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European Socio-Economic Classification: A Validation Exercise Figen Deviren Office for National Statistics.

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Presentation on theme: "European Socio-Economic Classification: A Validation Exercise Figen Deviren Office for National Statistics."— Presentation transcript:

1 European Socio-Economic Classification: A Validation Exercise Figen Deviren Office for National Statistics

2 Introduction The UK context Creating E-SeC Validation Using the Labour Force Survey Results Conclusions

3 The UK context 8 classes5 classes3 classes 1 Higher managerial and professional occupations 1.1 Large employers and higher managerial occupations 1 Managerial and professional occupations 1.2 Higher professional occupations 2 Lower managerial and professional occupations 3 Intermediate occupations2 Intermediate occupations 4 Small employers and own account workers 3 Small employers and own account workers 5 Lower supervisory and technical occupations 4 Lower supervisory and technical occupations3 Routine and manual occupations 6 Semi-routine occupations5 Semi-routine and routine occupations 7 Routine occupations 8 Never worked and long- term unemployed Never worked and long-term unemployed

4 Deriving NS-SeC Questions asked about occupation SOC 2000 Questions about Employment status Questions on Size of organisation NS-SeC Deriving NS-SeC Questions asked about occupation SOC 2000 Questions about Employment status Questions on Size of organisation NS-SeC SupervisorSelf-employed

5 Deriving E-SeC SOC 2000 ISCO-88 Employment status Supervisory responsibilities Working alone E-SeC Deriving E-SeC SOC 2000 ISCO-88 Employment status Supervisory responsibilities Working alone E-SeC Size of organisation

6 Validation For our purposes validation meant Will E-SeC provide a representative picture of the UK that is comparable to the one provided using the NS-SeC? Does E-SeC have a similar predictive power to that of NS-SeC?

7 Choice of survey The Labour Force Survey –Sample size, 72,500 of working age (men aged 16 - 64, women aged 16 - 59) –Recent quarterly data – Autumn 2005 –Available at both individual and household levels –Relevant questions

8 Comparison of E-SeC and UK NS-SeC (reduced categories) Source: Labour Force Survey, Autumn 2005

9 Case comparability Agree at 7 categories Agree at 3 categories No agreement Source: Labour Force Survey, Autumn 2005

10 A Comparison of E-SEC and NS-SEC for males Source: Labour Force Survey, Autumn 2005 Lower sales, service and technical

11 A Comparison of E-SEC and NS-SEC for females Source: Labour Force Survey, Autumn 2005

12 European Socio-Economic Classification by sex Source: Labour Force Survey Autumn 2005

13 Lower managers, professionals, higher supervisory and technicians: E-SeC and NS-SeC by age and sex. Source: Labour Force Survey, Autumn 2005

14 Routine occupations: E-SeC and NS-SeC by age and sex Source: Labour Force Survey, Autumn 2005

15 Comparison of E-SeC and NS-SeC at household level Source: Labour Force Survey, Autumn 2005

16 European Socio-Economic Classification by sex of household reference person Source: Labour Force Survey, Autumn 2005

17 Predictive power NS-SeC is accepted as a predictor of ill-health Linear regression – binary outcome yes/no Choice of variables Significance of classifications

18 Chronic morbidity for males (individual level) Source: Labour Force Survey, Autumn 2005

19 Chronic morbidity for females (individual level) Source: Labour Force Survey, Autumn 2005

20 Predictive power – Individual level -using NS-SeC as an independent variable BS.E.Exp(B) sex-0.010.0010.992 Age25_340.180.0021.196 Age35_440.490.0021.63 Age45_540.930.0022.541 Age55_641.510.0024.513 ethn20.130.0021.142 quals-0.210.0010.813 degree-0.390.0020.68 nsec_h20.130.0021.139 nsec_h30.220.0021.242 nsec_h40.130.0021.14 nsec_h50.340.0021.403 nsec_h60.390.0021.481 nsec_h70.480.0021.612 Constant-1.920.0030.147 Chronic morbidity - using E-SeC as an independent variable BS.E.Exp(B) sex-0.010.0010.995 Age25_340.260.0021.291 Age35_440.560.0021.75 Age45_541.000.0022.726 Age55_641.580.0024.846 ethn20.160.0021.175 quals-0.220.0010.802 degree-0.400.0020.67 esec_h20.160.0021.177 esec_h30.220.0021.251 esec_h40.150.0021.162 esec_h50.360.0021.438 esec_h60.350.0021.421 esec_h70.470.0021.596 Constant-2.020.0030.133 Results of the regression analysis containing age, ethnicity and educational attainment

21 Predictive power – Household level Chronic morbidity - using E-SeC as an independent variable BS.E.Exp(B) sex-0.170.0010.848 Age25_340.220.0021.245 Age35_440.540.0021.717 Age45_540.970.0022.638 Age55_641.580.0024.835 ethn20.120.0021.124 quals-0.420.0010.655 degree-0.220.0020.804 esec_h20.110.0021.113 esec_h30.260.0021.296 esec_h40.160.0021.175 esec_h50.330.0021.391 esec_h60.450.0021.566 esec_h70.480.0021.615 Constant-1.790.0040.168 -using NS-SeC as an independent variable BS.E.Exp(B) sex-0.170.0010.842 Age25_340.270.0021.306 Age35_440.590.0021.801 Age45_541.020.0022.764 Age55_641.620.0025.072 ethn20.130.0021.143 quals-0.450.0010.637 degree-0.240.0020.786 nsec_h20.150.0021.160 nsec_h30.260.0021.297 nsec_h40.170.0021.187 nsec_h50.340.0021.409 nsec_h60.380.0021.468 nsec_h70.480.0021.614 Constant-1.830.0040.160

22 Conclusions The picture of the UK using E-SeC is broadly similar to that obtained when using NS-SeC Differences observed between the two classifications for lower managers/professionals and routine occupations by age and sex E-SeC is comparable to NS-SeC when used as a predictor of chronic morbidity. More validation needed?

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