「華人戴明學院」是戴明哲學的學習共同體 ,致力於淵博型智識系統的研究、推廣和運用。 The purpose of this blog is to advance the ideas and ideals of W. Edwards Deming.

2016年8月10日 星期三

Low wages are both a cause and a consequence of low productivity. US economy: The productivity puzzle

American productivity is still in a rut, having fallen for three straight quarters. How can more be done with less? From the archive

Free exchange: doing less with more

June 29, 2014 5:23 pm

US economy: The productivity puzzle

Long-term prosperity depends on the capacity of every American to increase output constantly. Can they?
B8WBY3 Three combines harvesting rows of swathed wheat in farmers field aerial view near Colgate North Dakota©Alamy
Bumper crop: the success of US farmers in increasing their productivity is a model that some, such as MIT’s Erik Brynjolfsson, think can be replicated
To glimpse the miracle of productivity growth there is nowhere better to look than the bountiful fields of the US Corn Belt. A hundred years ago, an army of farmers toiled to produce 30 bushels an acre; now only a few hands are needed to produce 160 bushels from the same land.
The rise of modern civilisation rested on this trend: for each person to produce ever more. For the past 120 years, as if bound by some inexorable law, output per head of population increased by about 2 per cent a year. That is, until now.




There is a fear – voiced by credible economists such as Robert Gordon of Northwestern University – that 2 per cent is no law but a wave that has already run its course. According to Prof Gordon’s analysis, 2 per cent could easily become 1 per cent or even less, for the next 120 years.
The US Federal Reserve is already edging down its forecasts for long-term interest rates. “The most likely reason for that is there has been some slight decline . . .  of projections pertaining to longer-term growth,” said Janet Yellen, chairwoman, at her most recent press conference.
Yet there are also techno-optimists, such as Erik Brynjolfsson and Andrew McAfee of the Massachusetts Institute of Technology, whose faith in new discoveriesis such that they expect growth to accelerate, not decline.
Then there are more phlegmatic economists, whose answers are less exciting but also less speculative – and come in a bit below 2 per cent for growth in output per head.
The productivity question is of the greatest possible consequence for the US economy, affecting everything from when interest rates should rise to where they should peak, from the sustainability of US debt to what is the wisest level of investment for every business in the country.
The answer depends on companies such as Climate Corporation, which fights the battle for agricultural productivity growth from its new front line, in the office buildings of Silicon Valley.
Climate Corporation, which was bought last year by Monsanto for $930m, works on “precision agriculture”, bringing the power of data science to bear on farming.
For example, the company says that by combining fertiliser use, soil type, weather data and other information in a single database, it can tell farmers exactly how much nitrogen is in a field and thus how much fertiliser they need to apply.
The boost to yields could be as much as 5 per cent – and that is just the start. “We’ve identified about 40 different decisions a farmer makes where there’s potential to apply data science,” says Anthony Osborne, the company’s head of marketing.
Whether computers can keep making broad contributions to productivity is one of the most important immediate issues.
But it is not the only issue. Growth in gross domestic product, the familiar statistic by which all economies are measured, can come about in several ways: more workers, with better skills; more capital such as factories, roads and machines, or new technology. Leaving aside the latter category, the consensus among economists is that most of these will not contribute as much to economic growth as they have in the past.
To start with, US population growth is at its lowest since the 1930s, having fallen from about 1.2 per cent a year in the 1990s to 0.7 per cent in recent years. This does not affect growth in living standards – it means fewer consumers as well as fewer workers – but adding less extra labour will slow the headline GDP growth rate that the Fed worries about.
On top of that, demographics will also slow growth in GDP per capita, which does affect living standards. Ageing will mean fewer active workers per head of population; most women have now joined the US labour force so that source of extra workers is running out.
Prof Gordon estimates that demographics could knock 0.3 percentage points off the long-run trend of 2 per cent growth.
“Everybody is pretty much in agreement in expecting slower growth in hours worked relative to what we’ve seen in the last 50 years,” says John Fernald, a senior research adviser at the Federal Reserve Bank of San Francisco.
The truest measure of economic progress, though, is the growth of GDP per hour worked. For every hour of human toil, how much is created? Here too, some factors that drove growth in the past are weakening, such as skills and education.
The expansion of primary, then secondary and then college education has helped the economy grow for generations, but average years of education have now reached a plateau. “The US is slipping back in the league tables of college completion and high school completion,” says Prof Gordon, suggesting this will account for another 0.2 percentage points off per capita growth.
That leaves technology. “I agree with much of what he says about the slowing demographics,” says Prof Brynjolfsson. “Where he and I differ is prospects for future innovation.”
