The Rise and Fall of Nations: Forces of Change in the Post-Crisis World - PDFDrive.com
THE RISE AND
FALL OF NATIONS
Forces of Change in the
Post-Crisis World
RUCHIR SHARMA
W. W. NORTON & COMPANY
Independent Publishers Since 1923
New York London
CONTENTS
PROLOGUE: Into the Wild
INTRODUCTION: Impermanence
1. People Matte
2. The Circle of Life
3. Good Billionaires, Bad Billionaires
4. Perils of the State
5. The Geographic Sweet Spot
6. Factories First
7. The Price of Onions
8. Cheap Is Good
9. The Kiss of Debt
10. The Hype Watch
11. The Good, the Average, and the Ugly
ACKNOWLEDGMENTS
NOTES
BIBLIOGRAPHY
INDEX
Prologue
INTO THE WILD
For each of the past twenty-five years, I have gone on a safari, either to India o
Africa. On one trip to Africa, I heard the story of a king who sends his son out to
learn the rhythms of the jungle. On his first outing, against the din of buzzing
insects and singing birds, the young prince can make out only the roar of the
lions and the trumpet of the elephants. The boy returns again and again and
egins to pick up less obvious sounds, until he can hear the rustle of a snake and
the beat of a butterfly’s wings. The king tells him to keep going back until he
can sense the danger in the stillness and the hope in the sunrise. To be fit to rule,
the prince must be able to hear that which does not make a sound.
The rhythms of the jungle are far removed from those of New York, where I
live, but this old African tale is quite relevant to a world reshaped by the global
crisis of 2008. The crisis turned the world on its head, disrupting trade and
money flows, unleashing political revolts, slowing the global economy, and
making it more difficult to discern which nations would thrive and which would
fail in such a transformed landscape. This book is about how to filter out the
hype and noise and pick out the clearest signals that foretell the coming rise o
fall of nations. It’s an attempt to recreate the education of the prince, for anyone
interested in the global economy.
People in the world of global finance often think of themselves as big cats,
predators alert to the rustlings of the economic jungle. But in Africa the
difference between the cats and the rest quickly dissolves. Each year on the
Mara-Serengeti plains of Kenya and Tanzania, more than a million wildebeest
walk a nearly two-thousand-mile loop that they have traced and retraced fo
generations. Moving behind the rains and accompanied by ze
a and gazelle, the
ungainly wildebeest are shadowed by the lion, the leopard, and the cheetah.
The contest looks stacked, but lions are relatively slow and short-winded and
catch their prey on less than one attempt in five. Cheetahs are faster, but because
they are smaller and often hunt alone, they are forced to concede many kills to
scavengers working in packs. Less than one cheetah in ten lives longer than a
scavengers working in packs. Less than one cheetah in ten lives longer than a
year. Lions do a bit better, but many males die young in te
itorial battles with
other males. The circle of life and death turns as
utally for the predator as fo
the prey, a fact that might give pause to the would-be lions of the global
economy.
I’ve lived in fear for my own survival since I entered this jungle. I started out
in investing as a twenty-something kid in the mid-1990s, when the United States
was booming and emerging nations were still seen as wild and exotic. Financial
crises swept from Mexico to Thailand and Russia, triggering painful recessions
and reshuffling the ranks of rising economies and world leaders. The collateral
damage in global markets wiped out many big investors, including a good
number of my mentors, colleagues, and friends.
Looking back, the demise of national leaders (and global investors) followed
a pattern. They initially followed a path that led to economic or financial
success, but then the path shifted and led to quicksand. It happened in the
emerging-world crises of the 1990s, in the dot-com bust of 2000–2001, and
again in 2008. Each time people got too comfortable doing what they were doing
in good times, then got swallowed when the earth shifted under their feet.
The cycles of market euphoria and despair often produce clichés about “herd
ehavior,” but even in the jungle life is more complicated than that stereotype. A
certain “swarm intelligence” guides the wildebeest, ensuring the survival of the
group even when it means an early death for many individuals. The wildebeest’s
circular migration has been mocked with the old prove
“the grass is always
greener on the other side,” but the herd is right about where the grass will be
greener. It follows the rains, north into Kenya in the spring, back south into
Tanzania during the fall.
The critical dangers appear twice a year at “the crossing” of the Mara River,
which the herd must ford while traveling both north and south. Normally, to
avoid predators, the herd heeds an ancient warning system—the shrieks of
aboons, the harsh calls of jungle ba
lers. But this system fails on the banks of
the Mara, where the wildebeest mass by the tens of thousands, with danger in
plain sight: floating crocodiles, rain-swollen waters, lions in ambush on the fa
side.
Heads down, the wildebeest appear to be talking all at once, their distinctive
ellows like so many Wall Street analysts on a conference call, plotting thei
next move. The herd waits for one member to go. If this animal takes a step and
etreats, fear paralyzes the multitude, but memories are short. Within minutes
another will try, and if it plunges in, the mass follows—many into waiting jaws
and deadly cu
ents. An estimated 10 percent of the wildebeest population
perishes each year, a large number of them during the crossing.
perishes each year, a large number of them during the crossing.
People working in global markets from New York to Hong Kong can get
sucked into a culture that is programmed, like the wildebeest, to remain in
constant motion. Every day research reports bombard these financial capitals,
urging the crowd to chase the next Big Thing or to run from the next Big
Co
ection. The compulsion to move gives rise to a new consensus every season
or every quarter, an impulse that has only grown since the global financial crisis.
Just take the year 2015. During the first quarter the chatter was all about how
you had to either get in or get out of the way of the surging Chinese stock
market, which then seemed like a one-way bet. The second quarter was all about
how Greece was going to take down the global economy, and during the third
quarter the financial panic in China dominated the conversation. Sometimes the
eports are right, and sometimes they’re wrong, but always they move forward,
forgetting what they were saying the day before, and why. At times the shifting
conversation appears to have no rhyme or reason.
Wall Street is fond of old sayings about how only the paranoid and the fittest
survive. I would phrase the issue a bit differently. The challenge is how to
channel a wise paranoia in the service of survival. Every crisis is greeted as a
enewed call to action, and the bigger the crisis, the more frantic the action.
Years after 2008 the fear of more big losses still runs so high that Wall Street’s
iggest players are likely to watch returns monthly rather than yearly, which
pressures money managers to trade constantly in the hope of avoiding even a
single bad month. This is happening despite evidence that gains are now more
likely to accrue to investors who trade less, proving, as one wag put it, that
“sloth is a virtue.”
