Abstract
Despite the bourgeoning field of political economy and the substantial emphasis on the Kantian peace, there has been very little systematic research on the extent to which regions begin to lose their autonomy under extensive trade globalization. While trade has been a significant concern in monadic and dyadic studies of conflict and peace, it has not been studied in a similar manner at the regional level. In this chapter we explore (a) some of the reasons why this is the case; (b) suggest some empirical mechanisms through which obstacles to analysis can be overcome; and (c) trace the pattern of trade relations within regions and within the global trading system. We differentiate between degrees of trade integration within regions (intra-regional trade) versus regional dependence (loss of regional autonomy) on global trade patterns (extra-regional trade). We conclude with some consequences for peace and conflict within and between regions.
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Notes
- 1.
We measure trade as (exports + imports)/2.
- 2.
Including Belarus, Moldova, Serbia, Russian Federation, Georgia, Azerbaijan, Armenia, Kazakhstan, Kyrgyzstan, Uzbekistan, and Turkmenistan. We exclude those states that are members of the EU or if they had established a path to EU membership prior to 2020.
- 3.
As another point of comparison, Hungary’s exports, an EU member but with friendly relations with the Kremlin, had, by 2018, exceeded Ukrainian exports to Russia.
- 4.
As some have argued (Bell & Long, 2016; Copeland, 1996) when the expectation is that trade relations are on the decline, it may make the use of force more appealing to policymakers. This would be even more the case here since declining trade relations have been part and parcel of Russian paranoia about losing its sphere of influence in the “near-abroad”.
- 5.
- 6.
Including whether trade relations are asymmetrical, dependent or interdependent, and whether the focus should be on contiguous or major trading partners.
- 7.
For a few exceptions, see Lupu and Traag (2012) (who develop the concept of trading communities that appear to approximate regions), Kim and Shin (2002), and Allen (2018). Lee and Pyun (2016) also find that the effects of dyadic trade are most clearly felt when states are proximate, implying a regional context to trade relationships.
- 8.
The approach allows states and regions to vary over time. However, making intra-regional comparisons when regions and their membership change make such comparisons virtually impossible. We make two exceptions to reflect changing political circumstance. First, European states are kept at two classifications: Western Europe and “Eastern Europe”. The latter, along with the creation of a Central Asian region, has no valid data prior to the end of the Cold War. In the case of Central Asia, most of those states were part of the USSR. In the case of Eastern Europe, prior to the Cold War, either states were part of the USSR (the Baltics, Georgia, Armenia, etc.), part of the former Yugoslavia (Serbia), or lacked meaningful trade and GDP data (e.g., Poland, Czechoslovakia, Bulgaria). We designate East Europe to include all states that were part of the former Soviet Union and had neither formal application to NATO nor to the EU for membership as of 2020. The other “eastern” European states are then designated as part of Western Europe (e.g., Hungary, Poland, etc.).
- 9.
Available at https://wits.worldbank.org/countrystats.aspx?lang=en.
- 10.
We merged the Gleditsch data (1948–2000) with the World Bank WITS data (2001–2020). For the World Bank WITS data, we filled missing values in the imports/exports with the exports/imports reported by the counterparty where available. The Gleditsch data does not have any missing values. The correlation between the two data sets for years when we had overlap was approximately 0.97. Next, we aggregated the trade data into a “country-year” format to obtain the total trade amount of each country each year. We measure total trade amount as (gross imports + gross exports)/2. Finally, we added GDP figures (1960–2020) for all countries in current dollars using the World Bank database. Because the World Bank data does not include Taiwan, we added Taiwanese GDP data from the IMF database.
- 11.
Data on GDP are from the World Bank.
- 12.
The one exception is during the 1990s, during which German unification was taking place along with a gradual integration of former East European states with the European community.
- 13.
After apartheid, intra-regional and all trade as a percent of regional GDP in Southern Africa had doubled (Fig. 16).
- 14.
Our network-based community detection procedure for the 2010–2019 timeframe indicates that between them, the fifteen states of the region cluster with no fewer than eight different trading communities, suggesting that not only is intra-regional trade low, but likely are also indirect intra-regional trading partners outside of the region.
- 15.
The region includes the Russian Federation and its possible allies in East Europe and the Caucuses, consisting of states that were formerly part of the USSR, and as of 2020, are neither in the application process nor have been granted membership in either NATO or the European Union, including Ukraine.
