Abstract
This paper considers the relationship between an unemployed person’s employability and job search success. Using a broad employability framework (covering individual, personal and external demand, and other factors) the paper considers a range of demand and supply factors, that were generally identified in applied and theoretical literature, that influence success in getting employment. The model is then used to consider the competing efficient metropolitan labor market and the local labor demand hypotheses in terms of the importance for this sample of skills mismatch and spatial mismatch. The findings suggest that professional qualifications, “soft” verbal skills and using speculative applications to employers were significantly associated with job search success. Length of unemployment, age, and having last worked in a manual occupation were negatively associated with job success, the latter decreasing the odds of getting a job to around thirty percent, suggesting difficulties in occupational “switching” for many job seekers. Higher academic qualifications were also significantly negative, as were those claiming that promotion chances will influence their reservation wage. The geographic accessibility to local jobs was significantly and positively associated with job search success. The results suggest that a range of employability factors and both skills mismatch and spatial mismatch are important in explaining job search success. The degree of “skills” or “spatial” mismatch in a local labor market will be contingent upon the characteristics of the local economy, employers, job seekers and the jobs being considered.
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Notes
For instance, those not willing to do shift work, females in part-time jobs, those with dependants, fewer years of education, longer length in unemployment, and lower incomes are less likely to travel longer distances to work (McQuaid et al. 2001).
Originally, 306 people were randomly surveyed at 13 Jobcenter offices but data on success in leaving unemployment was only provided by some of these Jobcenters so missing data were omitted from the analysis. There were no apparent biases in the information obtain on individual job seekers from the original sample or among those Jobcenters who provided data.
To avoid this, variables covering flexibility of job seekers and other factors in the framework were included, but then removed from the model due to their lack of significance and to be parsimonious.
A model testing if the effects of age were binomial (with both younger and older job seekers at a disadvantage) was tested but was not found to be an improved model.
Other search channels (Jobcenters, employment agencies, and word of mouth) were not significantly related and did not improve the model.
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Acknowledgements
I wish to thank anonymous referees for useful comments and Malcolm Greig for support in writing this paper, and Andrew Charlesworth, Robert Raeside and John Adams. All views and errors remain those of the author.