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Economists have always recognised that the long-run growth of productivity is, in the end, almost the only thing that matters for the living standards of the population as a whole. Recently, there have been significant downgrades to consensus estimates of productivity growth which, if maintained for long, would have enormous effects on the attainable level of gross domestic product per capita.
经济学家一贯认为，从根本上来说，生产率的长期增长几乎是唯一影响全体人类生活水平的因素。近来人们对生产率增长的普遍预期大幅下降，这一趋势如果长期保持下去，将对人均国内生产总值(GDP)的可实现水平造成巨大影响。
But the future impact of technology on long-run growth is one of the great unknowns — perhaps even the greatest — in economics.
但未来技术对长期增长的影响是经济学上的一大未知数——有可能还是最大的未知数。
An excellent example of this uncertainty occurred at the FT Business of Luxury Summit last week, in contributions from Johann Rupert and Martin Wolf. The former painted a picture of unprecedented technical advance, quoting examples from The Second Machine Age by Erik Brynjolfsson and Andrew McAfee. This book has captured the imagination by describing a future in which machine learning increases at exponential speed, rapidly replacing human skills in large parts of the economy. In a world of robot technology, driverless cars and delivery-by-drones, measured productivity growth would surely advance very quickly.
在近期英国《金融时报》奢侈品行业峰会(FT Business of Luxury Summit)上，来自约翰•鲁珀特(Johann Rupert)和马丁•沃尔夫(Martin Wolf)的观点就充分体现出了这种不确定性。鲁珀特援引安德鲁•麦卡菲(Andrew McAfee)和埃里克•布林约尔松(Erik Brynjolfsson)合著的《第二次机器革命》(The Second Machine Age)中所举的例子，描绘了前所未有的科技进步的景象。这本书描述的未来激起了人们的无限遐想：机器的学习能力以指数速度增长，迅速在经济的大部分领域取代人类技能。在一个机器人科技、无人驾驶汽车和无人机送货的世界里，人们衡量的生产率增长必定前进得非常快。
Martin Wolf, however, disagreed. He argued that the great technological advances of the 19th and 20th centuries would not be replicated in the future, so productivity growth would remain subdued, as it has been since about 2003. Sympathising with the somewhat gloomy paper published by Robert Gordon in 2012, Martin felt that the low-hanging technological fruits had already been picked, and that the period of rapid advance that ended in the early 1970s was an aberration.
马丁•沃尔夫不认同这一点。他认为19世纪和20世纪那种技术大进步无法在未来复制，因此生产率增长将像大概2003年之后一样，持续处于低迷状态。他与罗伯特•戈登(Robert Gordon)2012年发表的一份有些悲观的报告意见一致，马丁感到，容易摘得的技术果实已经被摘下，上世纪70年代初结束的那段技术飞速进步的时期具有偶发性。
Who is right?
谁对谁错？
My own response to Martin was to suggest that he might be under-estimating the seismic change that is taking place in the availability and communication of all types of information, as represented for example in the arrival of the iPhone. This single product has increased consumer well-being in ways that are difficult to capture in official economic statistics. Many of the key consumer advances that have taken place in the past few decades can now be done better, or more conveniently, by a single gadget. Almost none of this is picked up by the consumer price index, which continues to measure all these items separately, while not giving any weight to the extra convenience now freely available to the consumer.
对于马丁，我认为他可能低估了各种类型的信息的获取和交流正在发生的重大改变，iPhone的问世就体现出这一改变。这款产品提高消费者福祉的方式难以用官方经济数据反映。过去几十年中在消费者领域发生了许多关键性进步，现在只靠一个设备就可以达到更好的效果，或者更方便地达到目的。消费者价格指数(CPI)几乎不会计入这一切，CPI一直单独衡量所有的项目，不会将现在消费者免费享用的额外便利纳入考虑。
What is more, most individuals in advanced economies now have greater and easier access to information than any individual, however elevated, had in (say) 1990. Soon, that advantage will also apply to most citizens in emerging economies, which will therefore leap-frog the legacy technologies (for example. telephone wires) of the advanced world.
此外，现在发达经济体的大多数个人比过去的任何人都能更便利地接触到更多信息，哪怕过去（比如1990年）的这个人多么位高权重。很快，新兴经济体的大多数公民也将拥有这一优势，进而超越发达国家的传统技术（比如电话线路）。
In his 2008 paper Ideas and Growth, Robert Lucas persuasively argued that productivity growth in advanced economies in recent centuries “is mainly an intellectual achievement, a sustained flow of new ideas” (see also the videohere). Any way of improving the flow of ideas increases the pace at which individuals can learn from others who are smarter or better informed than themselves. In these models, the propagation of knowledge is a prime determinant of growth, and that propagation is surely changing at a dramatic pace at present.
