Applied Data, Data Analysis, Financial Services Analytics

Data Science and Trade Wars

Data science and machine learning can also apply to the world of geopolitics. With respect to the current imbroglio between US and Chinese trade negotiators, there are two systemic issues that must be recognized. The first, (as pointed out by China watchers such as Nicholas Lardy and Elizabeth Economy) is that Xi Jingping has no intention of relaxing the CCP’s control of the Chinese economy and the associated structural controls. The second, and perhaps the only one the US can influence, is negotiation posture and approach.

With respect to approach, the trend analysis is quite clear in that the US insistence of taking a bilateral approach, is not yielding significant results. One only has to map US administration position statements to Chinese activity (or in this case, inactivity) to realize a one-on-one approach is ineffective. By studying past Chinese policy moves, one notices that any semblance of structural reform only occurs if the Chinese believe a substantial bloc of countries is allied against it. In this case, the US (read, Donald Trump) decision to forego presenting a unified front with both the Europeans and Japanese is proving to be counter-productive. The policy of further alienating allies with other tariff threats (e.g., automobile and steel) and criticizing multilateral approaches such as the WTO is also a major drag on negotiation efficacy.

In deference to the US administration’s criticism of the WTO, we should note that the Chinese have been able to circumvent it in some cases. However, I would point out that by refusing to acknowledge and use enforcement mechanisms such as “targeted sanctions” instead of tariffs and WTO’s appellate branch, the current approach further reduces the chance any substantive change in Chinese policy–again this is born out by a data science approach towards trade data .  As for the existing tariffs, (i.e., taxes on American consumers), any negative impacts on the Chinese will be short lived. One does not need to be a Nobel Prize winning economist to understand the negative knock on effects of tariffs for all parties concerned and measures taken to circumvent them. The Chinese will adjust, supply chains will be adapted, and soya will be sourced from South America.

To conclude on a somewhat positive note, all may not be lost for proponents of a liberal economic order. Despite the fallacies of tariff effectiveness and “trade wars being easy to win”, the current strife between China and the United States is considered a negative mark for Xi Jingping within China. There are senior members within the CCP who are not pleased with Xi’s power grab and are critical (albeit very cautiously) of his approach in managing the US relationship. While we may not be able to exert behavior-changing pressure on the Chinese in the short term, change may end up occurring in the medium to long term through internal Chinese political dynamics. In the meantime, the best approach for the West (US, South America and Europe) and East Asia (e.g., Japan and South Korea) is a unified approach through WTO enforcement mechanisms. Full stop.


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About Michael Armao

Michael Armao is the founder and CEO of Verstand AI and brings over 20 years of IT and data architecture experience to the firm. Having spent over a decade working in Homeland Security and the Intelligence Community, Michael now dedicates himself to building and executing the commercial decision science and product engineering vision of the company.

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