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| Main Authors: | , , |
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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15508836 |
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Table of Contents:
- <p># Data and Code for the Publication <br>**"Vegetation cover mitigates the economic impacts of warming"**</p> <p>## Repository Structure</p> <p>- **`Vegetation_code_finalmay25.do`** — Main Stata script to replicate all regression tables (main and supplementary).<br>- **`basevegetfin.dta`** — Cleaned panel dataset used for all estimations.<br>- **`matrices2 (1).xlsx`** — Excel file used to compute marginal effects and interaction terms (vegetation × temperature).<br>- **`ME_FIG2 (1).png`** and **`NDVI_MEs_mapped (3).png`** — Figures showing marginal effects and spatial heterogeneity, generated via Python.<br>- **`README_veget.md`** — Current README file.</p> <p>## 1) Replication of Results</p> <p>To replicate the paper’s results:</p> <p>**In Stata:**<br>- Open `Vegetation_code_finalmay25.do`<br>- This script reproduces:<br> - **Main Table 1** (baseline specification)<br> - **Table S1** – Robustness checks<br> - **Table S2** – Alternative standard errors<br> - **Table S3** – Extreme heat specifications<br> - **Table S4** – Alternative vegetation measures<br> - **Tables S5A–S5C** – Heterogeneous effects by vegetation types<br> - **Table S6** – Temporal variation in vegetation effectiveness</p> <p>## 2) Marginal Effects and Visualizations</p> <p>**In Python (Jupyter recommended):**<br>- Use `matrices2 (1).xlsx` to extract interaction coefficients and standard errors<br>- Plot marginal effects using your preferred script (not included here, but used for published figures)</p> <p>## 3) Figures</p> <p>- `ME_FIG2 (1).png` — Marginal effect of temperature conditional on vegetation levels<br>- `NDVI_MEs_mapped (3).png` — Map of spatial heterogeneity in marginal effects based on NDVI</p> <p> </p> <p> </p>