Data and Code for: Measuring Geopolitical Risk

Principal Investigator(s):  View help for Principal Investigator(s) Matteo Iacoviello, Board of Governors of the Federal Reserve System; Dario Caldara, Board of Governors of the Federal Reserve System

Version:  View help for Version V1

Name File Type Size Last Modified
  audit_coded 01/14/2022 10:43:AM
  data_paper 01/14/2022 02:33:PM
  disaster_estimation 01/14/2022 11:38:AM
  disaster_regressions 11/16/2021 01:58:PM
  figures_paper 01/25/2022 04:56:PM
  firm_documentation 01/14/2022 11:51:AM
  firm_level_gpr 11/18/2021 04:27:PM
  firm_level_searches 01/13/2022 07:03:PM
  firm_regressions 01/13/2022 06:30:PM
  granger_causality 11/16/2021 03:11:PM

Project Citation: 

Iacoviello, Matteo, and Caldara, Dario. Data and Code for: Measuring Geopolitical Risk. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-03-24. https://doi.org/10.3886/E154781V1

Project Description

Summary:  View help for Summary
Overview

This 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 [email protected]




Data Availability Statement

All 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 directory

1. Monthly Geopolitical Risk Data Used in the Paper (data_paper)

See README.txt file in the directory for details

data_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 details

input file: run_figures_tables.do

3. 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 details

input file: run_all.m

4. 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 details

input file: run_replication_country_gpr.do

5. 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.do


7. 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.do

12. 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 for details.

16. Auxiliary Material: Search Queries for Firm-Level GPR Index (firm_level_searches)

(requires Anaconda)

See README.txt file in the directory for details.






Scope of Project

Subject Terms:  View help for Subject Terms Geopolitical Risk; War; Terrorism; Business Cycles; Disaster Risk; Firm-level Investment; Textual Analysis; Earnings Calls; Quantile Regressions
JEL Classification:  View help for JEL Classification
      C10 Econometric and Statistical Methods and Methodology: General
      D80 Information, Knowledge, and Uncertainty: General
      E32 Business Fluctuations; Cycles
      H56 National Security and War
Geographic Coverage:  View help for Geographic Coverage United States and other countries
Universe:  View help for Universe United States, Advanced and Emerging Economies, Firms in the United States
Data Type(s):  View help for Data Type(s) aggregate data; text

Methodology

Data Source:  View help for Data Source Newspapers, Firms Earnings Calls
Collection Mode(s):  View help for Collection Mode(s) other
Unit(s) of Observation:  View help for Unit(s) of Observation month, day, quarter
Geographic Unit:  View help for Geographic Unit country

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Published Versions

V1 [2022-03-24]

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