In the summer of 2014, after many safaris, I saw a big cat actually catch its
prey for the first time, in Tanzania. Late one afternoon my friends and I came
upon a cheetah, panting hard after, our guide told us, two failed chases earlier in
the day. Over the next two hours, the cheetah waited in a little dugout as it
ecovered its
eath; the light faded with evenfall, and the wind shifted to ca
y
its scent away from a solitary male gazelle. When conditions were right, the
cheetah made its move, creeping slowly, slowly, low and unseen through the
short savannah grass to within fifty yards of its target. Then it accelerated to
sixty miles per hour and—in a zigzag final dash that took fractions of a second—
ought down the gazelle.
More telling than the burst of speed was the stillness that preceded it. Big
cats are programmed to survive by conserving energy, not to waste it in constant
motion. The most common sighting of a lion involves watching them take a nap;
they are known to sleep eighteen to twenty hours a day. When cats do succeed
on the hunt, they try not to expend much effort on battles over the meal. And
they don’t panic over cyclical turns in the weather. During the violent afternoon
ains that sweep the Masai Mara plains in Kenya, I’ve watched the wild animals
stop where they are and stand stock still—predators within striking distance of
their prey—until the deluge ends. They seem to understand instinctively that
cloudbursts are one beat in the normal rhythm of their days and that panic will
only lead to greater chaos.
Many accomplished survivalists inhabit the jungle, and not all are big cats.
The best defenses belong to the hulking vegetarians, the elephants and the
hinos. Even a lion pride will rarely take on a seven-ton elephant with six-foot
tusks. The best spies may be the wildebeest, with their network of baboons and
irds. The best hunters may be the hyenas, who despite their popular depiction
as thieving scavengers are among the most successful large predators. Unlike the
cats, a hyena has endurance, can run down virtually any animal, and does not
target mainly the old and infirm. Moving in packs of up to sixty, hyenas fear no
prey. On the plains of the Serengeti, I once saw a pride of lions cede its kill to a
pack of twenty persistent hyenas.
Early on in my career, painful experience taught me that anyone who wants
to survive longer than the five-year political and economic cycles that buffet the
global economy needs to abso
a few laws of the jungle. Do not expend energy
on daily or quarterly blips in the numbers. Adapt to a changing landscape rathe
than let ego obstruct a strategic retreat. Focus on big trends, and watch for the
crossings. Build a system to spot important signs of change, even when everyone
around you is comfortably going with the cu
ent flow. Over the past twenty-five
years I have spent long hours on the road, trying to build a system of rules fo
spotting telltale shifts in economic conditions.
What goes for survival in the wild and on Wall Street also goes for the
survival of nations in the world economy. There is no one role model. Every
nation is equally vulnerable to the cycles of boom and bust that kill off most runs
of strong economic growth and that ultimately transform sprinting cheetahs into
exhausted cats. The waves of crisis following the 2008 global meltdown crippled
many economies, weak and strong, developed and developing. Following the
well-established patterns of economic development, the new stars of a new era
are likely to emerge from nations that are overlooked as scavengers and slow-
footed vegetarians and whose rise is starting without a lot of hype. Anyone
trying to understand the rise and fall of nations needs to internalize the fact that
the global economy is a noisy jungle; booms, busts, and protests are part of its
normal rhythms. What follows is my guide to identifying the ten telltale signs of
major turns for the better or worse, even those that don’t make a sound.
THE RISE AND
FALL OF NATIONS
Introduction
IMPERMANENCE
IN THE YEARS BC—BEFORE THE CRISIS OF 2008—THE WORLD
enjoyed an unprecedented economic boom that extended from Chicago to
Chongqing. Though the boom ran for only four years and its foundations were
thin, many observers saw it as the beginning of a golden age of globalization.
Flows of money and goods and people would continue to expand at a record
pace, increasing wealth and spreading it as well. More poor nations would ente
the ranks of the rich nations. More of their citizens would escape poverty and
earn a comfortable living, na
owing the gap between the 1 percent and the rest.
With their newfound clout, the rising global middle class would put pressure on
dictatorships to loosen censorship, hold genuine elections, and open up new
opportunities. Rising wealth would beget political freedom and democracy,
which would beget greater prosperity.
Then came 2008. The years BC gave way to the years AC. After the Crisis,
the expectation of a golden age gave way to a new reality. Hype fo
globalization yielded to mutterings about “deglobalization.” The big picture is
complicated and contradictory, because not all the flows that globalization
traditionally describes have slowed or reversed. The flow of information, as
measured by Internet traffic, for example, is still surging. The flow of people, as
measured by the number of tourists and airline passengers, is rising sharply. But
overall the number of economic migrants moving from poor countries to rich
ones has fallen, despite the heated controversy that
oke out in 2015 ove
Muslim refugees from Syria and Iraq. And the flows of money that most directly
influence economic growth—capital flows between nations and trade in goods
and services—have slowed sharply.
Nations have been turning inward, rebuilding ba
iers to trade and fencing
themselves off from their neighbors. In the 2010s, for the first time since the
1980s, global trade has been growing more slowly than the global economy. Big
international banks have pulled back to within their home borders, afraid to loan
international banks have pulled back to within their home borders, afraid to loan
overseas. After surging for more than three decades, flows of capital reached a
historic peak of $9 trillion and a 16 percent share of the global economy in 2007,
then declined to $1.2 trillion or 2 percent of the global economy—the same share
they represented in 1980.
When money dries up and trade recedes, so does economic growth. National
economies often suffer recessions, but because there are always fast-growing
nations somewhere in the world, the global economy rarely shrinks as a whole.
The International Monetary Fund therefore defines a global recession not in
terms of negative GDP growth but in terms of falling income growth, job losses,
and other factors that make the world feel like it is in the grips of a recession.
According to the IMF, there have been four such instances: in the mid-1970s, the
early 1980s, the early 1990s, and 2008–9. In all four cases, global GDP growth
fell below 2 percent, compared to its long-term growth rate of 3.5 percent.*
Global growth also dropped under 2 percent in 2001, when the U.S. tech bu
le
urst. For practical purposes, then, it can be said that there have been five
worldwide recessions since 1970, and they had one thing in common. They all
originated in the United States.
