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Geopolitical risk spillovers and its determinants

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Abstract

Geopolitical risk (GPR) tends to cascade from one country to another. Understanding GPR transmission is important to devising risk management strategies for institutional investors and corporate managers, and national security policies for governments. In this paper, we measure and explain cross-country transmission of GPR. Our sample covers 19 country-based GPR indexes of Caldara and Iacoviello (Measuring geopolitical risk, 2018) from January 1985 to December 2016. We apply the spillover model of Diebold and Yilmaz (Int J Forecast 28:57–66, 2012) to measure pairwise as well as system-wide GPR transmission. The estimation results show a substantial amount of GPR transmission across our sample countries, with certain countries and geographical clusters being more prominent than others. We then explain the pairwise GPR transmission using a cross-sectional regression motivated by a gravity model framework. We find that certain bilateral linkages such as bilateral trade and geographical proximity significantly explain the pairwise GPR transmission. This transmission is positively associated with both countries’ debt burdens and geographical sizes, transmitting country’s fiscal imbalance, and is negatively associated with recipient country’s economic size. The results imply that these factors may be used to predict the trajectory of GPR, which is an important input for the assessment of cross-border investment appraisals as well as international stability initiatives.

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Notes

  1. Instead of distinguishing between contagion, spillover, diffusion, and spread, we view GPR contagion as a transmission mechanism/process.

  2. See Global Risks Reports published in 2016, 2017, and 2018; World Economic Outlook, October 2017, and Economic Bulletin, March 2016, published by the World Economic Forum, International Monetary Fund, and European Central Bank, respectively. These reports highlight the growing importance of GPR and its transmission. See Suárez-de Vivero and Mateos (2017) for a good collection of such reports.

  3. Caldara and Iacoviello (2018) refer to two separate surveys, one conducted by Bank of England and another by Wells Fargo/Gallup in 2017, which highlight growing concerns among investors, managers, and policy makers about heightened GPR.

  4. For the USA, the Web site also contains other components of GPR index such as GPR_Threat, GPR_Act, GPR_Narrow, GPR_Broad, and GPR_Nuclearthreat. However, to ensure consistency in our analysis, we use the ‘benchmark’ GPR index for the US.

  5. According to Caldara and Iacoviello (2018), the following keywords are used to capturing six dimensions of GPR: Group 1 [(Geopolitical AND (risk* OR concern* OR tension* OR uncertaint*) “United States” AND tensions AND (military OR war OR geopolitical OR coup OR guerrilla OR warfare) AND (“Latin America" OR “Central America” OR “South America” OR Europe OR Africa OR “Middle East” OR “Far East” OR Asia)];

    Group 2 [(“nuclear war" OR “atomic war” OR “nuclear conflict" OR “atomic conflict" OR “nuclear missile*") AND (fear* OR threat* OR risk* OR peril* OR menace*)];

    Group 3 [“war risk*” OR “risk* of war” OR “fear of war" OR “war fear*” OR “military threat*” OR “war threat*” OR “threat of war” (“military action” OR “military operation” OR “military force”) AND (risk* OR threat*)];

    Group 4 [“terrorist threat*" OR “threat of terrorism” OR “terrorism menace” OR “menace of terrorism” OR “terrorist risk” OR “terror risk” OR “risk of terrorism” OR “terror threat*”];

    Group 5 [“beginning of the war” OR “outbreak of the war” OR “onset of the war” OR “escalation of the war” OR “start of the war” (war OR military) AND “air strike” (war OR battle) AND “heavy casualties”];

    Group 6 [“terrorist act” OR “terrorist acts”].

  6. In simple VAR framework, the results of variance decomposition and therefore spillovers are driven by Cholesky factor orthogonalization and are potentially order dependent. However, the spillover measures based on a generalized VAR framework, the results are not order dependent. For more details, see Koop et al. (1996) and Pesaran and Shin (1998).

  7. Some of these factors such as common language and geographical proximity were also suggested by the Emerging Risk Report (2016), produced by LLOYD’S, in their “framework for understanding the emergence and spread of civil unrest.”

  8. For the sake of grouping, we consider Turkey as part of Gulf region, because being a Muslim country it may be affected more by the GPRs of Israel and Saudi Arabia than other countries, except the USA, in the sample.

  9. Bilateral trade volume between Turkey and Venezuela increased by 500% in the last 6–7 years. It is because the initial level of bilateral trade was very low.

  10. Note that budget deficit, debt (central government debt), and market capitalization of each country have been measured as a percentage of gross domestic product (GDP) of the respective country. See Appendix A for variable description.

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Authors and Affiliations

  1. School of Economics and Finance, Massey University, Albany, Auckland, New Zealand

    Faruk Balli, Hatice Ozer Balli, Mudassar Hasan & Russell Gregory-Allen

  2. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Faruk Balli

  3. Lahore Business School, The University of Lahore, Lahore, 54000, Pakistan

    Mudassar Hasan

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Appendix A. Details of data and sources

Appendix A. Details of data and sources

Variable name

Definition

Source

Exports ij

Share of the total exports of origin country i to country j relative to the total exports of country i. It is averaged for the period between 1985 and 2016

OECD STAN Bilateral Trade Database

Imports ij

Share of the total imports of origin country i from country j relative to the total imports of country i. It is averaged for the period between 1985 and 2016

OECD STAN Bilateral Trade Database

Contiguous ij

A binary variable that takes 1 if origin country i and country j are sharing a border, and 0 otherwise

CEPII

Colony ij

A binary variable that takes 1 if origin country i has been a colony of country j, and 0 otherwise

CEPII

Common Colony ij

A binary variable that takes 1 if origin country i and country j have remained under the influence of same colonial power, and 0 otherwise

CEPII

Common Language ij

A binary variable that takes 1 if origin country i and country j share at least one common language, and 0 otherwise

CEPII

Distance ij

Physical distance (in kilometers) between origin country i and country j

CEPII

Budget Deficit i

Budget deficit (surplus) of country i as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Budget Deficit j

Budget deficit (surplus) of country j as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Debt i

Central government debt of country i as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Debt j

Central government debt of country j as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Area i

Geographical area (in squared kilometers) of country i. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Area j

Geographical area (in squared kilometers) of country j. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Market Capitalization i

Stock market capitalization of country i as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

Market Capitalization j

Stock market capitalization of country j as a percentage of its GDP. The figure is averaged for the period between 1985 and 2016

World Development Indicators (WDI)

DS ij

Directional mean spillover (in %) of GPR transmitted by origin country i to country j

These amounts are calculated by authors by applying the spillover model of Diebold and Yilmaz (2012) on 19 GPR series of Caldara and Iacoviello (2018). These series are available on http://www.policyuncertainty.com/

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Balli, F., Balli, H.O., Hasan, M. et al. Geopolitical risk spillovers and its determinants. Ann Reg Sci 68, 463–500 (2022). https://doi.org/10.1007/s00168-021-01081-y

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