Presentation is loading. Please wait.

Presentation is loading. Please wait.

The Returns to Academic and Vocational Qualifications Steven McIntosh Department of Economics University of Sheffield.

Published byGage Gaskell Modified over 10 years ago

Similar presentations

Presentation on theme: "The Returns to Academic and Vocational Qualifications Steven McIntosh Department of Economics University of Sheffield."— Presentation transcript:

1 The Returns to Academic and Vocational Qualifications Steven McIntosh Department of Economics University of Sheffield

2 Introduction Work done for the Department for Education and Skills, who wanted: estimates of returns to qualifications to detailed qualifications estimates of how returns vary by prior qualifications estimates of age earnings profiles Published in Oxford Bulletin of Economics and Statistics, 2006.

3 Returns to Education OLS estimation of log-linear earnings function. Data – pooled QLFS producing annual data sets for 1996, 1998, 2000 and 2002.

4 Econometric Issues Coefficient on education can be biased due to: Omitted ability measures Omitted family background measures Measurement error on education variable Sample composition bias. Results suggest biases cancel out, leaving OLS a good estimate of true returns

5 Specification Issues Include all qualifications that individuals hold, not just highest qualification: Estimates based on all people who obtain the qualification Lack of common support with the no qualifications group No need to decide which is the highest qualification

6 Qualification1996199820002002 higher degree0.1130.0830.1310.129 (0.025)**(0.015)**(0.016)**(0.015)** first degree0.2340.2530.2490.258 (0.014)**(0.010)**(0.011)**(0.010)** other HE0.0900.0680.0900.060 (0.042)*(0.025)**(0.024)**(0.029)* HE diploma0.0710.0720.0600.074 (0.025)**(0.019)**(0.020)** 2+ A levels0.1630.1600.1450.142 (0.013)**(0.010)** The Returns to Academic Qualifications – All Full-Time Male Employees

7 Qualification1996199820002002 1 A level0.0950.0430.0610.041 (0.024)**(0.014)** (0.015)** A/S levels0.026-0.0480.035-0.043 (0.087)(0.044)(0.035)(0.034) 5+ GCSEs A*-C0.2720.2660.2740.246 (0.011)**(0.008)** 1-4 GCSEs A*-C0.1630.1620.1630.139 (0.010)**(0.007)**(0.008)** GCSEs D-F0.0910.0820.0630.061 (0.015)**(0.010)** (0.011)** The Returns to Academic Qualifications – All Full-Time Male Employees

8 Qualification1996199820002002 professional quals0.3260.3360.3650.413 (0.022)**(0.017)** (0.019)** teaching qualifications0.0490.0570.0710.094 (0.024)*(0.016)**(0.017)**(0.016)** nursing qualifications0.0710.0870.1140.078 (0.036)*(0.024)**(0.026)** HNC/HND0.1430.1540.1290.139 (0.014)**(0.009)** (0.010)** RSA higher0.0410.037-0.0340.003 (0.170)(0.069)(0.068)(0.040) ONC/OND0.1110.0890.1120.079 (0.013)**(0.010)** City & Guilds Ad. Craft0.0410.0670.0400.039 (0.014)**(0.009)** NVQ 3-50.0310.0570.027 (0.027)(0.014)**(0.011)* The Returns to Vocational Qualifications – All Full-Time Male Employees

9 Qualification1996199820002002 City & Guilds Craft0.0090.0750.0810.078 (0.016)(0.014)**(0.017)**(0.016)** BTEC diploma0.0940.0310.0520.045 (0.027)**(0.022)(0.023)* NVQ 2-0.068-0.066-0.081-0.088 (0.023)**(0.014)**(0.013)**(0.012)** City & Guilds other0.039-0.036-0.039-0.048 (0.014)**(0.012)**(0.015)**(0.014)** NVQ1-0.118-0.099-0.075-0.066 (0.041)**(0.025)**(0.019)**(0.020)** RSA lower-0.068-0.088-0.065-0.072 (0.030)*(0.019)**(0.022)**(0.020)** other0.0480.0540.0570.050 (0.007)**(0.005)** The Returns to Vocational Qualifications – All Full-Time Male Employees

