Abstract
The purpose of the study is to construct smart specialization indicators for LAU-1 regions in Finland. Established indices are based on indicators on region’s revealed comparative advantage, and the degree of diversification in its sub-regional industrial structure. Further, we introduce a measure that can be used to assess the socio-economic importance (employment) of diversification and specialization for a region. The data of indices is based on the Statistic Finland (2015) with Local Administrative Unit level 1 (LAU1), 70 regions in Finland. The potential S3 Indices measured here reveal sub-region’s Smart specialization position within 70 sub-region in Finland in 2015. The common economic knowledge states that manufacturing industries are the most export-oriented, highly productive, and thus, can approximate the region’s success in international trade and competitive advantages. The study is based on smart specialization indices: the Herfindahl-Hirschman Index for regional resilience (HHI), regional relative specialization index (RRSI) based on Balassa-Hoover Index (B-H), and the relative employment volume index in manufacturing sector (LIMI). By index examination, we can obtain knowledge about a region’s smart specialization status and potentials. Results reveal that, firstly, each sub-region has its own smart specialization characters with different risk profile. Secondly, specialization strategy (RRSI) in smart specialization has yielded more secure strategy than sub-regional resilience strategy in Finland. Sub-regions like Helsinki and Tampere have similar industrial structure like Finland as whole and they are resilient: they will benefit from nation-wide economic and industrial policy, and they have good ability to resist economic shocks. Our study reveals that there are some other similar smaller (LAU-1) sub-regions in Finland – like Rauma. As such, this kind of research based basic information is critical to been taken into account while constructing sustainable strategies for regional development. Similar calculations can be performed for all regions in Europe. DOI: http://dx.doi.org/10.5755/j01.eis.0.12.21872
Highlights
The purpose of the study was to construct smart specialisation indicators for LAU-1 regions in Finland
The study is based on three smart specialisation indices: the Herfindahl-Hirschman Index for regional resilience (HHI), the regional relative specialisation index (RRSI) based on the Balassa-Hoover Index (B-H), and the relative employment volume index in the manufacturing sector (LIMI)
This study concerns the specialisation and diversification of the competitive/industrial sector in LAU-1 sub-regions in Finland concerning their position in terms of smart specialisation
Summary
The purpose of the study was to construct smart specialisation indicators for LAU-1 regions in Finland. Interest is shifting towards quantitative macro indicators and statistics, because only they can reveal a region’s relative potential and economic success in relation to other regions Both kinds of information are important in order to produce sustainable Smart Specialisation Strategies (see OECD 2013, Borsekova et al 2017). In Europe there are numerous regions whose cultural and socio-economic features may be highly distinctive; what fits well for one region may be totally inadequate for another Despite these difficulties, in its handbook ‘Implementing Smart Specialisation’ (Gianelle et al 2016, Paliokaite, Martinaitis & Reimeris 2015, Santonen, Kaivo-oja & Suomala 2014, Virkkala et al 2014), the European Commission presents a framework and the desirable properties that are expected from smart specialisation indicators.
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