This repository contains code and documentation for a research project examining the effect of Sweden’s 2023 nuclear reclassification on electricity production. The analysis uses a regression discontinuity design (RDD) to estimate the short-run impact on nuclear output.
See the output file for the full PDF report.
This report is a more academic, formal, journal-style most suitable for readers with a good foundation in econometric methods.
On June 1, 2023, Sweden formally reclassified nuclear energy as a "fossil-free" source under its climate and energy framework. This project evaluates whether that change was associated with a measurable shift in daily nuclear electricity generation. The analysis relies on high-frequency generation data and applies a sharp RDD centered on the policy date.
RDD_Sweden_Nuclear/
├── code/
│ ├── Sweden_RDD.Rmd # Main report with code, results, and text (knit to PDF)
│ ├── Sweden_RDD.R # Standalone R script version of the analysis
│ └── Extra_Sweden_RDD.R # Script to clean and transform raw data
│
├── data/
│ └── README.md # Instructions for downloading raw datasets from the source
│
├── output/
│ └── Sweden_RDD.pdf # Final PDF version of the report
│
├── LICENSE # MIT License governing reuse and distribution
└── README.md # Project overview and reproduction instructions
- Refer to
data/README.mdfor instructions on accessing the raw datasets from the ENTSO-E Transparency Platform. - Run
Extra_Sweden_RDD.Rto clean and merge the raw files. - Use
Sweden_RDD.Ror knitSweden_RDD.Rmdto reproduce the analysis and results.
This project uses R (version 4.0 or later) and the following R packages: rdrobust, rddensity, fixest, dplyr, ggplot2, lubridate, readr,tidyr
Looking back, a central issue was the assumption that the policy would have an immediate effect on nuclear electricity output. In reality, its impact is more plausibly felt through investment decisions, affecting capacity over the long run rather than short-run production. This weakens the case for using a regression discontinuity design, especially with time as the running variable. A difference-in-differences (DiD) approach, perhaps using a country like Finland as a control, would likely have been more appropriate. It would better match the policy’s timeline and help account for confounding seasonal and weather-related variation in electricity generation.
This project is released under the MIT License. See the LICENSE file for details.
Ibrahim Al Jahwari