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This study analyzes the spatial evolution of the Danish IT sector during the 1990s upswing, examining agglomeration, specialisation, and diversity forces. It delves into factors shaping industry evolution and the impact of externalities. The paper focuses on employment growth, regional influences, and educational levels within the sector.
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GROWTH AND EVOLUTION OF THE DANISH IT SECTOR:GEOGRAPHICAL AGGLOMERATION, SPECIALISATION, AND DIVERSITY • Christian Østergaard and Bent Dalum • IKE/DRUID and Center for TeleInFrastructure (CTIF) • Department of Business Studies, Aalborg University • Syros Workshop 14 July 2007
Introduction and stylized features • Purpose: to analyse the spatial evolution of the Danish IT sector during the upswing of the 1990s • IT sector = (ICT – C) • The spatial evolution indicates a ‘non random’ agglomeration of the sector around the ‘larger’ urban areas. • Employment and the number of firms have more than doubled • The paper will focus on the dominant forces shaping the spatial evolution of the industry and analyse how industrial dynamics caused the industry to agglomerate in the two ‘largest’ urban areas
What kinds of externalities are most important for the spatial evolution of industries? • Specialisation • Agglomeration forces that make the location of a firm in a particular region more likely once there are other firms in the same industry located in this region (Marshall-Arrow-Romer = MAR) • Diversity • new industries would benefit from being located in metropolitan regions with a high degree of diversity in the workforce (Jacobs, 1969)
Some characteristics of the IT sector (in DK) • Low entry barriers • Some, but not prohibitive, physical capital requirements. • Labour intensive • The right skills are decisive, but ‘general skills’ can do a lot. • The education level of the employees • In 1999 17% of the employees held a MSc compared to 3.5% for the total private sector. 32% held a BSc or higher, while the average was 9%. • 24.3% of the entrepreneurs in 1998 held a BSc or higher compared to 12.4% of the total.
Propositions: • Hypothesis 1: Regions with high employment ‘specialisation’ (defined as above average employment share) will remain specialised and regions with low specialisation will stay at a low level. Those who have, shall have more. • Hypothesis 2: Regions with a ‘large’ town and a ‘large’ and diverse labour market will benefit from Jacobs externalities leading to positive effects on regional IT employment growth. • Hypothesis 3: Universities providing BSc or MSc education in engineering and/or computer science will have positive effects on IT employment growth in a region.
Conclusions • The leading regions of Copenhagen and Aarhus in 1992 have been preserved, the ranking of the followers has changed moderately, while the remaining regions are still lagging behind. However, Aalborg became specialised • Self-augmenting processes sustain specialised regions at a high activity level and vice-versa • The persistent employment specialisation in the Copenhagen and Aarhus regions indicates a specialisation effect as well as a diversity effect • the demise of Vejle points at lack of a specialisation effect. • the lack of growth in Odense points at lack of a specialisation effect • the supply of highly educated graduates in Aalborg compensates for lack of diversity • Supply of highly educated people and initial size of the IT sector are the main factors behind the evolution of the IT sector.