Higher education funding reforms in England: the distributional effects and the shifting balance of costs

household survey made up of a five quarter rotating panel. Prior to 1997, data on
earnings were collected in the fifth quarter, and from 1997 onwards, data on earnings
were also collected in the first quarter. To estimate the dependence in earnings for
graduates, we restrict the sample to graduates aged 19 through 60 who are full- or
part-time employees or in government employment or training programmes, and for
whom we observe two positive earnings observations, which leaves us with a sample
of just under 35,000 graduates.¹⁵ Note that the earnings simulations are drawn from all
available years of LFS data, and for these we use graduates for whom we observe at
least one earnings observation, which leaves us with a total of just over 135,000
earnings observations. The simulated employment paths and re-entry earnings ranks
are based on mobility patterns observed in the British Household Panel Survey
(BHPS) between 1991 and 2004, inclusive.

Figure provides a picture of the simulated lifetime earnings distribution for graduate
men and women.¹⁶ The median values for lifetime earnings (between ages 22 to 60)
for men is simulated to be £2 million between the ages of 22 to 60, while for women
the median simulated lifetime earnings is around £1.3 million. One important feature
of these distributions to note is that they are much less skewed compared to more
commonly observed cross-sectional distributions of wages. This is because taking into
account mobility in individual earnings ranks over time reduces the level of inequality
considerably.

Figure . Simulated lifetime earnings distributions for men and women

(approximately 60,000 households are interviewed each quarter in the LFS, compared to around 5,500
households recruited in wave 1 of the BHPS). It is worth noting however that our simulations of the
lifetime earnings distributions from both data sources are very similar.

15 This means that we drop employees who did not provide data on earnings in both quarters, whether
due to attrition from the survey (around 40% of our sample of graduate employees leave the sample
between waves 1 and 5) or refusal to answer earnings-related questions (in general this ranges between
10 and 20 per cent). Note that we nonetheless retain large samples to estimate dependence in earnings.
It is difficult to know the extent of the biases, if any, induced by sample selection, and a full analysis of
this is beyond the scope of this paper.

16 In this figure, lifetime earnings are simply added across ages 22-60, without any discounting.

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