Great Convergence and the Rise of the Rest

Abstract

In the 1980s, 1990s, and even 2000s, many economists failed to detect behind the formal indicators the profound changes in the Third World that prepared for fundamental changes and the onset of the Great Convergence. In the meantime, as one can see from the figures in this chapter, the symptoms of the movement from the trend of the Great Divergence toward the Great Convergence already became apparent in the 1960s and 1970s.

Full text

85© Springer International Publishing Switzerland 2015
L. Grinin, A. Korotayev, Great Divergence and Great Convergence,
International Perspectives on Social Policy, Administration, and Practice,
DOI 10.1007/978-3-319-17780-9_3
Chapter 3
Great Convergence and the Rise of the Rest
In the 1980s, 1990s, and even 2000s, many economists failed to detect behind for-
mal indicators the profound changes in the Third World that prepared fundamental
changes and the onset of the Great Convergence. Even at that time the absolute
majority of Western economists seem to have been in unanimous agreement over
the absence of absolute convergence across the world (see, e.g., Sadik 2008 ; Epstein
et al. 2007 ; Seshanna and Decornez 2003 ; Workie 2003 ; Canova and Marcet 1995 ;
Durlauf and Johnson 1995 ; Desdoigts 1994 ; Paap and van Dijk 1994 ). Thus, Sachs
et al. noted in 1995 that in 1970–1995 there had been no overall tendency for the
poorer countries to catch up, or converge, with the richer countries.
In 1996 Sala-i-Martin, having analyzed a large cross-section of 110 countries,
stated that one of the main lessons to learn from the classical approach to conver-
gence analysis is that “the cross-country distribution of world GDP between 1960
and 1990 did not shrink, and poor countries have not grown faster than rich ones.
Using the classical terminology, in our world there is no σ-convergence and there is
no absolute β-convergence” (Sala-i-Martin 1996 : 1034).
Much attention was given to empirical testing of the convergence hypothesis in
Quah’s works (see, e.g., 1996a , b , c ). Using the model of growth and imperfect capi-
tal mobility across multiple economies to characterize the dynamics of (cross-
country) income distributions, Quah tested the convergence hypothesis and came to
conclusion that the evidence showed little unconditional cross-country convergence.
This idea corresponds quite well to the one expressed by Lee et al. ( 1997 ) that
world countries are not converging, but diverging, which they resumed from consid-
ering international per capita output and its growth using a panel of data for 102
countries between 1960 and 1989. Much the same conclusion was almost simulta-
neously made by Bianchi ( 1997 ) who empirically tested the convergence hypothesis
from the perspective of income distributions in a cross-section of 119 countries. By
means of statistical techniques such as non-parametric density estimation and boot-
strap multimodality tests, Bianchi tested for the number of modes and estimated,

86
consistently with the detected number of modes, the income distribution of a cross-
section of 119 countries in 1970, 1980 and 1989, concluding that his fi ndings sup-
port the view of clustering and stratifi cation of growth patterns over time, standing
in sharp contrast with the unconditional convergence prediction.
One of the most recent works refuting the unconditional convergence hypothesis
is the one by Acemoglu ( 2009 ), which contains a cross-country analysis of GDP per
capita values between 1960 and 2000; what is more, he maintains that “there is a
slight but noticeable increase in inequality across nations” (Ibid.: 6).
The conclusion on the continuation of divergence was shared by many research-
ers, for example, Gaulier et al. ( 1999 ), who based their research upon empirical
evidence obtained from the analysis of 86 countries. A more recent work by Howitt
and Mayer-Foulkes ( 2004 ) similarly resumed that among the countries of the world
the divergence, not convergence could be observed starting from the early nine-
teenth century (see also Clark 2007 ; Allen 2011 ).
Numerous students shared the point of view on the absence of absolute conver-
gence throughout the countries of the world (see, e.g., Sadik 2008 ; Epstein et al.
2007 ; Seshanna and Decornez 2003 ; Workie 2003 ; Canova and Marcet 1995 ;
Durlauf and Johnson 1995 ; Desdoigts 1994 ; Paap and van Dijk 1994 ).
In the meantime, as one can see from the fi gures in this chapter, the symptoms of
the movement from the Great Divergence trend toward the Great Convergence one
became rather well visible already in the 1960s and 1970s.
Below we will demonstrate how much the Great Convergence process has
advanced by now notwithstanding all those conclusions and predictions, whereas
the explanation of the Great Convergence factors will be given in Chap. 4 .
Long-Term Divergence–Convergence Trends
as Regards the GDP
According to Maddison’s ( 2001 , 2010 ) data the share of the West in the world GDP
(at PPP) grew quite noticeably in 1000–1800 (which correlates quite well with vari-
ous “small divergence” theories); however, the explosive growth of this share started
after 1800 (which, in its turn, correlates very well with the California School’s Great
Divergence theory). By the end of the nineteenth century, the share of the West in
the world GDP exceeded 50 %, whereas in the 1950s and 1960s it was more than
60 %. However, according to Maddison, since the late 1960s this share started to
decrease with an accelerating speed (see Fig. 3.1 ).
It is diffi cult not to notice that the shape of this curve resembles rather strikingly
the shape of the curve of the world population relative growth rates’ dynamics (see
Fig. 3.2 ).
3 Great Convergence and the Rise of the Rest

87
0%
10%
20%
30%
40%
50%
60%
0 200 400 600 800 100012001400160018002000
Fig. 3.1 Dynamics of the share of the West (In this chapter we denote as “the West” the following
group of countries (roughly corresponding to the high-income OECD countries at the onset of the
explicit Great Convergence in the late 1980s): all the countries of Western Europe, the USA,
Australia, New Zealand, Canada, and Japan.) in the world GDP. Data sources : till 2008—Maddison
( 2010 ); after 2008—World Bank ( 2014 ): NY.GDP.MKTP.PP.KD. To secure the compatibility of
two series, the World Bank GDP data have been re-calculated with Maddison’s coeffi cients of the
conversion of nominal US dollars into international dollars at purchasing power parity (PPP)
0
0.5
1
1.5
2
2.5
0
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
Fig. 3.2 World population relative growth rates’ dynamics, 1–2003 (%). Source : Коротаев et al.
( 2007 : 12). Before 1800 the curve represents a trend line that does not take into account cyclical
and stochastic fl uctuations
Long-Term Divergence–Convergence Trends as Regards the GDP

