Since the monthly counting of the Geopolitical Risk Index (GPR) started in 1985, the index peaked in ************, immediately after the 9/11 terrorist attack on the World Trade Center and Pentagon in the United States. The attack is perceived to be the deadliest terrorist attack in the 20th and 21st century, and ultimately caused the start of the so-called war on terror, with U.S. invasions of Afghanistan (2001) and Iraq (2003) following in the aftermath. Russia-Ukraine war The GPR was also high in ********** following Russia's invasion of Ukraine at the end of February that year. The attack on an independent state meant that the relations between Russia and the West reached a new low after the collapse of the Soviet Union, and several sanctions were imposed on Russia. 1991: a turbulent year Apart from the 9/11 attacks in 2001, the index reached its highest level in ************. This was a result of the ongoing Gulf War following Iraq's invasion of Kuwait, but also Soviet troops storming the Lithuanian capital in order to stop the country's secession from the Soviet Union. Additionally, a massacre of Tutsi in Rwanda highlighted the growing tensions in the East African country, which ultimately resulted in the genocide in 1994.

Key information about Australia Geopolitical Risk Index

• Australia Geopolitical Risk Index was reported at 0.165 % in Feb 2025.
• This records an increase from the previous number of 0.082 % for Jan 2025.
• Australia Geopolitical Risk Index data is updated monthly, averaging 0.069 % from Jan 1985 to Feb 2025, with 482 observations.
• The data reached an all-time high of 0.515 % in Mar 2022 and a record low of 0.005 % in Feb 1989.
• Australia Geopolitical Risk Index data remains active status in CEIC and is reported by Dario Caldara and Matteo Iacoviello.
• The data is categorized under World Trend Plus’s Geopolitical Risk Index – Table: Geopolitical Risk Index: By Country.

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

Key information about Argentina Geopolitical Risk Index

• Argentina Geopolitical Risk Index was reported at 0.045 % in Feb 2025.
• This records an increase from the previous number of 0.031 % for Jan 2025.
• Argentina Geopolitical Risk Index data is updated monthly, averaging 0.025 % from Jan 1985 to Feb 2025, with 482 observations.
• The data reached an all-time high of 0.263 % in Nov 2018 and a record low of 0.000 % in Sep 2021.
• Argentina Geopolitical Risk Index data remains active status in CEIC and is reported by Dario Caldara and Matteo Iacoviello.
• The data is categorized under World Trend Plus’s Geopolitical Risk Index – Table: Geopolitical Risk Index: By Country.

The Compass Series of Indexes is comprised of three unique and complementary Indexes that gauge the extent of global political, macroeconomic, and geopolitical risk: A Military Conflict Risk Index in five key geopolitical conflict regions, a Cold War Two Index in Russia, the US, and China, and a Polarization Risk Index in the G7 economies. Collectively, they provide investors, policymakers, and other decision makers with otherwise unavailable and comprehensive datafeeds that allow them to confirm and refute hypotheses and confidently navigate these risks.

The Cold War Index The Cold War II Index tracks – in Russia, the US, and China – six public sentiment indicators related to the geopolitical conflict and five current and future economic conditions indicators. The Index runs 24/7 and, unlike typical polls in these countries, draws on broad-based, anonymous, non-incented opinion.

The Military Conflict Risk Index The Military Conflict Risk Index measures, on a continuous, real-time basis, the perceptions of military conflict intensification from citizens in five major geopolitical conflicts: Russia-Ukraine, China-Taiwan, India-Pakistan, Iran-Israel, and South Korea-North Korea.

The Polarization Risk Index The Polarization Risk Index measures, on a quarterly basis, polarization within each G7 country as a key indicator of political stability. The Index uniquely draws on broad-based, anonymous opinion, minimizing biases associated with conventional polling.

As of Winter 2019 to 2020. the exchange transfer and trade sanction risk score of Iran was at ** ranking it as very high risk. The overall evaluation of the political risk situation of Iran was rated at ** on the PRI index, which is considered to be high.

United States Retail Sales Nowcast: sa: YoY: Contribution: Business Cycle Indicators: Geopolitical Risk Index data was reported at 0.195 % in 12 May 2025. This stayed constant from the previous number of 0.195 % for 05 May 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: Business Cycle Indicators: Geopolitical Risk Index data is updated weekly, averaging 0.015 % from Feb 2020 (Median) to 12 May 2025, with 274 observations. The data reached an all-time high of 5.703 % in 17 Apr 2023 and a record low of 0.000 % in 14 Apr 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: Business Cycle Indicators: Geopolitical Risk Index data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Retail Sales.

To facilitate a comprehensive analysis of the spatial settings of geopolitical risk, we have developed an evaluation index system for geopolitical risk, grounded in the multi-scale risk perception framework. Using this system of evaluation indicators, we calculated the geopolitical risk for nine countries in Southeast Asia for the period 2013-2021. The dataset contains sources and raw data for the relevant indicators.

Increasing geopolitical tensions and conflicts can cause disruptions for business operations. So, how do firms perceive geopolitical risk? The risk can differ between firms, but measurements focus primarily on the macro-level. Therefore, we introduce a new index to measure risk perceptions on the firm-level that we apply to Belgian public firms. To construct the index, we use a text-based content analysis method with a tailored dictionary. We use the index to examine whether geopolitical risk differs between firms and sectors, what the drivers of the risk are in high firms that experience high risk, and how the risk evolves over time. The study contributes to both the economic and security literature by introducing a new index and by creating and exploring new data on Belgian public firms. In addition, the index could become a helpful tool for policy makers that want to finetune their decisions on economic and security policy.

