An evolutionary perspective on regional growth

1. An evolutionary perspective on regional growth Ron Boschma Department of Economic Geography Utrecht University http://econ.geo.uu.nl/boschma/boschma.html DIMETIC course July 3, 2007

2. 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

3. 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)

4. 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?

5. 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

6. 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

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

8. 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?

9. (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)

11. 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)

12. Survival curves by pre-entry entrepreneurial background

13. 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

14. 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

15. 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

16. 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

17. Related variety and regional growth: analytical framework • 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

18. Regional export profile 3 4 31 32 41 42 43 311 312 313 314 321 322 411 421 422 431 432 433 1 digit2 digit 3 digit

19. Related variety and regional growth: analytical framework • 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)

20. Regional Export Profile Regional Import Profile 3 3 31 31 311 312 313 311 312 313 1 digit 2 digit 3 digit

21. Results excluded variable South n=103 *p < 0.10, **p <0.05, ***p<0.01

22. Results excluded variable South n=103 *p < 0.10, **p <0.05, ***p<0.01

23. Results excluded variable South n=103 *p < 0.10, **p <0.05, ***p<0.01

24. 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)