Old world city systems and economic networks 950-1950 how the growth and decline of cities and the rise and fall of city-size hierarchies is related to the network structure of intercity connections Doug White UC Irvine - PowerPoint PPT Presentation

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Old world city systems and economic networks 950-1950 how the growth and decline of cities and the rise and fall of city-size hierarchies is related to the network structure of intercity connections Doug White UC Irvine

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Title: Old world city systems and economic networks 950-1950 how the growth and decline of cities and the rise and fall of city-size hierarchies is related to the network structure of intercity connections Doug White UC Irvine


1
Old world city systems and economic networks
950-1950 how the growth and decline of cities and
the rise and fall of city-size hierarchies is
related to the network structure of intercity
connectionsDoug White UC Irvine
  • November 20 2009 talk
  • Social Dynamics and Complexity
  • ASU

2
economic networks and city systems using physics
models measures with large samples, time
series, inferential statisticsPhysical
measures examples
  • 1 Entropy minimum energy configuration given
    constraints/processes
  • 2 LDC Long-distance correlations
  • 3 q-scale entropy is (1) with (2) and power law
    tails when q gt 1
  • 4 q-scale network degree distribution parameter
    for a network where size is a LDC q-scale
    attractor to between hubs
  • 5 Time-lag cross-correlations for city size
    distribution q-scale parameters.
  • 1.Species, species populations, energy in
    habitat areas (J Harte)
  • 2.Cities depend on trading partners
  • 3.City size distributions, power law tails 1 lt q
    lt 2
  • 4.q-scale social circles simulation model of
    complex networks (White,Tsallis,
    Kejzar,Farmer,White 2006)
  • 5.q-scales of cities in city-system regions show
    temporal time lags from 0 (synchrony) to hundreds
    of years

