an evolutionary perspective on regional growth

An evolutionary perspective on regional growth

Ron BoschmaDepartment of Economic Geography

Utrecht Universityhttp://econ.geo.uu.nl/boschma/boschma.html

DIMETIC course

July 3, 2007

Structure of lecture

• spin-off dynamics and regional development

• agglomeration economies and regional development

• British automobile case: related variety

• related variety and regional growth: Italian case

Evolutionary perspective in economic geography

• spatial distribution of firm-specific routines in a population over time: competition, innovation and imitation

- how new routines emerge and diffuse in space when a new sector develops (variety, selection, retention)

- through which mechanisms inter-firm learning takes place

• two mechanisms of inter-firm learning:

- spin-off dynamics: regional phenomenon (near parent organization)

- agglomeration economies: geographically localised knowledge spillovers (not available outside region)

Spin-off dynamics

• spin-off process: growth and spatial concentration of industry (Silicon Valley, etc.)

• two evolutionary principles

- Polya urn process (Arthur): probability of new spin-off in region is equal to the number of incumbent firms in region

- spin-off process as transfer mechanism of routines within a region (Klepper)- spin-offs inherit routines from parent firms- successful parents generate more successful spin-offs (‘success breeds success’)

• other mechanisms of local knowledge transfers?

Agglomeration economies

• advantages that can be exploited by firms when located together

• two evolutionary principles- dynamic view on agglomeration economies: they come into being as

a new industry grows and concentrates in a region (Arthur): how relevant knowledge spillovers become increasingly available in those regions that, by chance, have generated most entrants at the first stage of the life cycle of a new industry (self-reinforcing processes)

- agglomeration economies as mechanism of knowledge diffusion within a region- co-location (monitoring/observing)- local networks (through which knowledge circulates in a region)

• ‘spin-off dynamics’ and ‘agglomerations economies’ provide different evolutionary explanations for same phenomena

Spatial analysis of the British automobile industry 1895-1968

• Boschma and Wenting (2007), ICC, vol. 16, no. 2, pp. 213-238

• own data collection

- Culshaw and Horrobin (1974); Georgano (1968)- population dynamics: entries, exits (incl. mergers and acquisitions),

age, location, time of entry, pre-entry background of entrepreneurs

• evolution of market structure of British automobile industry

- 1895-1921: rapid growth- 1922-1932: shake-out- 1933-1968: consolidation

• spatial concentration: Coventry Britain’s motor city

Number of automobile producers, entrants and exits in Great Britain, 1895-1968

Spin-off dynamics and/or agglomeration economies

• Cox regressions to explain survival or hazard rates of automobile firms

• dependent variable: age of entrant

• (1) agglomeration economies:

- LOCREL: localization economies in related industries (regional employment in coach and cycle making industries)

- URBECON: urbanization economies (regional population density)

- LOCECON: local competition or localization economies (number of automobile firms in region): positive or negative effect?

• (2) time of entry

- ENTR1: cohort 1 (1895-1906)

- ENTR2: cohort 2 (1907-1919)

• (3) pre-entry background of entrepreneurs

- EXPEF: experienced firms (related industries)

- SPINOF: spin-offs (automobiles)

- PARENTS: spin-offs from successful parents

• (4) dynamic perspective: stages of life cycle industry

- 1st stage: LOCREL and EXPEF (related industries)

- 2nd stage: LOCECON and SPINOF (and PARENTS)

Table 1. Estimation results of the Cox regressions

LOCREL -0.202** -0.266** -0.241** -0.215** -0.346* 0.069 0.073 0.075 0.076 0.139

URBECON 0.041 0.048 0.061 0.052 0.166 0.053 0.053 0.053 0.053 0.094

LOCECON 0.025** 0.030** 0.029** 0.028** 0.026 0.007 0.008 0.008 0.008 0.016

ENTR1 -0.370** -0.313* -0.292* 0.143 0.144 0.145

ENTR2 -0,193 -0,158 -0,148 0.149 0.148 0.149

EXPEF -0.853** -0.864** -0.978** 0.154 0.154 0.310

SPINOF -1.293** -0.300 -0,607 0.197 0.483 1.023

PARENTS -0.356* -0.280 0.165 0.344

Chi-square 13.121** 20.191** 72.390** 75.390** 24.442**-2 Log Likelihood 3626,713 3606,509 3565,284 3560,668 1027,602 N=380 N=380 N=380 N=380 N=133

