The relationship between transport disadvantage and employability: Predicting long-term unemployment based on job seekers' access to suitable job openings in Flanders, Belgium. (July 2019)

• Record Type: Journal Article
• Authors: Fransen, Koos; Boussauw, Kobe; Deruyter, Greta; De Maeyer, Philippe
• Is Part Of: Transportation research. Volume 125(2019)
• Page Start: 268
• Page End: 279
• Publication Date: 2019-07
• Subjects: Unemployment -- Job accessibility -- Social equity -- Transport disadvantage; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2018.01.023
• Languages: English
• ISSNs: 0965-8564

Abstract

Highlights: Job accessibility as an indicator for employment has been studied widely. Existing studies fail to capture job seekers' individual labor-market opportunities. The study proposes an accessibility-based predictive model for long-term unemployment. Various inequities in long-term unemployment exist in Flanders, Belgium. The results have important ramifications for transport and spatial planning policies. Abstract: In no research domain has the application of accessibility been so vital as in the area of linking disadvantaged individuals to job opportunities. The inability to reach locations of employment and, therefore, partake in paid labor is considered to have severe consequences on an individual's economic security and quality of life as well as society's general level of welfare. Unfortunately, existing studies on job accessibility primarily apply aggregate measures that aim to link the population group of active, employed workers to pre-existing job locations. As a result, they fail to capture the person-specific labor-market opportunities for those individuals who are actually unemployed as well as the degree to which accessibility to opportunities is related to actual employment rates. The proposed paper answers this limitation by constructing a predictive model for long-term unemployment for job seekers in Flanders, Belgium, dependent on their access by private and public transport to job openings that correspond to their individual preferences and competences. In addition to accessibility, the predictive capacity was determined for various socio-demographics such as age, gender, migration background, educational background and preferred job type. The proposed regression model shows that job accessibility is negatively related to long-term unemployment. In addition, various inequities in long-term unemployment exist for the selected case study. Especially job seekers with a migration background and with higher age (55 years or older) have significantly higher probabilities of remaining unemployed. A conditional inference regression tree indicates that the most disadvantaged groups have a two to three times higher probability of being long-term unemployed. Moreover, higher accessibility levels prove to only benefit those who already are in a more advantaged position. These findings have important ramifications for policies focusing on improving employment rates, as they allow to specifically address those areas of research where major gains can be made.