Growth in GDP per hour worked depicts an interesting pattern over time. According to Prof Gordon, at a rate of 2.4 per cent, it was fast from the 19th century until 1972. It then slowed to 1.4 per cent a year until 1996.
The internet boom pushed the rate up to 2.6 per cent – it was this period that led Alan Greenspan, former Fed chairman, to talk about a “productivity feast” – but by 2004, well before the financial crisis, the surge was over. Since 2004, barring a measurement problem, growth in output per hour has been 1.3 per cent.
Whether it’s robotics or software for knowledge work, if you take the labour input to zero you get a pretty astronomical productivity number
The dispute is this: in the coming decades, should we expect growth like that which we experienced from 1996 to 2004, at 2.5 per cent, or like the period since 2004, of 1.3 per cent? While Prof Brynjolfsson has Star Trekvisions of utopian technological progress, Prof Gordon is more of a cyberpunk, imagining a world in which the computers may become more powerful but living standards for average humans improve only slowly.
Computation is the root of Prof Brynjolfsson’s optimism: his book with Prof McAfee is called The Second Machine Age and argues that the impact of information technology has only just begun to be realised. Exponential expansion in computing power, and the ability to diffuse innovations rapidly, could mean growth like that of the late 1990s.
“The reason I’m optimistic is that I don’t rely primarily on extrapolating past economic trends,” says Prof Brynjolfsson. After visiting labs, he says, “I just come away astonished at what’s in the pipeline. Most of it has not yet reached commercialisation.”
Rather than referring to historical data, he points to Google’s self-driving car, to the potential for computer systems that diagnose disease and answer legal queries, and the growing flexibility of robotics. Such automation will free up a host of labour for new tasks, just as other innovations did in the past. “Whether it’s robotics or software for knowledge work, if you take the labour input to zero you get a pretty astronomical productivity number,” he says.
By contrast, Prof Gordon expects a lower pace of productivity growth, perhaps in line with that achieved in the past 10 years. To hit even that target, he points out, means keeping up a steady stream of new creations such as smartphones.
The heart of his argument is that the discoveries of the past – running water, the internal combustion engine, the electric lightbulb – were simply more important than those of today. From 1870 to 1972, he points out, American homes went from lightless, isolated places of drudgery to buildings of air-conditioned comfort, with a dishwasher in the kitchen and a car in the garage.
Think of every employee you’ve had contact with in the last two or three days, and think, is that person going to be replaced by a robot in the next 20 years?
Prof Gordon is also dismissive of the potential productivity gains from inventions such as driverless cars: being able to answer email instead of turning the steering-wheel, for example. “The real productivity gains would presumably come from driverless trucks,” he says, but then points out that a UPS delivery van would still need a driver to remove the parcels from the vehicle.
He is more impressed by the potential of robotics but less convinced the moment has arrived when they are sufficiently powerful to supplant humans. “Think of every employee you’ve had contact with in the last two or three days, and think, is that person going to be replaced by a robot in the next 20 years?”
One curious aspect of both professors’ arguments is how uneconomic they are. Their focus is more about what is left to discover than the economy’s ability to make those discoveries. Prof Gordon’s approach would struggle to explain the 1996 acceleration in productivity growth, while Prof Brynjolfsson’s has little to say about the slowdown after 2004.
Yet economics has quite a lot to say about the process of making discoveries, based on the less than revolutionary insight that breakthroughs depend on the effort put into researching them.
In a recent study, Mr Fernald and Charles Jones of Stanford University break down the inexorable 2 per cent growth in US output per person from 1950 to 2007 in a different way. They find almost none of it comes from more capital per worker.
About 0.4 percentage points comes from human capital (better education). But by far the largest contribution – 1.6 percentage points of the total – comes from the fact that more people are working on research and development.
To sustain that magical run of 2 per cent growth in output per person, the US may need more Silicon Valleys to emerge in China and India
In part, that is because there are more people (and thus more bodies to do research). But mainly it is the result of devoting a steadily larger portion of the total population to work on research and development.
This analysis allows for a more grounded forecast than speculation about what technologies remain to invent. “The pessimistic part of that equation for the future is human capital,” notes Mr Fernald, as the contribution from better education is petering out. It is also impossible for the US to keep devoting ever more of its population to working in research and development.
But this is not true of the world as a whole. Huge populations in China, India and elsewhere are joining the global economy, improving their education systems and putting more researchers to work at the scientific frontier. Any discoveries they make can be used in the US as easily as anywhere else.

