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Phases of global demographic transition correlate with phases of the Great Divergence and Great Conv Версия в формате PDF 
Написал AK   
20.02.2015

Andrey Korotayev, Jack A. Goldstone, Julia Zinkina

Phases of global demographic transition correlate with phases of the Great Divergence and Great Convergence

 

  

  Published in: Technological Forecasting & Social Change 95 (2015) 163–169.

 

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Abstract

The Great Divergence and, to a lesser extent, the Great Convergence phenomena have attracted considerable scholarly attention. However, the existing attempts at explaining these phenomena and their background share two significant drawbacks: first, no model (to the best of our knowledge) has managed to account for both the Great Divergence and the Great Convergence so as to explain the timing of the trend change (around 1970s). Second, most existing models concentrate heavily on the economic forces, frequently neglecting the demographic factor. We offer an approach to overcome these drawbacks, revealing a close coupling between phases of global demographic transition and phases of the Great Divergence and Great Convergence. As we account for the crucial role of the demographic component in these processes, we show that the timing of the trend change was not coincidental. Our findings suggest that the dynamics of global population growth and the Great Divergence and Great Convergence therefore may be considered so closely coupled as to be two sides of the same coin. On the other hand, they also suggest that the Great Divergence and Great Convergence should be treated as a single process, as two phases of the global modernization.

 

 

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Introduction

In the 19th century, northwestern Europe saw the birth of capital-intensive and fossil-fuel based manufacturing. Spreading throughout Europe and the United States, these changes triggered the explosive growth of a gap in per capita incomes between the First and Third World that has become known as the Great Divergence (see, e.g., Pomeranz, 2000; Goldstone, 2008, 2012; Clark, 2008; Allen, 2011). In the twentieth century, the Great Divergence peaked before the First World War and continued until the early 1970s, then, after two decades of indeterminate fluctuations, in the late 1980s it was replaced by the Great Convergence as the majority of Third World countries reached economic growth rates significantly higher than those in most First World countries (e.g., Sala-i-Martin, 2006; Korotayev et al., 2011; Spence, 2011; Derviş, 2012).

The majority of the voluminous research on various aspects of the Great Divergence, taken as a whole, mainly focuses on five causes, such as geography, human capital, science and technology progress, cultural/political institutions, and international trade/colonies (for a substantial review see Goldstone, 2002, 2008, 2012; Chen, 2012). The cornerstone for the theory of convergence were laid by Alexander Gerschenkron (1952), who developed the ‘theory of relative backwardness’, stating that ‘the opportunities inherent in industrialization may be said to vary directly with backwardness of the country’ (Gerschenkron, 1952: 6), as well as by Robert M. Solow (1956), whose model accounted for the diminishing returns to capital and implied that in poor countries even small amounts of capital investment would substantially raise the productivity. Abel and Bernanke note that according to Solow model, if the economy is open, the absolute convergence gets support of some additional economic forces. Since poorer countries have less capital per worker and therefore a higher marginal product of capital than the more affluent countries, investors from richer countries will be able to get greater profits by investing in poor countries. Therefore, foreign investment should provide a more rapid increase in capital stock in poor countries, even if the level of domestic savings in these countries is low (Abel and Bernanke, 2005: 234). It is easy to see that both the ‘Gershenkron’ factor and the ‘Solow’ factor of the faster growth of the peripheral (and especially semi-peripheral) economies are well mutually complementary, as the capital diffusion tends to be accompanied by technology diffusion (what is more, the capital diffusion is one of the main creators of the technology diffusion channels).

However, the existing attempts at explaining these phenomena and their background share two significant drawbacks: first, no model (to the best of our knowledge) has managed to account for both the Great Divergence and the Great Convergence so as to explain the timing of the trend change (around 1970s) (for our earlier attempt to account for this with a special mathematical model see Zinkina et al., 2014). Second, most existing models concentrate heavily on the economic forces, frequently neglecting the demographic factor. We offer an approach to overcome these drawbacks, revealing a close coupling between phases of global demographic transition and phases of the Great Divergence and Great Convergence. We show here that the dynamics of the size of the gap in GDP per capita between the First and Third Worlds corresponds to the dynamics of the growth rate of the world population (the specific countries we identify as composing the “First World” and “Third World” are listed in the Supplementary Information). We provide supporting evidence that this is not coincidental, and that the demographic component plays an important role in these processes.

