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75 据估计在1993—2007年，在17个国家的国内生产总值（GDP）里，机器人在总增长中所占的比例超过了十分之一。参见G. Graetz and G. Michaels, forthcoming, “Robots at Work,” Review of Economics and Statistics。
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76 J. Bughin et al., 2017, “How Artificial Intelligence Can Deliver Real Value to Companies,” McKinsey Global Institute, https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies.
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77 实际上技术带来的许多好处无法估量，这在原则上可以为生产率的下降提供一些解释。在最近的一项研究中，经济学家奥斯坦·古尔斯比（Austan Goolsbee）和彼得·可莱诺（Peter Klenow）使用了一种新的方法来衡量那些基于互联网的技术的价值，他们的研究对象是人们上网的时间。基于“消费涉及收入和时间的支出”这一直觉，他们估计与互联网相关的消费者盈余可能高达3%（人均中位数为每年3000美元）。参见A. Goolsbee and P. Klenow, 2006, “Valuing Consumer Products by the Time Spent Using Them: An Application to the Internet,” American Economic Review 96 (2): 108–13。查德·斯弗森（Chad Syverson）最近使用美国人时间使用调查和个人可支配收入的数据，扩展了关于时间价值的分析。他根据古尔斯比和可莱诺得出的3%的估值，计算出2105年与互联网相关的人均消费者盈余约为3900美元。（2017, “Challenges to Mismeasurement Explanations for the US Productivity Slowdown,” Journal of Economic Perspectives 31 [2]: 165–86）尽管如此，我们仍不清楚在计算机时代误测现象是否更加严重。事实上，美国参议院于1995年任命的博斯金委员会也发现了大量未被衡量的、质量有待改进的证据。因此，在近期的生产率放缓是否是误测这一点上，已经不是误测是否存在的问题，而是误测在近年来是否变得更严重的问题了。经济学家已经证明，这一问题的回答是否定的。虽然确实存在误测，但这种错误似乎在变小，而不是变大。与计算机硬件和相关服务以及无形资产（如专利、商标和广告支出）的价格相关联的误测只会让生产率增长放缓更严重。1995—2004年，国内与计算机相关的产品和服务的产量下降了，这意味着在一些数字技术方面的误测变严重了，当时的误测问题比现在更严重。将这些调整汇总在一起，1995—2004年公布的劳动生产率数据增加了0.5个百分点，但2004—2014年仅增加了0.2个百分点。（参见D. M. Byrne, J. G. Fernald, and M. B. Reinsdorf, 2016, “Does the United States Have a Productivity Slowdown or a Measurement Problem?,” Brookings Papers on Economic Activity, 2016 [1]: 109–82）即使我们将消费者从维基百科、谷歌、脸书等免费服务中获益的高端收益考虑在内，也只能解释经济放缓的三分之一左右的内容。斯弗森认为如果生产率增速没有下降，2015年的GDP将增长16%，美国经济将增加2.9万亿美元，这相当于每个公民的收入增加9100美元或每个家庭的收入增加23,400美元。（2017, “Challenges to Mismeasurement Explanations for the US Productivity Slowdown”）我们的基本观点是，误测范围可能很大，但不足以解释生产率的下降。生产率放缓似乎是结构性的，同时也是真实的。
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78 Brynjolfsson, Rock, and Syverson, forthcoming, “Artificial Intelligence and the Modern Productivity Paradox,” 25.
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79 C. F. Kerry and J. Karsten, 2017, “Gauging Investment in Self-Driving Cars,” Brookings Institution, October16. https://www.brookings.edu/research/gauging-investment-in-self-driving-cars/.
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80 Brynjolfsson, Rock, and Syverson, forthcoming, “Artificial Intelligence and the Modern Productivity Paradox,” 25.
