This study focuses on age and digital exposure as factors driving individuals to be (1)
employees
or
entrepreneurs
, (2)
full-time
or
part-time
, or (3)
opportunity
or
necessity
entrepreneurs. It extends occupational choice models, relying on a utility maximization framework, to entrepreneur types incorporating age and digital exposure effects. Using 132 months of Current Population Survey data and multilevel modelling with individuals’ fixed effects and metropolitan area random effects, the study finds that (1) workers with low- and high- digital exposure are more likely to become entrepreneurs than peers with medium digital exposure, mirroring digitization’s “push” and “pull” mechanisms on entrepreneurship; (2) age strengthens digitization’s “pull” mechanism to be
entrepreneurs
(versus
employees
) and
opportunity
(versus
necessity
) entrepreneurs; (3) digital exposure has a weak marginal potential to increase workers’ odds to be
part-time
(versus
full-time
) entrepreneurs. The study also notes the importance of location and concludes with discussion and implications.
The study examines the role of home-to-new-job-hub distance on employment propensity using a unique dataset compiled from integrated micro-level administrative records of work-eligible welfare recipients and earnings. Our empirical findings confirm the Spatial Mismatch Hypothesis. Our home-to-new-job-hub distance measure is an innovative weighted measure incorporating both abundance of actual employment opportunities and geographic distance. Other unique contributions of this study include using point-to-point residence and job hub locational information, modeling with community controls, and industry specific analysis. This study also identifies policy implications in advancing employment prospects of inner-city residents receiving government assistance.
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