 

Methods Summary

GDP and population data were obtained from Maddison (2010) and the World Bank’s World Development Indicators Database (World Bank, 2014). First World countries comprised 30 Western European Countries, the USA, Canada, Australia, New Zealand, and Japan. GDP was totaled across these countries, and divided by total population to obtain First World GDP per capita. We designated as Second World countries the U.S.S.R. and its successor republics, Yugoslavia and its successor republics, and 5 eastern European countries. The Third World population and GDP were obtained by subtracting the sum of First World and Second World GDP and population from the World totals. Full specification of the country lists for First and Second worlds are given in the Supplementary Information.

                Data was taken for the following years, to span the entire period 1—2012 AD, at points spaced to capture the movements of GDP/capita: AD 1, 1000, 1500, 1820, 1870, 1913, 1940, 1952, then every five years up through 2012.   Full data is given in the Supplementary Information.

 

Parallel Dynamics

The general dynamics of the gap in GDP per capita, shown as the ratio between the GDP/capita in the First and Third Worlds from AD 1 to 2008, is presented in Fig. 1a.  This curve can be seen to display a rather close similarity to the curve of the world’s population growth rate (shown here as the annual increase per thousand) presented in Fig. 1b. This similarity becomes especially salient when both curves are plotted in the same graph (Figs. 1c and 1d), and persists whether looking at the full span of two millennia or only at the two most recent centuries.

 

Figure 1 | Dynamics of the gap in GDP per capita and annual world population growth rates.

In (a) the figures on the Y-axis denote by how many times the average GDP per capita in First World countries exceeded that in Third World countries for a given year. Thus, the value of 7 for 2000 means that in 2000 the GDP per capita was 7 times higher in the First World states than in the Third World countries. Note that a "gap" value of 1 means there is no difference between the groups. In (b) the Y-axis gives the global population growth rate in annual increase per thousand.  Until 1940, the world population growth rate curve depicts the trend line and does not take into account cyclical and stochastic fluctuations (see Supplementary Information). In (d) we present a subset of data from (c) for the last 210 years.

                Regression analysis indicates that the correlation between the relative growth rates of the world population and the GDP per capita gap between the First and Third World has a remarkably high value (see Fig.2):

Figure 2 | Correlation between the gap in GDP per capita between the First and Third World and the growth rate of world population (‰). Note that the value of constant α in the regression model y = α + βx in our case equals 0.96 ≈ 1. Incidentally, this suggests that when the world population stabilizes (that is, when the global modernization phase transition is completed), the gap between the First and the Third World may almost disappear. (Data in Supplementary Information)

 

                We are dealing here with a very tight correlation, accounting for 92% of all the variation. The match between the dynamics of world population growth, on the one hand, and the dynamics of the gap between the First and the Third World GDP per capita, on the other, looks especially salient in Fig. 3, where a logarithmic scale is used to facilitate the comparison across different scales.

 

Figure 3 | The gap in GDP per capita between the First and the Third World, 1–2008 and the growth rate of world population (‰), logarithmic scale. Note that this is the same data as in figure 1d just on log scale, and that a constant gap between the two curves represents a constant factor (i.e., the 0.37 found from the regression) between them.

                The high correlation of the two time series is apparent. The significant acceleration of the world population growth rate observed in the 19th century (from 4.1‰ per year c. 1820 to 7.95‰ by 1870) corresponds to an explosively accelerated widening of the per capita income gap between the First and Third World. During the period of 1870–1940 the deceleration of world population growth corresponded to a certain slowdown in the pace of the Great Divergence. Then, following the Second World War, a surge of acceleration of world population growth took place; and, as expected, it coincided with a renewed, corresponding acceleration of the global Divergence. Even a certain hitch in the acceleration of the world population growth rates that was observed in the 1950s was accompanied by a certain hitch in the Divergence speed. Both the gap between the First and Third World GDP per capita and the relative world population growth rate reached their peaks almost simultaneously (at 8.1 times for the gap and a rate of 20.65‰ per year for world population growth) in the late 1960s. There followed a decade in which the values of both variables declined, commencing the Great Convergence.  However, in the late 1970s and early 1980s both the slowing-down of the world’s population growth rate and the decrease of the per capita income gap were interrupted (almost simultaneously). One could observe, throughout most of the 1980s, certain proportional, and mostly simultaneous, increases in both the per capita income divergence between the First and the Third World, and the world population growth rate. Then in the late 1980s there began a sharp and mostly steady (though not without certain hitches) decrease of both the GDP gap and the world population growth rate that has continued to the present day.

