The Impact of Geopolitical Risk on Trade Costs

ABSTRACT

This paper investigates the impact of geopolitical risk on trade costs across 43 countries from 1995 to 2019. The results show that geopolitical risk enters trade costs regressions positively and significantly. These findings are robust to the consideration of the different sub-periods, the sub-samples ex US and countries with the highest geopolitical risk, more control variables, the alternative estimation method, and the endogeneity issue. Given the importance of trade costs for welfare gains from trade, our results suggest a potential role for policy reforms that aim to reduce the geopolitical risk across the countries.

KEYWORDS:

• Geopolitical risk
• trade costs
• international trade
• trade welfare gains
• country-level risk‌

JEL CODES:

• F10
• F14

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 The sample countries include Argentina, Australia, Belgium, Brazil, Canada, Switzerland, Chile, China, Colombia, Germany, Denmark, Egypt, Spain, Finland, France, United Kingdom, Hong Kong, Hungary, Indonesia, India, Israel, Italy, Japan, South Korea, Mexico, Malaysia, Netherlands, Norway, Peru, Philippines, Poland, Portugal, Russia, Saudi Arabia, South Africa, Sweden, Thailand, Tunisia, Turkey, Taiwan, Ukraine, United States, and Venezuela.

2 The time series graph of the geopolitical risk for each selected countries can be found in the webpage of Caldara and Iacoviello (2022): https://www.matteoiacoviello.com/gpr_country.htm.

3 In the dataset, the value of trade costs is provided in ad valorem equivalent form. For example, the ad valorem equivalent trade costs of country A-country B for manufacturing goods in 2005 is 40%. It suggests that trading manufacturing goods between country A and country B involve additional costs amounting to approximately 40% of the value of goods as compared to when the two countries trade these goods within their borders.

4 We use the boxplots to show the distributions of total trade costs, trade costs of agricultural goods, and manufactured goods in our sample from 1995 to 2019. The details are reported in Figure A1 of Appendix 3.

5 It is important to note that the data on the regional trade agreement change across years. For example, the regional trade agreement dummy variable takes one after the trading country pair starts a regional trade agreement, while the regional trade agreement dummy variable takes zero before starting a regional trade agreement.

6 Our reduced-form empirical model is based on the gravity equation framework summarised in Head and Mayer (2014). We use the gravity equation for the following reasons. Firstly, the gravity equation has served as the workhorse model in empirical trade due to its intuitive appeal and empirical success. A large literature employs the gravity equation to quantify the effects of various policies on international trade. Secondly, due to its solid theoretical foundations, the gravity equation could guide our estimation approach and enable us to perform different sector analysis in trade costs.

7 This aggregation approach has already been used in the literature (see, for instance, Hou, Wang, and Xue 2021).

8 For modelling trade frictions in the gravity model, we refer the reader to Anderson and Van Wincoop (2004).

9 In terms of a potential nonlinear relationship between geopolitical risk and trade costs, we take the log form of geopolitical risk and run the regressions again. We find that the log form of geopolitical risk has a significant and positive relationship with trade costs. The results are consistent to our previous main findings. The results from this additional analysis are available upon request.

10 Compared with EPU index, the geopolitical risk index captures the events that could give rise to heighten financial volatility and policy uncertainty. More details are seen in Caldara and Iacoviello (2022).

11 The detailed introduction of Economic Policy Uncertainty index (EPU) would be found in: https://www.policyuncertainty.com/. The introduction of World Uncertainty Index (WUI) and World Trade Uncertainty Index (WTU) would be found in: https://worlduncertaintyindex.com/.

Additional information

Funding

We gratefully acknowledge the financial support from the National Natural Science Foundation of China [grant number 71971133], the Philosophy and Social Science Foundation of Shanghai [grant number 2023BGJ008] and the Fundamental Research Funds for the Central Universities.