This thesis evaluates the efficiency of educational policies, especially those which result in surplus education. In particular, in Chapter 2 we explore whether the positive return of overeducation is due to increases in productivity or due to ability signals. We adopt the methodology proposed by Wolpin (1977) and implemented by Brown and Sessions (1999) to examine our hypothesis. We find significant evidence supporting the strong screening hypothesis which infers that surplus education has purely private returns. Furthermore, in Chapter 3 we test whether our results hold using a panel dataset. Chapter 4 examines the often accepted statement that additional education decreases unemployment. We analyse how educational mismatch, and in particular surplus education, affect the likelihood of job loss and the re-employment rates especially in a period of economic crisis. We employ a pooled data logit model, and examine the partial relationships between the probability of job loss and over, under and adequate education. In addition, we evaluate the effect of surplus education on the re-employment hazard profiles using a discrete time duration model. Finally, in Chapter 5 we use an alternative methodology to test the signalling effects of surplus education. In particular we adopt the employer learning specification which assumes that the longer an individual is in the labour market and gains experience, the more likely it is to reveal his or her true productivities to employers (Farber and Gibbons, 1996). We expect that if the interaction term of required or surplus education with experience has a positive sign then we have evidence of productivity effects. If the coefficient of the interaction term is negative then the model provides evidence of signalling.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:617637 |
| Date | January 2014 |
| Creators | Kyrizi, Andri |
| Contributors | Kedir, Abbi; Mora, Francisco Martinez |
| Publisher | University of Leicester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2381/28969 |
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