Synchronous East-West

Urban and Empire Upsweeps?

Christopher Chase-Dunn, Hiroko Inoue, Alexis Alvarez, Kirk Lawrence and James Love

Institute for Research on World-Systems

University of California-Riverside

Frederic Teggart’s Rome and China

 

Earlier studies found a curious interregional synchrony in the growth and decline of large cities and empires. From about 500 BCE until about 1500 CE cities and empires in East Asia and the West Asian/Mediterranean region appeared to be growing and declining in the same periods, whereas intervening South Asia did not conform to the East/West pattern. This paper reports the results of a reanalysis of these patterns and our effort to see if major scale increases (upsweeps) in the sizes of cities and empires in the East and the West were synchronous or not.

To be presented at the 2009 conference of the Social Science History Association, Long Beach, CA Sunday, November 15: 10:15 AM-12:15 PM. Session on Synchrony in History. V. DRAFT: v. 11/17/09 xxxx words

This paper is available at http://irows.ucr.edu/papers/irows53/irows53.htm

 

New graphs of east/west cities and empires together. Results of  new search for east/west city and empire synchrony.  Also south asia synchrony?

Upward sweeps stuff.  Diff between cycles and upsweeps.

Population stuff.

Partial correlations.  Adrefs turchin, upsweeps pap. Strogatz,  lagged synch? 

 

 

 

            The growth and decline patterns and upward sweeps in the sizes of the world’s largest cities and empires and their changing locations over the past three millennia provide an important window on world history and sociocultural evolution. Earlier research has shown what appears to be a fascinating synchrony in the growth/decline phases of the largest cities and empires in East Asia and in the West Asian/Mediterranean region (e.g. Chase-Dunn and Willard 1993; Chase-Dunn, Manning and Hall 2000; Chase-Dunn and Manning 2002). 

Using data on the population sizes of largest cities and the territorial sizes of largest empires it has seemed that medium-term growth/decline phases in East Asia and in the West Asian/Mediterranean region experienced synchronous cycles between 500 BCE and 1500 CE.[1] So for two thousand years, when the largest city was growing in East Asia, the largest city in West Asia was also likely to be growing, and they also tended to decline in size simultaneously. With a completely different data set based on the territorial sizes of the largest states and empires in each region, the same phenomenon has been found. But this same synchrony is not found in the South Asian subcontinent (India) where cities and states were growing and declining, but not in the same time periods as in East Asia and West Asia. In this paper we distinguish between smaller and larger increases and decreases.  A small increase and decrease is called a cycle, while a relatively large increase is called an upward sweep or upsweep. It is the upsweeps that account for the long-term trend of growth in sizes of settlements and polities, and so they are the important events in the evolution of larger and more complex human societies. The earlier research on East/West synchrony does not distinguish between cycles and upsweeps. In this paper we want to investigate whether or not the East and West upsweeps in settlement and polity sizes were synchronous.

Earlier Findings

            The population and areal sizes of human settlements have increased since the emergence of sedentism around 12,000 years ago, and so have the sizes of the largest polities. But these general long-term trends have been complicated by sequential middle-term declines in the sizes of the largest cities and empires in all regions where urban and polity sizes have been studied quantitatively. The population size estimates of both modern and ancient cities are subject to large errors, and existing compilations (Chandler 1987; Modelski 2003) badly need to be improved using better methods of estimation (e.g. Pasciuti and Chase-Dunn 2002). The same can be said for existing compilations of estimates of the territorial sizes of the world’s largest empires (Taagepera 1978a, 1978b, 1979, 1997). When these upgraded estimates become available, the East/West synchrony findings discussed here will need to be reexamined with the improved data.

            This phenomenon of East/West urban and empire synchrony in middle-run growth/decline phases has been subjected to several different methods of analysis. Both changes in the size of the largest cities and changes in the steepness of the city-size distributions have been used. And earlier studies have used two different kinds of spatial units of analysis: constant regions and expanding political-military networks (interaction networks of fighting and allying states). The East/West synchrony has been found with both.

 Detrending is important because the long-term trend for city and empires sizes to increase and so this alone would produce a positive correlation across distant regions. Two different methods of detrending have been used: partial correlation controlling for year and decadal change scores in which the earlier year is subtracted from the later year. In the studies of empire sizes, empires that touch adjacent macro-regions such as the Mongol Empire of the thirteenth century CE have been removed from the analysis because they build in a degree of synchrony by appearing in both regions at the same time. The synchrony finding is strong even when this case has been removed from the calculations.