The Income Gap and World Population Growth as Tightly-Coupled Processes

It could not be entirely ruled out, of course, that at least some of the consistency in this picture may be attributable to coincidence. However, the existence of a high correlation between the two time series can be explained. In truth, both of the global processes (the global demographic transition, otherwise known as the global demographic modernization, on the one hand, and the Great Divergence turning into the Great Convergence, on the other) ought to be viewed as interrelated and showing two sides of one phase transition in the development of the World System – the global modernization (see Zinkina et al., 2014 for some more detail).

                The explosive acceleration of the Great Divergence in the 19th century was quite naturally accompanied by a significant acceleration of the world population growth rate. The economic and technological modernization of the West, which propelled it to global leadership in labor productivity and per capita income, was then the major factor that determined the scope of divergence (e.g., Mokyr, 1990; Goldstone, 2002, 2008; Clark, 2008; Allen, 2009, 2011). At the same time, these positive developments in the West led to substantial improvements in the production, harvesting, storage, and transportation of food, and gains in public health and sanitation, resulting in increasing life expectancies and significantly declining mortality rates across all industrializing countries. In other words, the vast economic improvements brought about by the Industrial Revolution advanced the Western countries to the first phase of the demographic transition (e.g., Chesnais, 1992; Caldwell et al., 2006; Dyson, 2010; Reher, 2011). In this phase, lasting throughout most of the 19thcentury in the industrializing countries, mortality declined sharply while fertility remained at a high level (e.g., Caldwell et al., 2006; Gould, 2009; Dyson, 2010; Reher, 2011; Livi-Bacci, 2012). The result was a rapid acceleration of population growth in the countries of the West, which was a very important factor in the acceleration of world population growth rates in the 19th century (Gould, 2009; Dyson, 2010; Reher, 2011; Livi-Bacci, 2012) (see Figure 4).

 

Figure 4 | The total world population growth against the background of population dynamics of the 1st an 3rd world, millions, logarithmic scale.

                From 1870 to 1920, most industrialized countries entered the second phase of the demographic transition, in which fertility began to decline and population growth slowed.  This decelerated the growth of world population. The gap in GDP between the First and Third worlds continued to grow, but more slowly.  While in the First World slowing population growth and continued economic development led to ever-higher per capita GDP, the Third World also began to benefit from the rapid growth in international trade and the diffusion of railroads and international investment.

                In the period after the Second World War, the acceleration of world population growth and the increase in the speed of Divergence were also rather strongly interconnected. At this later phase of global modernization, the main contribution to the acceleration of world population growth was made by the entrance of the majority of the Third World countries (where the overwhelming majority of the world population lived) into the first phase of the demographic transition (e.g., Caldwell et al., 2006; Gould, 2009; Dyson, 2010; Reher, 2011; Livi-Bacci, 2012). It is of note that in most cases the demographic transition in the developing world was not as much connected to radical increases in economic growth rates (as was observed in the Western countries during the prior period), but predominantly arose from the diffusion of healthcare technologies that caused a very rapid decline of infant and child mortality (from 350+‰ to 35‰or less). Thus, Preston (1975, 1980) reveals in his classical works that the spectacular life expectancy growth observed in the developing countries in 1940 – 1970 was only 15 – 25% due to improvements in nutrition, income, and other living standards indicators, while 50 – 80% of this growth were stipulated by the diffusion of medicine and health care technologies. The drop in mortality associated with the Third World’s first phase of the demographic transition was therefore even more rapid than that which occurred in the First World; combined with still high fertility the result was a dramatic acceleration of world population growth.

                The resulting population growth in the Third World was more rapid than any seen in world history; growth rates of 30‰ or even 40‰ pushed world population growth rates to new highs. However, such rapid growth rates also held down the growth of per capita incomes in developing countries relative to the rapid gains being made in the First World in the decades after WWII (even though the First World also experienced a brief surge in population growth rates after the War).  It was only when Third World countries also began to limit fertility, entering their second phase of the demographic transition, that their per capita GDP growth sharply accelerated to levels above those of the First World.  With this transition, world population growth began to drop sharply, as did the income gap; we have since been seeing the Great Convergence.

                The crucial role of population dynamics in driving GDP/capita in this phase can be seen in the fact that overall GDP growth rates in the Third World were already roughly as high as those in the First World in the 1950s and 1960s, as shown in Figure 5.  However, in the Third World this growth arose against the background of a demographic explosion (that is very characteristic for the first phase of the demographic transition [see, e.g., Chesnais, 1992; Caldwell et al., 2006; Dyson, 2010; Reher, 2011; Livi-Bacci, 2012]), whereas First World countries were by then in the second phase of the demographic transition and experiencing rather slower population growth.  From 1950 to 1970 the population of Third World countries increased by 56%, more than twice as much as that of First World countries, which grew by only 24% in this period. As a result, during the 1950s and 1960s the gap between the First and Third World in per capita GDP increased substantially despite the fact that overall GDP growth rates in the developed and developing countries were almost identical in those years.