FT Video

June 2014: James Mackintosh on why there are reasons to be positive about weak US GDP figures, which, he says, reflect problems with snowfall rather than fundamentals.
In that case, the improvements that come from scientific discovery may be sustainable. Productivity growth need only slow to about 1.6 per cent. Add in some modest increase in population and the economy as a whole could expand at 2 per cent per year or a little more. Mr Fernald’s long-run forecast is 2.1 per cent. This suggests that the Fed open market committee’s latest projection of 2.2 per cent is not far off.
Climate Corporation shows how innovative the US still is – and how computers can yet boost productivity in unexpected ways. To sustain that magical run of 2 per cent growth in output per person, however, the US may need more Silicon Valleys to emerge in China and India, and add their heft to the eternal pursuit of another bushel of corn from the same acre of land.
Intel, clock speed and the measurement of productivity growth
Is the recent slowdown in productivity growth nothing but a statistical mirage? A recent study by economists David Byrne, Stephen Oliner and Daniel Sichel notes a fascinating discrepancy between price and performance data for microprocessors (see chart above). This is important because the rapid progress of processing power is what drives the technology revolution.
Moore’s Law – the trend identified by Intel co-founder Gordon Moore that computer power doubles every two years – has continued apace. But at the same time, whereas the measured price of computing power was falling at a rate of 70 per cent a year between 1998 and 2000, the pace of decline more recently has slowed to 3 or 4 per cent. That translates into a slower pace of measured productivity growth.
Mr Oliner, currently at the American Enterprise Institute, a Washington think-tank, has a few ideas about what may be happening. One is an increase in Intel’s market power. “Starting in about 2006, which is when the break occurred, Intel really solidified its market position relative to AMD,” its main competitor, he says. Less competition may mean slower price declines for its older products.
In about 2006, Mr Oliner continues, “Intel itself had a major breakthrough and developed multi-core chips.” Instead of driving up “clock speed”, the most familiar way of measuring the processing speed of a chip using megahertz or gigahertz, it started including multiple copies of the basic processor within the same chip. If computing power were still measured using clock speed, however, the pace of improvement would appear to suddenly decline.
The US Bureau of Labor Statistics uses a range of tools to measure computing power. One argument in favour of its data – which suggests the pace of progress in computer chips has slowed massively – is that consumers seem to be replacing their desktops less frequently.


