CEPR
CENTER FOR ECONOMIC AND POLICY RESEARCHThe Scorecard on
Development, 1960–2016:
China and the Global
Economic Rebound
By David Rosnick, Mark Weisbrot, and Jacob Wilson*
October 2017

Center for Economic and Policy Research1611 Connecticut Ave. NW
Suite 400
Washington, DC 20009

tel: 202–293–5380
fax: 202–588–1356
www.cepr.net* David Rosnick is an Economist at the Center for Economic and Policy Research (CEPR) in Washington, DC. Mark Weisbrot is the
Co-Director and an Economist at CEPR. Jacob Wilson is an International Program Intern at CEPR.

Contents
Introduction ........................................................................................................................................................ 1
Two Measures of World Growth and the Effects of China and India ...................................................... 4
Economic Growth Since the Last Report ...................................................................................................... 7
Approach............................................................................................................................................................. 9
Economic Growth ............................................................................................................................................. 9
Mortality and Life Expectancy .......................................................................................................................10
School Enrollment ...........................................................................................................................................17
Miscellaneous Indicators .................................................................................................................................20
Chinese-Led Growth .......................................................................................................................................23
Conclusion ........................................................................................................................................................25
Appendix ...........................................................................................................................................................28
References .........................................................................................................................................................30

Acknowledgements
The authors thank Jake Johnston and Lara Merling for research assistance, and Rebecca Watts and
Dan Beeton for editorial assistance.

Introduction
In his last speech at the United Nations, then President Barack Obama hailed the economic and social
achievements of globalization for the developing world. In doing so, he noted:“Over the last 25 years, the number of people living in extreme poverty has been cut from nearly 40
percent of humanity to under 10 percent.”1
According to World Bank data, this is true.2 Like many political leaders, Obama attributes this successas measured by poverty reduction ― while simultaneously recognizing various shortcomings ― to“globalization,” including “the principles of open markets.”
But the story behind the numbers is vastly different from Obama’s narrative. For the 25 years that herefers to, two-thirds of the approximately 1.1 billion people who were pulled across the extreme
poverty line were in China.3 If we go back a bit further, and look at the period from 1981 to 2010, it
is even more a story of Chinese success: about 94 percent of the reduction of extreme poverty was in
China.4
Not only that, but as noted below, much of the remaining third of the reduction in extreme poverty
during the past 25 years was also attributable to China, and it happened in the twenty-first century,
when China rapidly became one the largest importers in the world of other developing countries’
exports,5 as well as a source of hundreds of billions of dollars of loans, direct investment, and aid.6
If the story of globalization’s success ― never mind its failures ― is mainly a story of Chinese
globalization, then it must be a very different story than the standard narrative. Chinese global
economic integration was not based on the neoliberal reforms and policies that were adopted by thevast majority of low- and middle-income countries since the 1980s. China did not establish an
independent central bank or abandon the industrial and development policies of prior decades, as
most low- and middle-income countries did. They maintained state control over the banking system,
had strict currency controls and a huge role for state-owned enterprises, and until recently the state
controlled most investment. Foreign investment was regulated to make it compatible with statedevelopment planning. Technology transfer and other performance requirements ― conditions

1 Obama (2016).
2 There are some disputes about this poverty data and its interpretation. See, for example, Sumdaram (2016) and Reddy and Lahoti(2016).
3 Hofman (2016).
4 Olinto, et al. (2013).
5 IMF DOTS (2017a).
6 Cooper (2016).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound1

attached to foreign investment to make sure that the host country gets some benefit from foreign
investment, such as the use of locally produced inputs, or the hiring of local managers7 ― werecommon and are still an issue of contention with the United States today.8
The story that actually happened has quite different implications for what we can learn from history
about economic policy than does the standard narrative. Of course, much of the Chinese model would
not apply to most low- and middle-income countries because China was transitioning from a planned
to a mixed economy. (The comparison with other transition economies is still relevant, since China
sustained the fastest-growing economy in world history for decades during its transition, while Russia
and most other former Soviet states went through serious depressions and of course never came close
to China’s performance when they recovered). But in any case there would still be a lot to learn fromthe Chinese experience, possibly more than from the prevailing orthodoxy in most of the rest of thedeveloping world.
It is not only political leaders and journalists that seem to conflate Chinese globalization with theexperience of most of the world, in evaluating the economic and social progress of recent decades. A
number of economists have done the same.
Richard Baldwin, in his 2016 book “The Great Convergence: Information Technology and the New
Globalization,” presents a comprehensive theory of globalization that portrays the global integration
since 1990 ― as distinguished from previous periods ― as driven by advances in communications
technology. For Baldwin, these advances, which drastically lowered the cost of moving ideas, reversed
a centuries-long trend of “The Great Divergence” ― where the gap between rich and poor nations,in terms of manufacturing output, increased. He writes:
From 1990, the trend flipped; a century’s worth of rich nations’ rise had been reversed in justtwo decades. Their share [of manufacturing output] is now back to where it was in 1914. This
trend, which might be called the “Great Convergence,” is surely the dominant economic factof the last two or three decades.9
He is referring to the share of world manufacturing belonging to the G-7 countries, which fell from65 to 47 percent from 1990 to 2010. He notes that these 18 percentage points were gained by just six
countries (China, South Korea, India, Poland, Indonesia, and Thailand), while the rest of the world
stayed roughly the same at about 28 percent.