 

Figure  5 |Relative GDP dynamics of the First and Third World 1950–1970, 100 = 1950 level.

 

                Hence, the close coupling between economic and demographic dynamics in both of these phases of global modernization is clear. However, it differed rather significantly as regards its contents and direction across the periods. In the West of the 19th century it was per capita GDP that served as the main independent variable whose growth then led to the decrease of mortality and the acceleration of the population growth, whereas in the postwar Third World it was the population growth rate that led; the initial acceleration of population growth initially held back per capita GDP growth, but the deceleration of population growth then produced a demographic dividend (more workers and fewer dependents) that helped produce much higher GDP growth rates.

                Our last figure demonstrates how closely the economic and demographic dynamics were linked. The peak of the gap in GDP per capita in the late 1960s also coincided with the absolute minimum in the share of the working-age population in the total population in Third World countries (UN Population Division, 2014). It was precisely when the impact of falling fertility started to produce a rising percentage of workers – the ‘demographic dividend’ – in developing nations (e.g., Bloom et al., 2001; Bloom and Sevilla, 2002; Mason, 2001, 2007; Hawksworth and Cookson, 2008: 7–10) that the income gap with the First World started to decline (see Figure 6).

 

Figure 6 |Dynamics of the percentage of the Third World population that is in the working age range (15-65 years old), 1950–2010.

 

                Therefore, we can argue that the peak in the income gap between the First and Third World occurring with almost perfect accuracy at the same time as the peak in world population growth rates is no coincidence.  It is because the onset of the great Convergence depended on a slow-down in growth rates in the Third World that decelerated world population growth.

Conclusion

Our research shows that throughout the modern era the gap between First and Third world incomes has been very strongly influenced by the timing of their entry into the first and second phases of the demographic transition. We would not say that the dynamics of the Great Divergence and Great Convergence are determined entirely by the dynamics of the global demographic transition. The onset of the modernization process, including the reorganization of politics, the economy, and social life, was due to many factors (see, e.g., Mokyr, 1990; Barro, 1991; Sachs et al., 1995; Sala-i-Martin, 1996; Quah, 1996; Lee et al., 1997; Pomeranz, 2000; Yifu Lin, 2003; Allen, 2009, 2011; Clark, 2008; Korotayev et al., 2011; Spence, 2011; Goldstone, 2002, 2008, 2012). However, we are quite ready to claim that, once begun, the impact of modernization on incomes was strongly dependent on the timing of the phases of the demographic transition in different regions. The dynamics of global population growth and the Great Divergence and Great Convergence therefore may be considered so closely coupled as to be two sides of the same coin. On the other hand, our findings suggest that the Great Divergence and Great Convergence should be treated as a single process, as two phases of the global modernization. Potential further research in this direction may imply the analysis of the Great Divergence and Great Convergence as phases of the global modernization, which may help to find the deep underlying causes of the detected synchronization, to forecast if the detected correlation will continue, or to detect the “physical sense” of the 0.37 factor found by the regression analysis of the dataset in Figure 2 above.

                In conclusion, let us summarize our answer to the following question: “Was underdevelopment a cause or an effect of the fast population growth?” It is important to stress that we are dealing in our case with a truly dynamic relationship between the two variables in question, which implies the absence of any simple answer to such a question. Actually, the casual direction of this relationship was rather different at different phases of the global modernization transition. In the 19th century the modernization of the West led both to the fast acceleration of its economic growth (against whose background the “Rest” started to look “underdeveloped”), and to the explosive growth of the population of the West (and, hence, to a substantial increase in the world population growth rates) through the decrease of the mortality rates in the West (caused ultimately just by the economic modernization of the West and acceleration of its economic growth). After the Second World War the casual link appears to have been the opposite. In the first decades after the war, in most cases the demographic transition in the developing world was not as much connected to radical increases in the GDP per capita growth rates (as was observed in the Western countries during the prior period), but predominantly arose from the diffusion of healthcare technologies that caused a very rapid decline of infant and child mortality. In this period the population explosion in the Third World resulted in the situation when both the world population growth rates reaching and the gap between the First and the Third World reaching their maximum levels (though the GDP growth rates in the 1950s and the 1960 were approximately the same in the First and Third World, the explosive growth of the population of the developing countries against the background of the declining population growth rates in the developed countries led to the further increase in the gap between them as regards per capita incomes). On the other hand, the entering of the majority of the Third World countries into the second phase of the demographic transition (implying the radical decline of the fertility rates) contributed in a rather significant way both to the start of the decline of the world population growth rates and the onset of the Great Convergence (that implies the shrinkig of the gap between the First and Third World as regards per capita GDP values). However, at all phases of the global modernization transition the link between the two variables in question remained rather strong that results in a rather strong correlation between them that we have detected.

