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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper compares survey based labour earnings data for English graduates, taken from the UK's Labour Force Survey (LFS), with the UK Government administrative sources of official individual level earnings data. This type of administrative data has few sample selection issues, is substantially longitudinal and its large samples mean the earnings of subpopulations can be potentially studied (e.g. those who study a specific subject at a specific university and graduate in a specific year). We find that very broadly the LFS and administrative data show a similar distribution of graduates' earnings. However, the administrative data has considerably less gender disparity, higher high quantiles and more time series persistence. We also report on how the distribution of graduate and non-graduate earnings fell during each year of the great recession. Terms of use: Documents in

Using data from the Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA), we estimate a dynamic model of health and employment. We estimate how transitory and persistent health shocks affect employment over time. In a first step, we formulate and estimate a dynamic model of health. The procedure accounts for measurement error and the possibility that people might justify their employment status by reporting bad health. We find that health is well represented by the sum of a transitory white noise process and a persistent AR(1) process. Next, we use the method of simulated moments to estimate the employment response to these shocks. We find that persistent shocks have much bigger effects on employment than transitory shocks, and that these persistent shocks are long lived. For this reason employment is strongly correlated with lagged health, a fact that the usual cross-sectional estimates do not account for. We also show that accounting for the dynamics of health and employment leads to larger estimates of health's effects on employment than what simple OLS estimates of health on employment would imply. We argue that the dynamic effect of health on employment could be generated by a model with human capital accumulation, where negative health shocks slowly reduce the human capital stock, and thus, gradually cause people to exit the labor market.

Much research and policy attention has been on socio-economic gaps in participation at university, but less attention has been paid to socio-economic gaps in graduates' earnings. This paper addresses this shortfall using tax and student loan administrative data to investigate the variation in earnings of English graduates by socio-economic background. We find that graduates from higher income families (with median income of around 77,000) have average earnings which are 20% higher than those from lower income families (with median income of around £26,000). Once we condition on institution and subject choices, this premium roughly halves, to around 10%. The premium grows with age and is larger for men, in particular for men at the most selective universities. We estimate the extent to which different institutions and subjects appear to deliver good earnings for relatively less well off students, highlighting the strong performance of medicine, economics, law, business, engineering, technology and computer science, as well as the prominent London-based universities.

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Estimates of how health affects employment vary considerably. We assess how different methods and health measures impact estimates of the impact of health on employment using a unified framework for the US and England. We find that subjective and objective health measures, and subjective measures instrumented by objective measures produce similar estimates when using sufficiently rich objective measures. Moreover, a single health index can capture the relevant health variation for employment. Health deterioration explains up to 15% of the decline in employment between ages 50 and 70. Effects are larger for the US than England, and for the low educated.