Abstract
The Biden administration's escalating restrictions on China's semiconductor industry signal a shift in the U.S.-China technological competition. These measures, including sanctions, export controls, and supply chain containment, aim to deny China access to advanced semiconductor technology and expertise. This turn towards weaponizing semiconductor dominance indicates national security now drives the contest beyond purely economic interests. The U.S. has moved from a defensive posture of containing China's rise to an offensive posture of imposing steep costs by cutting off its access to cutting-edge technology. Stackelberg game theory models demonstrate how the U.S. leverages its current advantages in semiconductors to force difficult tradeoffs on China. This stranglehold aims to hobble China's technological ambitions and preserve U.S. semiconductor leadership.
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Notes
Malkin and He [59].
Weinstein [97].
Department of Commerce Bureau of Industry and Security [25].
U.S.-China Economic and Security Review Commission [94].
Ming-Chin [64], p. 1.
U.S.-China Economic and Security Review Commission [94].
Şeymanur Yönt [80]. The US measures targeting China’s semiconductor industry: Another brick in the wall. TRTWorld research center, Istanbul, Turkey. November 3. https://researchcentre.trtworld.com/featured/the-us-measures-targeting-chinas-semiconductor-industry-another-brick-in-the-wall/
Blinken [13]; See Alex W. Palmer, An Act of War’: Inside America’s Silicon Blockade Against China. New York Times, July 27, 2023.
There is an interesting discussion to be had on whether this offensive strategy of the U.S. is necessary. Mearsheimer 20 would argue it is long overdue. Kirshner [55] would argue that to the extent it is shaped by Mearsheimer’s realist theory, it is on shaky foundations. From an offensive realist angle, Kim [54] argues it is misplaced. Also, see Jalil [45].
Fuller [35].
Wu [100].
On sequential games, see Breton et al. [14].
Blackwill and Harris [12].
Abdelal and Kirshner [1].
Wu [100].
Sullivan [83].
The use of Stackelberg game models has been influenced by the growing literature on Stackelberg security games. See Fiez, Chung, & Ratliff [34].
Wu [100].
Sullivan [83].
Sullivan [83].
Ibid.
Lucas Niewenhuis, “US Commerce Secretary: We must view the CHIPS Act ‘as a matter of national security’ to compete with China in semiconductors,” CNBC, August 10, 2022. https://www.cnbc.com/2022/08/10/us-commerce-secretary-gina-raimondo-talks-china-chips-and-ai.html
White House [98].
Sullivan [83].
Miller [63].
Triolo, Allison, and Lau, [89].
Miller [63].
The Semiconductor Industry Association [88].
Wasser & Rasser [96].
Brown and Singh [18].
Shivakumar and Wasser [81].
On the logic on how assets become strategic, see Ding and Dafoe [27].
Malkin, [60].
Source: U.S. Senate Committee on Foreign Relations Hearing, June 17, 2021. (Quote on page 47) https://www.foreign.senate.gov/imo/media/doc/061721_Full%20Committee%20Hearing%20Transcript.pdf
As Beaumier and Cartwright ([9]: 16) underscore in their study, the U.S. offensive strategy isn’t drive by China’s role in chipmaking because it remains modest.
Price Waterhouse and Cooper (PwC) [73].
Ibid.
Grimes and Du [40].
Majerowicz [61].
Lewis [56], p. 13.
Girard [39].
Culpan [24]
The Chips Act 2022. The Act merges two bipartisan bills: the Endless Frontier Act (S. 3832, [75]) and the CHIPS for America Act (S. 3933, [76]). The former was designed to increase investment in high-tech research crucial to US national security, while the latter aimed to bring semiconductor manufacturing back to the US. The Endless Frontier Act intended to turn $150 billion in government R&D funding into a $500 billion investment, with additional investments from the private sector and a coalition of technological allies. The CHIPS for America Act originated from the $12 billion onshoring of Taiwan Semiconductor Manufacturing Company (TSMC) to ensure a secure supply chain of sophisticated semiconductors. Both these bills were eventually combined into the U.S. Innovation and Competition Act (USICA) (S. 1260, [77]), which later resulted in the bipartisan CHIPS and Science Act (Peters, [72]).