As q ? 1, q-scale entropy converges to
Boltzmann-Gibbs entropy
P(X x) (1-(1-q)x/?)1/(q-1) (1 lt q 2) As x
?max and P ? 0 the tail of this distribution
converges to a log-log power-law slope -ß ?
1/(1-q), so P (1- ßx/?)-ß
3
Probability distribution q-fits for a person
being in a city in the region with at least
population x (fitted by MLE) Smooth lines are
fitted curves in successive time periods, jagged
lines bootstrap point distributions used to
estimate error boundsEach distribution is for
all the cities of a region, e.g., China, in one
of the 8 time periods, at 50 year intervals from
Chandler 1987
1.0 .1 .01 .001
1.0 .1 .01 .001 0001
The mle Pareto Type II q-scale. Measures the
shape of the body of the curve, while beta10
measure fits the log-log slope of the tails,
which vary independently of q.
Cum prob P(X x) on a log scale
Cum prob P(X x) on a log scale
Goodness of fit for q and beta10 are found by
bootstrap probability simulation, with iterations
added around each of four of the 8 periods
x City size log of 10
thousand 1 million
City size log of 10 thousand
1 million
city systems in the last millennium
Shalizi (2007) right graphsvariant q-fits
4
Whole period 900 1950 Credits
White, Tambayong, Kejzar 2008
Are there inter-region synchronies? Time-lag
cross-correlations give lag 0 perfect
synchrony lag 1 state of region A predicts
that of B 50 years later lag 2 state of region
A predicts that of B 100 years later lag 3
state of region A predicts that of B 150 years
later, etc.
The relation of q-scales in region
MiddleEastAfghanIndia to Chinese cities is
(1) synchronously inverse but with (2) 100-150
year lags affects them positively
5
Moving to inter-Asian regions on the Silk Road,
excluding India Time-lagged cross-correlation
effects of Mid-Asian q-scale on China q-scale
These and the other cross-correlations hold on
average for the 1000 year time period.
MiddleEastAfghan Robust Cities affect Robust
Chinese Cities with 50 year lag
(150 year lagged effect, 21 year lag, etc.)
6
For endpoints further away on the Silk
Roads Time-lagged cross-correlation effects of
China q-scale on Europe q-scale
(100 year lagged effect)
7
Time-lagged cross-correlation effects of the Silk
Road trade on Europes beta (beta is the slope of
the power-law tail of the urban distribution)
(50 year lagged effect)
Chinese Silk road trade affects Elite tails of
European Cities with a 50 year lag
Mideast cities q have a small effect on European
cities q with 150 year lag
8
European cities q-scale synchrony with of
France population living in Paris, with 100 year
decay
9
Variations in q and the power-law slope ß for
900-1970 in 50 year intervals
Credits White, Tambayong, Kejzar, Tsallis, 2006,
2008
city systems in the last millennium
10
Are these random walks or historical Periods?
Runs Test Results
city systems in the last millennium
11
Is there Eurasian synchrony or are there
time-lagged effects? Some synchrony when
dependent variable closely related in same region
but conservative (Euro beta, Paris ) Mostly
time-lagged effects of leading regions, i.e.,
directional not symmetric, with lagging regions,
consistent with Modelski Thompson 1996 w
Devezas 2008, i.e., globalizing econ./pol.
leaders Next we test whether, if economic
competition is increased by multiconnectivity
(structural cohesion) The dynamics of trade is
influenced by the trading network whether
monopolized by chokepoints or competitive. Leaders
-to-lagger economic effects follow the dynamics
of trade.
12
0900 AD
From first stirrings of globalization to the 21st
Century Credits White, Tambayong, SFI
Europe Central Asia Medit. China
Near East India
Silk routes
In these slides I will connect the city network
city size distributions and power-law tails
connected to q-exponential scaling of city sizes
Bagdad Changan (Xian)
Changan
Changan
Changan
low q with thin power law tails of global hubs
CORRELATES with global network links
Q (scaling sizes)
13
1000 AD 960 Song capital at Kaifeng, invention
of national markets, credit mechanisms diffuse
N3
Silk routes
Global network links characterize low q (power
law tail for city sizes)
14
1100 AD
Silk Routes
Global network links characterize low q (more
exponential body with power law tail for city
sizes)
15
1150 AD
1127 No. Song capital of Kaifeng conquered,
Song move to south, capital at Hangchow
Silk Routes diminish
Global network links characterize low q (more
exponential body with power law tail for city
sizes)
16
1200 AD Song capital at Hangchow Golden Horde
silk routes
Silk Routes diminish
Global network links characterize low q
17
1250 AD
cutnodes
edgecut
Broken network links lead change to high q led
by China, 50 years
18
1300 AD
1279 Mongols conquer Song Kublai Khan Mongol
trade
Broken network links characterize high q (here
tenuous interregional connectors)
19
1350 AD
Mongols refocus on Yuan administration of
China Silk routes unimportant
Broken network links characterize high q (here
tenuous interregional connectors)
20
1368 Ming retake China Silk routes unimportant
1400 AD
Renewed network links characterize low q (power
law tail)
21
1450 AD
1421 Ming move capital to Peking Silk routes
unimportant
World population growth turns super-exponential
Renewed network links characterize low q (power
law) high q led by China, 100 years
22
1500 AD
Renewed network links characterize low q (power
law tail) but China high q leads change
23
1550 AD
Broken network links characterize high q
24
1600 AD
Renewed network links will lead change to low q
(here tenuous interregional connectors)
25
British/East India circumferences of the
trading circles are small, sufficient by 1720 and
1760 to induce fully competitive market pricing
? Network cohesion plus close regional distances
Britain India
COMPANY ROUTES in 1620 evolve thru malfeasance by
ship captains to independt market price
capitalism from 1720
Erikson, Emily and Peter S. Bearman. 2006
Malfeasance and the Foundations for Global Trade
The Structure of English Trade in the East
Indies, 16011833 American Journal of Sociology
(2006) 112(1)195-230. Fig. 3
26
1650 AD
Renewed network links characterize low q (power
law tail) China crash synchronized
27
1650 AD
Renewed network links characterize low q (power
law tail) China crash synchronized
28
1700 AD
Broken network links return to high q esp. for
China leading
29
1750 AD
Broken network links typify high q China
leading bifurcated world
30
1800 AD
Circum-European cities start to overtake China
in number
Broken network links typify high q bifurcated
world
31
1825 AD
European cities overtake China in number and
size Industrial revolution
Broken network links typify high q trifurcated
world best example of high local navigability
British opium trade from India
32
1850 AD
Broken network links typify high q trifurcated
world but China developing power-law tail
British benefit from peace treaty
(here tenuous interregional connectors)
33
1875 AD
Broken network links typify high q bifurcated -
China power-law tail thinning toward low-q
British benefit as opium legalized
(here tenuous interregional connectors)
34
1900 AD
Broken network links typify high q trifurcated
Eurodominant - China leads shift to low-q 50 yrs
British benefit opium legal
35
1925 AD
Broken network links typify high q trifurcated
- rise of Japan - China returns to high q
British trade but opium banned Britain lease on
Hong Kong from 1898
36
Start of a low q Zipfian tail for world city
distribution trifurcated but linked by
airlines
37
World land C ?F ?CF
?F ?C ?F routes integrating
N-cohesion (2competitive 1monopoly land trade)
leads q-scale, dichotomized (city rise/fall), in
moving averages for 150 year periods
N leads q to 1500, competitive trade ?
cities Inverse of N ? leads q to 1750, Portuguese
British Indian markets create choke-point trade
? city q-scale q ? leads inverse of N (more
choke-points) 1750-1900 (industrial revolution
maritime displaces land trade)
N ? q
N ? q
N ? q
q ? N
World land routes disintegrating
N.Sung S.Sung Genoa Portugal Dutch
Engl.British USA--- Decol.
__________________ /Mongols /Venice
38
Transaction costs, hegemony and inflation as
q-correlated temporal variables
Europe and Mediterranean
Commercial
Inflation Lo/hi
Financial capital
Peace of Westphalia
Dominant Routes
Struggle for Empire Sea Battles to 1815
Trade net (low cost) versus (high cost)
Global Maritime Economy Industrial Rev. from
1760 Political Revolutions to 1814
Maritime (low cost) versus Land routes
trade (pop. growth)
Conflict on Land ? Sea trade routes safer than
land, 1318-1453/4 (Spufford407)
Sea routes safe French Sov.
Landed Armies safe land routes 1500-1650
Maritime Conflicts (Jan Glete)
Landed Trade Secure
Baltic conflicts connection to Novgorod and
Russia (lost) Swedish hegemony European
access
39
Euro-Hegemon examples (Arrighi 1994) Commercial Fi
nancial Constantinople Venice Genoa Amsterdam Lon
don New York
40
The Medieval pause and Conclusions
  • WHY DOES THE MEDIEVAL EUROPEAN RENAISSANCE
    ECONOMY FALTER CIRCA 1300?
  • Major problem in Population Growth/Resource base
  • Partly conflicts on land, internecine struggles
  • Credit crisis between North and Southern Europe
  • China invaded, change in Silk routes
  • Trade dominance in the long terms begins to shift
    from betweenness centrality (Genoa commercial
    capital) to global Flow Centrality (Bruges
    financial capital), with later oscillations.
  • Major collapse, long recovery "Long 13th century
    reaches to today
  • Conclusions city systems in the last millennium
  • City systems unstable have historical periods of
    rise and fall over hundreds of years exhibit
    collapse.
  • City system growth periods in one region, which
    are periods of innovation, have time-lagged
    effects on less developed regions if there are
    active trade routes between them. 
  • NETWORKS AFFECT DEVELOPMENT.
  •  