 

SUPPLEMENTARY INFORMATION

 

This Supplementary Information for “Phases of global demographic transition correlate with phases of the Great Divergence and Great Convergence” documents in more detail the data and methods that support Korotayev et al.’s finding of high correlation between the dynamics of the Great Divergence and Great Convergence, on the one hand, and the dynamics of the world population growth rate, on the other.

Data and Methods

The Gross Domestic Product (GDP) per capita is a widely used national accounting measure of economic prosperity. The World Bank defines it as “the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources” (World Bank, 2014). We obtained the long-term data (from 1 up to 2008 AD) on the GDP dynamics (in 1990 International Geary – Khamis dollars at purchasing power parity) from Angus Maddison’s database (Maddison, 2010).  For the period after 2008 the data have been obtained from the World Development Indicators Database (World Bank, 2014).

                To secure the compatibility of data, the World Bank GDP data have been recalculated in accordance with Maddison’s coefficients of conversion of current US dollars into international dollars at purchasing power parity. The following countries from Maddison’s country list have been identified as the “First World countries”: 30 Western European countries (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Sweden, Switzerland, UK, Ireland, Greece, Portugal, Spain + 14 small Western European countries, for which Maddison only provides summary estimates of their GDP and population), 4 “West European offshoots” (Australia, New Zealand, Canada, USA), and Japan. The GDP values for the First World for particular years were calculated by summing up Maddison’s GDP estimates for each of the 16 Western European countries, 4 Western European offshoots, Japan, and the summary estimate for the 14 small Western European countries. We applied a similar procedure to obtain the population figures for the First World. The First World GDP per capita for each year in the time series results from dividing the year’s total GDP of the First World countries into their total population that year. Computations of the Second World’s GDP, population, and GDP per capita have been conducted similarly. We put these former Eastern Bloc countries in the “Second World” category: former constituent republics of the Soviet Union, Czechoslovakia, and Yugoslavia + Albania, Bulgaria, Hungary, Poland, and Romania. We calculated the “Third World” GDP by subtracting the First and Second World GDP from the world GDP. The Third World population figures were produced the same way. We calculated the Third World GDP per capita for each year in the series by dividing the total GDP of the Third World into its total population for the given year.

We obtained the population data from Angus Maddison’s database (Maddison, 2010). We decided to use this database because Angus Maddison provides population estimates precisely for the time-points and countries for which he provides his GDP figures. Hence, this is the only database that allows us to calculate the long-term dynamic estimates of the per capita income gap between the First and Third World. We opted to use the UN Population Division (2014) data for the world population relative growth rate past 1950 (no estimates for the earlier period are available there). The UN Population Division provides its estimates for the world population annual growth rates for five-year intervals (for example, for the period of 1950–1955 it states the average annual estimate for this period of 1.786% per year). For comparison, we used mid data points as regards the values for the gap between the First and Third World.

As we are interested in the correlation between phases of global demographic transition and phases of Great Divergence and Great Convergence, Figures 1–3 for the period before 1940 display the trend line only, omitting those data points that reflect cyclical and stochastic fluctuations: (specifically, the data points for the years 1600, 1700 and 1900). Thus, the following dataset has been used to construct Figures 1-3 (see Table S.1):

Table S.1: Data used for the construction of Figures 1–3

FIRST, SECOND, AND THIRD WORLD POPULATION GROWTH RATES, POPULATIONS, AND GDP PER CAPITA

S.1a. Population of the First, Second, and Third World

Row #

Year

1st World population, mlns

1st World population annual growth rate, %

2nd World population, mlns

2nd World population annual growth rate

3rd World population, mlns

3rd World population annual growth rate, %

1.

   2.

3.

4.

5.

6.

7.

8.

