The Thesis seeks to make a contribution to our current understanding of the\ud complex relationship between higher education and the graduate labour market in\ud the UK on both a methodological and policy level. Using administrative data from\ud the Universities' Statistical Record (USR) on complete cohorts of individual\ud students who left university between 1980 and 1993, the Thesis develops along\ud three main avenues: i) identifying the key determinants of graduates' first\ud destinations (Chapters 2 and 3); ii) comparing alternative indicators of\ud employment-related university performance and assessing their robustness to data\ud aggregation (Chapter 4); iii) estimating the differences in graduates' occupational\ud earnings by degree subject (Chapter 5).\ud The study on first destination considers a broad range of possible outcomes\ud distinguishing between temporary and permanent as well as 'graduate' and 'nongraduate'\ud employment, professional training and postgraduate study, involuntary\ud unemployment and unavailability for work. The analysis reveals significant\ud effects on graduates' employability associated with gender, university type,\ud degree subject, degree class, socio-economic background, and prior qualifications\ud (Chapter 2). Moreover, the impact of all the main factors affecting graduates'\ud early careers has a significant correlation with the business cycle (Chapter 3).\ud In Chapter 4 we compare employment-related university performance indicators\ud constructed from student-level and university-level data, respectively. Despite\ud student-level data on university statistics now being publicly available, institutions\ud are currently assessed according to indicators based on university-level data,\ud implicitly obtained by averaging over individuals the corresponding student-level\ud information. We find significant differences between the two sets of indicators\ud and argue that the observed discrepancies are the result of an aggregation bias. A\ud Monte Carlo experiment is used to test the validity of this conclusion.\ud Finally, Chapter 5 looks at the differences of graduates' occupational earnings by\ud degree subject using USR and NES data from 1980 to 1993. We discuss the issue\ud of self-selection of students into the subject of study and apply three alternative\ud modelling strategies to control for self-selection: the proxy and matching method,\ud propensity score matching and a simultaneous equations model accounting for\ud 'selection on unobservables'. The evidence suggests the presence of a significant\ud selection bias originating from the unaccounted correlation between unobservable\ud individual characteristics affecting both occupational earnings and subject choice.\ud Moreover, the ranking of university subjects changes over time
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