Entry rates into higher education

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1. Main facts and figures

  • in 2017, White pupils had the lowest entry rate into higher education (where ‘entry rate’ is the percentage of state school pupils aged 18 years getting a higher education place), and Chinese pupils had the highest
  • White pupils had the lowest entry rates in every year since 2007; Chinese pupils had the highest entry rates in every year between 2006 and 2017
  • between 2006 and 2017, entry rates increased for all ethnic groups
Things you need to know

The data does not take into account pupils’ individual characteristics or their past academic achievements, all of which affect their likelihood to get a place at university or college.

What the data measures

This data measures the percentage of 18 year olds from different ethnic backgrounds who got a higher education place in the UK (referred to here as the 'entry rate').

The data only includes pupils from state schools in England who applied to universities and colleges through the Universities and Colleges Admissions Service (UCAS).

The ethnic categories used in this data

Data on ethnicity is broken down into 6 broad groups:

  • Asian
  • Black
  • Chinese
  • Mixed
  • White (including White ethnic minorities)
  • Other

2. Entry rates into higher education by ethnicity

Percentage of state school pupils aged 18 years getting a higher education place by ethnicity
Year Asian Black Chinese Mixed White Other
% % % % % %
2006 34.5 21.6 53.6 22.9 21.8 27.0
2007 34.6 23.1 52.8 24.3 22.2 27.1
2008 35.7 25.7 52.0 25.0 23.5 27.9
2009 36.1 27.0 52.6 25.7 24.1 27.8
2010 35.0 28.4 52.6 25.6 24.2 27.8
2011 37.0 31.7 60.1 28.9 25.8 30.5
2012 36.1 31.4 57.1 27.8 24.7 30.6
2013 38.6 34.7 57.4 29.2 26.1 32.0
2014 39.8 36.0 59.3 31.0 27.3 34.3
2015 42.3 38.4 61.0 32.3 27.9 36.8
2016 44.1 39.1 60.8 33.4 28.9 38.0
2017 45.8 40.4 63.0 34.0 29.3 40.1

Download table data for ‘Entry rates into higher education by ethnicity’ (CSV) Source data for ‘Entry rates into higher education by ethnicity’ (CSV)

Summary of Entry rates into higher education Entry rates into higher education by ethnicity Summary

This data shows that:

  • in 2017, Chinese pupils had the highest entry rate into higher education (at 63.0%), while White pupils had the lowest (at 29.3%)
  • Chinese pupils had the highest entry rates in every year between 2006 and 2017
  • White pupils had the lowest entry rates for 11 consecutive years since 2007; the lowest entry rate in 2006 was for Black pupils
  • between 2006 and 2017, entry rates increased for all ethnic groups, and are currently at the highest level across all ethnic groups
  • the greatest increase in entry rates between 2006 and 2017 was among Black pupils (increasing from 21.6% to 40.4%); the lowest increase was among White pupils, where entry rates increased from 21.8% to 29.3%

3. Methodology

Higher education entry rates are estimates. They are calculated by linking UCAS admissions data with pupil data contained in the:

The method used to link the school and UCAS data requires a full match across a range of identifying details to UCAS applicants who live in England. The published entry rates are lower than the real value because ambiguous matches are not used.

The Department for Education does not have access to the underlying data used to calculate the entry rates.

Rounding

Percentages have been rounded to 1 decimal place.

Related publications

Higher education participation: socio-economic, ethnic and gender differences - BIS research paper 186

4. Data sources

Source

Type of data

Administrative data

Type of statistic

Official statistics

Publisher

Department for Education

Publication frequency

Yearly

Purpose of data source

The Universities and Colleges Admissions Service (UCAS) End of Cycle Report provides data that allows UCAS and others to find out more about progression, participation and inequalities in higher education admissions.

5. Download the data

Entry rates into higher education - Spreadsheet (csv) 9 KB

This file includes the following variables: measure, time, time_type, ethnicity, ethnicity_type, geography, value and value_type.