Geography and Growth: The New Economic Geography (NEG) Perspective

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 dynamic approach deals with geography and growth NEG begins in 1991 and time to take stock (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 geography and/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, not in 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 75 Mexico % intra-industry trade Germany Hungary USA South Korea 50 Japan Australia 25 1991 1994 1997 year 2000

Intra-industry trade; China and Chinese Taipei, 1976-2005 0.6 Intra-industry trade; Grubel-Lloyd index (3-digit level, weighted average) 0.5 Chinese Taipei 0.4 China GL-index 0.3 0.2 0.1 0.0 1975 1980 1985 1990 1995 2000 year 2005

NEG Key Insights II: Krugman (1979): introduce internal increasing returns to scale l = α + i x i Internal IRS: model of imperfect competition (Dixit and Stiglitz, 1977) β Rationale for intra-industry trade, but no role for geography (or growth) yet

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; ifα>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 market size externality) The 1 million $ Q: where will footloose firms&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) relative real wage (w1/w2) 1,03 1 0,97 E F C D B A 0 0,5 1 share of manufacturing workers in region 1 (lambda1)

The Tomahawk diagram Panel a 1 S 1 λ 1 0.5 B 0 1 S 0 Transport costs T Sustain points Break point Stable equilibria Unstable equilibria Basin of attraction for spreading equilibrium Basin of attraction for agglomeration in region 1 Basin of attraction for agglomeration in region 2

NEG Extensions See previous slide (Tomahawk), extreme set of equilibria: change menu of aggl. and spreading forces [e.g. no labour mobility, congestion, nontradable 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 for analysis 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) 1950 b. His togram of ln(incom e per capita) 1968 25 25 20 20 number of countries 15 10 number of countries 15 10 5 Guinea Bissau 0 Qatar Kuw ait 5.7 6.6 7.5 8.4 9.3 10.2 11.1 ln(income per capita) 5 Malaw i Burundi Chad Guinea 0 Qatar 5.7 6.6 7.5 8.4 9.3 10.2 11.1 ln(income per capita)

1) Per capita income increases over time; 2) (increasing) dispersion (no convergence) c. His togram of ln(incom e per capita) 1986 d. His togram of ln(incom e per capita) 2003 25 25 20 20 number of countries 15 10 number of countries 15 10 5 Tanzania Chad Guinea 0 USA 5.7 6.6 7.5 8.4 9.3 10.2 11.1 ln(income per capita) 5 0 Zaire USA 5.7 6.6 7.5 8.4 9.3 10.2 11.1 ln(income per capita)

Regional income inequality in the EU NUTSII regions: 2) persistent differences? 1 EU regional income inequality; Lorenzcurves 1995 and 2004 diagonal cumulative share of income 2004 1995 0 0 1 cumulative share of population

Regional income inequality in the EU: 3) scale matters EU regional income inequality: Theil index and Gini coefficient 0.06 0.24 Gini coefficient (right hand scale) 0.05 0.20 Theil between countries (left hand scale) 0.04 0.16 0.03 0.12 Theil within countries (left hand scale) 0.02 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 0.08

Leaders and laggards in the world economy, 1-2003: 4) lumpiness and 5) leapfrogging income per capita (% of world average) 500 Switzerland 400 300 Netherlands Australia UK USA 200 Italy Italy Iran 100 Iraq New Zealand Many Many India W Offshoots Australia China oafrica 0 1 year 1000 1500 1600 1700 1800 1900 2000

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 LUMPY Evolution of agglomeration: STATIC model fo 12 regions Herfindahl index 0.5 0.4 0.3 0.2 0.1 0 0 200 400 600 800 reallocation

STATIC NEG model (12 region Krugman model) already shows LEAPFROGGING!! Evolution of share of manufacturing 0,5 0,4 0,3 3 6 9 0,2 0,1 0 0 200 400 600 800 reallocation

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 Knowledge spillovers 1 Implied T 0 0.2 0.4 0.6 0.8 1 1.5 1.26 1.14 1.06 1 Agglomeration unstable; spreading stable Agglomeration stable; spreading stable Agglomeration stable; spreading unstable Freeness of trade

Finally Q3: value added of NEG growth view Within (!) mainstream endogenous models of growth & innovation: -focuses on spatial linkages (NEG adds geography) -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 between Chinese cities; lower trade barries in SSA) Highly stylized example: EU integration with Krugman (1991) model

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

Summing Up/Discussion. NEG adds geography to mainstream economics Incorporation of NEG into growth models yields new theoretical and empirical insights A discussion about the relevance of the NEG perspective is a discussion about the relevance of mainstream economics EEG and NEG: complements/substitutes?