I am not taking the second half of the course this fall, but will likely continue with SNA in this field through next Winter.
The Indo-Pacific Rim encompasses the vast coastlines of Western North and South America as well as India and Eastern Asia and Australia. This region represents approximately half of global trade [extrapolated from TPP and Asia-Pacific Data[i]], and acts as the highway for much of the world’s energy needs that emanate from the Middle East and move through the Indian Ocean. While the region has always had particular significance due to the confluence of spheres of influence, cultures, state powers, and international actors, the recent rise of Chinese power has greatly shifted the dynamics of trade and political-militaristic heft. Not merely from a geopolitical standpoint, though, the Chinese surge has increased the economic needs of this region as well, which will have major impacts around the world.
Background:
In recent years, numerous attempts have been made to consolidate Indo-Pacific trade and power into a single relationship. The US has entered into the QUAD[ii]talks, twice, to partner with Japan, Australia, and India for military exercises. The US also spearheaded and then famously backed out of the TPP- though the TPP-11 is still in force. Similarly, China’s One Belt One Road and String of Pearls initiatives have gained significant attention on the world stage. Presently, the US-China ‘trade-war’ dominates most headlines.
While all of this coverage speaks to the importance of the region, I have not found it to be predictive in its approach. This begs key questions about correlation and causation with respect to the conditions at play in this region. This study seeks to uncover what if any relationships can be identified according to goods traded that may help the region to avoid future conflicts.
Research Questions:
How does trade factor in the diplomatic relationships of the Indo-Pacific Rim?
Does it outweigh rhetoric? Does it dictate relations? Does it correlate? If so, how?
How do ‘hot’ countries correlate with each other?
Data Collection:
Data collection for this study should be relatively simple to obtain, the difficult part will be trimming it into useful categories. The World Trade Organization[iii], Census Bureau[iv],and other pubic repositories of trade information such as the WorldBank[v] or USEIA[vi]house most of the trade data required for this study. For example, the latter offers downloadable Excel formats of US oil exports and imports by country and year. I would need to adjust numbers for ‘energy’ rather than simply ‘oil’ according to a rubric to be determined based on availability of clean numbers. Similarly, it will make sense to separate Cars from Car Parts, which though similar are produced at different locations. Those data that are not readily available can be researched and converted into readable UciNet formats manually as necessary. Attribute demographic data is readily available per country.
Network Measures:
This study fundamentally assesses the extent to which goods being traded in the Indo-Pacific Rim correlate to the broader issues that affect the region. Like the W2W project, I will use different cuts at two data sets to flesh out a solution. The baseline data set will represent trade relationships among the following Pacific Rim players: USA, China, Hong Kong (separately), Russia, India, and the TPP-11 countries (former TPP, minus US). Those trade relationships will be within the confines of the most traded goods by volume in the Indo-Pacific market[vii]: Energy, Cars, Car Parts, Electronics, Textiles, Cotton, Food. This two-mode representation will be able to show directional relationships between states by good. From this we should be able to determine which goods are most sought after, by whom, and who supplies them. This baseline data set will provide initial indications about which countries are potentially over-leveraged. It may also offer insights into which countries supply others with the raw materials necessary to fuel their export industries or feed their people.
The first data set will then be bumped up against a geopolitical quantification of the same nations. This is the ‘heat index’ data that I will collect according to 2018 media data and state department intelligence, which will rank each nation’s attitude toward the other nations. For example, US rhetoric towards Canada could be considered hot (aggressive), whereas Canada’s toward the US may be ‘cool’ (not positive, but not aggressive). This will allow us to sort by ‘positive’ versus ‘aggressive’ international public relations, and see how those groups factionalize or align according to, for example, complementary trade goods (oil and auto) or dependent goods (cars and car parts).