7 KPMG (2017).

8 Donnan (2017).
9 Baldwin (2016a), p1.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound2

However, more than 80 percent of the convergence went to China, with the rest being shared by theremaining five countries ― including India and Indonesia, home to more than 1.6 billion people.10
Therefore, the “Great Convergence” in manufacturing is, at least so far, primarily a Chinese
phenomenon.
Clearly, the lumping together of China with other groups of low- and middle-income countries canobscure, if one is not careful, how narrowly distributed the gains from globalization have been, bycountry; although Baldwin notes that even six countries is a surprisingly small group. But mostimportantly, since China’s economic policies during this period were so different from most of thedeveloping world, the standard aggregation makes it difficult to get even a cursory look at the net
effect of the most widespread policy changes of the era.
One way to get a first look at what the net effect of what such widely adopted policy changes might
have been is to compare the era of neoliberal reforms with that of prior decades. We first did that in2001, and found a sharp drop-off in the rate of growth of GDP per capita for the vast majority oflow- and-middle-income countries for the last two decades of the twentieth century, as compared withthe prior two decades (1960–1980).11 There was also a broad decline in the rate of progress on healthand some social indicators, including life expectancy, infant and child mortality, adult mortality, andeducational attainment.
The methodology for the comparison is relatively simple. We would expect diminishing returns interms of growth rates, as developing countries would typically grow faster than high-income countries.
And we would also expect diminishing returns in the case of health indicators; e.g., it would
presumably be more difficult to advance 10 years in life expectancy from a starting point of 70 thanof 50. In order to adjust for diminishing returns, we compared groups of countries that began at a
certain level of per capita GDP in 1960, with those that started at the same level of per capita GDP
in 1980 ― rather than simply looking at what happened to growth rates for the same group ofcountries over time. The same methodology was applied to comparisons of health and social
indicators. Of course, in some regions the growth collapse of the 1980–2000 period was so profoundthat it was obvious even without controlling for diminishing returns, or looking at country averages.
In Latin America, for example, regional per capita GDP grew by 91.5 percent from 1960 to 1980, butjust 5.7 percent from 1980 to 2000.
We returned to the comparison, including all countries for which there was data, five years later andfound mostly similar results.12 But by 2011, a noticeable rebound had occurred, both in GDP per
10 See Baldwin (2016a) and (2016b).
11 Weisbrot et al. (2001).
12 Weisbrot, Baker, and Rosnick (2005).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound3

capita and in progress on some of the major health and social indicators. Some possible reasons forthe rebound were discussed in our 2011 paper13 and elsewhere,14 and are noted below. This paper
updates the prior comparisons with the latest data from additional years of the twenty-first century.

Two Measures of World Growth and the Effects ofChina and India
There are many ways in which we may examine growth of economic activity in the world. One way
would be to treat the world as a single economy: we may total the gross domestic product of every
country, divide by the total population, and observe how fast this grew each year. A second approach
would be to simply average per capita growth rates among countries; rather than treating the world asa single economy, this would describe the average experience across countries. Finally, we might also
weight such per capita growth rates by population to observe the experience of the average person.
From a policy perspective, the second of these ― looking at the averages across countries ― makes
the most sense. Each country represents a distinct observation with different economic policy choices.
We would not want to say that countries followed successful policies of development because “China
and Honduras” grew rapidly any more than one would want to say “Bill Gates and I are rich”; rather,
we would want to say countries have a mixed record with large-economy China succeeding and smalleconomy Honduras less so. True, China’s policy affected a much larger share of the world’s populationand of the world’s economy; but it still represents one policy experiment, as does Honduras’.15
It may be that these measures do not much differ. Briefly, then, we will compare the first two
approaches. We will then examine the effect of removing China and/or India from the analysis so as
to observe their impact on each measure. Obviously, removal of one or two countries will have little
effect on the unweighted average growth across countries. However, these countries represent asignificant fraction of the world economy and therefore their exclusion may have a noticeable effecton the world’s growth when the world is taken as a single economy.
In Figure 1, we have linked year-to-year growth rates to create per capita GDP measures indexed to1950. The “Country Average” line is based on the simple average of country growth rates, so China
and Honduras are equally weighted. Over the 65 years from 1950 to 2015, this measure suggests thatper capita GDP has risen by 329 percent (indexed value of 4.29) — a bit under 2.3 percent per year.
The other data takes the world as a single economy, and indicates a 297 percent increase (or little more
13 Weisbrot and Ray (2011).
14 Weisbrot (2015), Chapter 3.
15 Certainly, development policy is not the only factor in a country’s economic growth.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound4

than 2.1 percent per year). This measure weights larger economies more heavily, and therefore
indicates that overall, growth has been a little slower in larger economies in comparison to smaller
ones.
FIGURE 1
World Growth in Real, Per Capita GDP
4.5
4.29
3.97

4.0

Index (1950 = 1)

3.5

3.0

2.5

2.0

1.5

1.0
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Country Average

World as Single Economy

Sources: Feenstra, Inklaar, and Timmer (2015) and IMF WEO (2017b).