- 16.
Although that trend reverses somewhat in during the 2010s.
- 17.
Following Kim and Shin (2002), we adjusted trade network ties for inflation and output growth, and then used only those ties having amounts greater than $10 million to calculate densities. For a given region, the regional density is defined as the ratio of the number of observed ties to the number of theoretically possible ties between regional members.
- 18.
To quantify the overlap, we identify for each geopolitical region subsets of countries belonging to the same trade community, and we measure the share of the biggest subset.
- 19.
The Western European case underscores another utility for the community detection measure: it can show how states newly integrated into a region are contributing to or detracting from its relative economic interdependence. In the Western European case, the detection measure shows that virtually all the Central European states that were previously in the East European region during the Cold War, or were not independent states (e.g., the Baltics, Slovakia, or the states emerging from the dissolution of Yugoslavia) but joined the Western European region after the Cold War, by 2016 cluster together with the rest of the dominant grou** for Western Europe.
- 20.
Under certain conditions it may be plausible to have more than one dominant power residing in the region, as is the case in Western Europe (the UK, France, and Germany), where the potential for conflict between them can erase intra-regional trade benefits for cooperation. What appears to be important, however, is that all the dominant powers in residence benefit substantially from intra-regional trade relationships.
- 21.
It is not our purpose here to treat trade as a dependent variable and to account for conditions likely to increase or deflate intra-regional trade.
- 22.
The table treats cooperation and conflict as two separate dimensions, based on the assumption that states (e.g., Peterson & Zeng, 2021), and especially states within the same region engage in both types of relationships simultaneously. As we note below, this appears to be the case both for East Asia and Eastern Europe.
- 23.
Available at https://transresearchconsortium.com/.
- 24.
Our analysis underscores a strong difference between dyadic versus region level approaches to studying the effects of trade on conflict and cooperation. While substantial numbers of dyads in international politics pass the threshold we suggest are necessary for their trade relationship to have a positive effect on cooperation, at the regional level only four of the fourteen regions appear to meet the first criterion of having high levels of intra-regional trade during the 2010s, and only three do so during the 2000s. Conducting inquiry at the regional level creates fewer cases and more research design complexity for analysts than a dyadic level of analysis of trade and its conflict/cooperation consequences. No wonder then that so little scholarship focuses on the regional level.
- 25.
We do not assume a linear relationship between trade and cooperation since we don’t expect incremental changes in trade relationships to yield similar changes in cooperation. Instead, we suggest that the most likely effects occur when a certain sufficiently high threshold value is crossed in the trade relationship, one which can create substantial costs for actions that may negatively impact trading partners.
- 26.
We assess “benefits” from intra-regional trade on the part of dominant powers residing in the region in terms of whether such dominant powers are engaged in intra-regional trade levels that are substantially below the norm of their region’s intra-regional trade. Substantially lower levels of intra-regional trade by the dominant power would suggest that for it, intra-regional trade is less consequential than for other members of the region.
- 27.
The correlation between a region’s intra-regional trade in one decade and its intra-regional trade in the previous decade is 0.95.
- 28.
Nevertheless, the longitudinal data for East Europe further underscore the possibility that the dramatic decline in the region’s intra-regional trade may have contributed to the hostilities between Russia and Ukraine, both in 2014 and 2022.
- 29.
For a similar approach but at the dyadic level of analysis, and using exports rather than exposure, see Mousseau (2019).
- 30.
This threshold is at half of the highest level of dependency exhibited in the figure by the Maghreb region.
- 31.
The correlation between level of global market dependence and regional wealth is −0.21.
- 32.
We smooth out annual fluctuations by averaging values across each decade for all substantive variables.
- 33.
The adjusted R squared value for the model, incorporating only three variables, is also quite high at 71%.
- 34.
- 35.
Note for instance that despite the intense rivalry between China and Taiwan, Taiwanese trade with China represents roughly 45% of its total trade (in 2021).
References
Aaron, A. (2022, June 20). Berlin is having second thoughts about its trade dependence on China. World Politics Review. https://www.worldpoliticsreview.com/articles/30622/berlin-reconsiders-merkel-s-approach-to-germany-china-relations
Allen, M. A. (2018). The influence of regional power distributions on interdependence. Journal of Conflict Resolution, 62(5), 1072–1099.