88
We believe this is not a mere coincidence. Actually, some time ago we already
made the following observation:
“One could hardly fail to notice that the turnaround of the secular trend toward the growth
of the gap between the World System Center and the World System Periphery
1 to the trend
toward the decrease of this gap coincided with an amazing accuracy (almost about a year)
with the turnaround of a number of other secular (and sometimes even millennial) trends to
the opposite ones. We should note the transition from millennial trends to the increase in
global relative growth rates of population and GDP (as well as GDP per capita) to contrary
trends to the decrease of those rates. One may also note a turnaround of the millennial trend
toward the decrease of the effectiveness of the energy consumption to the opposite one (i.e.,
to the growth of this effectiveness). There are certain grounds to maintain that this syn-
chronicity is not coincidental, as it refl ects the point that we are dealing here with different
aspects of the single process of the World System development, with different aspects of the
single process of the World System’s withdrawal from the blow-up regime and the start of
its movement toward the trajectory of sustainable development. Indeed, all those new trends
that emerged in the 1970s and the 1980s (the ones toward the slowdown of the relative
growth rates of world population and GDP, toward the growth of energy consumption effec-
tiveness and the decrease of the economic gap between the Center and the Periphery) have
a certain ‘common denominator’—all of them lead to a certain stabilization of the World
System development and to a certain discharge of the strains that have accumulated within
it” ( Коротаев etal. 2010: 68–69).
This important point will be considered in more detail in Appendix B to the pres-
ent monograph.
Consider now in more detail the dynamics of the share of the GDP of the West
and the Rest after 1800 (Fig. 3.3 ).
This diagram suggests that, according to Maddison, the West’s share in the world
GDP started to contract since the late 1960s. However, until the late 1990s this con-
traction proceeded at a rather slow rate; the West’s share in the world started to
decrease (and—respectively—the share of the Rest started to increase) at a really
fast pace after 2000.
In Fig. 3.4 one can see in an especially clear way the point that for quite a long
time the West’s GDP has been growing slower than the total GDP of the Rest.
As we see, between 1968 and 2012 the total GDP of the Rest grew by seven
times,
2 whereas the West’s GDP only tripled within the same period of time.
However, this was only after 2000 when the GDP growth rates of the Rest started to
exceed the Western growth rates in a really radical way
3 (see Fig. 3.5 ).
As we see, after 2000 the total GDP of the West has only grown by 20 %, whereas
the GDP of the Rest has doubled, that is, it has grown by 100 %—thus, as regards
1 As we will see below in Appendix B, the long-term curve of the gap between the First and Third
World as regards per capita GDP resembles the curve of the world population growth rate dynam-
ics even more.
2 It appears necessary to stress that we will obtain such results only when we apply Maddison’s
coeffi cients for the GDP conversion at purchasing power parity. As we will see below, when using
other coeffi cients we tend to get signifi cantly different results (especially, as regards the period
between 1968 and 1998).
3 And—as we will see below—we will get a similar result in this case even if use any other GDP
conversion coeffi cients.
3 Great Convergence and the Rise of the Rest

89
20%
30%
40%
50%
60%
70%
80%
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 2020
The West
The Rest
Fig. 3.3 Dynamics of the share of the West in the world GDP after 1800 (according to Maddison).
Data sources : till 2008 (including 2008)—Maddison ( 2010 ); after 2008—World Bank ( 2014 ):
NY.GDP.MKTP.PP.KD. In order to secure the compatibility of data for the period after 2008, the
World Bank GDP data have been recalculated in accordance with Maddison’s coeffi cients of con-
version of nominal US dollars into international dollars at purchasing power parity (PPP)
0
100
200
300
400
500
600
700
1968 1973 1978 1983 1988 1993 1998 2003 2008
GDP of the West
GDP of the Rest
Fig. 3.4 Relative dynamics of the GDP of the West and the rest of the world (according to
Maddison), 1968–2012, 100 = the 1968 level
Long-Term Divergence–Convergence Trends as Regards the GDP

90
average annual economic growth rates, the Rest has been developing fi ve (!) times
as fast as the West.
In the meantime, it appears essential to take into account the point that here much
depends on the unit of measurement we use—that is, on the type of dollars with
which we measure the GDP (and which GDP conversion coeffi cients at PPP we
use). Indeed, as soon as we start using World Bank coeffi cients, the resultant picture
changes in a rather signifi cant way (see Fig. 3.6 ).
As we see, when we use World Bank GDP conversion coeffi cients, we get the
impression that, as regards the variable in question, the convergence of the West and
the Rest only started after 1994; it proceeded very slowly until 1999, but it acceler-
ated immensely between 1999 and 2012, whereas after 2002 it proceeded at a really
fast pace—as a result of which already in 2012 the share of the Rest in the world
GDP exceeded the West’s share (while just 15 years ago the share of West exceeded
the share of the Rest almost twice).
Note that after 2000, the World Bank data on the relative GDP growth rates in the
West and the Rest (calculated in constant 2005 international dollars converted at
PPP using the World Bank conversion coeffi cients) portray a picture (see Fig. 3.7 )
that is very similar to the one that we arrived at above when using Maddison’s
estimates.
On the one hand, the almost complete identity of the curves for 2008–2012 is not
surprising here at all, as above we extended Maddison’s time series to those years
on the basis of the World Bank data; however, on the other hand, it is much more
100
110
120
130
140
150
160
170
180
190
200
2000 2002 2004 2006 2008 2010 2012
GDP of the West
GDP of the Rest
Fig. 3.5 Relative dynamics of the GDP of the West and the rest of the world (according to
Maddison), 2000–2012, 100 = the 2000 level
3 Great Convergence and the Rise of the Rest

