68 Finance and economics The EconomistFebruary 10th 2018
I
N 1996 Alan Greenspan began asking whythe flashyinforma-
tion technology spreading across America seemed not to be lift-
ing productivity. He was not the first to wonder. A decade earlier
Robert Solow, a Nobel prizewinner, famously remarked that
computers were everywhere but in the statistics. ButMr Green-
span was uniquely positioned, as the chairman of the Federal Re-
serve, to experiment on the American economy. As the unem-
ployment rate dropped to levels that might normally trigger a
phalanx of interest-rate rises, Mr Greenspan’s Fed moved cau-
tiously, betting that efficiencies from newITwould keep price
pressures in check. The result was the longest period of rapid
growth since the early 1960s. Despite his success, few central
bankers seem eager to repeatthe experiment and many remain
blinkered to issuesother than inflation and employment. That is
unfortunate. A little faith in technology could go a long way.
Central bankers are not known to be a visionary bunch. Turn-
ing new ideas into more efficient ways of doing things is the job of
firms. The capacity of an economy to produce—the supply
side—is primarily shaped by things such as technological pro-
gress, population growth and the skill level of the workforce.
Monetary policy is typically thought not to influence this process.
Its responsibility isthe demand side of the economy, or people’s
willingness to spend. Central bankers typically see themselves as
drivers who press on a vehicle’s accelerator and brakes. The state
of the engine is someone else’s bailiwick.
Not all economists have seen so sharp a delineation between
supply and demand. In 1973 Arthur Okun mused that in an econ-
omy with very low unemployment firms would coax more out-
put out of their workers. More efficient firms would outbid less ef-
ficient ones for scarce labour, boosting productivity. By letting
spending grow rapidly and unemployment tumble, a central
bank might induce productivity to grow faster. In the 1980s Olivi-
er Blanchard and Larry Summers further developed this notion
in their work on “hysteresis”. They reasoned that, ifweak de-
mand led to a long period of joblessness, workers might find their
skills becoming obsolete and their connections to the labour
market eroding. A short-run monetary failure could create a long-
run drop in supply. Correspondingly, a central bank that respond-
ed to recession by allowing unemployment to fall to inflation-stoking levels might find that this overheating lures discouraged
workers back into the labour force, and pushes firms to give them
the training and equipment they need to thrive. Demand, in such
cases, might create its own supply.
In fact, the role of a central bank in managing productivity is
even more fundamental than these theoriessuggest. Good mon-
etary policy is essential to capturing the full benefits of new tech-
nologies. Suppose, for example, that a tech firm creates a cheap,
AI-powered, wearable doodah as good in monitoring health and
diagnosing ailments as going to the GP. Deploying it takes some
capital investment and hiring, but also leads to much larger re-
ductions in spending on conventional practices. In other words,
this magical innovation leads to a rise in the productivity of
health services. Hurrah for that! Butthe need to shift resources
around in response to this disruptive new technology creates
some difficulties. Spending on health care isa reliable source of
growth in employment and in demand. A sudden drop in such
growth might push an economy into a slump. The cost savings
that consumers, health insurers and governments enjoy thanks
to the new technology would help; perhaps some people would
plough their newly saved cash into elective procedures like plas-
tic surgery, at clinics which might then have to expand and hire
new workers. But there is no guarantee that lost spending on doc-
tors and related equipment will be offset by increases elsewhere.
Indeed, in a paperpublished in 2006, SusantuBasu, John Fer-
nald and Miles Kimball concluded that advances in technology
are usually contractionary, tending to nudge economies towards
slump conditions. They estimated thattechnological improve-
ments tend to depress the use of capital and labour (think, in this
example, stethoscopes and doctors) and business investment
(new clinics) for up to two years. To those living through such pe-
riods, this depressing effect would show up in lower inflation
and wage rises. That, in turn, suggests that an alert central bank
with an inflation target ought to swing into action to provide
more monetary stimulus and keep price and wage growth on
track. That stimulus should spur more investment in growing
parts of the economy, helping them to absorb quickly the re-
sources freed up by the new, doctor-displacing technology and
thus averting a slump.
Two obstacles usually get in the way of such a benign out-
come. First, these steps unfold with a lag. The slowdown in price
and wage growth will be gradual, as displaced workers tighten
their belts and compete with other jobseekers for new employ-
ment. Central banks might then wait to see whether low inflation
reflects a genuine economic trend or is merely a statistical blip.
Even after they act, their tools take time to have an effect.What is not seen
The greater difficulty may be the trouble that central bankers
have in imagining that dizzying technological change is possible,
let alone imminent. And the risks they face are asymmetric. Had
Mr Greenspan been wrong, the high inflation that resulted would
have been there for all to see; had he played it safe, no one would
have known thata boom had been achievable. Such possibilities
can only be guessed at; they are not found in the data. Sober tech-
nocrats are not given to leaps of faith. But to risk a bit of inflation
for a chance at a productivity-powered windfall is a wager more
central bankers should make. 7Great good to come
Central banks must occasionally gamble that faster productivity growth is possibleFree exchange
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