Apr 18, 2023 | 1

Economic Geography as seen from Economics:

Neglect, (Re)Discovery & (Missed) Opportunities

Harry Garretsen (Spatial Economic Analysis (SEA) Lecture, RSA 2012 Delft)

                                       

.

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SEA journal: “… methods of

spatial economics”

Central theme RSA 2012 conference: spatial interactions

Why me? →→→→→→→→

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Spatial interactions or dependencies…….. › ……..central to the field of economic geography

(EG)..

› …....aims to explain (uneven) spatial development…..

› ………various analytical approaches………

› This lecture: what does economics have to offer to the analysis of spatial interactions and hence to EG?

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OUTLINE

1. Central theme: EG & spatial interactions….2. …….. in economics prior to 19913. …….. 1991: New Economic Geography (NEG)4. Krugman’s NEG: his 3 key ”Nobel” insights

5. 20 years on: missed opportunities??6. Example: Urbanization in China7. How to proceed with (N)EG?

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Does it matter where Delft

is located in The Netherlands?

YES:

space & location matter

The Litmus Test of EG

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Spatial interactions in economics pre-1991

› International economics?

› Regional economics?

› Urban Economics?

› CONCLUSION: Neglect or, at best, partial analysis

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Something changed between 1991 and 2008!!!

Krugman:

Nobelprize 2008

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New Economic Geography/Geographical Economics

› Three main insights make for core NEG model

› NEG what’s in a name? NEG vs geographical

economics

› This model sets the scene for remainder lecture

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NEG 3 key insights (I)

› NEG’s core model: Krugman (1991, JPE)› NEG originates in international trade theory,

not in urban/regional economics› We proceed in 3 steps: Krugman (1979, 1980,

1991) › International trade theory in 1979: old (=18th

century) theory (Ricardo) at odds with facts› Theory: inter-industry trade; facts: intra-

industry trade (it’s not “cloth for wine” anymore)

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Manufacturing intra-industry trade; 1988-2000, selected countries Manufacturing intra-industry trade (% of total manufacturing); 1988-2000

25

50

75

1991 1994 1997 2000year

% in

tra-in

dust

ry tr

ade

Hungary

Japan

South Korea

Mexico

USA

Germany

Australia

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NEG 3 Key Insights (II)

› Krugman (1979): introduce internal increasing returns to scale

› Model of imperfect competition (Dixit and Stiglitz, 1977)

› Rationale for (intra-industry) trade, but no role for geography yet……..

ii xl

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Average costs under increasing returns to scale

Averagecosts

Output

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NEG 3 Key Insights (III)

› Krugman 1980: add transport costs to IRS

› Assume two countries, a and b: Sa >Sb (market size S for A larger than B);

› And assume transport costs T>0; if α >(T x Sb), then locate firm in larger

market

› “Home market effect”: geography matters› But: why should Sa>Sb to begin with????

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NEG 3Key Insights (IV)

› Krugman (1991): 1st NEG model: add factor (=labour) mobility to T and IRS

› Also external IRS (pecuniary or market size externality)

› Big Q: where will footloose firms&workers locate?

› Answer: it depends……………

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NEG 3 Key Insights (V)

› ……..it depends on relative strength of agglomeration and spreading forces

› Agglomeration forces: home market effect, price index effect

› Spreading forces: competition effect› “Tug of War”: key model parameters, notably

level of transp. costs, T [Where’s the novelty of Krugman 1991?]

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Sustain points

Break point

Transport costs T10

1

1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1

Basin of attraction for spreading equilibrium

Basin of attraction for agglomeration in region 1

Basin of attraction for agglomeration in region 2

Panel a

Sustain points

Break point

Transport costs T10

1

1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1

Basin of attraction for spreading equilibrium

Basin of attraction for agglomeration in region 1

Basin of attraction for agglomeration in region 2

Sustain points

Break point

Transport costs T10

1

1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1

Basin of attraction for spreading equilibrium

Basin of attraction for agglomeration in region 1

Basin of attraction for agglomeration in region 2

Panel a

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………….a very happy economist on October 13th 2008

So basically, α+T+λ give us……….

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NEG after Krugman (1991)

› Reception of NEG in- and outside economics

› NEG after 1991:

Theory? Extensions of core 1991 model?

Empirics? Real test of underlying model?

Policy Relevance? General vs specific policies?

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Reception…….

› Economics: initial wave of research; NEG has done its job, no longer separate sub-field of research?

› Outside economics: Not new, bad economics and real lack of geography

› Krugman (2011): Middle-aged NEG does not look too well??

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What happened? (I)

› THEORY: focus on mix of agglomeration and spreading forces, but too little progress? (n-region problem?, simulations?)

› EMPIRICS: outburst of NEG inspired empirical research, but where’s the real test of NEG?

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1.0

0.5

1.0 1.2 1.4 T

2

1

1 = 2

1, 2

1 = 2

1.0

0.5

1.0 1.2 1.4 T

2

1

1 = 2

1, 2

1 = 2

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What happened? (II)› Empirical research: focus on short run

instead of long run version of NEG!!!› “Krugman (1980) beats Krugman (1991)”

› Market potential/access: not relevant on regional level??

/1

1

11

R

sssrsr ITYW

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What happened (III)?

› POLICY RELEVANCE? (see THEORY+EMPIRICS):

1. General conclusion: policy in a lumpy world, role of threshold effects (Baldwin et al, 2003)

2. Specific policy conclusions rather difficult or based on “wrong” version of NEG model (main example: World Bank, World Development Report 2009)

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a. Effective average tax rate, 19 OECD countries

0.0

0.2

0.4

0.6

1980 1985 1990 1995 2000year

effe

ctiv

e av

erag

e ta

x ra

te

0.00

0.05

0.10

0.15

average(left scale)

minimum; Ireland (left scale)

maximum; Germany (left scale)

Japan

standard deviation (right scale)

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The Wiggle Diagram

share of firms in North

rN/rS

0 1

tN-tSA

C

DB

(i) geo ec. intermediate trade costs

(ii) geo ec. high trade costs

(iii) standard tax competition

share of firms in North

rN/rS

0 1

tN-tSA

C

DB

(i) geo ec. intermediate trade costs

(ii) geo ec. high trade costs

(iii) standard tax competition

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Lessons (Not) Learned

› Lack of theoretical progress & wrong focus in empirical research: main message of NEG got lost!!

› So what? [assuming(!) mainstream economics can add to understanding of spatial interactions]

› Example: Urbanization in China (to show comparative advantage of NEG)

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Two background papers for our example› Bosker M, S Brakman, H. Garretsen & M Schramm:

1. “Adding Geography to the New Economic Geography”, Journal of Economic Geography, 10(6), pp. 793-823, 2010.

2. “The New Economic Geography of Prefecture Cities in China: The Relevance of Market Access and Labor Mobility for Agglomeration”, mimeo, February 2012

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Behavior of NEG models in n-region case

› Does “real world”with many regions which are not equi-distant and differ in size resemble anything like the “Tomahawk” or “Bell-Shaped Curve” from the 2 region NEG models?

› Answer: (qualified) YES

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Transport costs and the long run equilibrium when distance matters, n=194

a. With inter-regional labor mobility

0

0.2

0.4

0.6

0.8

1

0.4 1.4 2.4transport costs

He

rfin

da

hl i

nd

ex

b. Without inter-regional labor mobility

0

0.01

0.02

0.0 0.7 1.4transport costs

Her

finda

hl in

dex

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Transport costs, distance, initial conditions, n=194

a. With inter-regional labor mobility

0

0.2

0.4

0.6

0.8

1

0 5 10transport costs

Her

finda

hl in

dex

b. Without inter-regional labor mobility

0

0.01

0.02

0 7 14transport costs

Her

finda

hl in

dex

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Motivation for Chinese cities study› Are Chinese cities too small? (despite rapid

urbanization)….› … if so: does China, does not benefit fully from

agglomeration economies?

› Main culprit: Hukou system (restricted interregional labour mobility)

› What will happen with increassed labour mobility?› Krugman (2011): China=NEG; “what if” questions

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Set up of analysis

› NEG model (extensive mix of agglomeration and (!) spreading forces (housing rents))

› Use wage equation to estimate structural model parameters (notably “freeness of trade”)

› Model simulations (with real migration dynamics)

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Initial (2000) distribution

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Conclusions based on China example

› Use strong (and novel) points of NEG approach: agglomeration is endogenous; NEG provides answers to “what if” questions

› Comparative advantage of NEG, but this advantage is not used very well

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Final words……..

How to proceed? 1.Economics can be of greater use to analysis of EG/spatial interactions, 2.Make better use of NEG while recognizing its limitations

3.More collaboration or debate? (today’s lecture……) Credible models in Economic Geography at large? (Garretsen& Martin, SEA, 2010)