(standard errors in parentheses)

** significant at the 0.01 level* significant at the 0.05 level

Conclusions British automobile case

• locations matter

- agglomerations with related activities: effective transfer of knowledge requires related variety

- specialized agglomerations: negative impact on performance due to strong local competition

• pre-entry backgrounds matter

- the more close the routines are related to automobiles (spin-offs and experienced entrepreneurs), the better the new entrants perform

- especially when they originate from parents with successful parents

• need to distinguish between phases life-cycle of industry

- 1st stage: experience in related activities (entrepreneurs and location), no competition effect

- 2nd stage: experience in automobiles (entrepreneurs, but decreasing importance of location), strong competition effect (negative)

Survival curves by pre-entry entrepreneurial background

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

1 6 11 16 21 26 31 36 41 46 51 56 61 66

Age (years)

Surv

ival

rat

e (L

N%

)_

Spinoffs

Experienced Firms

Inexperienced Firms

Related variety and regional growth: Italian case

• Boschma and Iammarino (2007)

• debate on whether local specialisation (localisation economies) or diversification (Jacobs’ externalities) induce knowledge spillovers and regional economic growth (Glaeser et al., 1992; Henderson et al., 1995)

• meaning of Jacobs’ externalities unclear: distinction between related and unrelated variety (Frenken et al., 2007)

• importance of diversity and relatedness of extra-regional linkages for regional growth: may bring new and related variety into the region

• to assess their impact on economic growth of Italian provinces 1995-2003

Related variety and regional growth: theoretical framework

• Jacobs’ externalities concept problematic

• two effects (Frenken et al. 2007):

- knowledge spillover effect: requires related variety: some but not too much cognitive proximity

- portfolio effect: unrelated variety absorbs sector-specific shocks

• related variety = sectors related in terms of shared or complementary competences

Related variety and regional growth: theoretical framework

• extra-regional linkages: to avoid lock-in

• too much reliance on regional knowledge may be harmful: need for global pipelines (e.g. Bathelt et al. 2004)

• however, access to non-regional knowledge not sufficient: local absorptive capacity is required to understand and transform external knowledge into economic growth

• related variety crucial: inflows of extra-regional knowledge related (but not quite similar) to existing knowledge in region particularly enhance interactive learning and regional growth

Related variety and regional growth: analytical framework

• dependent variables: regional growth 1995-2003 at the NUTS 3 level (103 provinces)

– employment growth

– value added growth

– labour productivity growth


• independent variables:

– variety: export data by sector at 3 digit level (121 sectors): entropy measure at 3-digit-level

– related variety: weighted sum of entropy at 3 digit level within each 2 digit class

– unrelated variety: entropy at 1 digit level

Regional export profile

1 digit 2 digit 3 digit

3

31 32

311 312 313 314 321 322

4

41 42 43

411 421 422 431 432 433


• independent variables (cont.):

– import variety: import data by sector at 3 digit level (121 sectors): entropy measure at 3-digit-level

– related import variety: sums of products of relative size of export sector i and related import (entropy from other sectors at 3 digit except i within each 2 digit class)

– import similarity: sums of products of the absolute sizes of a 3-digit industry’s exports and imports

– dummies for Italian macro-regions (NORTHWES, NORTHEAS, CENTRE, SOUTH)

Regional Export Profile Regional Import Profile

1 digit 2 digit 3 digit

3

31

311 312 313

3

31

312 313311

Results

employment growth 1995-2003

value added growth

1995-2003

productivity growth 1995-2003

Variety -1.514 -1.725 -0.356

Related variety 3.584 11.680** 7.224*

Unrelated variety 5.947 8.818 2.242

Import variety -1.409 -0.486 1.058

Rel import variety 3.290** 0.539 -3.462**

Import similarity 0.126 -0.585*** -0.695***

Northwest 0.618 -9.068*** -7.457***

Northeast 0.710 -6.952*** -5.502***

Centre 2.677* -3.441* -4.622***

R-square 0.171 0.294 0.368

F 2.137 4.309 6.015excluded variable Southn=103*p < 0.10, **p <0.05,

***p<0.01

Related variety and regional growth: research challenges

• check whether the impact of related variety differs within groups of industries based on advanced technological systems

• need for case studies at the regional level: related variety prerequisite for long-term growth?

• non-local linkages among Italian provinces (e.g. by including neighbouring effects based on Moran statistics)

an evolutionary perspective on regional growth

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