United States Unemployment Rate Nowcast: sa: Contribution: Business Cycle Indicator: Geopolitical Risk Index data was reported at 0.000 % in 12 May 2025. This stayed constant from the previous number of 0.000 % for 05 May 2025. United States Unemployment Rate Nowcast: sa: Contribution: Business Cycle Indicator: Geopolitical Risk Index data is updated weekly, averaging 0.047 % from Jan 2020 (Median) to 12 May 2025, with 279 observations. The data reached an all-time high of 12.178 % in 06 Jan 2025 and a record low of 0.000 % in 12 May 2025. United States Unemployment Rate Nowcast: sa: Contribution: Business Cycle Indicator: Geopolitical Risk Index data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Unemployment Rate.

Energy storage technology as a key support technology for China’s new energy development, the demand for critical metal minerals such as lithium, cobalt, and nickel is growing rapidly. However, these minerals have high external dependence and concentrated import sources, increasing the supply risk caused by geopolitics. It is necessary to evaluate the supply risks of critical metal minerals caused by geopolitics to provide a basis for the high-quality development of energy storage technology in China. Based on geopolitical data of eight countries from 2012 to 2020, the evaluation indicators such as geopolitical stability, supply concentration, bilateral institutional relationship, and country risk index were selected to analyze the supply risk of three critical metal minerals, and TOPSIS was applied to construct an evaluation model for the supply risk of critical metal minerals of lithium, cobalt, and nickel in China. The results show that from 2012 to 2017, the security index of cobalt and lithium resources is between .6 and .8, which is in a relatively safe state, while the security index of nickel resources is .2–.4, which is in an unsafe state. From 2017 to 2020, lithium resources remain relatively safe, and the security index of nickel has also risen to between .6 and .7, which is generally in a relatively safe state. However, the security index of cobalt has dropped to .2, which is in an unsafe or extremely unsafe state. Therefore, China needs to pay attention to the safe supply of cobalt resources and formulate relevant strategies to support the large-scale development of energy storage technology.

NARDL estimation results for the effect of domestic (country-specific) GPR and US GPR on stock market returns and volatility.

Graph and download economic data for Economic Policy Uncertainty Index for United States (USEPUINDXD) from 1985-01-01 to 2025-07-10 about uncertainty, academic data, indexes, and USA.

Graph and download economic data for Global Economic Policy Uncertainty Index: Current Price Adjusted GDP (GEPUCURRENT) from Jan 1997 to Apr 2025 about uncertainty, adjusted, GDP, indexes, and price.

The average for 2023 based on 193 countries was -0.07 points. The highest value was in Liechtenstein: 1.61 points and the lowest value was in Syria: -2.75 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

This paper examines the effects of three distinct groups of uncertainties on market return and volatility in the Asia-Pacific countries, including (i) the country-specific and US geopolitical risks; (ii) the US economic policy uncertainty; and (iii) the US stock market volatility (using the VIX and SKEW indices). Our sample includes 11 Asia-Pacific countries for the 1985–2022 period. We employ the nonlinear autoregressive distributed lag approach (ARDL) estimation technique to capture the asymmetric effects of uncertainties on market return and volatility, which are documented in the literature. Some findings are documented as follows. First, we find that US uncertainty indices, including US geopolitical risk, US economic policy uncertainty, and US VIX, significantly impact Asia-Pacific stock markets, while the impacts of domestic geopolitical risk and the US skewness index (SKEW) are relatively weak. Second, Asia-Pacific stock markets tend to overreact to uncertainty shocks stemming from US economic policy uncertainty and US geopolitical risk. Third, US economic policy uncertainty has more significant effects than the US geopolitical risk. Finally, our research documents that Asia-Pacific stock markets react heterogeneously to good and bad news from US VIX. Specifically, an increase in US VIX (bad news) has a stronger impact than a decrease in US VIX (good news). Policy implications have emerged based on the findings of this study.

This study examines the association between home countries’ economic policy uncertainty (EPU) and foreign direct investment (FDI) inflows into Vietnam. Using data from 12 home countries from 2011 to 2022, we find that higher EPU significantly leads to lower FDI inflows into Vietnam. Also, we investigate how social connections between home countries and Vietnam, measured by the Social Connectedness Index, moderate the EPU - FDI relationship. Our findings show that social connectedness mitigate the negative impact of EPU on FDI by reducing information friction and enhancing trust in uncertain policy environments. These results are robust for home countries that experience periods of high global uncertainty and geopolitical risk, and are members of APEC.

The Budapest SE index is predicted to rise in the near term, with potential risks stemming from global economic uncertainty, geopolitical tensions, and domestic political developments. While the index has the potential for significant growth, it is important to be aware of these risks and consider appropriate investment strategies accordingly.

A list of the variables and their respective source of data collection.

Predictions for the SMI index remain uncertain. While bullish indicators such as strong earnings and positive investor sentiment suggest potential for further gains, concerns over economic headwinds, geopolitical risks, and rising interest rates pose significant downside risks. It is important to note that investing in the SMI index carries the risk of capital loss, and investors should carefully consider their financial situation and investment goals before making any investment decisions.