Associated Press. (2022, June 22). China hosts BRICS meeting amid rising economic concerns. https://www.staradvertiser.com/2022/06/22/breaking-news/china-hosts-brics-meeting-amid-rising-economic-concerns/
Aydin, A. (2008). Choosing sides: Economic interdependence and interstate disputes. Journal of Politics, 70(4), 1098–1108.
Bailey, M. A., Anton, S., & Voeten, E. (2015). Estimating dynamic state preferences from United Nations voting data. Journal of Conflict Resolution, 61(2), 430–456.
Barbieri, K. (2002). The liberal illusion: Does trade promote peace? University of Michigan Press.
Bell, S., & Long, A. G. (2016). Trade interdependence and the use of force: Do issues matter? International Interactions, 42(5), 750–773.
Bond, D., Bond, J., & Oh, C. (2003). Integrated data for events analysis (idea): An event typology for automated events data development. Journal of Peace Research, 40(6), 733–745.
Chen, F. R. (2021). Extended dependence: Trade, alliances, and peace. Journal of Politics, 83(1), 246–259.
Copeland, D. C. (1996). Economic interdependence and war: A theory of trade expectations. International Security, 20(1), 5–41.
Cornwell, D., & Colaresi, M. (2002). Holy trinities, rivalry termination, and conflict. International Interactions, 28(4), 325–353.
Dorussen, H., & Ward, H. (2010). Trade networks and the Kantian peace. Journal of Peace Research, 47(1), 29–42.
Gatzke, E., & Li, Q. (2003). War, peace, and the invisible hand: Positive political externalities of economic globalization. International Studies Quarterly, 47(4), 561–586.
Gartzke, E., Quan, L., & Boehmer, C. (2001). Investing in the peace: Economic interdependence and international conflict. International Organization, 55 (2), 391–438.
Gartzke, E., & Westerwinter, O. (2016). The complex structure of commercial peace contrasting trade interdependence, asymmetry, and multipolarity. Journal of Peace Research, 53(3), 325–343.
Gleditsch, K. S. (2002). Expanded trade and GDP data. Journal of Conflict Resolution, 46(5), 712–724.
Goldsmith, B. E. (2013). International trade and the onset and escalation of interstate conflict: More to fight About, or more reasons not to fight? Defence and Peace Economics, 24(6), 555–578.
Goldstein, J. S. (1992). A conflict-cooperation scale for WEIS events data. Journal of Conflict Resolution, 36(2), 369–385.
Haim, D. A. (2016). Alliance networks and trade: The effect of indirect political alliances on bilateral trade flow. Journal of Peace Research, 53(3), 472–490.
Hille, K. (2022, May 26). China builds coalition to counter America’s ‘barbaric and bloody’ leadership. Financial Times. https://www.ft.com/content/377cdb02-8a45-4ba2-b6ee-88620eb48f0b
Kim, S., & Shin, E.-H. (2002). A longitudinal analysis of globalization and regionalization in international trade. Social Forces, 81(2), 445–468.
Kinne, B. J. (2012). Multilateral trade and militarized conflict: Centrality, openness, and asymmetry in the global trade network. Journal of Politics, 74(1), 308–322.
Kleinberg, K. B., Robinson, G., & French, S. L. (2012). Trade concentration and interstate conflict. Journal of Politics, 74(2), 529–540.
Lake, D. A. (2007). Regional hierarchy: Authority and local international order. Review of International Studies, 35(1), 35–58.
Lee, H., & Rider, T. J. (2018). Evaluating the effects of trade on militarized behavior in the context of territorial threat. Foreign Policy Analysis, 14(1), 44–63.
Lee, J.-W., & Pyun, J. H. (2016). Does trade integration contribute to peace? Review of Development Economics, 20(1), 327–344.
Li, Q., & Reuveny, R. (2011). Does trade prevent or promote interstate conflict? Journal of Peace Research, 48(4), 437–453.
Lupu, Y., & Traag, V. A. (2012). Trading communities, the networked structure of international relations, and the Kantian peace. Journal of Conflict Resolution, 57(6), 1011–1042.
Morrow, J. D. (1999). How could trade affect conflict? Journal of Peace Research, 36(4), 481–489.
