Dear Harald Bathelt, Max Buchholz and Michael Storper,

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Hopefully I am not too late to send abstracts of two papers developed together 
with my colleague Uma Kollamparambil. These relate particularly  to your 
request for contributions that broaden our understanding of intra- and 
interregional inequality, so as to better understand and fight inequality.

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Abstract paper one

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The Impact of Foreign Direct Investment on Income Inequality: A Global 
Multilevel Path Analysis at the Country and City Scale.

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To what degree do country level and city level Foreign Direct Investments (FDI) 
affect wage inequality around the world? Because contemporary studies only 
explore the impact of FDI at the county level, rather than that of cities, it 
becomes imperative in our rapidly urbanizing world to better understand the 
impact of investment on wage inequality at both geographic scales - i.e. 
decomposed into interregional inequality [differences between countries] and 
intraregional inequality [differences within countries] (Kanbur (2014). The 
study also adds further value by revealing both the direct and indirect effects 
(causalities) of three different measures of FDI (investment value, investment 
count and investment distance) at city and country levels, using a multilevel 
Structural Equation Model (SEM). 

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The paper explores the impact of FDI on wage inequality of 800 world cities. 
Firstly, we show that FDI is causal to income inequality, and not the other way 
around.  Secondly, that there is no straightforward answer to whether FDI 
positively or negatively affects income inequality, because it depends on which 
metric you use, and whether you are looking at the country or city scale.  
Thirdly, that the value of investments (dollars) significantly reduces 
inequality at the city level but increases inequality at the country level.  
This shows that FDI disproportionately favours major cities where inequality is 
reduced, but that for most other cities within countries, the uneven 
distribution of FDI increases inequality of these cities. This supports theory 
on the uneven distribution of investment capital across regions (Rodriguez-Pose 
2010, Wei Yao and Liu 2009). Fourthly, that the number of investments (count) 
significantly reduces inequality at both city and country levels. This tells us 
that the more a city attracts investments from diverse sources, the more its 
inequality will decrease. Fifthly, we found that FDI from regional countries 
tends to decrease inequality, while investments from faraway global sources 
tend to increase inequality. This is likely because large multinationals invest 
at great distances utilizing technologies that do not create inclusive growth 
for local economies. Smaller multinationals tend to invest more regionally and 
with more accessible technologies.

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*       Kanbur, R., Rhee and J. Zhuang (2014) Inequality in Asia and the 
Pacific: Trends, Drivers, and Policy Implications, Routledge, 2014.
*       Rodríguez-Pose, Andres. 2010. “Trade and Regional Inequality.” World 
Bank Policy Research Working Paper No. 5347.
*       Wei K., Yao S., Liu, A. (2009) Foreign Direct Investment and Regional 
Inequality in China, Review of Development Economics, Volume13, Issue4, Pages 
778-791

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Abstract paper two

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Uneven Ties: Multilevel Centrality of Cities and Countries within the Global 
FDI Network and its Impact on Income Inequality

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Today, agglomeration economies (city-regions) are understood to be key drivers 
of FDI (Guimaraes et al., 2000; Burger et al., 2012), but beyond certain 
thresholds, can lead to negative externalities like rising labor costs and 
income inequality (Chan et al., 2008). However, notwithstanding that FDI 
manifests in cities, most studies are still carried out at the country level 
and neglect the urgency to disaggregate FDI and income inequality at country 
sublevels, e.g. intra-city or inter-city levels (Kanbur, 2014).  

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Contemporary economic globalization results in a multiplicity of configurations 
that are both relational and trans-scalar in nature and contradict conceptions 
that bias territorial assumptions concerning the nature of economic 
development. Instead, there is a growing recognition that a new spatial 
ontology has emerged, founded in network structures and flows across 
geographical domains, extent and duration (Larner & Le Heron, 2002; Coe et al., 
2008). This network consists of a mass of supply chains and corporate networks 
that tie worldwide producers and consumers together (Dicken, 2014; Hughes and 
Reimer, 2004).