This is not overly surprising as economies may be larger due to a larger population or to a higher levelof development; and we would expect less-developed countries to grow more rapidly. It is perhaps
more surprising that the gap is not wider.
In Figure 2, we consider the removal of China and/or India. In the upper left, we have the world —as complete as data allows. The graphs to the right exclude India, and the graphs in the second row
exclude China. As the figure shows, the effect of excluding India is very small — very slightly
narrowing the gap between the measures of per capita GDP growth by just two-hundredths of apercentage point.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound5

FIGURE 2
World Growth in Real, Per Capita GDP (Under Different Scenarios)
4.5

4.29
3.97

Index (1950 = 1)

4

4.5

3.5

3

3

2.5

2.5

2

2

1.5

1.5

1960

1970

1980

1990

2000

1
1950

2010

3.98

4

3.5

1
1950

4.28

1960

1970

World
4.5

4.25

4

1990

2000

2010

4.5

4.24

4

3.5

3.24

3.5

3

3

2.5

2.5

2

2

1.5

1.5

1
1950

1980

Excluding India

1960

1970

1980

1990

2000

2010

1
1950

3.22

1960

1970

Excluding China

1980

1990

Excluding China and India
Country Average

Sources: Feenstra, Inklaar, and Timmer (2015) and IMF WEO (2017b).

The Scorecard on Development, 1960–2016: China and the Global Economic ReboundWorld as Single Economy

6

2000

2010

On the other hand, excluding China from the calculation greatly reduces growth in the world
economy. On the whole, per capita GDP growth in the non-China world has slowed since the 1970s.
Yet, as the other measure indicates, countries have — on average — resumed growth since the 1990s.
That recent non-China growth has been lower when more heavily weighting large countries suggeststhat China has been a significant outlier among large economies. We will take this into account inmore careful analysis later.

Economic Growth Since the Last Report
In the aggregate, world economic growth was nearly unchanged in 2010–2015 when compared to
2000–2010 — at 3.9 percent annualized, compared to 4 percent, respectively. 16 However, a muchhigher decline can be seen when averaging countries’ growth as compared to aggregating the world asa single economy. The average rate of growth fell from 2.8 to only 1.8 percent per capita per year,with every region slowing, from 2010 to 2015. Figure 3 shows this comparison for the country
average, by region.

16 IMF WEO (2017b).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound

7

FIGURE 3
Regional Growth by Country Average 2010–2015 vs. 2000–2010
8
7.13
7

6

5

4

3.63

3.89

3.81
3.26

3
2.30
2

2.26
1.90 1.81

1.86

1.69

1.98

1.60

1.14

1.13
1

0
-0.48

-1
Advanced
Commonwealth of
Economies (NonIndependentEuro)
StatesEmerging andEmerging andDeveloping Asia Developing Europe
Simple Average (2000–2010)

Eurozone

Latin America &The Caribbean

Middle East &North Africa

Simple Average (2010–2015)

Source: IMF WEO (2017b).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound8

Sub-SaharanAfricaApproachIn the figures that follow, we describe worldwide progress by initial level and period. The worldconsists of all countries observed up to three times each — beginning in 1960, 1980, and 2000. 17
These country periods are pooled, then divided into quintiles; the quintile groups are only thenseparated by initial year of observation. Each figure shows the growth in the unweighted average foreach of the 15 groups (i.e., five quintiles for each initial starting year). Within each quintile then, allobservations are of similar initial level regardless of the time period. This allows a simple
comparison of progress across time without undue concern for diminishing returns.

Economic Growth
Figure 4 shows economic growth for each quintile of worldwide income. The quintiles are definedby start-of-period gross domestic product (GDP) per capita in 2011 international dollars, adjusted forboth inflation and for purchasing power parity (PPP). Growth in per capita GDP, however, is basedon each country’s national accounts adjusted only for inflation.
FIGURE 4
Real, Per Capita GDP

Annualized Growth (Percent)

4
3.41

4
2.98

3
3

2.92

2.99

3.18
2.90

2.45
2.20

2.16

2.33

2
1.45

2
1

1.33

0.99

0.93
0.70

1
0
<$1520$1520-2900$2900-7020$7020-14500>$14500

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

1960–1980

Sources: Feenstra, Inklaar, and Timmer (2015) and IMF WEO (2017b).

As Figure 4 clearly shows, average growth in per capita GDP slowed considerably over 1980–2000 incomparison to 1960–1980. This slowdown occurred across the full range of incomes. For quintiles 1through 4, growth increased again in the 2000–2015 period. There is nothing special about the dates
17 For more explanation see Weisbrot and Ray (2011).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound9

selected here. If we were to cherry-pick, we might find that 1980–1995 was an especially poor period:
the latter half of the 1990’s looked more like the 2000s than the 1980s. And including the 1970s in thefirst period ensures that we are not using a baseline that has extraordinarily favorable circumstances:the decade contained two major oil shocks that led to world recessions, as well as high inflation. If thefifties were included, the baseline period would have been stronger.
The slowdown in per capita GDP growth in the second time frame is quite large, especially over a 20year period. For example, a country starting out in the second quintile in 1960 would, on average,
increase its per capita income by 62 percent over the ensuing two decades; in 1980, the corresponding
increase would be just 15 percent.