Mousseau, M. (2019). The end of war: How a robust marketplace and liberal hegemony Are leading to perpetual world peace. International Security, 44(1), 160–196.
Newman, M. E. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences, 103(23), 8577–8582.
Oneal, J. R., & Russett, B. M. (1997). Assessing the liberal peace with alternative specifications: Trade still reduces conflict. Journal of Peace Research, 36(3), 423–442.
Peterson, T. M., & Zeng, Y. (2021). Conflict and cooperation with trade partners. International Interactions, 47(2), 266–290.
Pevehouse, J. (2004). Interdependence theory and the measurement of international conflict. Journal of Politics, 66(1), 247–266.
Polachek, S., & **ang J. (2010). How opportunity costs decrease the probability of war in an incomplete information game. International Organization, 64(1), 133–144.
Rhamey, J. P. (2012). Constrained to cooperate: Domestic political capacity and regional order. PhD dissertation, University of Arizona. Accessed on ProQuest/UMI (Publication Number 3505997).
Rosecrance, R. N. (1986). The rise of the trading state: Commerce and conquest in the modern world. Basic Books, New York.
Sakuwa, K. (2018). Approaches to explaining regional conflict and peace. In W. R. Thompson (Ed.), The Oxford Encyclopedia of empirical international relations theory. Oxford University Press.
Shalal, A. (2022, June 26). G7 aims to raise $600 billion to counter China’s belt and road. Reuters. https://www.reuters.com/world/refile-us-aims-raise-200-bln-part-g7-rival-chinas-belt-road-2022-06-26/
Stopford, J., & Strange, S. (1991). Rival states, rival firms: Competition for world market shares. Cambridge University Press.
The Economist. (2022a, January 8). African economies: When you are in a hole…how Africa can reduce its reliance on commodities. Economist, pp. 39–40.
The Economist. (2022b, July 9). Global infrastructure investment: building blocs. Economist, pp. 35–36.
The Economist. (2022c, May 26). Countering China in Africa. Economist. https://www.economist.com/special-report/2022/05/20/countering-china-in-africa
Thompson, W. R., Volgy, T. J., et al. (2022). Regions, power and conflict: Constrained capabilities, hierarchy, and rivalry. Springer.
Voeten, E. (2019). Data and analyses of voting in the UN General Assembly. In B. Reinalda (Ed.), Routledge handbook of international organization. New York: Routledge.
Volgy, T. J., Bezerra, P., Cramer, J., & Rhamey, J. P. (2017). The case for comparative regional analysis in international politics. International Studies Review, 19(3), 452–480.
Volgy, T. J., Gordell, K. M., Bezerra, P., & Rhamey, J. P. (2018). Conflict, regions, and regional hierarchies. In W. R. Thompson (Ed.), Oxford research encyclopedia of empirical international relations theory. Oxford University Press.
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Appendices
Appendix A: Regions and state membership
NORTH AMERICA | SOUTH AMERICA |
|---|---|
US | Argentina |
Canada | Bolivia |
Mexico | Brazil |
MAGHREB | Chile |
Algeria | Colombia |
Libya | Ecuador |
Morocco | Guyana |
Tunisia | Peru |
MIDDLE EAST | Uruguay |
Bahrain | Venezuela |
Egypt | EAST ASIA |
Iran | China |
Iraq | Japan |
Israel | South Korea |
Jordan | North Korea |
Kuwait | Mongolia |
Lebanon | Taiwan |
Oman | SOUTH ASIA |
Qatar | Afghanistan |
Saudi Arabia | Bangladesh |
Syria | Bhutan |
Turkey | India |
United Arab Emirates (UAE) | Maldives |
Yemen | Nepal |
Yemen | Pakistan Sri Lanka |
SOUTHEAST ASIA | CENTRAL ASIA (begins in 1992) |
Brunei | Kazakhstan |
Cambodia | Kyrgyzstan |
Indonesia | Uzbekistan |
Laos | Tajikistan |
Malaysia | Turkmenistan |
Myanmar | Western Europe additions (beginning 1992) |
Philippines | Albania |