91
35%
40%
45%
50%
55%
60%
65%
1980 1985 1990 1995 2000 2005 2010 2015
The West
The Rest
Fig. 3.6 Dynamics of the share of the West and the rest of the world (“the Rest”) in the global
GDP after 1980 (based on the World Bank data on the GDP calculated in 2005 purchasing power
parity international dollars). Data source : World Bank ( 2014 ): NY.GDP.MKTP.PP.KD
100
110
120
130
140
150
160
170
180
190
200
2000 2002 2004 2006 2008 2010 2012
The West
The Rest
Fig. 3.7 Relative dynamics of the GDP of the West and the rest of the world (based on the World
Bank data on the GDP calculated in 2005 purchasing power parity international dollars), 2000–
2012, 100 = the 2000 level
Long-Term Divergence–Convergence Trends as Regards the GDP

92
remarkable that both Maddison’s estimates and World Bank data portray an
extremely similar pattern for the period between 2000 and 2008.
Note that the results of such a comparison will be somehow different if we cal-
culate GDP not in power purchasing parity international dollars, but rather in US
dollars (whereas the GDP of particular countries is calculated by the conversion of
their GDP in local currency into US dollars according to market exchange rates).
Indeed, in this case we get a rather different picture (see Fig. 3.8 ).
As we see, in this case the initial gap between the West and the Rest appears to be
much larger. What is more, the convergence in the 1990s and the early 2000s looks much
less pronounced, whereas a really fast convergence only starts after 2003. However, for
recent years both systems of measurement demonstrate a rather similar pattern of an
extremely fast convergence, with the GDP growth rates of the World System core coun-
tries lagging very far behind the countries of the periphery
4 (see Fig. 3.9 ).
Thus, though different data series portray rather different patterns of conver-
gence between the West and the Rest as regards their shares in the world GDP, they
4 Note that here we quite consciously apply a simplifi ed dual World System structuration scheme
that only singles out the World System core and periphery and ignores the subdivision of the latter
into the periphery per se and semiperiphery.
10%
20%
30%
40%
50%
60%
70%
80%
90%
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
The West
The Rest
Fig. 3.8 Dynamics of the share of the West and the rest of the world (“the Rest”) in the global GDP
after 1980 (based on the World Bank data on the GDP converted into current US dollars according
to current market exchange rates). Data source : World Bank ( 2014 ): NY.GDP.MKTP.CD
3 Great Convergence and the Rise of the Rest

93
are very congruent regarding the point that in recent years the convergence has been
going on at extremely fast rates indeed.
Note, that an astonishingly similar picture of the world convergence pattern was
detected by William Thompson when he tried to trace long-term dynamics of the
Western share in the world manufacturing (see Fig. 3.10 ).
As we see, according to Thompson’s calculations a really fast convergence
between the West (≈ the World System core) and the Rest (≈ the World System
periphery) only started (as regards the very important variable in question) after
2000; however, afterwards it proceeded at precipitously high rates—thus, between
2005 and 2010 (just in 5 years!) the gap between the West and the Rest decreased
by one half. With such an extremely high convergence rate the Rest may catch up
the West (as regards its share in the world manufacturing) already by 2015–2020.
5
On the Dynamics of the West’s Share in the World Population
For a more profound understanding of the issue of the Great Divergence and Great
Convergence, it appears necessary to take into account the dynamics of the West’s
share in the overall population of the world (see Figs. 3.11 and 3.12 ).
5 However, this may happen a few years later (for reasons see Statistical addendum to this chapter ).
100
150
200
250
300
350
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
The West
The Rest
Fig. 3.9 Relative dynamics of the GDP of the West and the rest of the world (based on the World
Bank data on the GDP converted into current US dollars according to current market exchange
rates), 2003–2012, 100 = the 2003 level
Long-Term Divergence–Convergence Trends as Regards the GDP

94
0
10
20
30
40
50
60
70
80
90
100
1840 1860 1880 1900 1920 1940 1960 1980 2000
%
Developed 3rd World
Fig. 3.10 Long-term dynamics of the Western share in the world manufacturing, %, 1840–2010.
Source : Thompson (2014)
10%
12%
14%
16%
18%
20%
22%
24%
26%
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Fig. 3.11 Share of the West in the total population of the World, 1–2009 with a forecast till 2030
CE. Data source : Maddison ( 2010 )
3 Great Convergence and the Rise of the Rest

95
As we see, the point that an especially fast divergence between the West and the
Rest (as regards their shares in the world GDP) was observed in the nineteenth cen-
tury had a rather strong demographic component. In that century, the explosive
growth of the share of the West was accounted both by a very fast (at least in the
millennial perspective) increase in the productivity of labor (and, thus, the GDP per
capita) caused by the economic modernization,
6 and by a rather fast growth of the
share of the population of the West in the total population of the world caused by
the demographic modernization. Indeed, this was connected with the point that in
the nineteenth century the population of the West grew much faster than the popula-
tion of the Rest. This fact was not coincidental either—actually, in the West, the
acceleration of the growth of the labor productivity and the acceleration of the pop-
ulation growth were two aspects of the single modernization process. In the
nineteenth- century West, one of the main consequences of the start of an intensive
economic modernization was the start of its demographic modernization—that is,
the start of the demographic transition (Вишневский 1976 , 2005 ; Chesnais 1992 ;
Caldwell et al. 2006 ; Dyson 2010 ; Livi-Bacci 2012 ). As is well known, the fi rst phase
of the demographic transition (which the West passed precisely in the nineteenth
century) is characterized by a radical decrease of mortality (Вишневский 1976 ,
2005 ; Chesnais 1992 ; Caldwell et al. 2006 ; Gould 2009 ; Dyson 2010 ; Reher 2011 ;
6 In the same time the Rest lagged far behind the West as regards its economic modernization
(and—hence—as regards the labor productivity growth).
10%
12%
14%
16%
18%
20%
22%
24%
26%
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000 2020
Fig. 3.12 Share of the West in the total population of the World, 1800–2009 with a forecast till
2030 CE. Data source : Maddison ( 2010 )
Long-Term Divergence–Convergence Trends as Regards the GDP

