There are tentative signs that productivity growth might accelerate
有初步迹象表明生产率增长可能会提速

乐观的理由 Reasons to be cheerful-书迷号 shumihao.com

THE PROSPECTS for a productivity resurgence may seem grim. After all, the past decade has featured plenty of technological fatalism: in 2013 Peter Thiel, a venture capitalist, mused of the technological advances of the moment that “we wanted flying cars, instead we got 140 characters”. Robert Gordon of Northwestern University has echoed this sentiment, speculating that humanity might never again invent something so transformative as the flush toilet. Throughout the decade, data largely supported the views of the pessimists.
生产率复苏的前景看似黯淡。毕竟过去十年里技术宿命论的观点很流行。2013年,风险投资家彼得·蒂尔(Peter Thiel)在思考当时的技术进步时说,“我们想要会飞的汽车,结果却只得到最多能发140个字符的帖子”。西北大学的罗伯特·戈登(Robert Gordon)附和了这种看法,推断人类可能永远不会再发明出像抽水马桶这样具改造力的东西了。过去十年,数据大体上支持了悲观主义者的观点。

What is more, some studies of past pandemics and analyses of the economic effects of this one suggest that covid-19 might make the productivity performance worse. According to research by the World Bank, countries struck by pandemic outbreaks in the 21st century (not including covid) experienced a marked decline in labour productivity of 9% after three years relative to unaffected countries.
此外,对过去大流行病的一些研究以及对此次疫情的经济影响的分析表明,新冠病毒可能会令生产率表现变得更差。根据世界银行的研究,在21世纪受到流行病爆发(不包括新冠)冲击的国家在三年后劳动生产率相较未受疾病侵袭的国家显著下跌了9%。

And yet, stranger things have happened. The brutal years of the 1930s were followed by the most extraordinary economic boom in history. A generation ago economists had nearly abandoned hope of ever matching the post-war performance when a computer-powered productivity explosion took place. And today there are tantalising hints that the economic and social traumas of the first two decades of this century may soon give way to a new period of economic dynamism.
但是,更奇怪的情形亦有发生。在上世纪30年代的残酷岁月之后出现了历史上最不寻常的经济繁荣。二三十年前,经济学家对再次出现像二战后计算机驱动的那种生产率大爆发已经几乎不抱希望了。今天,一些撩拨人心的迹象表明,在经过本世纪前20年的经济和社会创伤之后,一段新的经济活力期也许即将到来。

Productivity is the magic elixir of economic growth. Increases in the size of the labour force or the stock of capital can raise output, but the effect of such contributions diminishes unless better ways are found to make use of those resources. Productivity growth—wringing more output from available resources—is the ultimate source of long-run increases in incomes. It’s not everything, as Paul Krugman, a Nobel economics laureate, once noted, but in the long run it’s almost everything.
生产率是经济增长的灵丹妙药。扩大劳动力规模或资本存量可以增加产出,但除非能找到更好的方法来利用这些资源,否则它们的作用就会逐渐减弱。生产率增长(也就是从可用资源中尽量获得更多产出)是长期收入增加的终极源头。正如诺贝尔经济学奖获得者保罗·克鲁格曼(Paul Krugman)曾指出的那样,生产率不是一切,但从长远来看它几乎就是一切。

Economists know less about how to boost productivity than they would like, however. Increases in labour productivity (that is, more output per worker per hour) seem to follow improvements in educational levels, increases in investment (which raise the level of capital per worker), and adoption of new innovations. A rise in total factor productivity—or the efficiency with which an economy uses its productive inputs—may require the discovery of new ways of producing goods and services, or the reallocation of scarce resources from low-productivity firms and places to high-productivity ones.
但是,经济学家对如何提高生产率的认识还不充分。劳动生产率的提高(即每工时产出更多)似乎是随教育水平提高、投资增加(提高了工人的人均资本水平)以及采用创新技术而来。全要素生产率(即一经济体利用其生产要素的效率)的提高可能需要发现生产商品和提供服务的新方法,或者将稀缺资源从生产率低下的企业和地方重新分配到生产率高的企业和地方。

