OverviewThis archive contains the files to reproduce the results in "Measuring Geopolitical Risk" as well as any additional documentation referred in the paper. Each directory is self-contained. For each directory, download all the files in order to run the necessary scripts. Instructions are given in the README files.Updated data can be found on the geopolitical risk index webpage, which can be found at the following url: https://www.matteoiacoviello.com/gpr.htm For questions or comments, please contact iacoviel@gmail.comData Availability StatementAll the data used in this paper are provided in this repository, with the exception of the Compustat quarterly firm-level data, which can be downloaded from https://wrds-www.wharton.upenn.edu/pages/ with a registered account.Software used The codes here run and have been tested either on Stata/MP 16.0 (for *.do files), on Matlab R2019/A (for *.m files), on R Version 4.04 (for *.R files), and on Anaconda 3 (for *.py, *.ipynb files). Most codes run in seconds/minutes on a personal laptop with 16GB ram, with the exception of the R code to estimate disaster episodes, which takes about 2 days using the standard settings from the Nakamura et al (2013) paper (nIter = 50,000, nRuns = 40). Directory list and list of main input files - if any - in each directory1. Monthly Geopolitical Risk Data Used in the Paper (data_paper)See README.txt file in the directory for detailsdata_gpr_export.dta (Stata format)data_gpr_export.xls (Excel format)2. Replication of Section I: Tables 1-2, Figures 1-8, Appendix Tables A.3-A.6, and Appendix Figures A.1-A.4 and A.10-A.14 (figures_paper) (requires Stata)See README.txt in the directory for detailsinput file: run_figures_tables.do3. Replication of Section III : VAR Evidence - Figures 9-10 and Appendix Figures A.5-A.7 (var_results)(requires Matlab)See README.txt in the directory for detailsinput file: run_all.m4. Replication of Section IV : Country-Specific GPR and Disaster Probability and Quantile Regressions - Tables 3-4 (disaster_regressions)(requires Stata)See README.txt in the directory for detailsinput file: run_replication_country_gpr.do5. Replication of Section V : Firm-Specific Geopolitical Risk - Table 5, Figure 11, Appendix Table A.7, and Appendix Figure A.9 (firm_regressions)(requires Stata)See README.txt file in the directory for details.input file: run_replication_firm_shuffled.do(Note that replication of the results here requires downloading firm-level balance sheet data through Compustat/WRDS. See firm_documentation below for instructions on how to build the firm_level.dta file)6. Auxiliary Material (Section V): Construction of Industry-Specific Exposure to Geopolitical Risk - Appendix Figure A.8 (industry_regressions)(requires Stata)See README.txt file in the directory for details.input file: run_replication_industry.do7. Auxiliary Material: Documentation on how to Build the firm_level.dta file (firm_documentation)See README_BUILD.txt file in the directory for details.8. Auxiliary Material (Section II): Tabulations of Daily Narrative GPR Data from The New York Times (narrative_index)See README.txt file in the directory for details.9. Appendix: Details on the Construction of the Human GPR Index (human_index)See README.txt file in the directory for details.10. Appendix: Audit of Articles Belonging to the GPR Index Described in Appendix Table A.3 (audit_coded)See README.txt file in the directory for details.11. Appendix: Granger Causality Tests --- Appendix Table A.8 (granger_causality)(requires Stata)See README.txt file in the directory for details.input file: run_granger_test.do12. Appendix: Replication of Textual Analysis in Appendix Tables A.1 and A.2 (text_analysis)(requires Matlab, including text analytics toolbox, and Stata for generating the formatted tables in the appendix)See README.txt file in the directory for details.input files: run_find_grams_textanalytics.m and run_app_tables_1_2.do 13. Auxiliary Material: Estimation of the Country Disaster Events from 1900 through 2019 (disaster_estimation)(requires R)See README.txt file in the directory for details.14. Auxiliary Material: Stata File with Firm-Level Geopolitical Risk Data (firm_level_gpr)See README.txt file in the directory for details.15. Auxiliary Material: Search Queries for News-Based GPR Index (news_searches)See README.txt file in the directory

This file is a crosswalk between BoardEx (https://wrds-www.wharton.upenn.edu/pages/about/data-vendors/boardex) and the Database on Ideology, Money in Politics, and Elections (DIME) v3.1 (https://data.stanford.edu/dime). If you use the crosswalk, please cite: Steel, Reilly S. 2024. "The Political Transformation of Corporate America, 2001-2022." Columbia Law and Economics Working Paper No. 4974868. URL: https://ssrn.com/abstract=4974868. The construction of the crosswalk is described in greater detail in the above paper, especially in the Online Appendix. NB: The crosswalk posted here links to v3.1 of DIME. Adam Bonica recently updated DIME to v4.0, which contains different donor IDs. The crosswalk will not work with v4.0. A new version of the crosswalk that maps onto v4.0 is currently in progress and will be released once validated.