But the next global recession is likely to be “made in China,” which in recent
years has risen to become the world’s second largest economy and single largest
contributor to annual increases in global GDP. In 2015, owing to the slowdown
in China, the global economy grew at a pace of just 2.5 percent, and by year end
was teetering on the
ink of another recession. China’s slowdown is hitting
fellow emerging nations particularly hard. Excluding the Middle Kingdom, the
other emerging nations are growing at an average pace of barely above 2
percent, which is slower than the much richer economy of the United States. The
average income of these poor and middle-class nations is no longer catching up
to that of the world’s leading economy. From Brazil to South Africa, emerging
economies are falling down the development ladder. The sense of possibility
created by rising global prosperity has transformed into a scramble to find a
survivable niche.
This is a world disrupted. The hope that prosperity would beget freedom and
democracy has faded as well. Every year since 2006, according to Freedom
House, the number of countries registering a decline in political rights has
outstripped the number registering an increase. In all, 110 countries, more than
half the world’s total, have suffered some loss of freedom during the past ten
years.1 The number of democracies has not changed dramatically, but repression
is on the rise even in countries, like Russia, that keep up the appearance of
elections. Few observers argue anymore that prosperity in China will lead to
democracy. They point instead to the rise of a new and increasingly assertive
form of authoritarianism, led by Russia and China and marked by regimes that
eject democracy as a universal value while defending softer forms of political
epression as expressions of unique national cultures.
The big blow to global prosperity and political calm came around 2010, as
the economic slowdown spread from the United States and Europe to the
emerging world. In the previous decade, the world had seen an average of about
fourteen episodes of major social upheaval each year, but after 2010 that numbe
shot up to twenty-two, fueled in many cases by growing middle-class anger at
ising inequality and at aging regimes that had grown co
upt and complacent in
the comfortable BC era.
The first big wave of revolt came in the Arab Spring, when protests fueled
y rising food prices sti
ed hopes that new democracies would take root in the
Middle East. Those expectations were dashed by the return of dictatorship in
Egypt and the out
eak of civil war from Libya to Syria. By 2011, the revolts
were spreading to the bigger emerging nations. These protests were driven by
economic grievances compounded by the global slowdown: by inflation in India,
political cronyism in Russia, and wages and working conditions in South Africa.
This unrest culminated in the summer of 2013, when millions of people joined
demonstrations in cities across the fading-star economies of Brazil and Turkey.
The American playwright Arthur Miller once observed that an era has
eached its end “when its basic illusions are exhausted.”2 Today the illusions of
widening prosperity that defined the pre-crisis era are finally spent. The last to
die was the faith that China’s boom would last indefinitely, lifting up countries
from Russia to Brazil, from Venezuela to Nigeria, which had been thriving
mainly by exporting commodities to the Chinese. Ever-growing demand from
China would drive a “super cycle” of rising commodity prices and growing
wealth from Moscow to Lagos. This storyline began to strain credulity by 2011,
when prices for copper and steel started to fall. It collapsed completely in late
2014, when the price of oil dropped by more than half in a span of months.
Nothing illustrates the impermanence of global trends better than the fate of
the most-hyped emerging nations of the 2000s, Brazil, Russia, India, and China.
Marketers rolled them into the acronym BRICs, to capture the idea that these
four giants were poised to dominate the global economy. Today the acronym is
often qualified with an adjective like
oken or crumbling, dismissed as a
“bloody ridiculous investment concept,” or reshuffled into a new acronym like
CRaBs, to capture how ungainly China, Russia, and Brazil look now. In the AC
era, the annual GDP growth rate of China has fallen from 14 percent to private
estimates of less than 5,3 of Russia from 7 percent to negative 2, and of Brazil
from 4 percent to negative 3. Of the original BRICs, only India has any hope of
growing anywhere near as fast in the 2010s as it did in the 2000s.
The unease of the AC era has been magnified by the rosiness of the
preceding boom and by the fact that so few observers saw the crisis coming. The
world looked forward to endless good times and instead got hard times. It
anticipated rising demand from the emerging middle class and instead, in many
countries, got falling demand from an angry middle class. In this tense global
scene, the standard fear of inflation has given way to fear of deflation, or falling
prices, which in some cases can be even more damaging for economic growth.
The hot names of the BC era have fallen deeply out of fashion. As money
flows dried up and reversed, the cu
encies of emerging nations have weakened
sharply. After attracting positive flows of capital every year since recordkeeping
egan in 1978, the emerging world saw an outflow of capital for the first time in
2014 and in 2015 the dam burst, with a massive outflow of more than $700
illion. This sudden loss of funding makes it more difficult for these nations to
pay foreign debts. Many emerging nations that fought hard to dig their way out
of debt are relapsing, becoming troubled bo
owers again. At the height of the
BC-era boom in 2005 the IMF had conducted zero rescue operations and looked
about ready to fold its bailout business, but it came roaring back in 2009 and
since then has been launching ten to fifteen new assistance programs each year,
from Greece to Jamaica.
In the AC era, the perils of growth are more widely acknowledged. The
global expansion that began in 2009 is on track to be the weakest in post–World
War II history. In 2007, just before the financial crisis hit, the pace of growth
was slowing in only one emerging economy out of every twenty. By 2013, that
atio was four out of five, and this “synchronized slowdown” was in its third
year, the longest in recent memory. It had ca
ied on longer than the
synchronized slowdowns that hit the emerging world after Mexico’s peso crisis
in 1994, or the Asian financial crisis in 1998, or the dot-com bust in 2001 o
even the crisis of 2008.4 As the sluggishness spread, the old hunt for the next
emerging-world stars gave way to a realization: Economic growth is not a God-
given right. Major regions of the world, including the Byzantine Empire and
Europe before the Industrial Revolution, have gone through phases stretching
hundreds of years with virtually no growth.
At Goldman Sachs, researchers looked back 150 years at countries that had
posted long runs of subpar growth and had seen their average income slip
elative to their peers. They found ninety such cases of stagnation that lasted at
least six years, including twenty-six that spanned more than ten years. These
least six years, including twenty-six that spanned more than ten years. These
slumps hit countries ranging from Germany in the 1860s and ’70s to Japan in the
1990s and France in the 2000s. The longest stagnation lasted twenty-three years
and struck India starting in 1930, while the second longest lasted twenty-two
years in South Africa, starting in 1982. These stagnations are not as famous o
well studied as the postwar Asian growth “miracles” that ran for decades and
lifted Japan (before 1990) and some of its neighbors to rich-nation status. But
stagnations are at least as common as miracles and are perhaps more relevant to
the AC era.
