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Winners of Dissertation Prize 2017 announced

Article dated: 4 July 2017

The winners of the Dissertation Prize 2017 have been announced.

The Dissertation Prize recognises and rewards undergraduate students who demonstrated flair and originality in using quantitative and/or qualitative data available through the UK Data Service for their dissertations. Each of the winners were awarded a prize: £500 (1st) £250 (2nd) £150 (3rd).

The winners of the 2017 Dissertation Prize are:

1st Prize

Haoyu Zhai

BSc in Politics with Quantitative Research Methods, University of Bristol

Dissertation title: A Three-Channel Study of British Immigration Attitudes 2013


Haoyu's research looks at the key determinants of individual-level public opinion on immigration in the United Kingdom, using statistical analysis of data from the 2013 British Social Attitudes Survey. Drawing on existing literature and theories, it develops a three-channel framework to more fully capture the multidimensional nature of individual-level immigration attitudes in the UK, incorporating the roles of economic, sociocultural and security factors. Specifically, it argues that negative perceptions about immigrants’ impacts in each of the three dimensions would lead to negative immigration attitudes among native individuals, and that such subjective perceptions are stronger determinants of natives’ immigration opinions than their sociodemographic characteristics. Results from bivariate correlation and ordinal regression tests have confirmed these hypotheses, by showing that perceived threats from immigrants on economic wellbeing, sociocultural identities and security indeed increase native British individuals’ hostility against them, and that these perception factors do have stronger effects than the position (demographic) factors in shaping native immigration attitudes. These findings complement existing studies in the field, and point to a multidimensional and perception-centred mechanism of individual-level immigration attitudes in the UK.

2nd Prize

Shamus Lee

BSc in Economics, University of Exeter

Dissertation title: Does Degree Class Matter? The Effects of Degree Classification on Graduate Earnings



Shamus's research analyses wage differentials by degree classification among graduates in the United Kingdom using the 1970 British Cohort Study. It deploys a ‘Mincerian’-inspired earning function to estimate the wage premiums associated with degree classification awards at the conditional mean of wage using ordinary least squares (OLS), and at conditional quantiles of the wage distribution using quantile regression (QR). The research identifies a premium associated with a good degree class (i.e., first and second-upper), as the OLS regression predicts that a good degree class relative to a lower degree class, on average, increases hourly wage by approximately 7.6%. The QR strategy also finds systematic differences in the degree class premium along the conditional wage distribution, and reports significant evidence that wage differential between good and lower degree class holders is stronger at higher quantiles of wage earnings, at approximately 5.4% for median wages to 10.9% for top decile wages. The results corroborate to existing literature that degree classification has both economical and statistical significances on graduate earnings.

3rd Prize

Joel Flynn

BA in Economics, University of Cambridge

Dissertation title: The Distribution of Wealth and Consumption Patterns in the UK



Using data from the Wealth and Assets Survey, Joel's research calibrates an overlapping-generations life-cycle model to match the UK wealth distribution and provide structural estimates of UK consumption patterns over the life-cycle that are consistent with the empirical evidence. It applies the calibrated model to study the aggregate consumption response induced by fiscal stimulus that targets wealth rather than income and estimate that the aggregate consumption response to fiscal stimulus targeted at households in the bottom wealth quintile is two to six times larger than to stimulus targeted at households in the bottom income quintile. The findings suggests that policymakers should pursue fiscal stimulus that targets low-wealth households, rather than the traditional approach of targeting low-income households. A by-product of the analysis is a novel algorithm that almost halves the computation time of the calibration from 269 hours under standard methods to 137 hours.

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