96
Livi-Bacci 2012 ). A comparable decrease of fertility is only observed at its second
phase (which the West entered only in the very end of the nineteenth century and the
early twentieth century). Respectively, throughout the whole nineteenth century the
very fast decline of mortality took place in the West against the background of still
very high fertility levels, that led to an explosive increase in the natural population
growth rates (due to the lagging modernization, in most countries of the Rest a
comparable acceleration of the demographic growth only took place in the second
half of the twentieth century). Thus, it is not coincidental at all that in the nine-
teenth-century West, the higher (than in the Rest) GDP per capita growth rates were
accompanied by the higher (than in the Rest) population growth rates, which led to
an especially fast growth of the West’s GDP share in the world GDP.
On the other hand, in the twentieth century, the West entered the second phase of
the demographic transition, the fertility started to decrease there more and more—
hence, the demographic growth rates decelerated in a very signifi cant way (in some
countries even to negative values). In the meantime, in the twentieth century the
majority of the countries of the Rest entered the fi rst phase of the demographic tran-
sition, which meant a very signifi cant decline of mortality against the background
of still very high fertility. As a result, already by the beginning of World War I the
share of the West in the world population had reached its peak, whereas afterwards
it began to decrease, but till the 1950s this decrease proceeded very slowly. However,
in the 1950s, when most countries of the Third World entered the fi rst phase of the
demographic transition, these countries experienced a demographic explosion,
which, additionally, took place against the post-Baby Boom fertility decrease in the
First World—as a result in the 1950s, 1960s, and 1970s the share of the West in the
total population of the Earth was decreasing very fast indeed. The rate of this
decrease only started to slow down after the late 1980s as a result of the entering the
second phase of the demographic transition by the majority of the Third World
countries (see, e.g., Caldwell et al. 2006 ; Gould 2009 ; Dyson 2010 ; Reher 2011 ).
On the Dynamics of the Gap Between the West
and the Rest as Regards the Per Capita GDP
All the above-said should be taken into account when we consider the dynamics of
the gap between the West and the Rest as regards the GDP per capita (see Figs. 3.13 ,
3.14 , and 3.15 ).
Note that Figs. 3.13 , 3.14 , and 3.15 above may suggest that the convergence
between the First and Third World only really started in the 2000s. However, this
impression is not quite correct. The fact is that at this point we should take into
account the fact that the Rest is not equal to the Third World, as in addition to the
Third World it includes the Second World (that is the former “Communist Block”—
the countries of the former USSR as well as the former Communist countries of the
East Europe). Thus, it appears necessary to consider separately the long-term eco-
nomic development of the Second World countries (see Figs.
3.16 , 3.17 , and 3.18 ).
3 Great Convergence and the Rise of the Rest

97
0
1
2
3
4
5
6
7
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Fig. 3.13 The dynamics of the gap in GDP per capita (by how many times) between the West and
the Rest, 1 – 2008
0
1
2
3
4
5
6
7
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Fig. 3.14 The dynamics of the gap in GDP per capita (by how many times) between the West and
the Rest, 1800 – 2008
Long-Term Divergence–Convergence Trends as Regards the GDP

98
4.5
5.0
5.5
6.0
6.5
7.0
1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Fig. 3.15 The dynamics of the gap in GDP per capita (by how many times) between the West and
the Rest, 1945 – 2008. Source : Maddison ( 2010 ). Note that Maddison provides GDP estimates in
1990 Geary–Khamis international dollars at purchasing power parity
$-
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
$9,000
0 500 1000 1500 2000
Fig. 3.16 The Second World per capita GDP Dynamics, 1 – 2008. Data source: Maddison ( 2001 ,
2010 ). Note that Maddison provides GDP estimates in 1990 Geary–Khamis international dollars
at purchasing power parity
As we can notice, in the Second World the economic crisis of the 1990s was
unusually deep and long with an average decline of the per capita GDP by more
than a third (that is it was signifi cantly stronger than the Great Depression in the
USA), whereas on average it took the Second World 16 years to return the per capita
output to the pre-crisis level (for comparison in the 1930s, the same task took the
USA 11 years).
3 Great Convergence and the Rise of the Rest

99
Now let us consider the long-term dynamics of the gap between the First and the
Second World as regards per capita GDP (see. Figs. 3.19 , 3.20 , 3.21 , and 3.22 ).
As we see, in the 1990s in the Second World countries a catastrophic decline of
the output was accompanied by an explosive growth of the gap between the First
and the Second World, which reached by the mid-1990s an unprecedented level.
Note that while by the mid-2000s the Second World managed to return its output to
the pre-crisis level, it failed to return the gap with the First World to this level, and
by 2008 it remained much higher than it had been observed at any point of time
before 1991. The point is that in the 1990s the economic collapse in the Second
World was observed against the background of a generally rather fast economic
growth of the First World countries, that is why by the moment when the Second
$-
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
$9,000
1800 1850 1900 1950 2000
Fig. 3.17 The Second World per capita GDP Dynamics, 1800 – 2008. Data source : Maddison
( 2001 , 2010 ). Note that Maddison provides GDP estimates in 1990 Geary–Khamis international
dollars at purchasing power parity
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
1950 1960 1970 1980 1990 2000 2010
Fig. 3.18 The Second World per capita GDP Dynamics, 1950 – 2008. Data source : Maddison
( 2001 , 2010 ). Note that Maddison provides GDP estimates in 1990 Geary–Khamis international
dollars at purchasing power parity
Long-Term Divergence–Convergence Trends as Regards the GDP

100
0
1
2
3
4
5
6
0 500 1000 1500 2000
Fig. 3.19 The dynamics of the gap in GDP per capita (by how many times) between the First and
the Second World, 1 – 2008
1.5
2
2.5
3
3.5
4
4.5
5
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Fig. 3.20 The dynamics of the gap in GDP per capita (by how many times) between the First and
the Second World, 1800 – 2008
2
2.5
3
3.5
4
4.5
5
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Fig. 3.21 The dynamics of the gap in GDP per capita (by how many times) between the First and
the Second World, 1950 – 2008
3 Great Convergence and the Rise of the Rest