It’s vital to understand that even the business cycle cannot be relied on to
evive nations in a predictable, linear way. Once an economy contracts beyond a
certain point, it can lose its capacity to self-co
ect. For example, a normal
ecession will raise unemployment and lower wages, which will eventually lead
to a new cycle of hiring and a recovery. If the recession is too long and deep,
however, it can destroy the skills of the labor force, trigger widespread
ankruptcies, and gut industrial capacity, leading to an even longer downturn.
The buzzword for this threat is “hysteresis,” which describes a period in which
slow or negative growth begets slower growth rather than recovery. In the
sluggish AC era, the new fear is that some nations may now be stuck in this
condition.
The fleeting and difficult nature of strong growth is now plain to see, and it
aises a simple question. How, in an impermanent world, can we predict which
nations are most likely to rise and which to fall? What are the most important
signs that a nation’s fortunes are about to change, and how should we read those
signs? To help navigate the normal condition of the world—an environment
prone to booms, busts, and protests—this book outlines ten rules for spotting
whether a country is on the rise, on the decline, or just muddling through.
Together the rules work as a system for spotting change. They are most
applicable to emerging nations, in part because those nations’ economic and
political institutions are less well established, making them more vulnerable to
political and financial upheaval. However, as I will show along the way, many of
the rules find useful applications in the developed world.
Pattern Recognition: The Principles Behind the Rules
A few basic principles underlie all the rules. The first is impermanence. At the
height of the 2000s boom, a variety of global forces—easy money pouring out of
Western banks, spiking prices of commodities, and soaring global trade—
doubled the growth rate of emerging economies. The scale of the boom was
doubled the growth rate of emerging economies. The scale of the boom was
unprecedented—by 2007, the number of nations expanding faster than 5 percent
eached one hundred, or five times the postwar norm—but forecasters assumed
this freak event was a turning point. Extrapolating from existing trends, they
figured that if all the hot economies stayed hot, the average incomes of many
emerging nations would soon catch up or “converge” with those of rich nations.
This form of straight-line forecasting was hardly new. In the 1960s Manila
won the right to host the headquarters of the Asian Development Bank (ADB)
ased in part on the argument that fast growth in the Philippines made it the
future of Asia. By the next decade, under the dictatorship of Ferdinand Marcos,
growth was stalling, but the ADB headquarters was in Manila for good. In the
1970s similar exercises in extrapolation led some American scholars and
intelligence analysts to predict that the Soviet economy was destined to become
the largest in the world. Instead, it collapsed at the end of the 1980s. By then
forecasters had handed the next century to Japan, but it became the next
economic star to falter.
None of that prevented a new round of excitement in the early 2000s,
focused on the rise of the BRICs, or BRICS (some included South Africa in the
group), and the commodity super cycle. As the hype was peaking around 2010,
the historical pattern for commodity prices—which tend to boom for a decade,
then fall for two decades—was about to reassert itself. Today talk of these
nations fulfilling their destinies as regional economic powerhouses seems like a
dim memory.
Recognizing that this world is impermanent leads to the second principle,
which is to never forecast economic trends too far into the future. Trends in
globalization have e
ed and flowed ever since Genghis Khan secured
commerce along the Silk Road in the twelfth century, and the cycles of business,
technology, and politics that shape economic growth are short, typically about
five years. The election cycle, too, runs for around five years on average, and it
can usher in reform-minded leaders with the potential to shake up stagnant
economies. As a result, any forecast that looks beyond the next cycle or two—
five to ten years at most—is likely to be upended. It also makes nonsense of
ecent talk of the coming Asian or even African century.
One aim of this book is to nudge our discussion of the world economy away
from the indeterminate future to a more practical time horizon of five to ten
years and to the job of spotting the next booms, busts, and protests. Predictions
for the next twenty to one hundred years cannot possibly be fulfilled when new
economic competitors can arise within five years, as China did in the early
1980s, as eastern Europe did in the 1990s, and as much of Africa did in the
2000s. In any five-year period, a new technology can spring seemingly from
nowhere, as the Internet did in the 1990s and as new digital manufacturing
techniques like 3-D printing are doing now. In the postwar period, even the
twenty-eight longest periods of “super-rapid” growth—in which per capita GDP
was rising faster than 6 percent a year—have lasted less than a decade on
average.5 So the longer a streak lasts, the less likely it is to continue. When a
country like Japan, China, or India puts together a decade of strong growth,
analysts should be looking not for reasons the streak will continue but for the
moment when the cycle will turn.
The tendency to believe good times will last forever is magnified by a
phenomenon known as “anchoring bias.” Conversations tend to build on the
point that starts (or anchors) them. In the 2000s, people who handicapped global
economic competition came to believe that double-digit annual GDP growth was
normal for China and that a rate of more than 7 percent was standard in
emerging economies. Those superhigh rates were unprecedented but came to
anchor the conversation. In 2010 the notion that the emerging world was about
to see its average growth rate drop to 4 percent was so far below the anchor that
it would have seemed implausible, even though 4 percent is the average growth
ate of emerging economies in the post–World War II era. In general, the co
ect
anchor for any forecast is as far back as solid data exists, the better to identify
the most firmly established historic pattern. The patterns of boom and bust
described in this book are based on my own research, including a database of the
fifty-six postwar emerging economies that managed to sustain a growth rate of 6
percent for at least a decade.
The habit of hanging on to a poorly chosen and improbable anchor is
compounded by the phenomenon of “confirmation bias,” the tendency to collect
only the data that confirm one’s existing beliefs. During the runaway optimism
of the 2000s, there was a lot of confirmation bias in hype for the BRICS, but in
most periods the prevailing intellectual fashion is pessimism. That is certainly
the greater risk today, when it is hard to convince people that any nation has a
chance to rise, given the rough global conditions. The question to ask, in any
period, is not the typical one: What will the world look like if cu
ent trends
hold? It is, rather, What will happen if the normal pattern holds and cycles
continue to turn every five years or so? In a sense, the rules are all about playing
the right probabilities, based on the cyclical patterns of an impermanent world.
To critics who are thinking that the five-to-ten-year horizon reflects a na
ow
and short-term Wall Street worldview, I would say wait. The chapters in this
ook will show that long runs of strong growth last because leaders avoid the
kinds of excesses that produce credit and investment bu
les, cu
ency and bank
crises and hyperinflation—the various kinds of busts that end economic
miracles. The rules double as a rough guide to long-term economic success.
