My

Project

Analyse the dynamics geography of urban inequality by linking together the economics of (national) inequality with the sociogeographical work on (urban) segregation

% income

% pop

Gini

Analysed for citizens

spaceless countries

• Plethora of measures available (Gini, 1%, capabilities, etc.)
• Considers dynamic relations with macro indicators (GDP, demographic growth, interest rate, etc.)
• Considers dynamic relations with micro indicators (years of schooling, gender, household, housing tenure, etc.)

Economic Inequality

Economic segregation

analysed for single cities

• Plethora of measures available (multigroup, multilevel, egohoods, etc.)
• Conceptualisation of the link between individual level and neighbourhood level (neighbourhood effects)
• Correspondance between segregation level and other city-level characteristics (Logan, mobility, social network)

Urban segre-gation

URBAN

SEGREGATION

ECONOMIC

INEQUALITY

The distribution of groups in the country (inequality) constrains the  group composition of each city

Neighbourhood effects affect the individual incomes and thus the overall distribution

Evident causal relations

between the two fields

They also share a pool of common explanations

URBAN

SEGREGATION

ECONOMIC

INEQUALITY

Schooling

Health

Inheritance

Housing

But the overlap is incomplete

URBAN

SEGREGATION

ECONOMIC

INEQUALITY

Population outside cities

Effect of space on income

Interaction at city level

Interaction at national level

Feedback loops of capital

Intermediate level of analysis

The urban landscape

as a dynamic field

One solution to reconcile them

Population outside cities

Effect of space on income

Interaction at city level

Interaction at national level

Feedback loops of capital

Intermediate level of analysis

The urban landscape

as a dynamic field

One solution to reconcile them

Population outside cities

Effect of space on income

Interaction at city level

Interaction at national level

Feedback loops of capital

Intermediate level of analysis

Delineating cities

Linking all scales dynamically

Making city delineation obsolete

> CRUCIAL BUT UNRESOLVED PROBLEM OF URBAN STUDIES

Institutional and political boundary

Physical limits

of built-up area

Functional areas of

integrated urban society

• City delineation captures the spatial extension of a certain definition (what we mean by city). Cf. Parr, 2007

Paris

10 km

30 km

~100 km

Making city delineation obsolete

> CRUCIAL BUT UNRESOLVED PROBLEM OF URBAN STUDIES

• The type of definition and delineation thresholds determine measured urban quantities and influence co-variations

Zipf's Law

Rosen & Resnick, 1980

Soo, 2005

+ Cottineau, 2017

Urban Scaling laws

Arcaute et al. 2015

+ Cottineau et al., 2017

+ Finance & Cottineau, 2018

Agglomeration Economies

Briant et al., 2010

Meijers & Burger, 2017

+ Cottineau et al., 2018

Social networks, mobility & segregation

Cottineau & Vanhoof, 2019

Urban morphology & segregation

Spielman & Harrison, 2013

+ Raimbault et al., 2018

Making city delineation obsolete

> CITIES and INTERURBAN links through a geographical fields approach

• Urban models need to consider the presence of other cities
• Individuals are the main actors navigating the landscape
• Cities still identifiable as intensity peaks

Work in progress

with J. Delloye, U. Lux.