Frederick Teggart’s  (1939) path-breaking world historical study of temporal correlations between events on the edges of the Roman and Han Empires argued the thesis that incursions by Central Asian steppe nomads were the key to East/West synchrony. An early study of city-size distributions in Afroeurasia (Chase-Dunn and Willard 1993; see also Chase-Dunn and Hall 1997: 222-223) found an apparent synchrony between changes in city size distributions and the growth of largest cities in East Asia and West Asia-Mediterranean over a period of 2000 years, from 500 BCE to 1500 CE.  That led to an examination of data on the territorial sizes of empires for similar East/West synchrony, which was also found (Chase-Dunn, Manning and Hall 1999). The empire size data also allow the examination of rise and fall sequences of large empires in South Asia, but these were not synchronous with the growth/decline phases of empires in East Asia or West Asia (Chase-Dunn, Manning and Hall 1999). Chase-Dunn and Manning (2002) re-examined the city size data using constant regions rather than political-military networks to see if the East/West synchronous city growth hypothesis holds when the units that are compared are constant regions rather than expanding political/military networks (see Figure 1).

Figure 1: Sizes of Largest cities in East Asia and West Asia/Mediterranean

Comparable other instances of distant systems that came into weak contact with one another can be found.  Within the Old World, the Mesopotamian and Egyptian core regions were interacting with one another by means of prestige goods exchange from about 3000 BCE until their political-military networks (state systems) merged in 1500 BCE. Chase-Dunn, Pasciuti, Alvarez and Hall (2006) have already examined this case for synchrony and have not found it, though the data on Bronze Age city and empire sizes are very crude with regard to temporality and accuracy. It is also possible to study the temporality of rise and fall and oscillations among distant regions in the New World (e.g. Peregrine 2005).

Chase-Dunn, Alvarez and Pasciuti (2005) also report detrended correlations between constant regions for total population estimates taken from McEvedy and Jones (1975). These total population estimates at 100-year intervals show rather high growth/decline synchronies for several regions, also noted and discussed by McEvedy and Jones (1975: 343-48).

The East/West growth/decline synchrony seems to be rather robust, though better estimates and finer temporal resolution of empire and city sizes might challenge it. Interregional synchrony can be caused when two cyclical processes get simultaneously reset, either by the same cause or by different causes. This could be a one-shot occurrence. Or a process that is similarly cyclical can cause synchrony. Candidates for the East/West synchrony are: climate change, epidemic diseases, trade interruptions, or attacks by Central Asia steppe nomads. Sorting this out will require data on these phenomena for the relevant regions over the relevant time period.

Possible Explanations

            Climate change might affect regions by causing growth and decline of agricultural productivity that in turn affects cities and empires. Perhaps because South Asia is nearer the equator, its climate change history is different and this might explain why its growth/decline pattern is different. The simplest thing would be to find “little ice ages” or other large climate changes that correspond with the big changes in city and empire sizes.

            But climate change could also be involved in somewhat more complicated ways. Central Asian steppe nomads (discussed below) were very susceptible to climate change because their pastoral economy was greatly affected by changes in temperature and rainfall. It is possible that climate change in Central Asia affected the nomads, who then carried out incursions and military campaigns that affected the cities and agrarian empires of the East and West.

            The above hypotheses all conceive of climate change as an exogenous variable. But it is also possible that city and empire growth change the climate. We know that population growth and the development of complex civilizations changes the environment by means of deforestation, soil erosion and the construction of large irrigation systems (Diamond 2005). These changes may have affects on climate. Modern studies show that the construction of large cities creates an “urban heat island” that changes the environment in the immediate vicinity and downwind of cities. Cities ingest and egest water, air and energy, and while industrial cities do this on a much larger scale, earlier large cities also did it to some extent. So large-scale agriculture and city-building may be causes of climate change. Thus climate change may also be an endogenous variable.

            We know that Central Asian steppe nomads who raised horses and sheep periodically formed large confederacies and attacked the agrarian empires of the East and the West (Barfield 1989). Famous examples are the Huns and the Mongols. Perhaps there was a cycle of Central Asian incursions that impacted upon the agrarian civilizations of the East and the West and that accounts for the synchrony.

            We know that epidemic diseases spread across Eurasia killing large numbers of people in cities, for example the Black Death (Bubonic Plague) of the 13th century. Perhaps earlier pandemics (e.g. the plague of Justinian) caused the synchrony.