101
World restored its pre-crisis GDP per capita level, the First World economies had
gone far ahead (see Fig. 3.23 ).
As a result, in the 1990s, the Second World share in the world GDP contracted in
a really signifi cant way. As we remember, when we use the World Bank data on the
GDP calculated in 2005 international dollars at purchasing power parities, we have
an impression that there was almost no convergence as regards the world GDP share
in the 1990s (and that such a convergence only started in the 2000s). However, the
picture changes very signifi cantly as soon as we separate the Third World from the
Second World (see Fig. 3.24 ).
As we see, after the division of “the Rest” into the Second and Third World we
see that a fairly fast convergence between the First and Third World (as regards their
shares in the global GDP) already started in the 1990s (with a certain hitch in the
last years of this decade). However, these were precisely the early 1990s when a
rather signifi cant decline of the Second World’s share in the global GDP occurred.
Thus, in the fi rst half of the 1990s a rather substantial increase in the Third World’s
share of the global GDP was almost entirely compensated by the simultaneous
decline of the Second World’s share (and this is just what creates an illusion of the
convergence absence in this period).
Respectively, after the division of “the Rest” into the Second and the Third
World, we can see that a rather noticeable convergence between the First and the
Third World started in the early 1990s (though with a certain hitch around the end
of this decade), see Fig.
3.25 .
These were already the 1990s when the developing countries managed to achieve
a substantial decrease of the gap with the developed countries as regards the GDP
per capita—from the ninefold value to the eightfold. However, a really sustainable
and fast reduction of this gap started after 1999, and between 1999 and 2012 it
2
2.5
3
3.5
4
4.5
5
1980 1984 1988 1992 1996 2000 2004 2008
Fig. 3.22 The dynamics of the gap in GDP per capita (by how many times) between the First and
the Second World, 1–2008, 1980 – 2008
Long-Term Divergence–Convergence Trends as Regards the GDP

102
0%
10%
20%
30%
40%
50%
60%
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
1st world GDP share 2nd world GDP share
3rd world GDP share
Fig. 3.24 Dynamics of
shares of the First, the
Second, and the Third World
in the global GDP, 1984–
2008 (based on the World
Bank data on the GDP
calculated in 2005 purchasing
power parity international
dollars). Data source : World
Bank ( 2014 ): NY.GDP.PCAP.
PP.KD. The fact that the First
World curve in this graph is
not entirely identical with the
one in Fig.
3.1 is accounted
for by the point that in two
cases two different
aggregation schemes were
used
60
70
80
90
100
110
120
130
140
1989 1992 1995 1998 2001 2004 2007
1st world GDP pc 2nd world GDP pc
Fig. 3.23 Relative Dynamics of the GDP per capita in the First and Second World, 1989–2008,
100 = 1989 level. Data source : Maddison 2010 . Note that Maddison provides GDP estimates in
1990 Geary–Khamis international dollars at purchasing power parity
3 Great Convergence and the Rise of the Rest

103
shrank from the eightfold to the almost fi vefold. If the lessening of this gap contin-
ues at the same rate (regarding which one may still express certain doubts in view
of both the perspective of the “reindustrialization of the West” and the threat of
middle income trap
7 with respect to some Third World leaders) the gap between the
developed and developing countries may almost disappear already in 20 years.
The analysis of the dynamics of the gap between the First and Third World with
respect to the per capita GDP on the basis of Maddison’s database produces results
rather similar to the ones obtained above on the basis of the World Bank database.
However, this is only Maddison’s database that allows considering this dynamics in
a deep historical perspective. In a two-millennia perspective it looks as follows (see
Fig. 3.26 ).
Consider now the dynamics of the gap between the First and Third World at the
scale of centuries and decades (see Figs. 3.27 and 3.28 ).
As we see, the gap between the developed and developing countries continued to
grow up to the 1960s; in the 1970s it somewhat contracted, but in the 1980s it grew
again. Curiously, these were just the 1990s when the Western economist undertook
a massive examination of the convergence issue (see, e.g., Barro 1991 ; Bianchi
1997 ; Canova and Marcet 1995 ; Desdoigts 1994 ; Durlauf and Johnson 1995 ; Lee
7 For more details on this trap see Statistical addendum below, or, e.g., The World Bank and the
Development Research Center of the State Council of the People’s Republic of China ( 2012 : 12)
and Гринин et al. ( 2014 ).
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
1984 1989 1994 1999 2004 2009
Fig. 3.25 The dynamics of the gap in GDP per capita (by how many times) between the First and
the Third World, 1984–2012 (based on the World Bank data on the GDP calculated in 2005 pur-
chasing power parity international dollars). Data source : World Bank ( 2014 ): NY.GDP.PCAP.
PP.KD
Long-Term Divergence–Convergence Trends as Regards the GDP

104
et al. 1997 ; Mankiw et al. 1992 ; Paap and van Dijk 1994 ; Quah 1996a , b , c , 1997 ;
Sachs et al. 1995 ; Sala-i-Martin 1996 —see the next chapter for a detailed review of
those publications). The most widespread method of this examination was to com-
pare the gap in the 1950s and 1960s (on the one hand) with, on the other hand, the
most recent data points (which, naturally—as the examination took place in the
0
1
2
3
4
5
6
7
8
9
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Fig. 3.27 Dynamics of the gap in GDP per capita (by how many times) between the West (the
First World) and the Third World, 1800 – 2008
0
1
2
3
4
5
6
7
8
9
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Fig. 3.26 Dynamics of the gap in GDP per capita (by how many times) between the West (the
First World) and the Third World, 1 – 2008
3 Great Convergence and the Rise of the Rest

