Vegetation cover mitigates the economic impacts of warming

# Data and Code for the Publication "Vegetation cover mitigates the economic impacts of warming" ## Structure - Base folder `/` includes the main Stata `.do` file to replicate all regression tables and a Python script for figure generation.- File `base_pnas2.dta` contains the cleaned panel dataset used for all estimations.- File `Vegetation_code_finalf.do` is the Stata script that reproduces all tables (Table 1 and Supplementary Tables S1 to S5).- File `matrices2.xlsx` provides the basis for calculating marginal effects, including vegetation and temperature interaction terms.- Figures (`ME_FIG2.png`, `NDVI_MEs_mapped2.png`) are generated using the Python script. ## 1) Replication of Results - Open Stata.- Run the file `Vegetation_code_finalf.do` to reproduce: - Main Table 1 (baseline specification), - Robustness checks (Table S1), - Alternative standard errors (Table S2), - Extreme heat specifications (Table S3), - Alternative vegetation measures (Table S4), - Heterogeneous effects by vegetation types (Tables S5A–S5C). ## 2) Marginal Effects and Visualizations - Open Python (preferably in a Jupyter environment).- Use the Excel file `matrices2.xlsx` to extract interaction coefficients and standard errors.- The marginal effects and plotting of conditional effects are handled in a separate Python script. ## 3) Figures - `ME_FIG2.png` shows the main marginal effect of temperature conditional on vegetation.- `NDVI_MEs_mapped2.png` maps the spatial heterogeneity of marginal effects using NDVI and temperature coefficients.