Singapore | Bosnia |
Thailand | Bulgaria |
Vietnam | Croatia |
WESTERN EUROPE | Czech Republic (Chechia) |
Austria | Estonia |
Belgium | Hungary |
Cyprus | Latvia |
Denmark | Lithuania |
Finland | North Macedonia |
France | Montenegro |
Germany | Poland |
Greece | Romania |
Ireland | Serbia |
Iceland | Slovakia |
Italy | Slovenia |
Luxembourg | EAST EUROPE (Beginning 1992) |
Netherlands | Armenia |
Norway | Azerbaijan |
Portugal | Belarus |
Spain | Georgia |
Sweden | Moldova |
Switzerland | Ukraine |
United Kingdom | Russian Federation |
WEST AFRICA | SOUTHERN AFRICA |
Benin | Angola |
Burkina Faso | Botswana |
Cameroon | Lesotho |
Cape Verde | Mozambique |
Cote D’Ivoire | Namibia |
Gambia | South Africa |
Ghana | Swaziland (Eswatini) |
Guinea | Zambia |
Guinea-Bissau | Zimbabwe |
Liberia | CENTRAL AFRICA |
Mali | Burundi |
Niger | Central African Republic |
Nigeria | Democratic Republic of the Congo |
Senegal | Republic of Congo |
Sierra Leone | Rwanda |
Togo | Chad |
EAST AFRICA | |
Djibuti | |
Eritrea | |
Ethiopia | |
Kenya | |
South Sudan | |
Somalia | |
Sudan | |
Tanzania | |
Uganda |
Appendix B: Intra-regional and global trade patterns by regions, 1960s–2010s
See Figs. 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, and 22.
W. Europe, intra-regional trade/all trade, all trade/region GDP, in percentages, 1960–2020
North America, intra-REGIONAL trade/all trade, and all trade/GDP, in percentages, 1960–2020
SE Asia, intra-regional trade/all trade, all trade/GDP, in percentages, 1960–2019
East Asia, intra-regional trade/all trade, all trade/GDP, in percentages, 1960–2019
East Africa, intra-regional trade/all trade, all trade/region GDP, 1970–2019
Central Africa, intra-regional trade/all trade, all trade/region GDP, 1970–2019
West Africa, intra-regional trade/all trade, all trade/region GDP, in Percentages, 1970–2019
Southern Africa, intra-regional trade/all trade, all trade/region GDP, in Percentages, 1970–2020
Maghreb, intra-regional trade/all trade, all trade/region GDP, in percentages, 1960–2020
Middle East, intra-regional trade/all trade, all trade/region GDP, in percentages, 1960–2020
South Asia, intra-regional trade/all trade, all trade/GDP in percentages, 1960–2019
Central Asia, intra-regional trade/all trade, all trade/GDP in percentages, 1990s-2019
“Eastern Europe”, intra-regional trade/all trade, all trade/GDP, in percentages, 1990s-2019
South America, intra-regional trade/all trade and all trade/GDP in percentages, 1960–2019
Appendix C: Density of intra-regional network, 1986, 1996, 2006, and 2016
Year | 1986 | 1996 | 2006 | 2016 |
|---|---|---|---|---|
North America | 1.000 | 1.000 | 1.000 | 1.000 |
South America | 0.591 | 0.645 | 0.673 | 0.673 |
Maghreb | 0.667 | 0.833 | 0.833 | 0.667 |
Middle East | 0.562 | 0.486 | 0.667 | 0.667 |
East Asia | 0.600 | 0.667 | 0.533 | 0.467 |
South Asia | 0.286 | 0.286 | 0.375 | 0.429 |
Southeast Asia | 0.400 | 0.533 | 0.689 | 0.689 |
Central Asia | – | 0.750 | 0.500 | 0.500 |
Western Europe | 0.434 | 0.635 | 0.784 | 0.760 |
Eastern Europe | – | 0.619 | 0.667 | 0.667 |
West Africa | 0.142 | 0.138 | 0.163 | 0.138 |
Southern Africa | 0.139 | 0.194 | 0.333 | 0.347 |
Central Africa | – | – | 0.033 | 0.067 |
East Africa | 0.143 | 0.250 | 0.196 | 0.196 |
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Yoon, E., Volgy, T.J. (2023). Intra-Regional Trade and Regional Exposure to the Global Economy: Implications for Cooperation and Conflict. In: Thompson, W.R., Volgy, T.J. (eds) Turmoil and Order in Regional International Politics. Evidence-Based Approaches to Peace and Conflict Studies, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-99-0557-7_9
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