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Notwithstanding that FDI generally manifests in city-regions, most studies on 
income inequality are executed at the country level. Furthermore, because 
city-regions are increasingly dependent on cross-border networks, an 
understanding of their economic development can no longer be restricted within 
their territorial boundaries. Considering these research gaps, our study 
uniquely deciphers the complex centralities of major cities and countries 
within the global FDI network, and how this impacts income inequality. By 
bridging global network and inequality studies, we address the necessity to 
integrate network and territorial development. Next, by means of multilevel 
structural equation modelling, we test how intra-regional and inter-regional 
income inequalities are influenced by different types and levels of FDI network 
centrality, i.e. structural hole, closeness, clustering coefficient and 
reciprocity. 

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Indeed, we show that network centrality measures explain income inequality at 
the city and country level, and that global interdependency is conditional to 
territorial development. Furthermore, it is shown that network centrality can 
either increase or decrease income inequality, depending on the measure or 
level observed - hereby emphasizing that a nuanced theoretical definition is 
required. The results show that city inequality is reduced by structural hole 
strength (innovation advantage of cities) and reciprocity (mutuality advantage 
of cities). The latter reveals a non-linear relationship, in which it reduces 
inequality in developing cities, but raises it for developed cities. Also, the 
clustering coefficient (the proximity advantage of countries), increases the 
income inequality of cities. Similar results are found at the country level.

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*       Guimaraes, P., Figueiredo, O. and Woodward, D., 2000. Agglomeration and 
the location of foreign direct investment in Portugal. Journal of Urban 
Economics, 47(1), pp.115-135.
*       Burger M.J., v.d. Knaap and Wall R.S (2012) Revealed competition for 
greenfield investments between European regions, Journal of Economic Geography.
*       Chan, K.W., Henderson, J.V. and Tsui, K.Y., 2008. Spatial dimensions of 
Chinese economic development. In China’s great transformation: Origins, 
mechanisms, and consequences of the post-reform economic boom, T Rawski and L 
Brandt (eds.), Cambridge University.
*       Kanbur, R., Rhee and J. Zhuang (2014) Inequality in Asia and the 
Pacific: Trends, drivers, and policy implications, Routledge.
*       Larner, W., & Le Heron, R. (2002). The spaces and subjects of a 
globalising economy: a situated exploration of method. Environment and Planning 
D: Society and Space, 20(6), 753-774.
*       Coe, N. M., Dicken, P., and Hess, M. (2008). Global production 
networks: realizing the potential. Journal of Economic Geography, 8(3), 271-295.
*       Dicken, P. (2014). Global shift: Reshaping the global economic map in 
the twenty-first century. Sage Publications Limited.
*       Hughes, A., & Reimer, S. (Eds.). (2004). Geographies of commodity 
chains. Routledge.

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Hopefully you find these abstracts of interest to your session? We would be 
delighted to contribute.

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Kind regards,

 �

Ronald Wall

 �

 �

Prof. Dr. Ir. Ronald Wall

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Full Professor, Chair in Economic Development of the City of Johannesburg and 
Gauteng Province.

 �

WITS School of Economic and Business Sciences, Faculty of Commerce Law and 
Management (CLM), University of the Witwatersrand (WITS), Johannesburg, South 
Africa.

 �

Economic Geographer, Urban Planner 



Contact information

E:  <http://www.ihs.nl/> www.ihs.nl

E:  <mailto:ronald.w...@wits.ac.za> ronald.w...@wits.ac.za 

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P: + 27 (0)11 71 78085

M: + 31 (0)6 41778693

M: + 27 (0) 613093393

 �

 �

From: AAG Economic Geography Speciality Group 
<ECONOMICGEOGRAPHY-L@LISTSERV.UCONN.EDU> On Behalf Of Maximilian Buchholz
Sent: Wednesday, November 7, 2018 7:17 PM
To: ECONOMICGEOGRAPHY-L@LISTSERV.UCONN.EDU
Subject: Intra- and interregional inequality, divergence and economic 
development

 �

Organizers: 
Harald Bathelt (University of Toronto), harald.bath...@utoronto.ca 
<mailto:harald.bath...@utoronto.ca>  �

Max Buchholz (University of Toronto), � <mailto:max.buchh...@mail.utoronto.ca> 
max.buchh...@mail.utoronto.ca
Michael Storper (LSE, UCLA, Sciences Po Paris), m.stor...@lse.ac.uk 
<mailto:m.stor...@lse.ac.uk>  

