Murphy, RJ; (2014) Little known facts about education: An empirical analysis. Doctoral thesis , UCL (University College London).

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Abstract

The thesis consists of four chapters utilising applied micro-econometric techniques to develop a deeper understanding of the education sector. I apply traditional economic concepts such as productivity, immigration, insurance and technological innovation to the field of education economics. Chapter one considers the consequences of academic rank in primary school on later test scores. Using administrative data tracking the student population in England, I estimate the impact of rank on later attainment through the variation in the test-score distributions across schools. The positive impact of rank on attainment helps to explain some puzzles in the education literature, such as the lack of impact of selective schools. The second chapter involves immigration and investigates how the influx of overseas students has affected enrolment of domestic students at UK universities. Using administrative data, I employ methods used in the labour literature to model crowd-out. I find no evidence of crowd-out of domestic students, and some evidence of crowd in amongst postgraduate students. Chapter three establishes the threat of accusations as new source of demand for trade union membership amongst teachers. I model union membership as legal insurance, where demand is determined by the threat of accusations. I measure threat primarily through the incidence of media stories concerning teachers in the local area. Combining these data with union membership data from Labour Force Surveys, I find that unionisation rates increase with media coverage of allegations. The final chapter is an estimation of the impact of restricting technology in the workplace on productivity. This is applied to the education setting using the autonomous decisions by schools to ban mobile phones. Obtaining histories of phone policies through surveys and combining this with administrative data on individual pupil level attainment, I use a difference in difference analysis to estimate the impact on student performance.

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