In countries like Brazil and India, one often hears the argument that if the
government focuses too na
owly on economic growth, then health, education,
and other measures of human development will suffer. But this is a false choice.
The countries with the lowest per capita income also tend to have the worst
human development records. Every year the UN puts out a Human Development
Index (HDI) ranking countries by educational measures like years of schooling,
health measures like life expectancy, and basic infrastructure measures like
access to running water and electricity. A nation’s overall rank on the HDI often
aligns very closely with its ranking for per capita income, which is the result of
its long-term growth record. India, for example, ranks 135 out of 187 countries
on the latest list. Only ten countries with lower per capita income rank higher fo
human development. Only five countries with higher per capita income rank
lower for development.
India has risen in the rankings, but only as its economy grew. Back in 1980,
when there were only 124 countries on the HDI, India ranked one hundredth.
Over the subsequent decades, India’s economy expanded by 650 percent, while
the global economy expanded by less than 200 percent, and as a result India
climbed in the HDI rankings. It now stands at eighty-ninth among the original
124 countries, up eleven spots. However, countries with stronger economic
ecords made bigger gains. China’s economy expanded by 2,300 percent, and its
HDI ranking climbed 30 places, from ninety-second to sixty-second. These gains
are not confined to the poorest countries, either. South Korea’s economy
expanded by 700 percent, and its HDI ranking rose 30 places, from forty-fifth to
fifteenth. There are of course exceptions—the people of South Africa live
unusually short lives for a country with an average income of $6,500, due in part
to a high murder rate and the AIDS epidemic. In countries that have fallen way
ehind their peers on specific development measures, a focus on these issues can
make sense. In general, however, if a country focuses on growth, development
will follow.
The Impractical Science
Public disillusion with the economics profession has been growing, since it
failed to foresee not only the events of 2008 but also the many crises that have
shaken the world before and since. Economists are under attack even within thei
own ranks for being too academic and for being too focused on elegant
mathematical models and theories that pretend humans always act rationally and
on historical data that change too slowly to capture what may come next.
Whether they are players in politics, diplomacy, or business, or are just engaged
citizens, practical people cannot begin to make plans without making an
educated guess as to what is coming next. This book is for those practical
people. They are duly skeptical of crystal balls, but they need to look forward,
and to recognize misleading economic futurology when they see it.
Increasingly, economics is seen as an impractical science. For some
academics, forecasting is an intellectual exercise, and rewards flow from
publishing big ideas. The result is often a one-dimensional or ideological
worldview. Some American and European intellectuals hint that Islamic culture
is too backward to promote rapid growth. Some people on the extreme right
elieve every government action is by definition bad. Liberals often trace strong
growth to democratic institutions, an explanation that can’t account for many
things, including the long boom in Asia from 1980 to 2010, when most regimes
in the region were illiberal.
Often economists and writers oversell the importance of a single growth
factor—the challenge of a remote geographic location, the advantage of liberal
institutions or the favorable demographics of a young and growing population—
as the key to understanding the rise and fall of nations. These factors, the subject
of compelling recent best sellers, are often important in shaping long-term
growth, but in my experience no single factor works well as a sign of how an
economy is likely to change over the next five years. For example, “the curse of
oil” is real: In poor nations that are not prepared to hit the oil lottery, large oil
discoveries tend to
eed co
uption and retard development. But a gut distaste
for co
upt petrostates can blind forecasters to the high likelihood that when
global oil prices enter a boom decade, many oil economies will follow.
It’s important to understand economic theories, but it is equally important to
learn how to apply them and in what combinations and situations. An economy’s
growth rate is the product of multiple factors, and the balance of these factors
will shift over time, as a country grows richer and as global conditions change.
Most mainstream forecasters understand this well but wind up with numbingly
Most mainstream forecasters understand this well but wind up with numbingly
complex systems. Institutions including the World Bank and the IMF count
dozens to hundreds of factors that have a statistically relevant impact on growth,
including everything from the share of university students who are studying law
to “ethno-linguistic fractionalization,” and whether the country in question is a
former Spanish colony.
Practical forecasters need to weed out data that is not forward looking,
eliable, and up to date. People in developed nations who wo
y about
information overload may be surprised by how difficult it is in emerging
countries to obtain solid cu
ent information on basic issues like the size of the
economy and by how e
atically these numbers are revised. In early 2014
Nigeria announced an official GDP number of $500 billion, thus almost
doubling the size of the economy overnight. This transformation attracted
elatively little attention, because people who watch emerging markets have
grown more or less numb to such statistical drama. Only one year before, Ghana
had issued an equally large revision, effectively promoting itself from a poor to a
middle-class country. Commenting on the Indian statistical bureau’s frequent
evisions of official economic data, former central bank governor Y. V. Reddy
once cracked to me that while the future is always uncertain, in India even the
past is uncertain.
Numbers coming out of the emerging world have a strange fluidity and a
way of morphing to meet the self-interest of major players. In China, analysts
skeptical of official GDP growth figures have started checking them against
other indicators, such as cargo traffic and electricity consumption. That check
can be pretty reliable, except that in 2015 reports emerged that government
authorities were instructing developers to keep the lights on even in empty
apartment complexes. The aim was to drive up electricity consumption data so
that it would confirm official economic growth claims. This is a classic case of
Goodhart’s Law, which says that once a measure becomes a target, it ceases to
e useful, partly because so many people have an incentive to doctor numbers to
meet it.6
One useful and timely data source is the prices in global financial markets,
which in normal times will accurately capture the world’s best collective guess
about the likely prospects of an economy. What author James Surowiecki has
called “the wisdom of crowds” has substance, and the market embodies it,
second by second, subject to emotional contagions but not wild revisions.7 A
sharp decline in the price of copper has almost always been an ominous sign fo
the global economy, earning the base metal the moniker “Dr. Copper” in
financial circles. In the United States, one of few countries where most lending
is done through bonds and other credit market products rather than through
anks, the credit markets started sending distress signals well before the onset of
the last three recessions, in 1990, 2001, and 2007. The credit markets also send
false signals on occasion, but for the most part they have been a fairly reliable
ellwether.
Despite their periodic bouts of euphoria and panic, stock markets also have a
track record of anticipating economic trends. Back in 1966 the Nobel Prize–
winning economist Paul Samuelson quipped that the stock market had “predicted
nine out of the last five recessions,” and writers aiming to disparage the
predictive power of markets have often cited him. But Samuelson was no more
impressed by professional economists, who in fact have a worse record than
markets. In a 2014 note Ned Davis Research showed that despite a few big
misses, in which the market tanked in anticipation of a recession that neve
came, the market has been a consistently good predictor of both good and bad
times for the economy. Going back to 1948, the benchmark S&P 500 Index has
on average started to turn down seven months before the peak of an expansion,
and it has started to turn up four months before the bottom of a recession. On the
other hand, Ned Davis reviewed the track record for professional forecasters
who are regularly surveyed by the Philadelphia
anch of the Federal Reserve
and found that as a group, these mainstream economists “called exactly none” of
the last seven recessions, dating back to 1970.8 In the United States, the National
Bureau of Economic Research is the official documenter of recessions, and on
average it has declared recession starts eight months after recessions actually
egan.
Market indicators aside, numbers alone cannot provide a handle on any
nation’s real prospects. Most economists tend to ignore any factor that is too soft
to quantify or incorporate into a forecasting model, even something as basic as
politics. Instead, they study “policy” through hard numbers, like government
spending and interest rates. But numbers can’t capture the energy unleashed by a
new leader’s intolerance for monopolists,
ibe takers, or stonewalling
ureaucrats. No nation has an entitlement to economic greatness, so leaders need
to push for it and keep pushing. My rules, therefore, offer a mix of ways to read
hard data on things like credit, prices, and money flows, as well as softer signs of
shifts in politics and policy.
These are the basic principles: Avoid straight-line forecasting and foggy
discussions of the coming century. Be skeptical of sweeping single-facto
theories. Stifle biases of all kinds, be they political, cultural or “anchoring.”
Avoid falling for the assumption that the recent past is prologue for the distant
Avoid falling for the assumption that the recent past is prologue for the distant
future, and remember that churn and crisis are the norm. Recognize that any
economy, no matter how successful or how
oken, is more likely to return to
the long-term average growth rate for its income class than to remain abnormally
hot (or cold) indefinitely. Watch for balanced growth, and focus on a
manageable set of dynamic indicators that make it possible to anticipate turns in
the cycle.
The Practical Art
These rules emerged from my twenty-five years on the road, trying to
understand the forces of change both in theory and in the real world. The reason
I developed rules at all was to focus my eyes and those of my team on what
matters. When we visit a country, we gather impressions, storylines, facts, and
data. While insight is embedded in all observations, we have to know which
ones have a reliable history of telling us something about a nation’s future. The
ules systematize our thoughts and have been back-tested to determine what has
worked and what has not. Eliminating the inessential helps steer the conversation
to what is relevant in evaluating whether a country is on the rise or in decline.
I have na
owed the voluminous lists of growth factors to a number that is
large enough to keep the most significant forces of change on our radar but small
enough to be manageable. In theory, growth in an economy can be
oken down
in a number of ways, but some methods are more useful than others. Growth can
e defined as the sum of spending by government, spending by consumers, and
investment to build factories or homes, buy computers and other equipment, and
otherwise build up the nation. Investment typically represents a much smalle
share of the economy than consumption, often around 20 percent, but it is the
most important indicator of change, because booms and busts in investment
typically drive recessions and recoveries. In the United States, for example,
investment is six times more volatile than consumption, and during the typical
ecession it contracts by more than 10 percent; while consumption doesn’t
actually contract, its growth rate merely slows to about 1 percent.
Growth can also be
oken down as the sum of production in various
industries, such as farming, services, and manufacturing. Of these,
manufacturing has been declining worldwide—it’s now less than 18 percent of
global GDP, down from more than 24 percent in 1980—but it is still the most
significant force of change, because it has traditionally been the main source of
jobs, innovation, and increases in productivity. So the rules have a lot to say
about investment and factories and much less about consumers and farmers.
Some say manufacturing is going the way of farming, as machines largely
eplace jobs, and my rules are evolving to account for this shift. But for now
manufacturing remains central to understanding economic change.
This is not an argument for tossing out the textbooks, just for zeroing in on
the forces of change that have the strongest predictive qualities. As a case in
point, textbooks talk about the importance of savings in driving investment and
growth, because banks funnel the money saved by households and companies
into investments in roads, factories and new technology. But savings is a
chicken-or-egg issue: It is not at all clear which comes first, strong growth o
high savings. Similarly, this book elaborates on subjects that will be familiar to
many, like the impact of overinvestment and debt binges, the scourges of
inflation and inequality, and the vagaries of political cycles. But there are
hundreds of ways to track and measure these factors, and the issue I try to
address is, for example, exactly how to parse the debt burden of a nation and
how to understand when debt signals a turn for the better or worse.
I eschew factors that matter to growth in the long run but that don’t work
well as signs of change. For example, education is everyone’s favorite way to
oost the talent of the labor force and raise productivity, but my rules pay little
attention to it. The payoff from investment in education is so slow and variable
that it is almost useless as a predictor of economic change over a five-to-ten-yea
period. Many studies have linked the post–World War II booms in the United
States and Britain to the advent of mass public education, but that change began
efore World War I. A recent study by the Centre for Cities think tank found that
the British cities that grew fastest in the 2000s were the same ones that had
invested most in education—in the early 1900s. The economist Eric Hanushek
found in a 2010 report that a twenty-year education reform program could result
in an economy one-third larger—but that increase would register seventy-five
years after the reform program began.
In many postwar cases the economy took off in educationally backward
nations like Taiwan and South Korea. As the Asia expert Joe Studwell has
pointed out, in Taiwan 55 percent of the population was illiterate in 1945, and
that share was still high at 45 percent in 1960. South Korea in 1950 had literacy
levels comparable to Ethiopia’s. In China, as the economy took off in the 1980s,
local officials spent heavily on roads, factories, and other investments that had a
fast impact on growth, because their careers depended on producing high growth
numbers immediately. Schools came later.
Investing in education is often seen as a sacred obligation, like defending
motherhood, and too few questions are asked about whether it is getting the jo
done. In some countries huge expenditures on the university system have had
done. In some countries huge expenditures on the university system have had
almost no economic impact, even over the long term. The emerging nation in
which the population has the highest average years of schooling (11.5) and the
largest share of university grads (6.4 percent) is Russia, where the Soviet era
legacy of excellence in science and technology education has yet to affect the
economy. Russia is still dependent on raw materials, and although it has a few
dynamic Internet companies, it lacks a tech sector to speak of and has been one
the world’s slowest-growing economies in the 2010s.