10 The Returns to Academic Qualifications – All Full-Time Male Employees, by Highest School Qualification, 1996-2002 QualificationNo school quals GCSEs D-F 1-4 GCSEs A*-C 5+ GCSEs A*-C 1 A level2+ A levels higher degree0.2350.2780.1390.1540.1590.053 (0.040)**(0.110)*(0.045)**(0.036)**(0.055)**(0.009)** first degree0.3910.1240.1690.1500.1060.197 (0.026)**(0.054)*(0.020)**(0.013)**(0.023)**(0.007)** other HE0.1290.2850.1160.102-0.021 (0.038)**(0.082)**(0.032)**(0.028)**(0.065)(0.021) HE diploma0.2100.1760.0620.0670.044-0.025 (0.034)**(0.054)**(0.030)*(0.023)**(0.035)(0.014)

11 QualificationNo school quals GCSEs D-F1-4 GCSEs A*-C 5+ GCSEs A*-C 1 A level2+ A levels professional quals0.5720.4380.2600.2730.2320.291 (0.036)**(0.059)**(0.032)**(0.020)**(0.032)**(0.012)** teaching quals0.1290.0870.0570.0610.115-0.014 (0.044)**(0.088)(0.039)(0.025)*(0.029)**(0.010) nursing quals0.2640.1500.1290.0020.024-0.045 (0.030)**(0.084)(0.030)**(0.026)(0.046)(0.025) HNC/HND0.2620.2100.2030.1420.124-0.015 (0.015)**(0.031)**(0.010)**(0.008)**(0.017)**(0.010) RSA higher-0.0010.022-0.0590.062-0.030-0.157 (0.082)(0.150)(0.066)(0.092)(0.061)(0.069)* ONC/OND0.1520.1400.1380.0810.021-0.072 (0.016)**(0.026)**(0.009)**(0.008)**(0.021)(0.016)** C&G Ad.Craft0.0460.0210.065-0.029-0.069-0.182 (0.010)**(0.016)(0.008)**(0.010)**(0.038)(0.027)** NVQ 3-50.0680.0580.0600.034-0.001-0.102 (0.015)**(0.023)*(0.011)**(0.013)**(0.028)(0.020)** The Returns to Vocational Qualifications – All Full-Time Male Employees, by Highest School Qualification, 1996-2002

12 QualificationNo school quals GCSEs D-F 1-4 GCSEs A*-C 5+ GCSEs A*-C 1 A level2+ A levels City & Guilds Craft0.0700.0920.027-0.006 -0.040 (0.012)**(0.020)**(0.014)*(0.019)(0.054)(0.038) BTEC diploma0.0120.0620.0830.0390.059-0.067 (0.031)(0.037)(0.017)**(0.022)(0.050)(0.047) NVQ 2-0.083-0.025-0.039-0.091-0.158-0.193 (0.013)**(0.017)(0.012)**(0.015)**(0.040)**(0.028)** City & Guilds other0.032-0.002-0.005-0.049-0.160-0.153 (0.011)**(0.018)(0.012)(0.016)**(0.039)**(0.025)** NVQ1-0.085-0.074-0.092-0.148-0.059-0.150 (0.019)**(0.026)**(0.021)**(0.029)**(0.109)(0.042)** RSA lower0.009-0.053 -0.069-0.097-0.170 (0.023)(0.033)(0.018)**(0.022)**(0.048)*(0.026)** other0.0870.0160.0170.023 0.041 (0.005)**(0.009)(0.006)**(0.007)**(0.015)(0.006)** The Returns to Vocational Qualifications – All Full-Time Male Employees, by Highest School Qualification, 1996-2002

13 Estimating Age Earnings Profiles 1. Assume the wage differential is constant at all ages. 2. With a single cross-section, interact age with qualifications, to determine how differential varies - but cohort effects with age effects. 3. Use cohort data set to isolate pure age effect - but will be based on education received 50 years ago 4. Create pseudo cohorts in repeated cross section data, to follow one cohort for a number of years, while still looking at recent attainment for young people.

