New Linked Payroll-Census Data Reveal Large Ethnic Wage Gaps

For the first time we present hourly wage gaps by ethnicity and sex using the payroll data (the Annual Survey of Hours and Earnings, or ASHE).

Although other data sources can be used to estimate ethnic wage gaps, payroll data are particularly high quality because they are provided by the employers.

Using Census 2011 data linked to the payroll data reveals, for the first time, how hourly wages constructed from payroll data differ by ethnicity and sex.

Because ethnic wage gaps differ markedly by sex it is important to account for both these personal characteristics in what have become known as inter-sectional wage gaps.

Figure 1: Mean and Median hourly earnings for employees in England and Wales in 2011, by ethnicity and gender

Figure 1 shows that, among men, average (median) hourly wages are highest among Indian employees, followed by Chinese employees, with white employees coming in a close third. Those with the lowest average (median) hourly earnings are Black African men.

Among women, average (median) hourly wages are generally more compressed across ethnic groups. Chinese women have the highest average (median) hourly earnings.

Comparisons of raw gaps can be misleading because we are not comparing ‘like’ individuals. But the ASHE-Census data help in this regards because they allow us to adjust for hourly pay comparisons across sex and ethnicity holding other characteristics constant.

Figure 2 shows what happens when we make this comparison for average (median) hourly wages among employees with the same levels of education and experience, the same type of job and with the same family circumstances.

Figure 2: Adjusted hourly earnings penalty in England and Wales in 2011, ethnic minorities vs white employees

Figure 2 shows the wage penalty attached to men and women of different ethnicities relative to white men and white women, respectively.

Whereas Chinese and Indian men and women were earning more than their white counterparts when we looked at raw hourly wage differences, it is apparent that this is because Chinese and Indian employees possessed better wage-enhancing characteristics – in particular their education. Once these differences are accounted for, Indian men and women earn a little less per hour than their white counterparts. Similarly, when other factors are accounted for, Chinese men and women earn a little less than white men and women, but these differences are not statistically significant.

Among both men and women, Black African employees earn the lowest adjusted wages. Black African men are earning around 35-36 log points lower wages per hour than comparable white males. Among women the differential is around 18 log points. These are huge penalties.


  • This research is produced by the WED team.
  • The estimates reported here are derived by matching the 2011 Annual Survey of Hours and Earnings (ASHE) to the 2011 Census for England and Wales. More recent data are not available, because the Census only comes along once every 10 years.
  • There are 7 ethnic groups, including White, Indian, Pakistani, Bangladeshi, Chinese, Black African, and Black Caribbean. We do not consider the mixed and other ethnic groups.
  • See here for more details of the data, method and results.