I also see limited use for various surveys that try, in essence, to make a
science of measuring some of the factors that can contribute to productivity. The
World Economic Forum’s Global Competitiveness Report focuses on twelve
asic categories, but many are slow-moving forces like institutions and
education. Finland, for example, has been near the top of the forum’s ranking
system for a long time, and in 2015 it ranked fourth in the world and first in a
dozen subcategories ranging from primary schools to antimonopoly policies.
Finland was also the survey’s top-ranked European Union country. Yet it
suffered one of the slowest recoveries from the crisis of 2008, far behind the
United States, Germany, and Sweden, and was about on par with the hardest-hit
countries of southern Europe. Finland was paying the price for having let its
debts and wages rise quickly and for its heavy dependence on exports of timbe
and other raw materials at a time when global prices for these commodities was
collapsing. Having good primary schools was no defense for Finland when more
important forces of change were at work.
The World Bank also puts out rankings of countries for everything from
quality of roads to how many days it takes to open a business, and these rankings
have become very popular. That creates a problem, as more than a few countries
have started hiring consultants to help them raise their rankings (anothe
example of Goodhart’s Law in action). In 2012 President Vladimir Putin set a
goal of raising Russia’s rank for “ease of doing business” from 120 to top 20
within six years, and he soon saw results. By 2015, Russia was ranked at 51—
more than thirty places ahead of China, and sixty places ahead of Brazil and
India. That raised a question: If it was so easy to do business in Russia, why
wasn’t anyone doing business there? Moscow in 2015 is increasingly hostile to
and isolated from international business, far more so than China or Brazil o
India. To the extent possible, I try to avoid relying on numbers that are
vulnerable to political manipulation and marketing.
The most significant forces of change vary from year to year and country to
country. In the AC era, the dominant economic storyline has been about debt:
which countries did the most to pay down debts amassed before 2008, and the
surprising number that have dug themselves deeper into debt trying to fight the
surprising number that have dug themselves deeper into debt trying to fight the
subsequent slowdown. As a whole, the world has a bigger debt burden now than
it did in 2008, which is a real issue. But my first chapter is not about the rule on
debt—it’s about people and population, which could have a bigger impact going
forward.
Another simple way to define economic growth is as the sum of the hours
that people work plus their output per hour or productivity. But productivity is
hard to measure, and the results are subject to constant revision and debate. On
the other hand, the number of hours people work reflects growth in the
workforce, which is driven by population growth, which is relatively easy to
count. Unlike economic forecasts, population forecasts depend on a few simple
factors—mainly fertility and longevity—and have a strong record for accuracy.
Before the start of the new millennium, the United Nations predicted global
population for the year 2000 a total of twelve times going back to the 1950s, and
all but one of those forecasts was off by less than 4 percent. The first rule
addresses the economic impact of population growth, and most of the others deal
one way or another with productivity. But I don’t use productivity growth data
directly because they are not reliable.
In a way, population trends are half the story. Since 1960 the global
economy, including both developed and developing countries, has had an
average annual growth rate of about 3.5 percent.† Half of it came from
population growth, more specifically labor force growth, or more people
working more hours. The other half came from gains in productivity. This 50-50
split still holds, with one distressing change, which is that both sides of the
equation are slumping.
The impact of population is very straightforward: a 1 percentage point
decline in growth in the labor force will shave about 1 percentage point off
economic growth. That is roughly what has been happening in the last decade.
Global GDP growth has been trending lower and is now running more than a full
percentage point below its long-term pre-crisis average. It is no coincidence that
since 2005 the growth in the global labor force, ages 15 to 64, has slowed to 1.1
percent, from 1.8 percent over the previous five decades. The implications of
this new population threat to the world economy are dark but not uniform across
countries. The working-age population is already shrinking in Germany and
China; it is growing, but very slowly, in the United States; and it is still booming
in Nigeria, the Philippines, and a few other countries. Slower growth in the
world population may cu
but won’t stop the constant rise and fall of nations.
The rest of the rules deal one way or another with the other half of the global
growth story, which is captured in a loose way by the productivity growth
numbers. Here too the global picture appears at best mixed. Between 1960 and
2005, the average annual productivity growth rate was around 2 percent, but that
ate downshifted by almost a full percentage point in the last ten years. Like
population growth rates, officially recorded productivity growth rates have fallen
y varying degrees, from less than a percentage point in the United States to
more than 2 points in South Korea and nearly 4 points in Greece. But while the
demographic downshift is indisputable, debate rages as to whether the
productivity decline is real.
Productivity growth is the sum of hard-to-quantify improvements in the skill
of workers, in the number and power of the tools they use, and in an elusive x
factor that tries to capture how well workers are employing those tools.‡ That x
factor, which can be influenced by everything from experience using a compute
to better management or better roads to get workers to their workplaces faster, is
the fuzziest part of this difficult calculation. Technoskeptics say that the last
decade’s decline in productivity growth reflects the fact that most recent
innovations involve relatively trivial advances in communications and
entertainment: Twitter, Snapchat and the like. Even with worker training and
experience, these advances will do much less to raise productivity than previous
innovations like electricity, the steam engine, the car, the computer, or ai
conditioning, which was a huge boost to human output per hour in a stuffy office
setting.
Optimists respond that productivity growth measurements aren’t capturing
the cost and time savings produced by new technologies, ranging from artificial
intelligence to increasingly powerful
oadband connections and the nascent
“Internet of things.” In the United States, for example, the cost of
oadband
Internet access has remained flat for many years, but
oadband connections
have grown much faster and gone mobile—a huge time savings that is not
captured in the productivity growth data.9 If the optimists are right, productivity
growth is considerably faster than cu
ent measurements show, and therefore so
is economic growth. Whichever side is right, both would agree that it is easier to
measure population growth, which has a more clear-cut impact on the economy.
Fewer working people mean less economic growth, and this impact has become
more visible worldwide in the last five years.
