Data set from Graduate labour market statistics

Graduate breakdowns by employment rates

Latest data
Published
Last updated
Employment rates for graduates only in 2023 by gender, ethnicity, disability, and class of degree.

Data set details

Theme
Higher education
Publication
Graduate labour market statistics
Release type
Geographic levels
National
Indicators
  • Employment Rate
  • High-Skilled Employment Rate
  • Inactivity Rate
Filters
  • Graduate Breakdown
  • Graduate Characteristic
Time period
2023

Data set preview

Table showing first 5 rows, from underlying data
time_periodtime_identifiergeographic_levelcountry_codecountry_namegraduate_characteristicgraduate_breakdownemployment_ratehs_employment_rateunemployment_rateinactivity_rateemployment_accuracy_flaghs_employment_accuracy_flagunemployment_accuracy_flaginactive_accuracy_flag
2023Calendar yearNationalE92000001EnglandDegree ClassFirst88.770.22.29.30040
2023Calendar yearNationalE92000001EnglandDegree ClassUpper Second 2:188.469.02.49.50000
2023Calendar yearNationalE92000001EnglandDegree ClassLower Second 2:286.463.42.211.60040
2023Calendar yearNationalE92000001EnglandDegree ClassThird85.057.14.411.00044
2023Calendar yearNationalE92000001EnglandDisabilityDisabled77.053.24.519.30030

Variables in this data set

Table showing first 5 of 6 variables
Variable nameVariable description
employment_rateEmployment Rate
graduate_breakdownGraduate Breakdown - Select the Graduate Breakdown you are interested in
graduate_characteristicGraduate Characteristic - Select the Graduate Characteristic you are interested in
hs_employment_rateHigh-Skilled Employment Rate
inactivity_rateInactivity Rate

Footnotes

  1. The sum of the employment, unemployment, and inactivity rates do not equal 100% because of rounding and the rates are based on average (mean) figures over four different calendar quarters from the Labour Force Survey.
  2. Labour Force Survey data are routinely reweighted in line with population estimates, further details are in the methodology. 
  3. This release is classified as ‘official statistics in development’ due to sampling variability from low response rates, impacting the data quality as some figures are calculated using small sample sizes, for more information refer to the methodology. 

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