Local labour markets and socio-economic change: evidence from Danish towns, 2008–2013

ABSTRACT

The recent financial and economic crisis had substantial but spatially differentiated impacts on growth. However, there is still a lot left to be understood about the local aspects of the crisis. One of these aspects is its socio-economic consequences. This paper investigates local socio-economic change to Danish towns from 2008 to 2013, with a focus on the impact of local labour market (LLM) structures on change. Socio-economic change in towns is measured both directly as mean income and employment growth, and indirectly as population and human capital growth. The paper relies on micro-data and uses robust regression to generate results. Several findings are presented, but the two main conclusions are: first, the LLM structures of towns still influence local socio-economic development; and, second, towns experience better socio-economic development if they are in close proximity to a larger labour market and/or have a large ratio of commuters in the working population.

KEYWORDS:

• Regional development
• local labour markets
• socio-economic change
• crisis
• robust regression
• Denmark

Disclosure statement

No potential conflict of interest was reported by the author.

ORCID

Kalle Emil Holst Hansen http://orcid.org/0000-0002-4109-8513

Notes

1. Based on Statistics Denmark's SOCIO2 classification for labour market attachment.

2. Based on the ISCED97 nomenclature.

3. Based on the NACE rev. 2 nomenclature.

4. Based on the ISCED97 nomenclature.

5. Moran's I test for spatial autocorrelation was done using GeoDa software. The Pseudo R-square of total town employment growth was 0.10702 with a Moren's I of 0.0077318; mean income growth Pseudo R-square of 0.29835 with a Moren's I of −0.00651381; Human capital ratio's Pseudo R-square of 0.27309 with a Moren's I of 0.00151196 using 99999 permutations and a 50000 weight. However, by using the same permutations and weight, towns’ growth in inhabitants’ gave a Pseudo R-square of 0.021180 with a Moren's I of 0.00176045; thus for these global spatial autocorrelation cannot be refuted.

6. The Danish Road and Addresses Database is continuously updated. The calculations were made in the summer of 2014 and based on road and addresses data from 2013.

7. LQ is calculated as: LQ = (Cie/Ce)/(Nie/Ne). Cie is the employment in a given industry in the town C, Ce is the total employment in the town C, Nie is the aggregated employment in a given industry of the included towns and Ne is the total town employment.

8. Primary sector activities; manufacturing; construction.

9. Energy and water supply and waste management; wholesale and retail trade, repair of motor vehicles and motorcycles; transportation and storage.

10. Accommodation and food service activities; administrative and support service activities; arts, entertainment and recreation; other service activities.

11. Information and communication; financial and insurance activities; real estate activities; professional, scientific and technical activities; advertising and market research and other professional, scientific and technical activities.

12. Education; public administration and defence compulsory social security; human health and social work activities.