105
1990s—corresponded to the late 1980s and early 1990s).
8 As one can easily guess
on the basis of Fig. 3.28 , such a scrutiny led Western economist in a rather system-
atic way to an apparently well-grounded conclusion that there was no convergence
between the developed and developing countries at all—one would rather speak
about a continuing divergence (albeit a rather weak one). Note that a rather sound
theoretical basis for such a conclusion had been established by that time by Paul
M. Romer’s ( 1986 ) theory of “increasing returns”, which implied in a rather clear
manner that the gap between poor and rich countries should in future increase rather
than decrease. Indeed, Romer wrote that the model of increasing returns offered “an
alternative view of long-run prospects for growth” that was contrary to the assump-
tions of convergence theory: “per capita output can grow without bound, possibly at
a rate that is monotonically increasing over time. The rate of investment and the rate
of return on capital may increase rather than decrease with increases in the capital
stock. The level of per capita output in different countries need not converge; growth
may be persistently slower in less developed countries and may even fail to take
place at all” (Romer 1986 : 1003).
Yet, as is suggested by the very Fig. 3.28 , rather paradoxically, just in that very
time when the Western economists arrived almost unanimously at the conclusion
8 The most wide-spread way to operationalize such a comparison looked as follows—the idea was
to identify the correlation between the per capita GDP levels in various countries of the world in
1950/1960, on the one hand, and the GDP per capita growth rates between 1950/1960 and 1990,
on the other. Quite logically, within such an operationalization scheme, a signifi cant negative cor-
relation was rather soundly interpreted as evidence for the presence of global convergence, a sig-
nifi cant positive correlation was as soundly interpreted as evidence for the presence of global
divergence, whereas an insignifi cant correlation was interpreted as evidence for the absence of
both global convergence and global divergence.
5
5.5
6
6.5
7
7.5
8
8.5
1950 1960 1970 1980 1990 2000 2010
Fig. 3.28 Dynamics of the gap in GDP per capita (by how many times) between the West (the
First World) and the Third World, 1950 – 2008
Long-Term Divergence–Convergence Trends as Regards the GDP

106
that there was no convergence between the developed and developing countries, that
very convergence was already gaining momentum!
9
Statistical Addendum to This Chapter: On the Structure
of the Present-day Convergence
10
First, let us view the dynamics of the gap in GDP per capita between the high-
income OECD countries and the low-income countries for the past three decades
(see Fig. 3.29 ).
One can see that the gap between the high-income OECD countries and the low-
income countries kept growing until 2000. All in all, between 1981 and 2000 this
gap increased very signifi cantly, from 25 times in 1981 to almost 40 times (however,
one should note here that, though the gap was still widening in the late 1990s, this
enlargement proceeded at a much slower pace as compared to the previous years).
In the 2000s, the gap started to contract rather fast, decreasing from 40 to 30 times
during only 12 years. Abstractly speaking, if this trend and pace persist, the gap will
essentially disappear in about three decades; though, of course, there are strong
doubts whether the low-income countries [“the bottom billion” as coined by Paul
Collier ( 2007 )] will manage to keep up the current fast pace of catch up the high-
income countries in terms of GDP per capita.
Let us now turn to the dynamics of the gap in GDP per capita between the high-
income OECD countries and the middle-income countries in the past three decades
(see Fig. 3.30 ).
Thus, the gap between the high-income and middle-income countries kept grow-
ing until 1990, approaching the value of 10 (which means that the GDP per capita
in the high-income countries exceeded that in the middle-income countries by an
order of magnitude). After 1990 one can observe a rather pronounced trend for this
gap to decrease. However, during the 1990s the gap was decreasing rather slowly,
going down from the value of 9.25–8.7 within a decade. In the 2000s the gap con-
tinued decreasing at a more accelerated pace, going down from 8.7 to 5.4 during 12
years (2000–2012).
Finally, let us view the dynamics of the gap in GDP per capita between the
middle-income countries and the low-income countries in the past three decades
(see Fig. 3.31 ).
Some important observations can be made at this point. Indeed, both the middle-
income (after about 1990) and the low-income (after about 2000) countries seem to
have been converging to the high-income countries in the latest years (as compared
9 We think, that this fi asco of the Western economic science was connected with the fact that
Western economists tried to apply basically linear models to the analysis of a highly nonlinear
process.
10 This Addendum has been prepared on the basis of our article “On the structure of the present-day
convergence” (Korotayev and Zinkina 2014 ).
3 Great Convergence and the Rise of the Rest

107
to the divergence trend observed in the previous decades).
11 However, at the same
time the low-income countries have been diverging from the middle-income coun-
tries for the whole period of the latest three decades. Thus, the gap between these
two groups of countries has been steadily growing for the latest 30 years; the GDP
per capita in the middle-income countries exceeded that in the low-income coun-
tries by three times in 1981; now this gap is more than fi vefold.
11 Notably, the change from divergence to convergence trend fi rst occurred in the middle-income
countries, and then (10 years later) in the low-income ones.
0
5
10
15
20
25
30
35
40
45
1980 1985 1990 1995 2000 2005 2010
High Income/Low Income
Fig. 3.29 Dynamics of the gap in GDP per capita (from here on we use 2005 constant interna-
tional dollars, PPP) (by how many times) between the high-income OECD countries (According
to the World Bank classifi cation, this group of countries includes Australia, Austria, Belgium,
Canada, Chile, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Iceland,
Ireland, Israel, Italy, Japan, Korea, Rep.; Luxembourg, the Netherlands, New Zealand, Norway,
Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, United Kingdom, United
States.) and the low-income countries (According to the World Bank classifi cation, this group of
countries includes Afghanistan, Bangladesh, Benin, Burkina Faso, Burundi, Cambodia, Central
African Republic, Chad, Comoros, the Democratic Republic of Congo, Dem. Rep.; Eritrea,
Ethiopia, the Gambia, Guinea, Guinea-Bissau, Haiti, Kenya, North Korea, Kyrgyzstan, Liberia,
Madagascar, Malawi, Mali, Mozambique, Myanmar, Nepal, Niger, Rwanda, Sierra Leone,
Somalia, South Sudan, Tajikistan, Tanzania, Togo, Uganda, Zimbabwe.), 1981–2012. Note : The
fi gures on the Y-axis scale denote by how many times the average GDP per capita in the high-
income OECD countries exceeded the one in the low-income countries for a given year. Thus, the
value of 25 for 1981 means that in 1981 the GDP per capita was 25 times higher in the high-income
OECD countries than in the low-income countries. Calculations made on the basis of the data
presented by: World Bank ( 2014 ): NY.GDP.PCAP.PP.KD
Long-Term Divergence–Convergence Trends as Regards the GDP