1

      1

29.170

0.02%

8.650

0.05%

188.000

0.02%

2

1000

34.930

0.15%

13.600

0.16%

218.800

0.08%

3

1500

75.468

0.26%

30.450

0.34%

332.510

0.26%

4

1820

175.259

0.85%

91.222

0.89%

775.227

0.22%

5

1870

268.024

1.07%

142.229

1.18%

865.479

0.63%

6

1913

424.048

0.76%

235.722

0.77%

1133.155

1.02%

7

1940

519.538

0.91%

289.952

-0.42%

1489.703

1.42%

8

1952

578.962

1.13%

275.670

1.61%

1763.317

2.23%

9

1957

612.327

1.14%

298.653

1.54%

1968.954

1.92%

10

1962

647.947

1.02%

322.400

1.12%

2165.441

2.49%

11

1967

681.667

0.92%

340.885

0.92%

2448.911

2.54%

12

1972

713.481

0.74%

356.932

0.92%

2776.085

2.23%

13

1977

740.210

0.66%

373.564

0.79%

3099.765

2.07%

14

1982

764.855

0.53%

388.588

0.77%

3433.864

2.14%

15

1987

785.157

0.72%

403.751

0.45%

3817.763

1.97%

16

1992

813.720

0.66%

412.976

-0.07%

4209.026

1.75%

17

1997

841.120

0.56%

411.442

-0.18%

4589.559

1.56%

18

2002

865.081

0.49%

407.828

-0.16%

4958.794

1.44%

19

2007

886.493

 

404.498

 

5325.698

 

 

 


 

S.1b. GDP of the First, Second, and Third World

Row #

Year

1st World GDP,

blns GK$

2nd World GDP,

blns GK$

3rd World GDP,

blns GK$

1.

   2.

3.

4.

5.

1

      1

16.081

3.516

85.805

2

1000

14.861

5.440

100.907

3

1500

52.979

15.154

180.188

4

1820

193.098

62.584

437.820

5

1870

503.084

133.809

472.790

6

1913

1556.674

367.145

809.371

7

1940

2592.861

605.114

1304.609

8

1952

3555.381

744.028

1611.868

9

1957

4380.500

982.081

2061.314

10

1962

5464.248

1244.181

2428.036

11

1967

7047.603

1590.067

3131.485

12

1972

8866.301

1920.703

4231.413

13

1977

10309.792

2314.840

5532.461

14

1982

11481.838

2441.464

6725.053

15

1987

13609.830

2686.645

8397.294

16

1992

15496.035

2151.633

10429.633

17

1997

17630.191

1816.500

13795.097

18

2002

19869.223

2204.331

16947.720

19

2007

22451.214

3114.180

23845.712

S.1c. GDP per capita in the First, Second, and Third World

Row #

Year

1st World GDP per capita, GK$

2nd World GDP per capita, GK$

3rd World GDP per capita, GK$

1.

   2.

3.

4.

5.

1

      1

551

406

456

2

1000

425

400

461

3

1500

702

498

542

4

1820

1102

686

565

5

1870

1877

941

546

6

1913

3671

1558

714

7

1940

4991

2087

876

8

1952

6141

2699

914

9

1957

7154

3288

1047

10

1962

8433

3859

1121

11

1967

10339

4665

1279

12

1972

12427

5381

1524

13

1977

13928

6197

1785

14

1982

15012

6283

1958

15

1987

17334

6654

2200

16

1992

19043

5210

2478

17

1997

20960

4415

3006

18

2002

22968

5405

3418

19

2007

25326

7699

4477


 

S.1d. World population annual growth rates and the gap in GDP per capita between the 1st and the 3rd world

Row #

Year

World population annual growth rate, ‰

Gap between the 1st and the 3rd world, times (= 1st world per capita GDP/3rd world per capita GDP)

1.

   2.

3.

4.

1

      1

0.17

1.21

2

1000

0.99

0.92

3

1500

2.71

1.30

4

1820

4.06

1.95

5

1870

7.95

3.44

6

1913

9.25

5.14

7

1940

10.88

5.70

8

1952

17.86

6.72

9

1957

18.28

6.83

10

1962

19.09

7.52

11

1967

20.65

8.09

12

1972

19.59

8.15

13

1977

17.76

7.80

14

1982

17.82

7.67

15

1987

17.97

7.88

16

1992

15.23

7.67

17

1997

13.01

6.97

18

2002

12.23

6.72

19

2007

11.98

5.66

20

2012

11.48

4.52

21

2017

10.43

 

For years 1–1940, figures in column 2 indicate the average annual world population growth rate in the period starting with the respective year. For example figure 7.95 in row #5, in column #3 (next to 1870) indicates that the average world population relative annual growth rate in 1870–1913 was equal to 7.95‰ per year. For years 1952–2017 they indicate the average annual world population growth rate for a respective 5-year period. For example figure 20.65 in row #11, in column #3 (next to 1967) indicates that the average world population relative annual growth rate in 1965–1970 was equal to 20.65‰ per year. For years 1–1940 world population growth rate estimates have been calculated on the basis of Maddison’s estimates for the world population; for years 1950–2010 these are UN Population Division estimates; for years 2010–2020 these are UN Population Division medium projections.        