All the rules try to capture the delicate balances of debt, investment, and
other key factors required to keep an economy humming. Over the course of this
ook, it will—I hope—become clear how the ten rules work together as a
system. To foreshadow the story in
ief, an economy is most likely to begin
ising steadily when the nation is emerging from crisis, has fallen off the radar of
the global markets and media, and has chosen a democratic leader with a
the global markets and media, and has chosen a democratic leader with a
mandate to reform. That leader will create the business conditions to attract
productive investment, particularly in factories, roads, and technologies that will
strengthen supply networks and thus help contain inflation. The probability that
a boom is about to end will rise as a nation gets too comfortable and as private
companies and individuals run up debts to buy frivolous luxuries, particularly
imported luxuries. This period of extravagance will make it impossible for the
nation to pay its foreign bills, while widening the gap between billionaires and
the rest, and between the countryside and the nation’s capital, provoking a
political backlash that
ings down the now aging regime, after which the cycle
can begin again.
The book’s final chapter sketches how the top emerging and developed
nations rank on the ten rules at a given point in time. The rankings change
constantly, so the last chapter merely offers a snapshot of how the rules work as
a system. The approach makes no promise of certainty in an impermanent world,
and the most it can hope to achieve is to improve the probability of spotting the
next shifts in the constant rise and fall of nations. It is a system for handicapping
global economic competition as a practical art rather than as an impractical
science. There are no sweeping forecasts for the year 2050, only an objective
effort to identify the most plausible outlook for the next five to ten years. The
aim: a practical person’s guide for spotting the rise and fall of nations, in real
time.
* Global GDP growth is measured here in market-determined exchange-rate terms.
† This figure refers to potential growth, which we calculate by taking the sum of productivity growth and
employment growth from the Conference Board Total Economy Database.
‡ Technically, productivity growth is the sum of increases in labor quality, capital deepening, and total
factor productivity.
1
PEOPLE MATTER
Is the talent pool growing?
AT FIRST I DIDN’T THINK THERE WAS MUCH MYSTERY TO the
lackluster global recovery. After 2008, when the United States fell into a deep
ecession and the world soon followed, economists argued that the recovery
would be painfully slow because this was a “systemic crisis,” not an ordinary
ecession, and I was persuaded. Their research showed that following a crisis
that devastates the financial system, an economy typically experiences weak
growth for four to five years even after the end of the recession. But as each yea
passed—five, six, seven—the global economy continued to perform more
weakly than expected. By 2015, there was still not a single major region of the
world where economic growth had returned to its pre-crisis average. I became
convinced that the sluggish recovery was not normal. It was a mystery: Where
was the missing growth?
Economists have put forth many reasons to explain why the world has been
slogging through its weakest recovery in the postwar era. Most of the
explanations focus on the way severe credit crises can depress the demand side
of the economy, as consumers and companies struggle to work off their debts
and slowly regain the confidence to spend money. Others blame weak demand
on rising income inequality, the regulatory crackdown on bank lending, or some
other symptom of postcrisis stress disorder. While all these arguments may have
some merit, the evidence is mixed as to what impact these factors had on
economic growth. In the United States, there are clear signs that consume
demand fully recovered by 2015: Car sales have hit new highs and job growth is
unning at a
isk pace, yet the headline GDP growth number is still well below
its pre-crisis pace. As often happens in a good mystery, perhaps the detectives
have been looking in the wrong place.
My team and I turned our attention from the arguments that primarily focus
on demand to those concerning supply, the side of the economy that supplies
labor, capital, and land, the basic inputs to growth. We found an unexpected
culprit. One critical cause of the missing growth was, of all things, a shrinking
supply of people in the active workforce. This finding was so thoroughly at odds
with popular fears about how human jobs are being replaced by the rise of robots
and artificial intelligence, it seemed hard to accept at first. How could too few
workers be a problem if technology has made them obsolete? But in this case at
least, numbers don’t lie.
A collapse in population growth was already under way before the 2008
crisis, and in fact it can explain a good chunk of the persistently disappointing
ecovery since. As we’ve seen, one simple way to measure an economy’s
potential to grow is by adding productivity growth and labor force growth, and
while both have slumped worldwide, the productivity slowdown is widely
disputed, since many experts think the official statistics are undercounting the
impact of new digital technologies. In the United States, by the official numbers,
productivity grew at an average pace of 2.2 percent between 1960 and 2005
efore slowing to just 1.3 percent in the past ten years. The population
slowdown was even more dramatic, and it is not in dispute. In the five decades
efore 2005, the U.S. labor force grew at an average annual pace of 1.7 percent,
ut slowed to just 0.5 percent over the past decade. In short, the clearest
explanation of the missing economic growth in the United States is the roughly 1
percent decline in labor force growth, which is largely a function of growth in
the population of working-age people, between 15 and 64.
The world still echoes with recu
ing fear about the “population bomb”
scenarios, which suggest that the number of people will outstrip supplies of food
and other resources, with explosive results. Those scenarios rely on the United
Nations’ oft-cited forecast for the year 2050, which shows that population will
ise by 2.4 billion people, from 7.3 billion to 9.7 billion. A number close to ten
illion may sound frighteningly high, but the UN forecast in fact takes into
account a dramatic slowdown in the population growth rate. Many fewer babies
are being born, and fewer young people are entering the working-age cohort,
while the overall population is growing mainly because people are living longer.
This mix is toxic for economic growth.
For much of the post–World War II era, global population grew at an
average of nearly 2 percent annually, which meant that the world economy could
also expect to grow at a baseline rate of close to 2 percent—and a couple of
percentage points more than that when output per worker was also growing.
Then around 1990 global population growth just fell off a cliff. The growth rate
Then around 1990 global population growth just fell off a cliff. The growth rate
has since halved to just 1 percent. The difference between 1 and 2 percent may
not sound like much, but if the population growth rate had stayed at 2 percent
since 1990, the global population today would be 8.7 billion, not 7.3 billion. The
world would not be aging so rapidly, and we would not be talking about
population’s impact on economic growth.
The economic impact of the decline in the population growth rate has taken
time to show up, because it takes a while for babies to reach the working age of
15. Of course, in many places people don’t actually start working until they
each 20 or 25, depending on how long they stay in school. So it takes fifteen
years or more for a baby bust to have a clear impact on the population
contribution to economic growth, which has become increasingly clear in the last
five years.
The fall in the global population growth rate was the delayed result of
aggressive birth control policies implemented in the emerging world in the
1970s, particularly the one-child policy China instituted in 1978. In emerging
and developed countries, the population slowdown was also fueled by rising
prosperity and education levels among women, many of whom decided to pursue
a career and have fewer children or none at all.
The roots of this demographic shift lie in basic changes in mortality and
fertility rates over the last half-century. Since 1960 advances in science and
health care have allowed people to live longer