美國西北大學(Northwestern University)的羅伯特•戈登(Robert Gordon)等值得信賴的經濟學家擔心,2%不是什麽規律,而是一個正在趨近終點的階段。按照戈登的分析,今後120年2%的增長率可能很容易變成1%,甚至更低。
美聯儲(Fed)已經在調低對長期利率的預測。美聯儲主席珍妮特•耶倫(Janet Yellen)在其最近的一場新聞發布會上表示:“最有可能的原因是,與較長期增長有關的預測……出現了一些小幅下降。”
然而也有一些信奉科技的樂觀主義者,比如麻省理工學院(MIT)的埃里克•布林約爾松(Erik Brynjolfsson)和安德魯•麥卡菲(Andrew McAfee),他們對新發現抱有極大的信心,以至於他們預計增長將會加速,而非下降。
答案取決於Climate Corporation等公司。該公司正從新的前沿陣地——硅谷辦公大樓——投入推動農業生產率增長的戰鬥。
Climate Corporation去年被孟山都(Monsanto)斥資9.3億美元收購。該公司致力於“精細農業”,讓數據科學的威力助推農業。
收成增幅可能高達5%,而這僅僅是開始。Climate Corporation營銷總監安東尼•奧斯本(Anthony Osborne)表示:“我們發現,一個農民做出的大約40個不同決定有可能用到數據科學。”
舊金山聯邦儲備銀行(Federal Reserve Bank of San Francisco)高級研究顧問約翰•弗納爾德(John Fernald)表示:“大家基本上都認為,與過去50年相比,工作時間的增長將會放緩。”
互聯網繁榮推動生產率年均增幅回升至2.6%,正是這段時期促使時任美聯儲主席艾倫•格林斯潘(Alan Greenspan)談論“生產率盛宴”。但早在金融危機爆發之前的2004年,這場盛宴就結束了。拋開測算方面的問題,自2004年以來,每小時產值增長率只有1.3%。
爭議的焦點是:我們應該預期今後幾十年的生產率增長是像1996年到2004年那樣達到2.5%,還是像2004年以來那樣僅為1.3%?盡管布林約爾松對烏托邦的技術進步有著“星際迷航”(Star Trek)式的憧憬,但戈登更像是賽博朋克(cyberpunk),在他設想的世界中,計算機可能變得更加強大,但普通人生活水準只是緩慢上升。
電腦運算是布林約爾松樂觀的根源:他曾與邁克菲合著《第二個機器時代》(The Second Machine Age),該書提出,信息技術的影響才剛剛開始展現。計算能力的指數級提高,以及快速傳播創新的能力,可能意味著20世紀90年代末的增長再度到來。
在最近一項研究中,舊金山聯儲的弗納爾德和美國斯坦福大學(Stanford University)的查爾斯•瓊斯(Charles Jones)用一種不同的方法分析了1950年至2007年美國人均產出每年2%的穩健增長。他們發現,勞動者人均資本的增加幾乎沒有任何貢獻。
Climate Corporation展示了美國依然強大的創新能力,以及電腦仍能以出人意料的方式提高生產率。然而,為了延續人均產出每年增長2%這一神奇趨勢,美國可能需要中國和印度出現更多的“硅谷”,讓他們加入對提高生產率的永恆追求,包括在同一英畝的土地再增產一蒲式耳玉米。
近期的生產率增速放緩是否只不過是一個統計上的誤判?最近,經濟學家大衛•伯恩(David Byrne)、斯蒂芬•奧利納(Stephen Oliner)以及丹尼爾•西謝爾(Daniel Sichel)發布了一份研究報告,指出微處理器的價格和性能數據之間有一種有趣的差異(見上圖)。這一點很重要,因為處理能力的快速提升正是技術革新的驅動力。
英特爾(Intel)的創始人之一戈登•摩爾(Gordon Moore)曾提出了摩爾定律(Moore's Law),認為計算機的性能每兩年就會翻倍。摩爾定律依然有效。與此同時,在1998年到2000年間,微處理器計算能力的單價曾每年下降70%,而最近其下降的速率已經放慢到每年3%到4%。這就意味著生產率增速的回落。
奧利納目前任職於華盛頓智庫機構美國企業研究所(American Enterprise Institute)。他對此有幾點解釋。其一就是英特爾的市場勢力提升了。“2006年轉折點就出現了,大概從那時開始,英特爾實實在在地鞏固了自己相對於AMD的市場地位”,奧利納說。AMD是英特爾的主要競爭對手。競爭變少,老產品降價的速度就可能會變慢。
美國勞工統計局(US Bureau of Labor Statistics)使用一組工具來衡量計算能力。他們得到的數據顯示計算機芯片的發展速度已經大幅放緩。支持這些數據的一條理由是,消費者置換他們的台式機的頻率似乎降低了。