            We also know that the Roman and Han empires were linked by long distance trade routes across the Silk Roads and by sea. Perhaps interruptions to trade, or periods of greater and easier trade flows, affected the Eastern and Western civilizations simultaneously.

            It is also possible that two systems that are cycling independently can become synchronized if they are both reset by a simultaneous accidental shock. This is the so-called “Moran Effect” known in population ecology. We have discussed this possibility in Chase-Dunn, Alvarez and Pasciuti (2006).

            Figure 2 is a propositional inventory that includes most of the possible causes of East/West synchrony.

Figure 2: Possible Causes of East/West Synchrony

More research is required to find out which of these possible causes was responsible for the East/West synchrony. We have found some evidence that temperature changes in China are not associated with the growth/decline phases of cities or empires in East Asia. This is evidence against the climate change hypothesis.

Cycles, Upward Sweeps, Collapses and Ceilings 

We empirically identify “upward sweeps,” when the scale of cities and states dramatically increased. We review and synthesize explanations of chiefdom-formation, state-formation, empire-formation and the rise and fall of modern hegemonic core states in order to produce formal explanatory models. And we study the emergent characteristics that distinguish these different scales in order to comprehend how the processes have qualitatively evolved, and in order to consider what kinds of qualitative transformation might occur in the future. Our approach avoids the unscientific pitfalls of progressivist, functionalist, inevitabalist and teleological presumptions that have plagued many earlier approaches to socio-cultural evolution. We do not identify complexity and hierarchy with progress, but neither do we assume that they are the opposites of progress.

            Our project compares relative small regional systems with larger continental and global systems, thus we must abstract from scale in order to examine changes in the structural patterns of small, medium and large human interaction networks. That said, we are also interested in medium term change in the scale of polities and settlements. We are not considering very long-term trends in this discussion. When an interacting set of polities or settlements is the unit of analysis nearly all systems oscillate in what we may term a normal cycle of rise and fall – the largest city or polity reaches a peak and then declines and then this or another city or polity returns to the peak again. We call this a normal cycle of rise and fall. It roughly approximates a sine wave, although few cycles that involve the behavior of groups of humans actually display the perfect regularity of amplitude and period found in the pure sine wave. In Figure 3 the cycle of rise and fall is half way down the figure and is labeled “normal rise and fall.” At the top of Figure 3 is a depiction of an upward sweep in which the size of the largest entity (state or city) increases by a factor of 2. Such a sweep may be relatively rapid or may be slow, and Rein Taagepera (1978a) contends the speed of the rise is often related to the sustainability of the upsweep, at least in the case of empires. Taagepera notices that empires that rise more slowly tend to last longer than those that rise abruptly. When an upward sweep is sustained and a new level of scale becomes the norm we call this an upward sweep. When it is temporary and returns to the old lower norm we call it a “surge” (see the 2nd line from the top in Figure 3). We also distinguish between three types of decline, a “normal” decline which is part of the normal rise and fall cycle, a short-term collapse in which a decline goes significantly below what had been established as the normal trough, and a sustained collapse in which the new lower scale becomes the norm for some extended period of time. Jared Diamond (2005) has examined the complex causes of a large collection of collapses, though he does not rely on quantitative indicators of collapse and he often focuses on particular societies or settlements that collapsed while ignoring neighboring societies or settlements that rose. If intersocietal interaction networks (world-systems) had been Diamond’s unit of analysis instead of single societies most of the cases of “collapse” that he studied would have been instances of normal rise and fall cycles rather than instances of system-wide collapse. A genuine collapse is when all the societies in a region go down and stay down for a long period. [2]

Figure 3: Types of medium-term scale change in the largest settlement or polity in an interacting region   

 

Replication of the Earlier Synchrony Findings: Cities

            The published studies that found synchrony between Eastern and Western growth/decline phases of largest cities in each region were based on Tertius Chandler’s (1987) compendium of estimates of the sizes of large cities. George Modelski (2003) has produced a new and improved compendium of city size estimates. For this paper we have used Modelski’s estimates to study upward sweeps of city sizes and here we use them to once again examine the question of East/West urban synchrony. The regions we are comparing are East Asia, including China, Korea and Japan, and the Central System, which is West Asia and North Africa (Mesopotamia and Egypt) and then the Mediterranean and then Europe (London). These are the same regions that were used in earlier studies of East/West Synchrony. The city size estimates are shown in Table 1 in the Appendix.