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81 N. F. Crafts and T. C. Mills, 2017, “Trend TFP Growth in the United States: Forecasts versus Outcomes” (Discussion Paper 12029, Centre for Economic Policy Research, London)。他们的发现与埃里克·巴特尔斯曼（Eric Bartelsman）的观察一致，即生产率预测表现得“非常糟糕，预测的标准误差超出了对政策有用的范围”。（2013, “ICT, Reallocation and Productivity” [Brussels: European Commission, Directorate-General for Economic and Financial Afairs]）
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82 H. Jerome, 1934, “Mechanization in Industry” (Working Paper 27, National Bureau of Economic Research, New York), 19.
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83 H. R. Varian, forthcoming, “Artificial Intelligence, Economics, and Industrial Organization,” in The Economics of Artificial Intelligence: An Agenda, ed. Ajay K. Agrawal, Joshua Gans, and Avi Goldfarb (Chicago: University of Chicago Press), 1.
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84 出处同上，15。
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85 Brynjolfsson, Rock, and Syverson, forthcoming, “Artificial Intelligence and the Modern Productivity Paradox.”
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86 N. F. Crafts, 2004, “Steam as a General Purpose Technology: A Growth Accounting Perspective,” Economic Journal 114 (495): 338–51.
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87 引自J. L. Simon, 2000, The Great Breakthrough and Its Cause (Ann Arbor: University of Michigan Press), 108。
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88 P. Colquhoun, 1815, A Treatise on the Wealth, Power, and Resources of the British Empire, Johnson Reprint Corporation), 68–69。也可参见J. Mokyr, 2011, The Enlightened Economy; Britain and the Industrial Revolution, 1700–1850 (London: Penguin), chapter 5, Kindle。感谢乔尔·莫基尔指出了这一点。
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89 Malthus, [1798] 2013, An Essay on the Principle of Population, 179.
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90 R. Henderson, 2017, comment on “Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics, by E. Brynjolfsson, D. Rock and C. Syverson,” National Bureau of Economic Research, http://www.nber.org/chapters/c14020.pdf.
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91 J. M. Keynes, [1930] 2010, “Economic Possibilities for Our Grandchildren,” in Essays in Persuasion (London: Palgrave Macmillan), 321–32.
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92 V. A. Ramey and N. Francis, 2009, “A Century of Work and Leisure,” American Economic Journal: Macroeconomics 1 (2): 189–224.
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93 W. A. Sundstrom, 2006, “Hours and Working Conditions,” in Historical Statistics of the United States, Earliest Times to the Present: Millennial Edition Online, ed. S. B. Carter et al. (New York: Cambridge University Press).
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94 Ramey and Francis, 2009, “A Century of Work and Leisure.”
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95 这些是建立在特定年龄的休闲方式和生存概率之上的。出处同上。
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96 这些结果与马克·阿吉亚尔（Mark Aguiar）和埃里克·赫斯特（Erik Hurst）得出的估计有出入，他们发现在1965年以后，闲暇时间有了更大的增长。主要原因是他们把育儿归类为休闲而不是家庭生产了。参见M. Aguiar and E. Hurst, 2007, “Measuring Trends in Leisure: The Allocation of Time Over Five Decades,” Quarterly Journal of Economics 122 (3): 969–1006。拉梅和弗朗西斯也将与孩子交谈和玩耍等活动归类为闲暇，将其他育儿任务归类为家庭生产。考虑到人们报告说与这些活动相关的幸福感更低，这种情况似乎很合理。参见J. Robinson and G. Godbey, 2010, Time for Life: The Surprising Ways Americans Use Their Time (Philadelphia: Penn State University Press.)。
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97 Keynes, [1930] 2010, “Economic Possibilities for Our Grandchildren,” 322.
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98 R. L. Heilbroner, 1966, “Where Do We Go from Here?,” New York Review of Books, March 17, https://www.nybooks.com/articles/1966/03/17/where-do-we-go-from-here/.
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99 D. H. Autor, 2015, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” Journal of Economic Perspectives 29 (3): 8.
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