Mortality and Life Expectancy
There is a very high cross-country correlation between life expectancy, and other measures of health,with income, although there is controversy over the causal relationship.18 This relationship also shows
up in our examination of the changes in per capita GDP growth rates and the rate of improvement inhealth indicators.
Patterns of progress in child mortality are little changed from those observed in the previous editionof this report, as can be seen in Figure 5. For those in the bottom two quintiles (96–396 deaths per
1,000 live births), mortality rates have fallen more rapidly in 2000–2015 after a notable slowdown in
the 1980–2000 period.

18 See Deaton (2013) and Weil (2015).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound10

FIGURE 5
Mortality Rate, Under Age 5 (per 1,000 live births)
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

175–396

96–175

41–95

20–41

4–19

0
-0.37 -0.24

Average Annual Change-1-0.81-0.76 -0.82
-1.60
-1.77
-2.01

-2
-3
-4
-5

-2.78
-3.81

-3.98

-3.92

-4.89

-6
-7

-6.18

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

The pattern is less clear in the upper quintiles as diminishing returns take hold.
Adult mortality rates, likewise, have fallen much more rapidly in the last 15 years — following adisastrous two decades.
At the upper quintiles, mortality rates have fallen slower over time — albeit from low levels. There issome acceleration in the most recent period that is especially sharp among males, as can be seen in
Figure 6. For males in the fourth quintile, mortality rates fell by 2.3 per year over 2000–2015
compared to 1.1 per year over 1960–1980. Among those in the fifth quintile, (77–186 deaths per 1,000
adult males), mortality rates had fallen by only 0.5 per year from 1960 to 1980, but 2.0 per year from2000 to 2015. Thus, despite diminishing returns, where mortality rates were already low, progress forthis group has been comparable to those in the middle back in the 1960s and 1970s.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound11

FIGURE 6
Mortality Rate, Adult, Female (per 1,000 female adults)
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

355–645

238–354

155–234

110–155

41–110

-1.17
-1.34
-2.17

-0.76
-1.11
-1.17

Averange Annual Change

2

0.86

0
-2
-1.89
-3.18 -3.02-4-6-4.60 -4.37

-4.53
-5.56

-8
-10
-12

-10.751960–1980

1980–2000

2000–2015

Source: World Bank (2017).

FIGURE 7
Mortality Rate, Adult, Male (per 1,000 male adults)
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

408–731

307–408

243–306

186–241

77–186

2

Averange Annual Change

0.33

0
-2
-4
-6

-3.47

-4.03

-0.61
-2.62
-3.39

-1.09
-1.79
-2.31

-0.53
-1.73 -1.97

-5.00
-5.52

-8
-10
-12

-10.461960–1980

1980–2000

2000–2015

Source: World Bank (2017).

In the first quintile, mortality rates fell rapidly from 2000 to 2015. Much of this, however, is likely abounce back in Sub-Saharan African countries, which saw mortality rates skyrocket during the
1980–2000 period. In particular, the second quintiles for both females and males regressed in the
1980–2000 period. As discussed in the previous report, this unusual result is in great part due to the
HIV epidemic — against which considerable progress has been made since that time period. Of 192
countries, only 16 have a period with an average increase in adult female mortality rates of at least
The Scorecard on Development, 1960–2016: China and the Global Economic Rebound12

three per year. All 16 countries that lost that much ground are located in Sub-Saharan Africa and didso over 1980–2000. Fourteen of those 16 were in the second quintile — the exceptions being
middle-quintile Zimbabwe and Botswana. All 16 began 2000 in the bottom quintile and all bounced
back in the most recent period.
If we reanalyze with these 16 countries removed, we still observe a noticeable slowing of progress in
the 1980–2000 period, especially in the second quintile. But we see neither the extreme failure nor
the exceptional bounce back. For example, we see the reanalyzed numbers for females below, in
Figure 8.
FIGURE 8
Mortality Rate, Adult, Female (per 1,000 female adults), With Selected Countries Removed
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

355–557

238–354

155–234

110–155

41–110

Average Annual Change

0
-1
-1.20
-1.30

-2

-2.20

-3

-2.80
-3.20
-3.00

-4
-2.80
-4.70 -4.40

-5
-6

-0.80
-1.10
-1.20

-4.50
-5.80 -6.00-7
1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

The rate of progress in reducing infant mortality also shows a sharp decline for 1980-2000, in thefirst three quintiles, with a rebound in the twenty-first century. This can be seen in Figure 9.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound13

FIGURE 9
Mortality Rate, Infant (per 1,000 live births)
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