                We must note that if we add to the dataset all of Maddison’s data points (that is, including the years 1600, 1700, and 1900), the correlation between the global demographic growth rate and the magnitude of the Great Divergence does not become weaker. In fact, it becomes stronger:  r2 = 0.93.   Thus the exceptional cyclic or stochastic fluctuations in GDP in these years do not affect the overall relationship between the income gap and the rate of global population growth.

 

Additional tests

One of the anonymous referees of this article notes that “the gap in incomes between the First and Third Worlds depends on how the world is divided between First and Third Worlds, but the total world population growth rate does not”. There is some truth in this comment. Indeed, one of the variables pertain to the whole world, whereas the other to a part of it (though – an overwhelming one). As the second world population only comprises a small part of the total population of the world, it was quite clear for us that the exclusion of the second world population should not affect the results of the test. However – for the sake of scientific rigor – we have decided to make an additional test (on the basis of the data presented above in Tables S.1a–S.1d) correlating the gap between the first and the third world with the growth rate of the population of the First and Third World. The gap between the first and the third world has been calculated on the basis of data in Tables S.1a and S.1b, using the following intermediate table (see Table S.2 below):


 

Table S.2:

CALCULATION OF THE GAP BETWEEN THE FIRST AND THE THIRD WORLD
AS REGARDS PER CAPITA GDP

Row #

Year

1st World GDP,

blns GK$

1st World population, mlns

1st World GDP per capita, GK$[1]

3rd World GDP,

blns GK$

3rd World population, mlns

3rd World GDP per capita, GK$[2]

Gap between the 1st and the 3rd world, times[3]

1.

   2.

3.

4.

5.

6.

7.

8.

4.

1

      1

16.081

29.170

551

85.805

188.000

456

1.21

2

1000

14.861

34.930

425

100.907

218.800

461

0.92

3

1500

52.979

75.468

702

180.188

332.510

542

1.30

4

1820

193.098

175.259

1102

437.820

775.227

565

1.95

5

1870

503.084

268.024

1877

472.790

865.479

546

3.44

6

1913

1556.674

424.048

3671

809.371

1133.155

714

5.14

7

1940

2592.861

519.538

4991

1304.609

1489.703

876

5.70

8

1952

3555.381

578.962

6141

1611.868

1763.317

914

6.72

9

1957

4380.500

612.327

7154

2061.314

1968.954

1047

6.83

10

1962

5464.248

647.947

8433

2428.036

2165.441

1121

7.52

11

1967

7047.603

681.667

10339

3131.485

2448.911

1279

8.09

12

1972

8866.301

713.481

12427

4231.413

2776.085

1524

8.15

13

1977

10309.792

740.210

13928

5532.461

3099.765

1785

7.80

14

1982

11481.838

764.855

15012

6725.053

3433.864

1958

7.67

15

1987

13609.830

785.157

17334

8397.294

3817.763

2200

7.88

16

1992

15496.035

813.720

19043

10429.633

4209.026

2478

7.67

17

1997

17630.191

841.120

20960

13795.097

4589.559

3006

6.97

18

2002

19869.223

865.081

22968

16947.720

4958.794

3418

6.72

19

2007

22451.214

886.493

25326

23845.712

5325.698

4477

5.66

 

The results of the test have turned out to be quite congruent with our expectations (see Fig. S.1):

 

 

Figure S.1 | Correlation between the gap in GDP per capita between the First and Third World and the growth rate of the population of the First and Third World (‰). (Data in Supplementary Information above).

 

Note that the exclusion of the second world population from our regression analysis has not resulted in any significant change as regards our initial test. R2 has remained virtually the same (0.923 as compared with 0.924). In addition, within the regression model y = α + βx, values of constant α (1.07 as compared to 0.96) and coefficient β (0.35 as compared to 0.37) has remained essentially the same). The point that in both tests the value of constant α has turned out to be very close to 1 appears of particular importance, as this appears to suggest that when the world population stabilizes (that is, when the global modernization phase transition is completed), the gap between the First and the Third World may almost disappear.