罗伯特•卢卡斯(Robert Lucas)在其2008年的报告《思想和增长》(Ideas and Growth)中进行了颇具说服力的论述。他认为近几个世纪以来，发达经济体的生产率增长“基本是智力的成果，来自于新思想的持续流动”。思想流动的任何改善会都加快个人从其他更聪明或更博识的人那里学习的步伐。在这些模型中，知识的传播是推动增长的最重要决定因素，而这种传播现在无疑正以极快的速度发生改变。
It would be great if we could accurately measure the impact of technological change on actual productivity growth. Some of this is relatively easy. For example, it is nowfairly clear that the temporary surge in productivity from about 1995-2003 depended largely on a surge in IT investment by a group of mainly service industries. But more often, direct measurement is extremely difficult.
如果我们能够精确衡量技术改革对实际生产率增长的影响就好了。有时衡量这种影响相对简单。比如，1995年到2003年间生产率的短暂大幅上升，主要依靠以服务业为主的一些行业对IT投资的激增。但一般来说，直接衡量这种影响极为困难。
In a 1998 paper, which deserves much wider recognition in the public debate, William Nordhaus showed how mismeasurement of the price of light, or illumination, has caused important distortions in official economic data for inflation and productivity since 1800. Mr Nordhaus simulates how the “price of light” might have been estimated in official consumer price index statistics, had they existed at the time.
经济学家威廉•诺德豪斯(William Nordhaus)1998年的一份报告理应在公开辩论中得到更广泛的承认。他在报告中证明了对光，或者说照明的价格的错估，使1800年以来官方对通胀和生产率的经济数据产生了重大扭曲。诺德豪斯模拟了如果当时存在官方CPI数据统计，在CPI中“光的价格”可能得到怎样的估算。
He proxies this by measuring the price of gas and electricity (“official” price estimates I and II in the graph), which would have been the inputs used as proxies for the price of light in standard CPI indices. He then compares this with the “true” price of light, which allows for the vast improvement in the efficiency of lighting technology over time. The difference is enormous: the “official” CPI would have over-estimated the inflation rate in the provision of light by 3.6 per cent per annum for many decades. Since light accounts for about 1 per cent of consumer spending, this alone means that the change in real GDP per capita was underestimated by about 7 per cent over two centuries.
他的模拟方式是衡量天然气和电力（右图中的“官方”价格I和II）的价格，在标准的CPI指数中，把这两者当做光的价格的替代品输入其中。然后他将这与光的“真实”价格进行比较，后者考虑了随时间推移照明技术能效的巨大提高。差异是巨大的：数十年里，“官方”CPI每年对照明方面的通胀率会高估3.6%。由于照明在消费者支出中约占1%，仅这一项就意味着实际人均GDP在两个世纪以来被低估了7%左右。
If we make an analogy between the price of light in the last two centuries, and the price of information in this century, the impact of IT and the smartphone on inflation may be severely mismeasured, in which case real income and productivity may already be growing much faster than officially estimated (see Martin Feldsteinhere).
如果我们把过去两个世纪的光的价格和本世纪信息的价格做一个类比，我们可能严重错估了IT技术和智能手机对通胀的影响——实际收入和生产率或许比官方估计的增长得更快。
Unfortunately, this single example does not prove that, taken overall, technology will contribute to faster increases in productivity in the period ahead. Mr Nordhaus uses his estimates on the price of light to make a very rough guess of the total distortion to the overall CPI that stems from similar types of mismeasurement, in which improvements in quality, and the arrival of new products, are omitted from the inflation data.
遗憾的是，仅这一个例子还无法证明，整体而言，技术将使生产率在接下来的时期中增长更快。诺德豪斯通过对光的价格的估计，对整体CPI的总体扭曲程度进行了非常粗略的推测，这些扭曲来自于类似的错估——通胀数据遗漏了质量的提升和新产品的问世。
He says that two-fifths of the calculations within the CPI are “virtually useless”, and his guess is that real incomes and productivity have been growing at 0.5-1.4 per cent per annum faster than shown in the official data — a huge potential error.
诺德豪斯表示，CPI中有五分之二的计算“几乎无用”。他推测，每年实际收入和生产率的增长比官方数据所显示的快了0.5%-1.4%，这是一个潜在的巨大错误。
Conclusion
结论
In order to be either optimistic or pessimistic about the great technology question, we therefore need to take a view on the future pace of all technical changes, compared with the sum total of all past changes. It is not enough to point to one or two dramatic new advances, however spectacular they may be.
为了对技术这个重大问题形成一种态度，无论是乐观的还是悲观的，我们需要考虑未来所有技术变革的步伐，并将其与过去一切变革的总量相比较。只针对一两次巨大的进步是不够的，不管它们多么引人注目。
So, while I remain optimistic that the collapse in the price of information will greatly advance productivity growth, it is hard to be completely sure that this will outweigh all other factors.
因此，尽管我对信息价格的大幅下滑将极大地促进生产率增长保持乐观，但很难完全确定其作用是否会超过所有其他因素。
Only the central banks and the government statisticians have the scale of resources needed to solve this empirical conundrum, and currently they seem reluctant to address the issue. Traditional statistical methods, however badly flawed, rule the roost.
只有央行和政府统计学家拥有解决这个实证难题所需的大量资源，而目前他们似乎不太情愿解决这个问题。传统的统计方法不管缺陷多么严重，依然将占据主导地位。