Globally, productivity growth decelerated sharply in the 1970s from scorchingly high rates in the post-war decades. A burst of higher productivity growth in the rich world, led by America, unfolded from the mid-1990s into the early 2000s. Emerging markets, too, enjoyed rapid productivity growth in the decade prior to the global financial crisis, powered by high levels of investment and an expansion of trade which brought more sophisticated techniques and technologies to the developing-economy participants in global supply chains. Since the crisis, however, a broad-based and stubbornly persistent slowdown in productivity growth has set in (see chart 1). About 70% of the world’s economies have been affected, according to the World Bank.
从全球范围看,战后几十年里生产率增长飙升,到了上世纪70年代急剧放缓。从90年代中期到21世纪的头几年,以美国为首的富裕国家生产率出现了一波提速。新兴市场在全球金融危机爆发前的十年里也经历了生产率的快速增长,这得益于高水平的投资和贸易的扩张给全球供应链中的发展中经济体带来了更先进的工艺和技术。然而,自金融危机以来,生产率增长持续放缓,范围广泛,顽固持久(见图表1)。根据世界银行的数据,全球约70%的经济体受到影响。

Accounting for the slowdown is a fraught process. The World Bank reckons that slowing trade growth and fewer opportunities to adopt and adapt new technology from richer countries may have helped depress productivity advances in the emerging world. Across all economies, sluggish investment in the aftermath of the global financial crisis looks a culprit: a particular problem in places with ageing and shrinking workforces. Yet while these headwinds surely matter, the bigger question is why new technologies like improved robotics, cloud computing and artificial intelligence have not prompted more investment and higher productivity growth.
要解释增长何以放缓是个令人头疼的难题。世界银行认为,近年来贸易增长放缓,从较富裕国家引进并因地制宜地应用新技术的机会减少,可能在一定程度上抑制了新兴世界生产率的提高。从全体经济体来看,全球金融危机后的投资低迷似乎是造成增长放缓的罪魁祸首之一,在劳动力老龄化和萎缩的地方尤其突出。然而,尽管这些不利因素确实有很大影响,但更大的问题是,为什么改进的机器人技术、云计算和人工智能之类的新技术并没有促进投资增长和生产率提升?

Broadly speaking, three hypotheses compete to explain these doldrums. One, voiced by the techno-pessimists, insists that for all the enthusiasm about world-changing technologies, recent innovations are simply not as transformative as the optimists insist. Though it is possible that this will turn out to be correct, continued technological progress makes it look ever less plausible as an explanation for the doldrums. AI may not have transformed the world economy at the dramatically disruptive pace some expected five to ten years ago, but it has become significantly, and in some cases startlingly, more capable. GPT-3, a language-prediction model developed by OpenAI, a research firm, has demonstrated a remarkable ability to carry on conversations, draft long texts and write code in surprisingly human-like fashion.
大体上说,有三种不同的假说尝试解释生产率低迷的问题。一种由技术悲观主义者提出,他们坚持认为尽管人们对改变世界的技术充满热情,但近年来的创新并没有乐观主义者所坚信的那样具有变革意义。尽管这最终可能会被证明是正确的,但持续的技术进步似乎使之越来越没有说服力。AI可能并没有以人们在五到十年前期望的那种惊人的颠覆性速度改变世界经济,但它的能力已有了显著的提升,在一些领域甚至堪称惊人。研究公司OpenAI开发的一种语言预测模型GPT-3展示了出色的开展对话、起草长文和编写代码上的能力,对真人的模拟程度令人吃惊。

Though the potential of the web to support an economy in which the constraints of distance do not bind has long underwhelmed, cloud computing and video-conferencing proved their economic worth over the past year, enabling vast amounts of productive activity to continue with scarcely an interruption despite the shuttering of many offices. New technologies are clearly able to do more than has generally been asked of them in recent years.
互联网在通过打破距离限制而支持经济发展上的潜力早已不怎么激动人心。但云计算和视频会议在过去一年中证明了它们的经济价值:在许多办公室关闭之时,它们让大量生产活动能近乎不中断地继续下去。显然,新技术能做的要比近些年人们对它们的期待更多。