Heat Index:
1 – Positive, 2 – Cool, 3 – Warm, 4 – Hot
I will also collect attribute data for each nation based on demographic data:
Dominant Religion:
1 – Christian, 2 – Islam, 3 – Buddhist, 4 – Hindu, 5 – Other, 6 - None
Political Structure:
1 – Democratic, 2 –Autocratic, 3 – Religious
Economic System:
1 – Capitalist, 2 – Communist, 3 - other
Military Strength
1 – Elite, 2 – Nuclear, 3 – Powerful, 4 – Arming, 5 – Weak
With this data collected and constructed, numerous hard-hitting relationships can be deduced. I would run E/I measures for goods to determine volume by country. I would also seek to understand what subgroups, factions, and eigenvector analyses could show us. For example, are ‘hot’ nations trade-isolates or are they highly connected, and what can we infer from that? Do trade subgroups also align according to religion or political system? Additional centrality measures such as betweenness may be able to identify key ‘bridge building’ or ‘hinge’ points (potentially Hong Kong, for example). The ultimate goal will be to uncover special relationships or nodes of overlapping relevance and then determine if they relate to diplomatic ties or fractures.
Hypothesis:
I expect that energy will be the commodity that correlates most closely to heat. India, China, and ASEAN are expected to represent two-thirds of the world’s 2040 increase in energy demand[viii]so understanding this relationship is fundamental to global security. I would also expect that trade relationships among complementary and dependent goods would be very high- so it will be interesting to see if this causally predicts positive diplomatic ties as well. Furthermore, it may be more likely that the supplier of the raw good has more capacity for aggressive dealings than the subsequent exporter of the finished good. We may also see clustering along the lines of political or religious systems.
I expect ‘heat’ to correlate highly with the military power attribute. This indicates that as a country matures militarily, heat, and perhaps trade, would also be affected in predictable ways. This would be significant as Russia, India, and perhaps Japan all sit poised for military growth in the coming century in response to China’s ramp up of its military. All of this will have rippling effects on the trade and security balance of the region.
Limits of Data:
This data set is large, if it proves too cumbersome the study can be conducted between smaller triads of nations to potentially develop relationships that can be extrapolated up (and proven in subsequent iterations). That said, any such study would include the following limitations:
1.) The heat index may have to draw from a longer time period than the trade 2017 trade numbers. This is because diplomatic relations are qualitative and not subject to blind quantification.
2.) This data treats the Pacific Rim as a closed system, which it is not. The study ignores the effects of One Belt, One Road as well as NAFTA-type Free Trade Agreements that some parties may be subject to.
3.) There are many other goods also traded, which are not considered. Ideally we would be able to represent the total bilateral trade relationship between each nation and each other nation, but that may be beyond the scope of this analysis.
4.) Tariffs – This study focuses simply on the exchange of goods. It does not factor in the highly combustible issue of tariffs. I try to account for this somewhat in the ‘heat’ index, but cannot pull it in directly. This could be accomplished with a one mode tariff array, indicating one of four relationships spanning mutually zero tariffs to mutually high tariffs by good.
5.) The study also leaves out East African, Middle-east, and some other Indo-Pacific players. The focus of the study is really on the growth of China and the potential conflicts it may have regionally, though I am aware these trade corridors are very far reaching.
Future Study:
As stated above, tariff data would provide the basis for a similar project that could be equally illuminating. Further questions arise naturally from a study of this sort: How have these developing relationships played into the current state of affairs? Are there year over year patterns and trends at work?
Also, should this research prove inconclusive, there would be further analysis on a more macro level. This could for example compare overall ‘trade’ compared to ‘investment activity’ and ‘Foreign Aid’ to determine which states are leveraged along those lines as well. The overall goal of these other studies would be the development of a scorecard by which to calibrate relations toward peaceful solutioning.
1 comment:
Interesting idea, though it needs a central Q to pull it together. How is SNA going to specifically fit into this? There was a discussion of the two-mode network relating states to goods, but at times it sounded more like a regression analysis. Would have liked to see more discussion around specific network and sub-group measures when contrasting baseline to heat map application.
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