110–224

68–109

34–68

16–34

3–15

Average Annual Change

0
-0.20
-0.31

-1
-0.63
-0.66
-0.64

-1
-1.06
-1.28 -1.41

-2
-2
-1.71
-2.32 -2.37

-3
-3
-4

-2.23
-2.92

-3.10

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

As go mortality rates, so must follow life expectancy. For life expectancy at birth, we again see
diminishing returns: improvements in life expectancy are more pronounced in countries with lower
initial life expectancy. However, we still observe that 1980–2000 was a period of relatively slow
progress on this front at the bottom. If life expectancies had increased at the 1960–1980 rate, thenpeople in second-quintile countries in 1980 would have enjoyed an additional five years of life on
average by 2000.
FIGURE 10
Life Expectancy at Birth, Total (years)
0.8

0.73

Average Annual Change

0.7
0.6
0.5

0.54

0.49
0.43

0.48

0.4

0.34

0.3

0.24

0.31

0.26

0.24
0.17
0.15

0.2

0.22
0.21
0.13

0.1
0.0
28–49

49–59

59–68

68–72

72–81

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound14

Again, much of this very sharp decline in the second quintile is due to HIV/AIDS. The only
significant fall in life expectancy (as opposed to a fall in the rate of improvement of life expectancy)
reported outside of 1980–2000 Sub-Saharan Africa was in Cambodia (from 41.2 years of life in 1960
to only 27.7 in 1980; this was obviously related to the war and political violence there). Cambodian
life expectancy also bounced back quickly, reaching 58.4 years in 2000 and 68.5 in 2015.
The story is similar when separating males and females, as can be seen in Figures 11 and 12. In thesecond quintile, we see a sharp falloff in progress (1980–2000), especially in female life expectancy
gains, and then a rebound. After gaining 1.3 years over the 20 years from 1960 to 1980, male life
expectancy at birth for the fifth quintile rose 3.4 years during the last 15 years (2000–2015).
FIGURE 11
Life Expectancy at Birth, Female (years)
0.9
0.77

Average Annual Change

0.8
0.7
0.6
0.5

0.51

0.51

0.56

0.43

0.4

0.35
0.31
0.29

0.3

0.21

0.19

0.2

0.24
0.17

0.21
0.19 0.19

0.1
0.0
29–50

50–61

61–71

71–75

75–85

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound

15

FIGURE 12
Life Expectancy at Birth, Male (years)
0.8
0.70

Average Annual Change

0.7
0.6
0.5

0.54
0.48

0.45

0.41

0.4
0.28

0.3

0.31

0.32

0.19

0.2

0.24
0.18

0.23
0.21

0.12
0.07

0.1
0.0
25–47

47–58

58–65

65–69

69–78

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

Finally, these results are reflected in the closely related odds of survival to age 65. In 2015, males inthe top quintile were nearly 7 percentage points more likely to survive to age 65 than they would
have had progress proceeded at the 1960–1980 pace. As with gains in life expectancy, we see thepattern of slowing progress and resurgence in the bottom three quintiles of survival rates.
FIGURE 13
Survival to Age 65, Male (percent of cohort)

Average Annual Change

1.4
1.17

1.2
1.0
0.8
0.6

0.70

0.68
0.59
0.49

0.47

0.4
0.23

0.54

0.28

0.38
0.31
0.22

0.2

0.36
0.33
0.16

0.0
15–39

39–53

53–62

63–71

71–86

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound16

FIGURE 14
Survival to Age 65, Female (percent of cohort)
1.4

1.24

1.2
1.0
0.8

0.76

0.74

0.79

0.54

0.54

0.6

0.47
0.42

0.4
0.22

0.35
0.27
0.21

0.22
0.20
0.19

0.2
0.0
18–45

45–61

62–75

75–82

82–93

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

School Enrollment
FIGURE 15
Gross Enrollment Ratio, Preprimary, Both Sexes (percent)
2.0
1.70

Average Annual Change

1.8

1.48

1.6
1.4

1.48
1.16

1.2
1.0

1.79

0.82
0.68

0.8
0.6

0.52

0.4

0.64

0.19

0.2
0.0
0–9

10–28

28–51

51–73

74–110

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).

Gross enrollment ratios in preprimary education rose more rapidly over 2000–2015 in comparison
to the two decades prior. The increase came across all quintiles, but in the fourth quintile we see the
The Scorecard on Development, 1960–2016: China and the Global Economic Rebound17

largest improvement in progress — from 0.7 percentage points per year to 1.5 percentage points per
year for countries with initial enrollment between 51 and 73 percent. Over the 15 years, thisincreased progress represents an additional 12 percentage points of preprimary enrollment. 19
For primary education, enrollment rates improved more rapidly in the lowest quintile — where
initial enrollment rates were less than 100 percent, as can be seen in Figure 16. Among quintiles
three through five, initial enrollment rates exceeded 100 percent ― which is possible because thedenominator is the population of primary school age. To the extent that older students are also
enrolled, this raises rates; as primary education becomes universal, the base becomes limited to
students of primary school age and gross enrollment rates must fall.
FIGURE 16
Gross Enrollment Ratio, Primary, Both Sexes (percent)

Average Annual Change

2.5

2.29

2.0
1.5

1.28

1.0

0.66
0.37

0.5

0.16

0.06

0.0
-0.01
-0.08

-0.5

-0.45 -0.48

-1.0
17–86

86–99

99–104

104–109

109–136

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).