That strengthens the case for a second explanation for slow productivity growth: chronically weak demand. In this view, expressed most vociferously by Larry Summers of Harvard University, governments’ inability to stoke enough spending constrains investment and growth. More public investment is needed to unlock the economy’s potential. Chronically low rates of interest and inflation, limp private investment and lacklustre wage growth since the turn of the millennium clearly indicate that demand has been inadequate for most of the past two decades. Whether this meaningfully undercuts productivity growth is difficult to say. But in the years before the pandemic, as unemployment fell and wage growth ticked up, American labour productivity growth appeared to be accelerating, from an annual increase of just 0.3% in 2016 to a rise of 1.7% in 2019: the fastest pace of growth since 2010.
这支持了对生产率增长缓慢的第二种解释:长期需求疲软。哈佛大学的拉里·萨默斯(Larry Summers)最强烈地表达了这种观点,认为政府无力刺激足够的支出,限制了投资和增长。释放经济潜力需要更多公共投资。进入21世纪以来,利率和通胀率一直处于低位,私人投资疲软,工资增长乏力,这些都清楚地表明过去20年的大多数时间里需求都不足够。很难说这是否严重影响了生产率增长。但在疫情之前的几年里,随着失业率下降和工资增长加快,美国的劳动生产率似乎在加速增长,2016年增长率仅为0.3%,2019年为1.7%,是2010年以来最快的增速。

But a third explanation provides the strongest case for optimism: it takes time to work out how to use new technologies effectively. AI is an example of what economists call a “general-purpose technology”, like electricity, which has the potential to boost productivity across many industries. But making best use of such technologies takes time and experimentation. This accumulation of know-how is really an investment in “intangible capital”.
但第三种解释为保持乐观提供了最有力的依据,它认为要弄清楚如何有效地利用新技术需要时间。AI是经济学家所说的“通用技术”的一个例子,和电力一样,它有潜力提高许多行业的生产率。但充分利用这些技术需要时间和尝试。在这方面专业知识的积累实际上就是对“无形资本”的投资。

Recent work by Erik Brynjolfsson and Daniel Rock, of MIT, and Chad Syverson, of the University of Chicago, argues that this pattern leads to a phenomenon they call the “productivity J-curve”. As new technologies are first adopted, firms shift resources towards investment in intangibles: developing new business processes. This shift in resources means that firm output suffers in a way that cannot be fully explained by shifts in the measured use of labour and tangible capital, and which is thus interpreted as a decline in productivity growth. Later, as intangible investments bear fruit, measured productivity surges because output rockets upward in a manner unexplained by measured inputs of labour and tangible capital.
麻省理工学院的埃里克·布林约尔松(Erik Brynjolfsson)和丹尼尔·洛克(Daniel Rock)以及芝加哥大学的查德·西威尔森(Chad Syverson)近期的研究认为,这种模式导致了一种他们称之为“生产率J曲线”的现象。新技术被首次采用之后,企业把资源转向无形资产投资,也就是开发新的业务流程。这种资源的转移意味着企业的产出会受影响,而这无法完全用可测量的劳动力和有形资本的转移来说明,因此被解释为生产率增长放缓。之后,随着无形投资开始取得成果,测得的生产率急剧提升,因为产出的飙升同样不能以可测量的劳动力和有形资本投入来解释。

Back in 2010, the failure to account for intangible investment in software made little difference to the productivity numbers, the authors reckon. But productivity has increasingly been understated; by the end of 2016, productivity growth was probably about 0.9 percentage points higher than official estimates suggested.
几位作者认为,回到2010年时,未能考虑软件方面的无形投资对生产率数据的影响不大。但生产率越来越被低估了。到2016年底,实际生产率增长可能比官方估计的数字高出约0.9个百分点。

This pattern has occurred before. In 1987 Robert Solow, another Nobel prizewinner, remarked that computers could be seen everywhere except the productivity statistics. Nine years later American productivity growth began an acceleration which evoked the golden age of the 1950s and 1960s. These processes are not always sexy. In the late 1990s, the soaring share prices of internet startups hogged the headlines. The fillip to productivity growth had other sources, like improvements in manufacturing techniques, better inventory management and rationalisation of logistics and production processes made possible by the digitisation of firm records and the deployment of clever software.
这种模式以前也曾出现过。1987年,另一位诺贝尔奖得主罗伯特·索洛(Robert Solow)指出,计算机的影响随处可见,除了在生产率的统计数据中。九年后,美国生产率开始提速,让人想起五六十年代的黄金时代。这些过程并不总是时髦酷炫。90年代末,互联网创业公司股价飙升经常占据新闻头条。刺激生产率增长的还有其他原因,例如公司数据的数字化和智能软件的部署所带来的制造工艺改良、库存管理改进以及物流和生产流程合理化。