Johnson [47].
Department of State [26].
Allen [5].
Commerce Department's Bureau of Industry and Security notice on expanded controls on semiconductor exports to China. Executive Order 14064—Administration of Proliferation Sanctions and Amendment of Executive Order 12851 (2021). Another source, BIS Expands Controls on Exports of Widely Used Semiconductors and Other Technologies to the People’s Republic of China (PRC) (2022).
See Breton et al. [14].
Ding and Dafoe [27], page 183.
For more on representing costs via functional forms in game theory see Gibbons, R. (1992). Game Theory for Applied Economists. Princeton University Press.
On modeling strategic interactions as continuous vs discrete see Clemhout, S. & Wan, H.Y. (1974). The decision to model the US export control strategy as a continuous variable S versus a discrete binary signal of "lenient" or "strict" controls simplifies the strategic interaction into a linear sequential game. However, strategic interactions between nations often involve more complex dynamics with a wider range of graduated actions. Modeling the strategy set as continuous rather than discrete allows incorporating these nuances and better capturing the fluid nature of policymaking.
On domestic coordination challenges in Chinese technology strategy see Naughton [68].
Forging strong yet balanced semiconductor alliances is critical to effectively weaponizing the supply chain against China. Morrow’s [65] asymmetric alliance theory elucidates the complex bargaining dynamics that enable alliance coordination. The US must leverage its asymmetric dominance in semiconductors to align allies’ interests in exporting constraints on China. Sufficient asymmetry allows the US to incentivize cooperation through rewards and punishments, preventing defection from export control regimes. However, excessive asymmetry risks the entrapment of allies in unfavorable policies contrary to their interests. The US must strike an optimal balance where it holds enough influence to elicit allied cooperation in export controls without dependence that leads to entrapment. Morrow’s focus on intra-alliance asymmetries provides a valuable framework for assessing the viability of joint US-allied export control strategies. In emphasizing power differentials and bargaining, it illuminates the factors critical for weaponizing the semiconductor supply chain.
Jervis [46]. Jervis' seminal work highlights the influence of subjective perceptions over objective facts in international politics, showcasing how decision-making and threat assessments are shaped by these perceptions. His focus on cognition and misperception serves as a crucial basis for comprehending the uncertainties involved in estimating security benefits arising from semiconductor alliances.
Chalkiadakis, Elkind & Wooldridge [20]. provide technical insights critical for computationally implementing game theoretic models to analyze real-world strategic interactions. Their review of algorithms and computational techniques for solving cooperative games directly relates to modeling alliance payoffs, stability incentives, and equilibrium strategies. This underscores the interdisciplinary expertise in computer science and programming needed to accurately operationalize game theory through numerical simulation. While game models provide theoretical abstraction, computational implementation enables real-world analysis of strategic dynamics. This paper demonstrates how algorithms and software tools can transform analytical game theory into practical policy applications. Citing this work highlights the technical complexities of capturing nuanced strategic calculations computationally. Overall, it lends authority regarding the critical expertise in algorithms, programming, and artificial intelligence necessary to effectively apply game theory to policy problems.
Paruchuri et., [70]. This paper proposes the algorithmic methods referenced for solving Stackelberg security games. It provides the underlying techniques used in the robustness check.
Fudenberg & Tirole [36]
Banks & Sundaram [7]. Analysis of computational complexity considerations in modeling repeated strategic interactions. Relevant to implementing the iterative semiconductor game.
See Dynamic belief elicitation to inform mental models of complex adaptive systems. Proceedings of the National Academy of Sciences. Discusses Bayesian elicitation of beliefs and updating for decision modeling. Applicable to the Bayesian priors in the model.
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