Progress in increasing gross enrollment in tertiary education has been less even. Quintile three
showed the most rapid progress in increasing overall gross enrollment rates, followed by the fourthand fifth quintile.

19 There are comparatively fewer observations for data on education than for other indicators cited throughout this report. For afurther discussion on education and data availability, see United Nations (2015).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound18

FIGURE 17
Gross Enrollment Ratio, Tertiary, Both Sexes (percent)
1.8

1.63

Average Annual Change

1.6

1.38 1.38

1.4
1.10

1.2
1.0

0.85

1.24

1.15

0.91

0.88

0.8
0.6
0.4

0.26

0.2
0.0
0–4

4–15

15–22

23–35

35–82

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).

This story over time is a little more clear, however, when breaking out enrollment rates by sex. For
males, enrollment rates improved most rapidly in the middle quintile, as can be seen in Figure 18. But
rates in the first and fifth quintiles increased their rates of improvement considerably, when compared
to 1980–2000.
FIGURE 18
School Enrollment, Tertiary, Male (Percent Gross)
1.4
1.19

1.2

1.25

Average Annual Change

1.05
1.0

0.87

1.15

1.12

1.07

0.89

0.8
0.6
0.4

0.36
0.27

0.2
0.0
1–9

9–17

18–25

25–37

39–96

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).
The Scorecard on Development, 1960–2016: China and the Global Economic Rebound19

For females in the second and fourth quintiles however, enrollment rates if anything rose faster
during the 1980–2000 period than in 2000–2015. For the 1980–2000 period, there is data for only
one country in the fifth quintile. By 2000, however, an additional 15 countries moved into the fifth
quintile after experiencing rapid increases in the prior period.
FIGURE 19
School Enrollment, Tertiary, Female (percent gross)

Average Annual Change

2.5

2.22
1.91
1.73

2.0
1.5
1.02

1.85
1.38

1.28
1.10

1.15

1.0
0.5

0.46

0.0
0–4

6–14

15–23

23–37

37–90

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).

Overall, female enrollment in tertiary education has been increasing at a faster rate than for men,
especially in the top three quintiles. In virtually all developed countries, female enrollment is now
greater than male enrollment. In Sub-Saharan Africa and Southern Asia, however, enrollment rates
have not increased at as high a rate overall, nor have female enrollment rates increased significantly
faster than those of males. 20

Miscellaneous Indicators
Progress in immunization of one-year-olds has slowed particularly among the lowest quintiles, as canbe seen in Figure 20 and 21. Diphtheria, pertussis, and tetanus (DPT) immunization rates in the firstquintile (1–42 percent) rose by an average of 3 percentage points per year between 1980 and 2000, buthave risen only 1.7 percentage points per year since then. Likewise, immunization rates for measles
among the first quintile rose more slowly — 2.3 percentage points per year compared to 3.0 in 1980–
2000.

20 United Nations (2015).

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound20

FIGURE 20
Immunization, DPT (percent of children ages 12–23 months)
3.5

Average Annual Change

3.0

2.99

2.5
2.0

1.74

1.67 1.68

1.5
0.78
0.45

1.0
0.5

0.08 0.09

0.0
-0.08

-0.5
1–42

43–71

72–87

88–96

-0.25
97–99

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).
FIGURE 21
Immunization, Measles (percent of children ages 12–23 months)
3.5

Average Annual Change

3.0
2.5

3.02
2.26

2.0

1.53

1.5

0.99

1.0

0.63

0.5

0.53
0.21 0.14

0.0-0.22 -0.21

-0.5
1–45

46–72

73–87

88–95

96–99

Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

1980–2000

2000–2015

Source: World Bank (2017).

However, the slowdown of the last 15 years is more modest than it initially appears. The first quintile
covers a very wide range of immunization rates, and some of the decline reflects movement from thefirst to second deciles, which can be seen below in Figures 22 and 23. For measles, the first decile
progress in immunization may have accelerated.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound21

FIGURE 22
Immunization, DPT (percent of children ages 12–23 months)
3.5
3

3.30

2.60

Average Annual Change

2.5

2.50
2.10
1.90

2

1.60

1.40
1.20

1.5
1

1.00
0.60
0.40 0.40

0.5

0.20
0.10

0

0.00
-0.10

-0.5

0.00
-0.10
-0.20

-0.40

-1
1–28

29–42

43–56

57–71

72–81

82–87

88–93

94–96

97–98

99–99

Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10
1980–2000

2000–2015

Source: World Bank (2017).
FIGURE 23
Immunization, Measles (percent of children ages 12–23 months)
4

3.70

3.5
3.10

Average Annual Change

3

2.90

2.5
2.00

2

1.60
1.40

1.5
1

1.30
0.70

0.80 0.80

0.5

0.30
0.20
0.20 0.20

0

0.10

0.00

-0.5
1–25

26–45

46–58

59–72

73–81

82–87

88–92

93–95

-0.10
-0.20
-0.30
96–97 98–99

Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10
1980–2000

2000–2015

Source: World Bank (2017).
The Scorecard on Development, 1960–2016: China and the Global Economic Rebound22