Linking geographical scales of inequality and segregation dynamically

CONCEPTUALLY

EMPIRICALLY

A library of explanatory mechanisms

A multi-model to simulate them

Methods to explore and select sub-models behaviour

Network theory as a tool to detect multi-scale clusters

From geoindustrial clusters

to segregation clusters

A library of explanatory mechanisms for inequality

cf. https://unequalread.hypotheses.org/

1 book review every 2 months

LITERATURE REVIEW -

along with space-time scales involved

A library of explanatory mechanisms for inequality

cf. https://unequalread.hypotheses.org/

1 book review every 2 months

Chantal Jaquet, les transclasses

Thomas Piketty, Capital in 21st century

Alacevich, Soci, Short history of inequality

LITERATURE REVIEW -

along with space-time scales involved

A library of explanatory mechanisms for segregation

LITERATURE REVIEW -

along with space-time scales involved

cf. https://unequalread.hypotheses.org/

1 book review every 2 months

A library of explanatory mechanisms for segregation

LITERATURE REVIEW -

along with space-time scales involved

cf. https://unequalread.hypotheses.org/

1 book review every 2 months

George, Géographie des inégalités

Sampson, Great american city

A multi-model implementing mechanisms for inequality & segregation

GEOSIMULATION

MULTI-MODEL

Contextual effects

Public education

Inheritance

Social norms

Production and job market

ELEMENTARY MECHANISMS

• Assembled

• Compared

• Calibrated

for different spaces and times

• for theory

• for scenarios

• for policy

cf. Cottineau et al., 2015 on a model of urbanisation in the post-Soviet space

Network theory as a tool to detect multi-scale clusters

INDUSTRIAL SIMILARITY x GEOGRAPHICAL PROXIMITY

cf. Cottineau & Arcaute 2019

Source: ONS, BSD

Network theory as a tool to detect multi-scale clusters

cf. Cottineau & Arcaute 2019

P > p1

P > p2 > p1

P > p3 > p2

Network theory as a tool to detect multi-scale clusters

cf. Cottineau & Arcaute 2019

Source: ONS, BSD

Network theory as a tool to detect multi-scale clusters

cf. Cottineau & Arcaute 2019

Source: ONS, BSD

Network theory as a tool to detect multi-scale clusters

cf. Cottineau & Arcaute 2019

Source: ONS, BSD

Network theory as a tool to detect multi-scale clusters

cf. Cottineau & Arcaute 2019

Source: ONS, BSD

From geoindustrial clusters to segregation clusters

REPLACE FIRM COMPOSITION BY POPULATION GROUPS

Multiscale measure

Possibility to integrate time

Possibility to link mechanism scale to cluster delineation

Identification of discontinuities

Linkage between scales, from individual to national

Adaptable to individual and zonal data depending on availability

From geoindustrial clusters to segregation clusters

FIRST TESTS FOR LONDON

Using Annual Survey of Hours and Earnings

From 20,000 to 46,000 people surveyed in Greater London each year

Located at postcode level

Indication of gross pay & hours worked

+ social occupation, age, sex, etc.

Economic similarity  defined as

• K-S max distance between pay distributions of small areas

• Absolute difference of Gini index

Creation of pay distribution per small areas based on London deciles

From geoindustrial clusters to segregation clusters

FIRST TESTS

FOR LONDON

Source: ONS, ASHE 2009

Acknowledging the various scales of economic inequality and segregation

Linking spatial and temporal scales in the measure and simulation of economic inequality 

SUMMARY AND PERSPECTIVES

Accounting for dynamical processes

SUMMARY AND PERSPECTIVES

URBAN

SEGREGATION

ECONOMIC

INEQUALITY

Listing mechanisms with scales

Using multiscale methods

Embedding cities in continuous space

SUMMARY AND PERSPECTIVES

> Explore discontinuity in space with non-mergers of close clusters

> Use individual data (register?) to initialise models

> Extend multiscale clustering to national scale

References

Parr, J. B. (2007). Spatial definitions of the city: four perspectives. Urban Studies, 44(2), 381-392.

Rosen, K. T., & Resnick, M. (1980). The size distribution of cities: an examination of the Pareto law and primacy. Journal of urban economics, 8(2), 165-186.

Soo, K. T. (2005). Zipf's Law for cities: a cross-country investigation. Regional science and urban Economics, 35(3), 239-263.

Cottineau, C. (2017). MetaZipf. A dynamic meta-analysis of city size distributions. PloS one, 12(8), e0183919.

Arcaute, E., Hatna, E., Ferguson, P., Youn, H., Johansson, A., & Batty, M. (2015). Constructing cities, deconstructing scaling laws. Journal of The Royal Society Interface, 12(102), 20140745.

Cottineau, C., Finance, O., Hatna, E., Arcaute, E., & Batty, M. (2018). Defining urban clusters to detect agglomeration economies. Environment and Planning B: Urban Analytics and City Science, 2399808318755146.

Cottineau, C., Hatna, E., Arcaute, E., & Batty, M. (2017). Diverse cities or the systematic paradox of urban scaling laws. Computers, environment and urban systems, 63, 80-94.

Briant, A., Combes, P. P., & Lafourcade, M. (2010). Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?. Journal of Urban Economics, 67(3), 287-302.

Meijers, E. J., & Burger, M. J. (2017). Stretching the concept of ‘borrowed size’. Urban Studies, 54(1), 269-291.

Cottineau, C., & Vanhoof, M. (2019). Mobile phone indicators and their relation to the socioeconomic organisation of cities. ISPRS International Journal of Geo-Information, 8(1), 19.

References

Petrović, A., Manley, D., & van Ham, M. (2019). Freedom from the Tyranny of Neighbourhood: Rethinking Socio-Spatial Context Effects, Progress in Human Geography, 1-21

Cottineau, C., Reuillon, R., Chapron, P., Rey-Coyrehourcq, S., & Pumain, D. (2015). A modular modelling framework for hypotheses testing in the simulation of urbanisation. Systems, 3(4), 348-377.

Piketty, T. (2018). Capital in the 21st century. In Inequality in the 21st Century (pp. 43-48). Routledge.

Alacevich, M., & Soci, A. (2017). Inequality: A Short History. Brookings Institution Press.

Jaquet, C. (2014). Les transclasses, ou la non-reproduction. France (Presses universitaires de).

Sampson, R. J. (2012). Great American city: Chicago and the enduring neighborhood effect. University of Chicago Press.

George, P. (1981). Géographie des inégalités. FeniXX.

Raimbault, J., Cottineau, C., Texier, M. L., Néchet, F. L., & Reuillon, R. (2018). Space Matters: extending sensitivity analysis to initial spatial conditions in geosimulation models. arXiv preprint arXiv:1812.06008.

Spielman, S., & Harrison, P. (2014). The Co‐evolution of Residential Segregation and the Built Environment at the Turn of the 20th Century: AS chelling Model. Transactions in GIS, 18(1), 25-45.

Cottineau C., Arcaute E., (to be published), "The nested structure of urban business clusters", Applied Network Science. Available at https://arxiv.org/abs/1905.05106

Dank u wel!

Get in touch if you're interested.

email    | clementine.cottineau@ens.fr

twitter  | @ClementineCttn

gitHub  | github.com/ClementineCttn

blog      | unequalread.hypotheses.org

slides   | slides.com/clementinecottineau/geographical-scales-of-economic-inequality

Seminar at                           

28th October 2019

This work contains statistical data from ONS which is Crown Copyright. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates.