geography and growth: the new economic geography (neg)...

Geography and Growth:

The New Economic Geography

(NEG) Perspective

Harry Garretsen

DIMETIC Summer School, 30-6-2009, Pecs

Nice timing for this lecture…..

• Right after Ron Boschma’s lecture:

is there life after EEG’s take on growth?

• Increasingly, NEG takes a dynamicapproach → deals with geography and growth

• NEG “begins” in 1991 and time to takestock (13 October 2008…………….)

Outline• New Economic Geography (NEG): key insights

(“trade and geography”, Krugman’s Nobelprize!)

• NEG work after Krugman (1991)

• Relationship with other theories of geographyand/or growth (very quickly)

• Stylized facts about economic growth

• NEG applied to economic growth

• Summing up/discussion…………..

NEG key insights I

• NEG’s core model: Krugman (1991, JPE)

• NEG originates in international trade theory, notin economic geography or growth theory

• 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)

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

du

str

y tra

de

Hungary

Japan

South Korea

Mexico

USA

Germany

Australia

Intra-industry trade; China and Chinese Taipei, 1976-2005

Intra-industry trade; Grubel-Lloyd index (3-digit level, weighted average)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1975 1980 1985 1990 1995 2000 2005year

GL

-in

de

x

China

Chinese Taipei

NEG Key Insights II:

• Krugman (1979): introduce internalincreasing returns to scale

• Internal IRS: model of imperfect competition (Dixit and Stiglitz, 1977)

• Rationale for intra-industry trade, but norole for geography (or growth) yet

iixl βα +=

Average costs under increasing returns to scale

Average

costs

Output

NEG Key Insights III

• Krugman 1980: add transport costs to IRS

-assume two countries A and B: S>S* (market size A larger than B);

-and assume transport costs T>0;

if α >TS*, then locate firm in larger market

• “Home market effect”: geography matters

• But: why should S>S* to begin with????

NEG Key Insights IV

• Krugman (1991): 1st NEG model:

add factor (labour) mobility to T and IRS

• Also external IRS (pecuniary or marketsize externality)

• The 1 million $ Q: where will footloosefirms&workers locate?

• Answer: it depends……………

NEG 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

• Relative strength: key model parameters, notably T

[Where’s the novelty of Krugman 1991?]

The relative real wage in region 1 (case of T=1.7)

0,97

1

1,03

0 0,5 1

share of manufacturing workers in region 1 (lambda1)

rela

tive

re

al w

ag

e (

w1

/w2

)

A

DC

B

E

F

The Tomahawk diagram

Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1

Basin of attraction for spreading equilibrium

Basin of attraction for agglomeration in region 1


Panel a

Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1




Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1




Panel a

NEG Extensions

• See previous slide (Tomahawk), extreme set of equilibria:

change menu of aggl. and spreading forces

[e.g. no labour mobility, congestion, non-tradable goods (housing)……..]

→ get rid of the Tomahawk

• Empirical implications? Yes ……..

• What’s the relevance for economic growth?

How to position basic NEG model?

• International trade theory? (NEG adds factor

mobility)

• Urban & Regional economics? (NEG adds

general equilibrium analysis of spatial linkages)

• (Evolutionary) economic geography? (same Q

but different tools)

• Economic growth theory? (basic NEG model is

static=allocation model, thus …→ ………..→

NEG and growth: 3 questions

• Why is (even static) NEG useful foranalysis of economic growth?

• How to turn NEG into a growth model?

• (Discussion) What’s the value added of NEG for innovation and growth analysis?

Q1: Why NEG might be useful

• 5 stylized facts on economic growth(“Kaldor” 2009):

1) Gdp per capita increases over time

2) Differences in growth are persistent

3) Scale matters (within-between country)

4) Growth process is lumpy (stagnation/ growth spurts

5) Changes in gdp rankings: “leapfrogging”

1) Per capita income increases over time; 2) (increasing) dispersion (no convergence)

a. His togram of ln(incom e per capita)

0

5

10

15

20

25

5.7 6.6 7.5 8.4 9.3 10.2 11.1

ln(income per capita)

nu

mb

er

of

co

un

trie

s

1950

Qatar

Kuw aitGuinea

Bissau

b. His togram of ln(incom e per capita)

0

5

10

15

20

25

5.7 6.6 7.5 8.4 9.3 10.2 11.1


nu

mb

er

of

co

un

trie

s

1968

Qatar

Malaw i

Burundi

Chad

Guinea

1) Per capita income increases over time; 2) (increasing) dispersion (no convergence)

c. His togram of ln(incom e per capita)

0

5

10

15

20

25

5.7 6.6 7.5 8.4 9.3 10.2 11.1


nu

mb

er

of

co

un

trie

s

1986

USA

Tanzania

Chad

Guinea

d. His togram of ln(incom e per capita)

0

5

10

15

20

25

5.7 6.6 7.5 8.4 9.3 10.2 11.1


nu

mb

er

of

co

un

trie

s

2003

USAZaire

Regional income inequality in the EU NUTSII regions: 2) persistent differences?

EU regional income inequality; Lorenzcurves 1995 and 2004

0

1

0 1cumulative share of population

cu

mu

lati

ve

sh

are

of

inc

om

e

19952004

diagonal

Regional income inequality in the EU: 3) scale matters

EU regional income inequality: Theil index and Gini coefficient

0.02

0.03

0.04

0.05

0.06

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

0.08

0.12

0.16

0.20

0.24

Theil within countries (left hand scale)

Theil between countries (left hand scale)

Gini coefficient (right hand scale)

Leaders and laggards in the world economy, 1-2003: 4) lumpiness and 5) leapfrogging

10001 1500 1600 18001700 200019000

100

200

300

500

400

income per capita (% of world average)

year

Italy

IraqIran

Netherlands

UK

Australia

USA

Switzerland

IndiaChina

oAfrica

W Offshoots

New Zealand

AustraliaMany Many

Italy

10001 1500 1600 18001700 200019000

100

200

300

500

400

10001 1500 1600 18001700 200019000

100

200

300

500

400

1 1500 1600 18001700 200019000

100

200

300

500

400

income per capita (% of world average)

year

Italy

IraqIran

Netherlands

UK

Australia

USA

Switzerland

IndiaChina

oAfrica

W Offshoots

New Zealand

AustraliaMany Many

Italy

Now return to Q1: standard growth models do focus on 1 and 2

(and 3), NEG emphasizes 3,4 and 5

1) Gdp per capita increases over time

2) Differences in growth are persistent

3) Scale matters (within-between country)

4) Growth process is lumpy (stagnation/ growth spurts

5) Changes in gdp rankings: “leapfrogging”

The Tomahawk diagram

Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1




Panel a

Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1




Sustain points

Break point

Transport costs T1

0

1

λ1

0.5

Stable equilibria

Unstable equilibria

B

S0

S1




Panel a

The LUMPY Evolution of agglomeration: STATIC model fo 12 regions

Herfindahl index

0

0.1

0.2

0.3

0.4

0.5

0 200 400 600 800

reallocation

STATIC NEG model (12 region Krugman model) already shows LEAPFROGGING!!

Evolution of share of manufacturing

0

0,1

0,2

0,3

0,4

0,5

0 200 400 600 800

reallocation

3

6

9

Q2: How to turn NEG into growth model?• Following i.a. Baldwin and Forslid (2000) many

(endogenous) NEG growth models

[→ see Baldwin&Martin (2004) for a survey]

Endogenous growth ingredients: (localized) knowledge spillovers +…….

NEG ingredients: spatial linkages (geography)

What does this growth-NEG “marriage” look like??

Stability in the

Baldwin-Forslid

economic growth-NEG

model

0.2 0.4 0.6 0.80 1

1.5 1.26 1.14 1.06 1∞

Freeness

of trade

Knowledge

spillovers

Implied T

1

Agglomeration stable; spreading unstable

Agglomeration stable; spreading stable

Agglomeration unstable; spreading stable

Finally Q3: value added of NEG growth view

• Within (!) mainstream endogenous models of growth & innovation:

-focuses on spatial linkages (NEG addsgeography)

-offers richer explanation of “growth facts”

-enables “what if” analysis of (policy) experiments or shocks……………….

The “what if” bonus

• Recall the Tomahawk for the basic idea

• Real “shocks” (wars & disasters); economic integration shocks (examples: EU integration; increased labor betweenChinese cities; lower trade barries in SSA)

• Highly stylized example: EU integrationwith Krugman (1991) model

Multi-region simulations of Krugman model for NUTSII regions (EU 15)

Summing Up/Discussion….

• NEG adds geography to mainstreameconomics

• Incorporation of NEG into growth models yields new theoretical and empiricalinsights

• A discussion about the relevance of the NEG perspective is a discussion about the relevance of mainstream economics

• EEG and NEG: complements/substitutes?

geography and growth: the new economic geography (neg)...

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