Finally, as can be seen in Figure 24, fertility rates among women aged 15–19 have fallen, across theboard, more rapidly than they had over 1960–1980.
FIGURE 24
Adolescent Fertility Rate (births per 1,000 women ages 15–19)
Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

135–235

95–134

56–92

29–55

1–29

Average Annual Change

0.5

0.14

0.0
-0.12

-0.5
-1.0

-1.00

-1.5
-1.62
-1.83

-2.0
-2.5
-3.0

-0.65
-0.74

-0.77

-0.99

-0.23
-0.36

-1.22
-1.38

-2.09
-2.79
1960–1980

1980–2000

2000–2015

Source: World Bank (2017).

Chinese-Led Growth
As noted above, one way in which China contributed to the twenty-first-century rebound of many
developing countries is through its demand for their exports.
From 1990 until its peak in 2013, the share of low- and middle-income country exports sent toChina increased from 0.8 percent to 9.7 percent, going from $4 billion to more than $520 billion.
Measured as a percent of low- and middle-income countries’ total GDP, the increase was from 0.1
percent to 2.6 percent, as can be seen in Figure 25.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound23

FIGURE 25
Low- and Middle-Income Country Exports to China
3.0%$600.00

2.5%$500.00

2.0%$400.00$360.541.5%$300.00

1.0%$200.00

0.5%$100.00

0.0%

Billions of USD (Current)

Percent of GDP$523.09

$1980

1985

1990

1995

2000

Exports to China as Percent of GDP (Left Axis)

2005

2010

2015

Exports to China (Right Axis)

Sources: IMF DOTS (2017a) and IMF WEO (2017b).

From 2013 to 2016, coinciding with a growth slowdown in China and falling commodity prices, lowand middle-income country exports to China decreased by about $150 billion, to 2.0 percent of theirGDP. The share of total low- and middle-income country exports going to China fell from 9.7 to 9.0
percent.
In 1990, the share of low- and middle-income country exports to the world’s advanced economies
was 73.9 percent. By 2013, it had fallen to 54.7 percent. In the last three years, it has increasedslightly, to 56.3 percent. As a percent of GDP, low- and middle-income country exports to advanced
economies peaked in 2006 at 18.3 percent before briefly dipping during the Great Recession. Still,even as advanced economies return to growth, low- and middle-income country’s exports to them,as a percent of GDP, have decreased in recent years to a 20-year low of 12.4 percent.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound24

Conclusion
Comparing the performance of low- and-middle-income countries in the twenty-first century withthat of prior decades, on per capita GDP growth and the rate of progress on various health and social
indicators, it is clear that there is still a sizeable rebound from the very unusual long-term failure of
the last two decades of the twentieth century. Including the additional six years of data since our last
paper does not seem to significantly change this comparison.
There are a number of possible explanations for the rebound. The most obvious is the unprecedented
economic growth of China, and its increasing importance to so many low- and middle-income
countries. China’s increased demand for their exports, noted above, not only provided a direct
stimulus to their economies, but in driving up commodity prices it also helped many countries
accumulate reserves and avoid balance of payment problems that in the past had constrained their
growth ― or in some cases led to severe economic crises.
The IMF’s loss of power in most middle-income countries may have also contributed to thosecountries’ improved economic performance in the twenty-first century. The IMF’s loan portfolio fell
from $105 billion to less than $20 billion from 2003 to 2007. It bounced back to new highs during theworld economic crisis and world economic downturn of 2008–2009, but the vast majority of the newlending went to Europe. The IMF has been an important driver of neoliberal policy reforms andprocyclical macroeconomic policies in low- and middle-income countries.21 The Fund has headed up
something of a creditors’ cartel for its borrowers in the developing world, in which loans from the
much-larger World Bank and other multilateral lending, including from rich country governments,
was generally contingent on IMF approval. But the middle-income countries of Asia, Latin America,and other regions mostly avoided borrowing from the Fund after the highly publicized bad experiencesof the Asian Financial Crisis in 1997–1999. And the creditors’ cartel was also greatly weakened.
During the world economic downturn, the IMF did include procyclical policies in many of its loan
agreements in developing countries, but there is some evidence that this was more moderate, or lessdamaging, than in the past.22 Irrespective of the role of the IMF, it is clear that the response of lowand middle-income countries to the 2008–2009 downturn was more likely to be countercyclical thanin prior downturns. A 2011 study found that 35 percent of developing countries had countercyclicalpolicies for the years 2000–2009, as compared to just 8 percent during 1960–1999.23 At the same time,

