On Thursday, August 3, at an event hosted jointly by WITA and the Asia Society Policy Institute, panelists looked at how Chinese companies, led by BYD, are making significant inroads into auto markets all around the world, including Europe with their low priced, high quality electric vehicles that have benefitted from Chinese government support. Discussants provided their perspective on what the rapid growth of the Chinese automotive industry mean for the global automotive market and trade policy, how governments should respond, and how environmental factors should be considered.

 

 

Michael Dunne, CEO, ZoZoGo, author of the upcoming book: Humiliation No More: China’s Master Plan to Dominate Electric Car Markets Worldwide

 

Brian Janovitz, Chief Counsel for China Trade Enforcement, Office of the U.S. Trade Representative

 

Jeffrey I. Kessler, Partner, WilmerHale, former Assistant Secretary for Enforcement and Compliance at the U.S. Department of Commerce

 

Hosuk Lee-Makiyama, Director, European Centre for International Political Economy (ECIPE)

 

Moderator: Wendy Cutler, Vice President and Managing Director, Asia Society Policy Institute (ASPI) Washington, D.C. Office

 

 

Subsidies to support electric vehicle purchases are a long-standing means of reducing carbon emissions. Since the 1990s, for example, the Norwegian government has actively encouraged the adoption of electric cars using tax exemptions and other measures, including permission to use HOV lanes, exemption from regional road tolls, access to half-price parking, and more.

 

Over the past two decades, the United States has pursued a similar—albeit less generous—approach. For example, the “qualified plug-in electric drive motor vehicle credit,” which resulted from legislation first established by the Energy Improvement and Extension Act of 2008, offers up to $7,500 in financial relief for going electric. Although the recently passed Inflation Reduction Act of 2022 has changed the qualification criteria for the credit (and changed the name of the program), the premise remains the same: if you go electric, Uncle Sam will support you.

 

It’s a nice idea. Electric cars are less polluting than gasoline autos. Less pollution means cleaner air, and cleaner air makes for a healthier planet. So why not use public funds to back EVs?

 

In a new study, the Breakthrough Institute’s Ashley Nunes, along with two co-authors, scrutinizes the economic efficiency of such subsidies. Emissions reductions are important, of course, but what matters even more (particularly as the national debt sits in the trillions of dollars), is how much these vehicles are driven and how often EV batteries must be replaced.

 

…As Congress debates whether EV subsidies should endure and, if so, for how long, Nunes’s study highlights the need to ensure these programs are targeted in ways that do the most good. His findings suggest that will mean moving away from universal subsidies for anyone interested in buying an EV and limiting subsidies to those who use EVs enough to realize the vehicle’s emissions advantage. Moreover, given that those who drive high utilization vehicles also have lower average incomes, offering EV subsidies as refunds, rather than nonrefundable tax credits, likely promotes greater EV adoption among the households that would maximize EVs’ emissions benefits.

 

 

When the European Commission in April 2021 proposed an AI Act to establish harmonised EU-wide harmonised rules for artificial intelligence, the draft law might have seemed appropriate for the state of the art. But it did not anticipate OpenAI’s release of the ChatGPT chatbot, which has demonstrated that AI can generate text at a level similar to what humans can achieve. ChatGPT is perhaps the best-known example of generative AI, which can be used to create texts, images, videos and other content.

 

Generative AI might hold enormous promise, but its risks have also been flagged up. These include (1) sophisticated disinformation (eg deep fakes or fake news) that could manipulate public opinion, (2) intentional exploitation of minorities and vulnerable groups, (3) historical and other biases in the data used to train generative AI models that replicate stereotypes and could lead to output such as hate speech, (4) encouraging the user to perform harmful or self-harming activities, (5) job losses in certain sectors where AI could replace humans, (6) ‘hallucinations’ or false replies, which generative AI can articulate very convincingly, (7) huge computing demands and high energy use, (8) misuse by organised crime or terrorist groups, and finally, (9) the use of copyrighted content as training data without payment of royalties.

 

To address those potential harms, it will be necessary to come to terms with the foundation models that underlie generative AI. Foundation models, or models through which machines learn from data, are typically trained on vast quantities of unlabelled data, from which they infer patterns without human supervision. This unsupervised learning enables foundation models to exhibit capabilities beyond those originally envisioned by their developers (often referred to as ‘emergent capabilities’).

 

The proposed AI Act (European Commission, 2021), which at time of writing is still to be finalised between the EU institutions, is a poor fit for foundation models. It is structured around the idea that each AI application can be allocated to a risk category based on its intended use. This structure largely reflects traditional EU product liability legislation, in which a product has a single, well-defined purpose. Foundation models however can easily be customised to a great many potential uses, each of which has its own risk characteristics.

 

It is sometimes repeated among economists and policymakers that the more economic dynamics are boring the better, as this would mean that the economy is stable and “in good health”. Sticking to the metaphor, we cannot help but observe that over the last few years the global economy has shown a significant worsening of its own conditions. Geopolitical fragmentation is not the cause of this, or at least not the only cause. However, overlapped with other exogenous negative shocks, it proved to have a strong role in intensifying the magnitude of impact on economic variables such as, for example, energy prices and consequently on inflation, even in its core component.

 

 

Political tensions were, indeed, always present in previous years. Besides their intensification, partly inevitable with the economic rise of China in the last decades, the main difference that marked a change with the past is that global economic stability was considered the primary common good, to which other political objectives should be subject to, while now it is clearly the opposite. In other words, geopolitical tensions are more likely to generate international economic consequences, which implies that geo-economics is a matter of renovated importance in a way that has been unusual probably since the end of Cold War. To give just an example, introducing limits to export with the Chips and Science Act, and discriminatory incentives on green technologies with the Inflation Reduction Act against WTO rules, the Biden administration has decided to go through commercial retorsions from other countries, economic tensions with such a strong partner as the EU, to affirm new primary objectives. These refer to the sphere of economic security, as clarified by the Secretary of the Treasury herself.

 

Such a change in priorities brings together some costs, those of the increased instability. It is worth to assume a long run perspective, and try to understand what these costs are, and who will pay for them. In order to do this, is useful to start considering how economic fragmentation was shaped. Most evident outcomes involved international trade, with a sharp increase in commercial restrictions, both inwards and outwards. These targeted mainly strategic goods such as energy sources and other critical raw materials, military and dual use goods and other technologically relevant products. As an anticipation of this open fight for technological supremacy, also vaccines had been somehow weaponized during Convid-19 pandemic. At the same time, firms started to consider a strong intensification of reshoring initiatives, also in their specific variants of nearshoring and friendshoring, in order to bring back production to safer of more convenient countries. Investments were thus indirectly affected, being gradually redirected, at first evidence mainly with a decrease from the USA (and less from advanced European countries) out of China, rather than in the opposite direction. As far as currencies are concerned, the weaponization of finance against Russia was expected to generate disaffection from the Western-dominated financial infrastructure and from the US dollar, as shown by the fact that China brought up the discussion on currencies in the BRICS context.

 

…Geoeconomic fragmentation is thus a real threat to globalized economy. For a few decades we have lived in the illusion that the economy could be immune or only partially affected by geopolitical tensions, partly induced by an economic theory identifying the economy just with the market. To some extent, this has proved to be true for a limited amount of time and in specific geographies. But as history can show it looks more like it was a phase than the norm. And the past can also teach that there is a concrete risk of a downward spiral, that should be avoided with more cooperation taking back the global economy as a priority in the world leaders’ agenda.