108
Thus, the general pattern of convergence and divergence between the high-
income, middle-income, and low-income countries during the last 30 years looks as
follows (see Fig. 3.32 ).
Our fi nding is quite concordant with some of the results presented in previous
publications. Thus, Ho ( 2006 ) studies the threshold effects of per capita income on
the convergence behavior of growth rates among 121 economies during the sample
period from 1960 to 2000. Convergence appears to be insignifi cant in the lowest-
income regimes, but is signifi cantly found beyond such regimes. Ho fi nds the income
threshold (which the country needs to overcome in order to start converging) to be
0
1
2
3
4
5
6
7
8
9
10
1980 1985 1990 1995 2000 2005 2010
High Income/Middle Income
Fig. 3.30 The dynamics of the gap in GDP per capita (by how many times) between the high-
income OECD countries and the middle-income countries (according to the World Bank classifi ca-
tion, this group of countries includes Albania, Algeria, American Samoa, Angola, Antigua and
Barbuda, Argentina, Armenia, Azerbaijan, Belarus, Belize, Bhutan, Bolivia, Bosnia and
Herzegovina, Botswana, Brazil, Bulgaria, Cameroon, Cape Verde, Chile, China, Colombia, Congo,
Rep.; Costa Rica, Cote d'Ivoire, Cuba, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt,
El Salvador, Fiji, Gabon, Georgia, Ghana, Grenada, Guatemala, Guyana, Honduras, India,
Indonesia, Iran, Islamic Rep.; Iraq, Jamaica, Jordan, Kazakhstan, Kiribati, Kosovo, Lao PDR,
Latvia, Lebanon, Lesotho, Libya, Lithuania, Macedonia, Malaysia, Maldives, Marshall Islands,
Mauritius, Mexico, Micronesia, Moldova, Mongolia, Montenegro, Morocco, Namibia, Nicaragua,
Nigeria, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Romania,
Russian Federation, Samoa, Sao Tome and Principe, Senegal, Serbia, Seychelles, Solomon Islands,
South Africa, South Sudan, Sri Lanka, St. Lucia, St. Vincent and the Grenadines, Sudan, Suriname,
Swaziland, Syrian Arab Republic, Thailand, Timor-Leste, Tonga, Tunisia, Turkey, Turkmenistan,
Tuvalu, Ukraine, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza,
Yemen, Zambia.), 1981–2012. Note : The fi gures on the Y-axis scale denote by how many times the
GDP per capita in the high-income OECD countries exceeded that in the middle-income countries
for a given year. Thus, the value of 9 for 1993 means that in 1993 the GDP per capita was nine
times higher in the high-income OECD countries than in the middle-income countries. Calculations
made on the basis of the data presented by: World Bank ( 2014 ): NY.GDP.PCAP.PP.KD
3 Great Convergence and the Rise of the Rest

109
0
1
2
3
4
5
6
1980 1985 1990 1995 2000 2005 2010
Middle Income/Low Income
Fig. 3.31 The dynamics of the gap in GDP per capita (by how many times) between the middle-
income countries and the low-income countries, 1981–2012. Note : The fi gures on the Y-axis denote
by how many times the GDP per capita in the middle-income countries exceeded that in the low-
income countries for a given year. Thus, the value of 4 for 1994 means that in 1994 the GDP per
capita was four times higher in the middle-income countries than in the low-income countries.
Calculations made on the basis of the data presented by: World Bank ( 2014 ): NY.GDP.PCAP.PP.KD
1
10
1980 1985 1990 1995 2000 2005 2010
High Income/Low Income
High Income/Middle Income
Middle Income/Low Income
Fig. 3.32 The dynamics of the gap in GDP per capita (by how many times) between the high-
income, the middle-income, and the low-income countries, logarithmic scale, 1980–2012
Long-Term Divergence–Convergence Trends as Regards the GDP

110
about $1,150. Malamud and Assane ( 2013 ) investigate the growth difference
between sub-Saharan Africa/SSA (which make up the majority of the lowest-
income group viewed by Ho and the low-income group investigated in this paper)
and the rest of the world and fi nd that SSA countries converge more slowly, if at all,
than the rest of world countries over the period from 1965 to 2000. Our results seem
to be well consistent with the fi ndings stated in both papers.
Possible Explanations of the Trends
Now let us turn to analyzing the forces and factors behind the above-revealed
specifi c pattern of the dynamics of per capita income gaps between the high-
income, middle-income, and low-income countries. Naturally, in a single paper
one can hardly present a comprehensive explanation (or even an attempt at mak-
ing the one) for the complex structure of convergence trends. So below, we will
try to outline only some main economic forces that are likely to have contributed
to the specifi c convergence-divergence pattern of recent years. Let us start with
the two fundamental convergence-driving forces proposed by Gerschenkron and
Solow (as quoted above), namely, the technological diffusion from the more
advanced countries to the developing ones, and weaker diminishing returns in the
developing countries.
As regards the technological diffusion, it is likely to proceed particularly fast in
the middle-income countries that have a suffi cient amount of well-qualifi ed work-
force (including labor force with professional technical education) which is essen-
tial for a successful practical implementation of the adopted technologies. Indeed, a
number of studies demonstrate that in order to benefi t from international technology
transfers, the learning capacity as well as the investment required to apply technolo-
gies in local production processes, play an important role (see, e.g., Nabin et al.
2013 ; Hoekman et al. 2005 ).
Now let us briefl y view the possible infl uence of another major convergence-
driving factor, namely, the larger marginal product of capital and investment profi t
in the developing countries as compared to the more affl uent societies. Abel and
Bernanke took this principle implied in the Solow model as a basis to expect a more
rapid increase in capital stock in poor countries (Abel and Bernanke 2005 : 234).
Indeed, already in 1998, the proportion of investment in GDP was much higher
in the middle-income countries than in the high-income ones (notably, this propor-
tion was the lowest in the low-income countries)—see Fig. 3.33 . By 2008, the pro-
portion of investment in GDP remarkably dropped in the high-income countries and
simultaneously grew in the low-income ones; so the low-income countries actually
outpaced their high-income counterparts with respect to this indicator. However, the
middle-income countries experienced the greatest increase in the proportion of
investment in GDP during the same period and by 2008 they far outpaced both the
high-income and the low-income countries (see Fig. 3.34 ).
3 Great Convergence and the Rise of the Rest