21 Weisbrot et al. (2009).
22 Weisbrot (2015), Chapter 3.
23 Frankel, Vegh, and Vuletin (2011), p. 4.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound25

some of the failed economic policies of the late twentieth century, such as overvalued fixed exchange
rates in Argentina, Brazil, Russia, and elsewhere were abandoned.
One factor that seems not to have contributed to the twenty-first-century rebound for mostdeveloping countries was the economic growth of the high-income countries. These high-income
countries’ aggregate real GDP growth averaged 3.1 percent annually from 1980 to 2000, but just 1.9
percent from 2000 to 2017.24
Whatever the explanations for the twenty-first century rebound, the striking long-term growth failureof the last two decades of the twentieth century remains unexplained and largely ignored. In thecomparison made in this paper, which looks at countries starting out at the same level of per capita
GDP in 1960, 1980, and 2000, countries starting out at these levels in later decades should ― all otherthings being equal ― show more rapid progress. We would expect this because there is more advanced
technology and knowledge available as compared to 20 years prior. The same should be true foradvances in life expectancy and other health indicators, because of advances in medicine, science, andpublic health. And yet the opposite happened in the last two decades of the twentieth century. These
decades coincided with a set of neoliberal reforms that were implemented in dozens of low- andmiddle-income countries: increasing independence of central banks, tighter (and more oftenprocyclical) fiscal and monetary policies, the abandonment of previously employed industrial anddevelopment policies, indiscriminate openings to international trade and capital flows, otherderegulatory reforms, and increasing protectionism with regard to intellectual property.
Of course, the fact that this long-term economic failure coincided with the widespread adoption of aset of reforms in low- and middle-income countries does not prove a causal connection. But it shouldat least be cause for concern, and some skepticism about these neoliberal reforms generally, as well as
the institutions that have promoted, enforced (the IMF and World Bank) or codified (the World Trade
Organization) these reforms in their rules. Both the long-term failure and the rebound of the twentyfirst century should be topics of interest to economists.
It is ironic that one of the few developing countries that decidedly did not follow a neoliberal pathsince 1980 multiplied its per capita income by a factor of 21 by 2017, 25 became the largest economy
in the world,26 and played a major role in pulling dozens of other countries out of their long slump.
This history, as we have seen, is somewhat different from the popular narrative that “globalization,”
24 IMF WEO (2017b).
25 Ibid., “China: Gross domestic product per capita, constant prices (National currency).”
26 On a purchasing power parity basis, China’s GDP was estimated by the IMF at $23.2 trillion in 2017, versus $19.4 trillion for theUnited States. See IMF WEO (2017b), “China: Gross domestic product based on purchasing-power-parity (PPP) valuation of country
GDP (Current international dollar)” and “United States: Gross domestic product based on purchasing-power-parity (PPP) valuationof country GDP (Current international dollar).”

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound26

as embodied in the way that most low and middle-income countries increasingly participated in the
global economy ― and the reforms that they adopted ― proved successful.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound27

Appendix
In comparison to earlier versions of this report, fourth quintile ($7,020–$14,500) growth over 1980–
2000 was relatively strong. Growth in this group came in at 2.2 percent per capita per year, compared
to only 1.1 percent in the previous editions. At it happens, every change in sample and data contributed
to increasing the growth estimate for this group. For one, differences in data for the same country
periods as in the previous report added 0.26 percentage points to the estimated rate.
FIGURE A1Reconciling Fourth Quintile 1980–2000 From Prior Data
2.5

Percentage Points

2

1.5

1

0.5

0
Old Scorecard

Updatednumbers

Moved out of
quintile

Moved into
quintile

New

Sources: Feenstra, Inklaar, and Timmer (2015) and IMF WEO (2017b).

Removing countries which in this report are no longer seen to be in the fourth quintile raises thegrowth estimate another 0.36 percentage points. This includes middle-quintile countries such as
Lebanon, Jordan, Suriname, Romania, and Guatemala ― all of which had been observed to experience
negative growth. The level of PPP-adjusted GDP in 1980 for São Tomé and Príncipe has beensignificantly reduced, putting it in only the second quintile. This removed from the fourth quintile acountry that was an especially terrible performer. Slow-growth Brazil, and Argentina, have also been
moved to the middle quintile along with relatively fast growth in Saint Lucia, Antigua and Barbuda,and Mauritius. On balance, all such shifts out of the fourth quintile removed a fair bit of poor numbers
into other quintiles.
Adding countries that were previously observed but seem to be in quintiles other than the fourth again
raised the growth estimate by 0.14 percentage points. These included countries that performed
relatively well for the period such as Turkey, Macao, and Oman, and “tigers” such as Ireland and
The Scorecard on Development, 1960–2016: China and the Global Economic Rebound28

Singapore. On balance, these did more to raise growth in the quintile than Algeria and Bulgaria’s poor
performances could lower it.
Finally, including previously unobserved country periods in the fourth quintile raised the estimate 0.32
percentage points. These additions consisted of a few small island nations (Aruba, Montserrat, theBritish Virgin Islands, and Anguilla) all of which performed well ― averaging over 4 percent percapita, annualized.
There is no particular reason why these changes should have all shifted the estimate all in the same
direction, and there is no obvious reason to believe that the latest estimate is “better” or “worse” thanthat of the 2011 report. However, we note that even doubling the estimated growth rate for 1980–
2000 does not suffice to close the gap relative to 1960–1980 or 2000–2015. The falloff in growthelsewhere was simply too large.

The Scorecard on Development, 1960–2016: China and the Global Economic Rebound29

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