ECON 687 — Replication Project

Paper: Mogstad, Romano, Shaikh, and Wilhelm. "Statistical Uncertainty in the Ranking of Journals and Universities." AEA Papers and Proceedings, Vol. 112, May 2022, pp. 626–631.

Authors: Jason Jankoski, Alan Lamb, Linna Wang

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Repository Structure

econ687-replication/
├── data/
│   ├── journal IF/        # Journal impact factor data (Stern, 2013)
│   └── Repec/             # University publication data (Zimmermann, 2013)
├── code/
│   └── 00_data_check.R    # Data diagnostic and proof-of-concept figures
├── output/                # Generated figures and tables (not tracked by Git)
├── report/                # Final report (R Markdown)
└── README.md

Getting Started

1. Clone this repository
2. Open econ687-replication.Rproj in RStudio
3. Set working directory to the repo root: Session > Set Working Directory > To Project Directory
4. Install required packages if needed (the script will prompt you):
   • ggplot2, dplyr, readxl, devtools
   • csranks from GitHub: devtools::install_github("danielwilhelm/R-CS-ranks")
5. Run code/00_data_check.R to confirm data loads and generate proof-of-concept figures

Data

Both datasets are included in this repository. No external data access is required.

• Journal IF data: data/journal IF/JEL_Data.xlsx — article-level citation counts for 232 economics journals (Stern, 2013)
• University data: data/Repec/top100unis.csv — average impact factors for 100 universities derived from RePEC (Zimmermann, 2013)

Requirements

• R 4.1.2 or later
• RTools (Windows users): https://cran.r-project.org/bin/windows/Rtools/
• Estimated runtime: ~12 minutes on a standard laptop