System (ECOS); and Statistics Korea. Each of the 1,380 ledger values carries a provenance record in data/source_catalog.csv giving the publisher, document, direct link, and the table, account or query it came from. The other input files carry their own source columns. The archive contains extracted values and the authors' analysis code. The original corporate reports, statistical publications and notices are not redistributed; the source columns link to their publishers. FILE_GUIDE.md lists every file in the archive and explains how to run the analysis.
Files
Steps to reproduce
Python 3.12. Extract the archive and open the folder up_financial_recovery. Install the pinned packages and run the script: python -m pip install -r requirements.txt python reproduce.py Results are written to results/: 18 table files matching Tables 1-5 and Supplementary Tables S1-S13, Figs. 1-4 in PNG, PDF and SVG with the plotted values behind each figure, selected numerical comparisons including those quoted in the text (key_results.csv), and the intermediate series. The script first checks every input file against the SHA-256 digests in input_manifest.json. To obtain the numerical results with the Python standard library only, run: python reproduce.py --no-figures --output-dir results_numbers. The figures use Times New Roman where it is installed and otherwise the Times-like STIX font bundled with matplotlib; no number depends on the font.
Categories
Funders
- Kepco International Nuclear Graduate School