The J-curve provides a way to reconcile tech optimism and adoption of new technologies with lousy productivity statistics. The role of intangible investments in unlocking the potential of new technologies may also mean that the pandemic, despite its economic damage, has made a productivity boom more likely to develop. Office closures have forced firms to invest in digitisation and automation, or to make better use of existing investments. Old analogue habits could no longer be tolerated. Though it will not show up in any economic statistics, in 2020 executives around the world invested in the organisational overhauls needed to make new technologies work effectively (see chart 2). Not all of these efforts will have led to productivity improvements. But as covid-19 recedes, the firms which did transform their activities will retain and build on their new ways of doing things.
J曲线给出了一种方法,可以将技术乐观主义及采纳新技术与差劲的生产率数据统一起来。无形投资在释放新技术的潜力方面的作用还可能意味着,尽管此次疫情造成了经济损失,但它也增加了生产率大幅增长的可能性。关闭办公室迫使公司投资于数字化和自动化,或者更好地利用现有投资。非数字化的老旧做法将不再被容忍。2020年,全球各地的高管都在投资于组织架构的改革以求有效地运用新技术,尽管这不会体现在任何经济统计数据中(见图表2)。这些努力并非都能带来生产率提升。但随着疫情逐渐消退,那些确实完成了转型的公司将维持并扩大新的经营模式。

The crisis forced change
危机推动变革

Early evidence suggests that some transformations are very likely to stick, and that the pandemic quickened the pace of technology adoption. A survey of global firms conducted by the World Economic Forum this year found that more than 80% of employers intend to accelerate plans to digitise their processes and provide more opportunities for remote work, while 50% plan to accelerate automation of production tasks. About 43% expect changes like these to generate a net reduction in their workforces: a development which could pose labour-market challenges but which almost by definition implies improvements in productivity.
从初步证据看,某些转变很可能会持续下去,而且疫情加快了采用新技术的步伐。世界经济论坛今年对全球企业的一项调查发现,超过80%的雇主打算加快流程数字化,并提供更多远程工作的机会;50%的雇主计划加速生产任务自动化。约43%的雇主预计这样的变化会导致员工人数出现净减少,这可能会对劳动力市场带来挑战,但人数减少几乎必定意味着生产率会提高。

Harder to assess is the possibility that the movement of so much work into the cloud could have productivity-boosting effects for national economies or at the global level. High housing and property costs in rich, productive cities have locked firms and workers out of places where they might have done more with less resources. If tech workers can more easily contribute to top firms while living in affordable cities away from America’s coasts, say, then strict zoning rules in the bay area of California will become less of a bottleneck. Office space in San Francisco or London freed up by increases in remote work could be occupied by firms which really do need their workers to operate in close physical proximity. Beyond that, and politics permitting, the boost to distance education and telemedicine delivered by the pandemic could help drive a period of growth in services trade, and the achievement of economies of scale in sectors which have long proved resistant to productivity-boosting measures.
将大量工作移到云端是否有可能提高国家经济或全球经济的生产率,这一点更难评估。在高产的富裕城市中,高昂的住房和物业成本让公司和员工无法在本可能用更少资源做更多事的地方运营和工作。比如说,假如科技工作者可以离开美国沿海地区,到生活成本更低的城市为顶尖公司工作,那么加州湾区严格的分区规划将不再构成发展瓶颈。在旧金山或伦敦,因远程工作增加而腾出的办公空间或许可以留给那些确实需要员工现场办公的公司去用。除此之外,在政治上也允许的情况下,受疫情推动的远程教育和远程医疗也许还可在一段时期里推动服务贸易的增长,并在那些长期都抗拒提高生产率的措施的行业中实现规模经济。

None of this can be taken for granted. Making the most of new private-sector investments in technology and know-how will require governments to engineer a rapid recovery in demand, to make complementary investments in public goods like broadband, and to focus on tackling the educational shortfalls so many students have suffered as a consequence of school closures. But the raw materials for a new productivity boom appear to be falling into place, in a way not seen for at least two decades. This year’s darkness may in fact mean that dawn is just over the horizon.■
这些都不是轻易就能实现的。要充分利用私营部门在技术和专业知识上的新投资,就需要政府设法快速恢复需求,并对宽带等公共产品做互补性投资,还要集中精力解决学校停课导致许多学生遭受教育短缺的问题。但是,新一轮生产率快速增长所需的要素似乎正准备就绪——以至少20年未见的态势。实际上,今年的黑暗也许预示着黎明即将来临。