The regional and sectoral mobility of high-tech workers: insights from Finland

Abstract

In this paper we employ data on 156,000 workers working within the Finnish high-tech industries in order to identify the extent to which labour mobility between sectors and regions is influenced by the characteristics of the locality in which the worker works. With these data we are able to estimate different types of binary, multinomial and ordered logit models to capture different types of inter-or intra-sector or region employment mobility. As we will see the different categories of employment mobility are influenced by different factors such that we cannot simply talk about 'labour mobility', but rather need to be specific regarding each particular form of employment mobility. Our results show that urbanisation and industrial diversity are not just associated with greater intra-regional mobility, as is emphasised by the agglomeration literature, but also greater inter-regional mobility.

Spatial distribution of job opportunities in China: Evidence from the opening of the high-speed rail

“…For example, Lee and Wolpin (2006) assess how the wage difference between the service and the goods sectors influences intersectoral labor mobility using a two-sector labor market equilibrium model. Simonen et al (2016) examine the impact of regional wage levels as well as other factors on inter-or intra-sector or region employment mobility in the high-tech sector in Finland. Due to its importance for job opportunities, wage rate has also received considerable attention in McLaughlin and Bils (2001), Beladi et al (2008), Mitra and Ranjan (2010), and Dustmann et al (2017).…”

“…The second widely recognized factor is the regional unemployment rate. A higher unemployment rate usually indicates a shortage of job opportunities and a surplus of labor force, leading to higher labor movements away from the region (Decressin and Fatás, 1995;Eliasson et al, 2003;Finnie 2004;Simonen et al, 2016). Third, it is commonly accepted that transportation infrastructure improvements tend to increase regional accessibility and connectivity, which in turn reduces travel times and transportation costs (Arbués et al, 2015;Guirao et al, 2017).…”

Research on Labor Market Institutional Environment and Labor Agglomeration—Analysis Based on Dynamic Spatial Panel Data

“…The technological progress occurring in cities expands the urban-rural income gap and has an important impact on the labor flow. It also contributes to the re-matching of the labor force which may have an agglomeration effect or dispersion effect (Peng Guohua, 2015(Peng, 2015; Mikhail, 2011 (Martynovich and Lundquist, 2016); Simonen, 2016(Simonen et al, 2016). Agricultural technological progress leads to the decrease of demand for the agricultural labor force and promotes the transfer of the labor force from agricultural sectors to industrial sectors (Xiao Linzi, 2014 (Xiao andXiao, 2014); Liang Xiangdong, 2017 (Liang and Yiyi, 2017))。Some scholars also comprehensively consider the benefits and costs in the process of labor agglomeration, analyze the multi-regional spatial equilibrium state under any spatial background, construct a spatial equilibrium model, and study the evolutionary characteristics of labor agglomeration (Cheng Jinwen, 2018) (Cheng and Yang, 2018).…”

Labor institution environment and labor agglomeration based on provincial panel data analysis

“…Generally, advancement in agricultural technology will lead to a decline in the demand for agricultural labor and promote the transfer of labor force from the agricultural to the industrial sector; urban technological advancement will lead to the rebalancing of labor force, which may have an agglomeration or dispersion effect (Peng Guohua, 2015; Xiao Linzi, 2014; Mikhail, 2011; J. Simonen, 2016;Liang Xiangdong, 2017).…”