41
Parts of the story in a nutshell Pax Mongolica
The routes are subject to policies of polities
and empires, part of periods of pol./econ.
dominance (Modelski et al. p.78,217)___Regional N.
Sung 930- S. Sung 1060- Genoa/Venice 1190-___to
Global____ Mongols 1250-90-1360 trans
Eurasian Portugal 1430- Global system
mapping Holland 1540- Global capital England
1640- Global industrial exports Britain 1740-
Global organization United States 1850-Global
information- Global market United States 1950-
Decolonization -1990 Depolarization - Global
hyperspace
42
Globalization
  • The Mongol administrative improvements of postal
    routes and support for merchants on the Silk
    roads were key to the rise of the Mongol Empire
    (on the scale of the later British Empire) and a
    first planned policy attempt at creating new
    routes for global trade and political
    globalization, i.e., going beyond earlier Roman
    and Greek (Alexandrian) attempts, for example.
    Modelski refers to the Mongols as a failed empire
    because they retreated to the east to dominate
    China until 1912. Their success and the benefits
    of East-West trade, however, were the spur to
    Portuguese and subsequent attempts at policy
    engineering towards globalizing trade and the
    periods of attempted West-East domination.
  • A next study of planned globalization will start
    in 1290 and review globalization policies and
    pitfalls.
  • Globalization as a learning process
  • Globalization policies at attempts as dominance
  • The cycles of leading polities
  • And the two shorter economic cycles within them
  • The costs of losing dominance
  • The effects of wars over dominance
  • Paths to mutual regional support and peaceful
    resolution of competition

43
end
44
(figures courtesy of Andrew Sherratt, ArchAtlas)
Cohesive extension of trade routes leads to a
host of other developments
45
Multiconnected regions gt structural cohesion
variables
(but the circumferences of these trading circles
are large, not sufficient to induce fully
competitive market pricing)
46
Multiconnected regions gt structural cohesion
variables
47
Multiconnected regions gt structural cohesion
variables
48
Multiconnected regions gt structural cohesion
variables
Some changes in the medieval network from 1000 CE
49
Multiconnected regions gt structural cohesion
variables
to 1500 CE (note changes in biconnected zones of
structural cohesion)
Project mapping is proceeding for cities and
trade networks for all of AfroEurasia and urban
industries for Europe in 25-year intervals,
1150-1500
(our technology for cities / zones / trade
networks / distributions of multiple industries
across cities for each time period includes
dynamic GIS overlays, flyover and zoomable web
images)
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