 Figure 4 below shows the results of the East/West comparision of largest cities and should be compared with Figure 1 above that shows the same results using Chandler’s compendium.

 

 


Figure 4: East/West Largest Cities

Figure 5: East-West Largest City Annual Growth Rates

Correlations

 

 

W annual growth rate

E annual growth rate

W annual growth rate

Pearson Correlation

1

.181

Sig. (2-tailed)

 

.215

N

49

49

E annual growth rate

Pearson Correlation

.181

1

Sig. (2-tailed)

.215

 

N

49

49

Table 1: East-West Largest City Growth Rate Correlation

The Pearson’s r bivariate correlation coefficient for the East and West largest annual growth rates is over the whole period from 1700 BCE to 1900 CE is .18 (n=49) and this is not a significant correlation. We also have examined the subperiod from 500 BCE to 1500CE during which an East-West city synchrony was found based on Chandler’s data using the new Modelski estimates, and no significant synchrony is found for this subperiod. So we conclude that the earlier finding was in error due to missing time points and inaccurate estimations of city sizes.

Replication of the Earlier Synchrony Findings: Empires

 

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Appendix

West

 

 

East

 

 

Year

Largest City Population

City Name

Year

Largest City Population

City Name

-1700

60

Babylon

1700

40

Erlitou

-1650

67

 

-1650

24

Erlitou

-1600

75

Avaris

-1600

24

BO (Yanshi)

-1500

60

Thebes

-1500

74

 

-1484

64

 

-1484

100

Zhengzhou

-1400

80

Thebes

-1400

104

 

-1300

120

Thebes

-1300

120

Yin

-1200

160

Pi-Ramses

-1200

120

Yin

-1173

150

 

-1173

120

Anyang/Yinxu

-1100

120

Pi-Ramses

-1100

112

 

-1000

120

Thebes

-1000

100

Haoqing

-900

100

Memphis/Thebes/Babylon

-900

125

Haoqing

-800

100

Memphis/Thebes/Babylon

-800

125

Haoqing

-700

100

Memphis/Thebes/Babylon/Nineveh

-700

100

Luoyang

-600

200

Babylon

-600

200

Louyang

-500

200

Babylon

-500

200

Loyang /Linzi

-400

200

Carthage/Babylon

-400

320

Xiatu

-300

500

Carthage

-300

350

Linzi

-200

600

Alexandria

-200

200

Luoyang

-100

1000

Alexandria

-100

400

Changan

1

800

Rome

1

420

Changan

100

1000

Rome

100

420

Luoyang

200

1200

Rome

200

100

Luoyang /Linzi

300

1000

Rome

300

250

Loyang

400

800

Rome

400

300

Nanjing

500

500

Constantinople

500

500

Luoyang/Nanjing

600

600

Constantinople

600

500

Luoyang

700

400

Constantinople

700

1000

Changan

800

700

Baghdad

800

800

Changan

900

900

Baghdad

900

200

Loyang/Kyoto

1000

1200

Baghdad

1000

400

Kaifeng

1100

1200

Baghdad

1100

1000

Kaifeng

1150

1100

Baghdad

1150

1000

 

1200

1000

Baghdad

1200

1000

Kaifeng/Hangzhou

1250

300

Cairo

1250

1250

 

1300

400

Cairo

1300

1500

Hangzhou

1350

350

Cairo

1350

1250

 

1400

360

Cairo

1400

1000

Nanjing

1450

380

Cairo

1450

1000

 

1500

400

Cairo

1500

1000

Beijing

1550

660

Constantinople

1550

1000

 

1600

700

Constantinople

1600

1000

Beijing

1650

700

Constantinople

1650

844

 

1700

700

Constantinople

1700

688

Edo

1750

676

London

1750

900

Beijing

1800

1117

London

1800

1100

Beijing

1825

2100

London

1825

1350

Beijing

1850

3750

London

1850

1648

Beijing

1875

4850

London

1875

900

Beijing

1900

6500

London

1900

1497

Tokyo

 

Table 2: Largest Cities in the East and the Central System (numbers in blue are interpolations)

 



[1] This was first noticed in 1992 by Chase-Dunn and Willard (1993) who were studying changes in the city-size distributions of several different regional world-systems. A striking similarity between the East Asian and West Asian city-size distribution trajectories was first confirmed by overlaying the graphs and holding them up to the bright light of a window.

[2] These are rare, but the long inter-regnum in South Asia between the demise of the Mauryan Empire and the rise of the Mughal Empire should be considered a regional collapse.