关键词: 政治风险, 动态溢出效应, 溢出指数模型, 金融危机, 恐怖袭击

Abstract: The continuous advancement of globalization has made the political and economic links between countries in the world increasingly close. Major risk events in one country are easily transmitted to other countries through direct or indirect channels. The global financial crisis in 2008, and the subsequent European debt crisis triggered turmoil in financial markets and political situations all over the world, giving a vivid example of the global linkage of political risks. In recent years, affected by the UK's “Brexit”, the China-US economic and trade friction, the COVID-19 epidemic and other events, the global political landscape has become more complicated, and geopolitical tensions have escalated and affected an increasingly wide range of areas. So how strongly does political risk spread across countries? Namely, to what extent can political risk in one country affect other countries? Answering this question is helpful to prevent or alleviate external political risks, as well as ensure the stable development of society and economy all over the world. The impact of political risk on macro- and micro-economic activity, as well as the cross-country spillover effects of variables related to political risk, has been extensively tested in previous research. However, no studies have directly verified the spillover effects of political risks among countries, and obtained the empirical results of transnational transmission of political risks. In this context, by using the spillover index method proposed by Diebold and Yilmaz in 2012 and 2014, the spillover relationship of political risks in 22 major global economies during July 1984 to August 2020 is calculated.
The research contributions of this paper mainly lie in the following three aspects. First, from the static and dynamic perspectives, this paper quantitatively calculates the overall and directional spillover indexes of political risks among 22 global economies, comprehensively captures the time-varying characteristics and correlation structure of spillover effects, so as to reveal the transnational transmission path of political risks. Second, this paper makes a detailed exploration of the peak period of the political risk spillover index, and analyzes the impact of major global economic and political events on the transnational transmission of political risk. Thirdly, taking China as the key object of investigation, this study makes an in-depth analysis of the outflow and inflow level of political risks between China and other 21 countries, and defines the spillover characteristics of political risks between China and major economies in the world, so as to provide policy suggestions for China to effectively prevent the negative impact of international political risks. The data used in this study is a monthly index of political risk in 22 major economies from July 1984 to August 2020. The 22 major economies are selected based on a combination of the list of G20 countries and the top 20 countries in terms of global GDP in 2018 and 2019, including 19 countries from the G20 and three countries that are not included in the G20 but among the top 20 countries in terms of GDP. Given that the International Country Risk Guide (ICRG) is the only institution that provides monthly assessment results of political risk, and uses the largest number of indicators to assess political risk, this study takes the political risk index by ICRG as a proxy variable of political risk. The index evaluates political risk from 12 aspects, with higher scores indicating less political risk for countries.
The research results mainly include the following four aspects. First, the average dynamic spillover effects of all countries are 45.16%, and the total dynamic spillover index is between 35.33% and 62.36%; Political risks show transnational contagion effect, and are transmitted through multiple direct and indirect correlations among countries such as politics, economy, society and culture. Second, the outflow index of political risk in each country has a larger fluctuation range than the inflow index, which again confirms the characteristics of transnational spillover of political risk; the outflow and inflow levels of developing countries are slightly higher than those of developed countries, indicating that developing countries in the stage of rapid development face more political uncertainties than developed countries; In addition, Saudi Arabia, Turkey and South Africa, among the major developing countries, show strong characteristics of spillover in both static and dynamic aspects, thus raising the overall spillover level of developing countries; Among developed countries, the spillover effects of political risk in Japan are highly volatile. Third, in general, China's political risk spillover effect is small, ranking low among all countries, with the fluctuation peak occurring after China's accession to the WTO and during the global crisis, indicating that China has a relatively stable political environment and strong ability to resist external interference; China shows larger net spillovers to developed countries than to developing countries. Lastly, Australia, India, and Japan have a strong two-way spillover relationship of political risk with China; South Africa is the main recipient of Chinese political risk spillover, while Switzerland, Argentina and Spain are the main sources of Chinese political risk spillover.

Key words: political risk, dynamic spillover effects, spillover index model, financial crisis, terrorist attack