111
Foreign investment infl ow into the developing countries contributes to conver-
gence in various ways. Generally, it has a signifi cantly positive direct effect on the
growth of income per capita (e.g., Alfaro et al. 2004 ; Blonigen and Wang 2005 ;
Borensztein et al. 1998 ). Moreover, FDI has a signifi cantly positive direct effect on
TFP growth, which is extremely important, as more than half of the cross-country
variation in both income per capita and its growth rates results from the differences
in TFP and its growth, respectively (for a detailed review see Woo 2009 ).
This taken into account, the particularly high economic growth rates in the
middle- income countries are clearly not coincidental.
21.22
23.62
17.92
0
5
10
15
20
25
High Income Middle Income Low Income
Fig. 3.33 Proportion of investments in GDP, %, 1998. Note : calculated on the data from World
Bank ( 2014 ): NE.GDI.FTOT.ZS
20.28
27.16
21.54
15
17
19
21
23
25
27
29
High Income Middle Income Low Income
Fig. 3.34 Proportion of investments in GDP, %, 2008. Note : calculated on the data from World
Bank ( 2014 ): NE.GDI.FTOT.ZS
Long-Term Divergence–Convergence Trends as Regards the GDP

112
Possible Global Implications of the Convergence–Divergence Pattern
Thus, in recent years the structure of convergence-divergence pattern has become
rather peculiar. The gap between the high-income and middle-income countries has
been rapidly decreasing. This fact is particularly noteworthy when taking into
account that the middle-income countries currently accommodate about 70 % of the
world population (about fi ve billion people). If the current pace persists in the near-
est decades, the prospects for these 70 % look really bright, as the gap between the
high-income OECD countries and the middle-income countries will essentially dis-
appear in just 15–20 years. However, such a bright prospect of the middle-income
countries fully converging to the high-income ones is very doubtful with a view to
the prospect of the “Reindustrialization of the West”, on the one hand, and the
“middle-income trap” 12 awaiting the middle-income countries, on the other. Indeed,
a number of Latin American countries were the fi rst to experience stagnation after
reaching middle-income levels and failure to move further into the ranks of high-
income countries. A number of works reveal the same threat to be currently looming
large for many developing countries in other regions, notably in Asia (including
China) (see, e.g., Grinin and Korotayev 2010a ; Kohli and Mukherjee 2011 ; Cai
2012 ; Kharas and Kohli 2011 ; Aiyar et al. 2013 ). Note also that the mathematical
model presented above in Appendix B also predicts a certain slow-down of the pro-
cesses of Great Convergence in the forthcoming decades. One should not exclude
the possibility of temporary reversals (similar to the one that was already observed
in 1997–1999).
The gap between the high-income and the low-income countries has also been
decreasing lately, but at a much slower pace. Meanwhile, the gap between the
middle- income and the low-income countries has been growing steadily. In the
early 1980s, this latter threefold gap was clearly outshadowed by the colossal gap
(almost a tenfold one) between the high-income and the middle-income countries.
The current situation is remarkably different: the low-income countries lag behind
the middle-income by more than fi ve times, which is almost equal to the gap
between the middle-income and the high-income countries.
As regards the low-income countries, we would like to emphasize that their total
population does not exceed a billion people (World Bank 2014 : SP.POP.TOTL),
which is less than the total population of the high-income countries. In other words,
“the bottom billion” is currently less than “the golden billion”. This means that
when looking at the convergence and divergence processes in terms of the popula-
tion numbers in the converging/diverging countries, we are bound to state that cur-
rently the processes of convergence clearly prevail over the processes of divergence
(much more people live in the converging countries than in the diverging ones).
However, this disposition is likely to dramatically change in the coming decades, as
12 As defi ned by Aiyar et al., the “middle-income trap” is “the phenomenon of hitherto rapidly
growing economies stagnating at middle-income levels and failing to graduate into the ranks of
high-income countries” (Aiyar et al. 2013 : 3). For a detailed description of the factors and mecha-
nisms of the middle-income trap see, e.g., Kharas and Kohli 2011 .
3 Great Convergence and the Rise of the Rest

113
the population growth rates in the “bottom billion” are much higher than in the rest
of the world. Indeed, the African populations have recently been growing more
rapidly than the non-African developing world grew at its peak , and that by 1970,
the ratio of young dependents to the working-age population had exceeded histori-
cal developing-country norms and even now remains that high (Ndulu et al. 2007 :
106; Zinkina and Korotayev 2014 ). A decade of economic successes has been
hardly enough to bring many countries just to the WHO recommended level of per
capita food consumption; however, if the fertility decline fails to accelerate and
population continues rocketing up, to sustain this level (let alone to surpass and start
to catch it up, which is utterly essential for improving the living standards of the
majority of population) is likely to become “mission impossible” (Zinkina and
Korotayev 2014 ; Зинькина and Коротаев 2013 ).
Thus, our analysis reveals a rather signifi cant re-confi guration of the World
System in the recent three decades. It is namely the middle-income countries that
have demonstrated the highest economic growth rates after 1990 (and even more so
after 2000). This is quite explicable, as in the modern world namely the middle-
income countries generally have the best opportunities for achieving high economic
growth rates. Indeed, the workforce in such countries is still rather cheap (as com-
pared to the high-income ones), but already benefi ts from rather high levels of edu-
cation and health system, which greatly increases the quality of the workforce (as
compared to the low-income countries). The low-income countries, on the other
hand, are lagging behind in terms of education (especially secondary and tertiary
education) and still demonstrate extremely high population growth rates which
increase the age-dependency ratio and decreases the economic growth rates. While
the middle-income countries have been converging to the high-income ones, the
low-income countries have actually been diverging from the middle-income ones.
This is a rather threatening trend which requires specifi c international attention to
removing the growth obstacles in the low-income countries (among other things, by
increasing the education level and the quality of the workforce, as well as by bring-
ing down the extreme population growth rates).
Long-Term Divergence–Convergence Trends as Regards the GDP