However, the abovementioned anonymous reviewer was not quite satisfied with this test, sending us (through the Editor) the following additional comments: “My read of Tables S.1a-S.1d leaves me with the impression that the additional test does not actually test the issue raised in my previous comments. Tables S.1a-S.1d keep a fixed selection of First, Second, and Third World countries. The point I was making is that this selection is arbitrary. To test this, the authors would need to evaluate data with a variable selection of countries. For example, what happens when the Second World countries are lumped in with the First World countries, or with the Third World countries?”

Hence, we decided to perform additional tests suggested by the reviewer. First of all, we lumped the Second World countries in with the Third World countries (using Tables S1a and S1b above), which resulted in a rather familiar dichotomization of the world into the West and the Rest. The test of the correlation between the gap in GDP per capita between the West and the Rest, on the one hand, and the world population growth rate, on the other, has produced the following results (see Figure S.2):

 

 

Figure S.2 | Correlation between the gap in GDP per capita between the West (= the 1st World) and the Rest (= the 2nd World + the 3rd World) and the world population growth rate (‰). (Data in Supplementary Information above). r = 0.90; p << 0.0001.

 

As we see, the correlation  in this case has turned to be somehow weaker than in previous cases; but it is still very strong (r = 0.90) and statistically significant beyond any doubt (p << 0.0001).

On the next stage we have performed another test suggested by the reviewer through lumping the Second World countries in with the First World countries. This also resulted in a rather familiar dichotomization of the world – this time into the Global North and the Global South. The test of the correlation between the gap in GDP per capita between the Global North and the Global South, on the one hand, and the world population growth rate, on the other, has produced the following results (see Figure S.3):

 

Figure S.3 | Correlation between the gap in GDP per capita between the Global North (= the 1st World + the 2nd World ) and the Global South (the 3rd World), on the one hand, and the world population growth rate (‰), on the other. (Data in Supplementary Information above). r = 0.974; p << 0.0001.

 

As we see, in this case we have the strongest correlation among all the tests that we have performed, which might suggest that the Second World (at least for the 19th and 20th centuries) might be more meaningfully considered as a part of the World System core, rather than a part of its periphery.

Actually, one can clearly see that the main concern of the anonymous reviewer in question is that the divisions of the world used by the authors of this article are “arbitrary”. The least arbitrary division used above seems to be the one into “the West” and “the Rest”. Still, there is a certain element of arbitrariness in this division too. And it seems to stem first of all from the point that we (following the very widespread convention) included in the First World (= “the West”) Japan. However, West Europe, West European offshoots, and Japan formed a meaningful entity after the Second World War. But was this entity meaningful in 1820? Or 1500? Or 1000 CE? Of course, not.

Hence, in order to exclude the arbitrariness in such a division of the world, it appears necessary to exclude from “the West” Japan. After this we will get a division of the world into Western Europe (+ its offshoots) and the rest of the world that could hardly be considered as arbitrary. Indeed, Western Europe formed a meaningful entity (known as “the West European civilization”) already around 1000 CE (to which the offshoots were added quite organically after the Great Geographical Discoveries).

Thus, in order to produce the least arbitrary subdivision of the world in two relevant parts we have excluded Japan from “the West” and added it to “the Rest” (using Maddison’s [2010] data of Japan’s GDP and population), which resulted in the division of the world into “the pure West” and “the pure Rest”.

The resulting correlation between the gap in GDP per capita between “the pure West” and “the pure Rest”, on the one hand, and the world population growth rate, on the other, looks as follows (see Figure S.4):

 

Figure S.4 | Correlation between the gap in GDP per capita between “the pure West” (= the 1st World – Japan) and “the pure Rest” (the 3rd World + the 2nd World + Japan), on the one hand, and the world population growth rate (‰), on the other. r = 0.924; p << 0.0001.

As we see, with this subdivision of the World System into the core and periphery (which seems the least arbitrary) the correlation between the variables in question remains very strong and statistically significant beyond any doubt.

Thus, we find a very strong relationship between the global divergence degree (measured as the per capita income gap between the World System core and the World System periphery), on the one hand, and the world population growth rates, on the other, with all the versions of the division of the World System into the core and the periphery that we have tested.

 

Acknowledgment

 

This research has been supported by the Russian Science Foundation (Project # 14-11-00634).

 

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[1] (Column 3 / Column 4) * 1000.

[2] (Column 6 / Column 7) * 1000.

[3] Column 5 / Column 8. 

 
 

 


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