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Session Description:

Scholarly attention to economic inequality in the social sciences has often 
focused on individual-level inequalities, and yet, the dynamics of inequality 
are explicitly geographic in nature. After a century of regional income 
convergence in the United States, this process has been slowing down since the 
1980s (Ganong & Shoag, 2017). Similarly, strong convergence between European 
regions in the postwar period has given way to divergence since the 1980s 
(Rosés & Wolf, 2018). Intergenerational social mobility superimposes these 
processes and adds more complexity. It varies greatly across regions (Chetty et 
al., 2014) and is highly dependent on localized economic contexts 
(Goodwin-White, 2016). Altogether, these economic geographies appear related to 
social factors and to systems of values, attitudes toward difference and 
perceptions of opportunity that are all created and recreated at the local 
level (Storper, 2018; Alesina et al., 2018). At the same time as inter-regional 
convergence came to a halt in the 1980s, poverty within U.S. cities became more 
spatially concentrated, having lasting effects on the economic outcomes of 
adolescents from the respective urban quarters (Holloway & Mulherin, 2004). 
Moreover, the benefits of high-technology employment (Kemeny & Osman, 2018), 
global FDI linkages (Bathelt & Buchholz, 2018) and international migration 
(Cooke & Kemeny, 2017), all appear to be distributed in ways that contribute to 
both inequalities between and within regions. 

 �

Geographers have made important contributions to our understanding of intra- 
and interregional inequality, yet we believe these discussions still need to 
invoke a broader response in the discipline. And we believe that the conceptual 
and methodological tools put us in a strong position to go much further to 
better understand and fight inequality. This set of sessions invites papers 
that provide new empirical or conceptual perspectives on dynamics of inter- and 
intra-regional economic inequalities. We welcome papers that consider forces or 
processes that contribute to both processes, but also those that treat them 
separately. Papers discussing how dynamics of inequality vary according to 
gender, race, citizenship status, and other demographic characteristics, or 
that take historical approaches to spatial inequality are welcome. We hope to 
stimulate increased attention to the dynamics of inequality, divergence and 
uneven development in economic geography.

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References:

Alesina, A., Stantcheva, S., & Teso, E. (2018). Intergenerational mobility and 
preferences for redistribution. American Economic Review, 108, 521–554.

Bathelt, H. & Buchholz, M. (2018). Outward Foreign Direct Investments as a 
Catalyst of Urban-Regional Income Development? Evidence from the United States. 
SPACES online, 2018-02. Toronto & Heidelberg: www.spaces-online.com 
<http://www.spaces-online.com> .

Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the land of 
opportunity? The geography of intergenerational mobility in the United States. 
Quarterly Journal of Economics, 129, 1553–1623. 

Cooke, A., & Kemeny, T. (2017). The economic geography of immigrant diversity: 
Disparate impacts and new directions. Geography Compass, 11, 1–14. 

Ganong, P., & Shoag, D. (2017). Why has regional income convergence in the U.S. 
declined? Journal of Urban Economics, 102, 76–90. 

Goodwin-White, J. (2016). Is social mobility spatial? Characteristics of 
immigrant metros and second generation outcomes: 1940-1970 and 1970-2000. 
Population, Space and Place, 22, 807–822.

Holloway, S. R., & Mulherin, S. (2004). The effect of adolescent neighborhood 
poverty on adult employment. Journal of Urban Affairs, 26, 427–454. 

Kemeny, T., & Osman, T. (2018). The wider impacts of high-technology 
employment: Evidence from U.S. cities. Research Policy. Advance online 
publication.

Rosés, J. R., & Wolf, N. (2018). Regional Economic Development In Europe, 
1900-2010: A Description Of The Patterns. Working Paper 278. London: London 
School of Economics and Political Science Department of Economic History 
Working Papers.

Storper, M. (2018). Separate worlds? Explaining the current wave of regional 
economic polarization. Journal of Economic Geography, 18, 247–270. �  � � 

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-- 

Maximilian A. Buchholz

PhD Student Geography, University of Toronto

max.buchh...@mail.utoronto.ca <mailto:max.buchh...@mail.utoronto.ca> 

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