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References: What Is a General Purpose Technology?

  1. General-purpose technology - Wikipedia - Defines the GPT concept formalized by Bresnahan and Trajtenberg, lists historical examples, and explains the three criteria (broad applicability, improvement over time, innovation spawning) that form this chapter's analytical framework.

  2. Technological revolution - Wikipedia - Provides historical context on how transformative technologies like the steam engine, electricity, and transistors restructured economies, supporting this chapter's comparison of historical GPTs to quantum computing.

  3. Moore's law - Wikipedia - Documents the sustained exponential improvement in transistor density over five decades, exemplifying the "improvement over time" GPT criterion that this chapter argues quantum computing fails to satisfy.

  4. General Purpose Technologies and Economic Growth (1998) - Elhanan Helpman, Editor - MIT Press - The foundational academic work on GPT theory, containing Bresnahan and Trajtenberg's formal model that this chapter applies to evaluate quantum computing's economic potential.

  5. The Rise and Fall of American Growth (2016) - Robert J. Gordon - Princeton University Press - Comprehensive economic history of how GPTs like electricity and the internal combustion engine transformed the American economy, providing the historical benchmark against which this chapter measures quantum computing.

  6. General Purpose Technologies: Engines of Growth? - Bresnahan and Trajtenberg, NBER Working Paper (1992) - The original paper defining the three-criteria GPT framework that this chapter uses to systematically demonstrate why quantum computing fails every test for being a transformative technology.

  7. Are Ideas Getting Harder to Find? - Bloom et al., American Economic Review (2020) - Examines declining research productivity across technologies, relevant to this chapter's discussion of whether quantum computing improvement trajectories can sustain the decades of progress required of a GPT.

  8. The Economics of Artificial Intelligence: An Agenda - Agrawal, Gans, and Goldfarb, NBER (2019) - Analyzes AI/ML as an emerging GPT using the same economic framework this chapter applies, providing contrast with quantum computing's failure to meet GPT criteria.

  9. Quantum Computing in the NISQ Era and Beyond - John Preskill, arXiv (2018) - Acknowledges the narrow applicability of near-term quantum computing, supporting this chapter's argument that quantum computing's limited problem scope disqualifies it as a general-purpose technology.

  10. The Narrow Path for Quantum Advantage in Optimization - Basso et al., arXiv (2023) - Demonstrates that quantum algorithms provide advantage only for highly structured problems, providing technical evidence for this chapter's central argument that quantum computing is narrowly applicable rather than broadly transformative.