14 Estimating Age Earning Profiles – Pseudo Cohorts 1234567 199621-2526-3031-3536-4041-4546-5051-55 199722-2627-3132-3637-4142-4647-5152-56 199823-2728-3233-3738-4243-4748-5253-57 199924-2829-3334-3839-4344-4849-5354-58 200025-2930-3435-3940-4445-4950-5455-59 200126-3031-3536-4041-4546-5051-5556-60 200227-3132-3637-4142-4647-5152-5657-61

15

16

17

18

19 TABLE 4 Age and cohort effects in estimated returns Male degreeFemale degreeMale GCSEMale vocational level 3 age0.133 (0.041)*0.042 (0.011)*0.002 (0.007)0.008 (0.030) age 2 /100-0.304 (0.105)*-0.054 (0.014)*-0.005 (0.009)-0.012 (0.077) age 3 / 1000.002 (0.001)*-0.000 (0.001) cohort 2-0.052 (0.026)0.005 (0.025)0.065 (0.019)*0.004 (0.019) cohort 3-0.049 (0.036)0.019 (0.036)0.077 (0.028)*0.017 (0.026) cohort 4-0.067 (0.046)0.003 (0.045)0.132 (0.035)*0.046 (0.034) cohort 5-0.086 (0.057)0.012 (0.052)0.144 (0.041)*0.084 (0.042) cohort 6-0.079 (0.065)0.038 (0.062)0.181 (0.047)*0.130 (0.048)* cohort 7-0.138 (0.072)0.170 (0.054)*0.180 (0.052)* Constant-1.617 (0.516)*-0.544 (0.194)*0.168(0.135)-0.033(0.378) Obs494249 R-squared0.600.660.790.37

20 Conclusion A lot of information in the LFS with which to estimate returns to a detailed list of qualifications. Pseudo cohort approach can be useful in estimating lifetime returns, but only for qualifications that are held by large numbers of people.

Download ppt "The Returns to Academic and Vocational Qualifications Steven McIntosh Department of Economics University of Sheffield."

Similar presentations

The Social Benefits of Higher Education

The Social Benefits of Higher Education
GASS™-2040 Gas Analysis Sampling Systems 2040-001.

GASS™-2040 Gas Analysis Sampling Systems
Evaluation of agricultural systems across time and spatial scales. An extended LCA approach. Amalia Zucaro, Silvio Viglia and Sergio Ulgiati.

Evaluation of agricultural systems across time and spatial scales. An extended LCA approach. Amalia Zucaro, Silvio Viglia and Sergio Ulgiati.
Classical Cryptography

Classical Cryptography
Childhood and adolescent precursors of adult labour force attachment: Influences of neighbourhood characteristics Piotr Wilk Psychiatry and Bechavioural.

Childhood and adolescent precursors of adult labour force attachment: Influences of neighbourhood characteristics Piotr Wilk Psychiatry and Bechavioural.
2 20 107 1 106 13 19 21 25 22/24 3 12 14 23 4 11 15 26 27 30 5 7 6 9 16 18 28 104 29 8/17 32/109 100 99 105 108 31 34 40/42 41 98 68 93 90/92 91 81 80.

/ /17 32/ / /
Reflection nurulquran.com.

Reflection nurulquran.com.
Acid – Base Titration.

Acid – Base Titration.
Workshop Non-technical innovation The new service economy and new horizons in a global world Luis Rubalcaba Professor of Economic Policy, University of.

Workshop Non-technical innovation The new service economy and new horizons in a global world Luis Rubalcaba Professor of Economic Policy, University of.
Labour quality and ICT capital skill complementarity: International comparisons Mary OMahony NIESR.

Labour quality and ICT capital skill complementarity: International comparisons Mary OMahony NIESR.
Input-Output Analysis in Current or Constant Prices: Does it Matter? Erik Dietzenbacher & Umed Temurshoev Faculty of Economic and Business University of.

Input-Output Analysis in Current or Constant Prices: Does it Matter? Erik Dietzenbacher & Umed Temurshoev Faculty of Economic and Business University of.
Plan.be Does Offshoring of Materials and Business Services Affect Employment? Evidence for a small open economy Bernhard Michel (FPB.

Plan.be Does Offshoring of Materials and Business Services Affect Employment? Evidence for a small open economy Bernhard Michel (FPB.
Albert Park, University of Michigan Sangui Wang, Chinese Academy of Agricultural Sciences Community-based Development and Poverty Alleviation An Evaluation.

Albert Park, University of Michigan Sangui Wang, Chinese Academy of Agricultural Sciences Community-based Development and Poverty Alleviation An Evaluation.
© ETSI All rights reserved

© ETSI All rights reserved
Heckle and Chide: Empowering matatu passengers to enforce better driving behavior in Kenya James Habyarimana Georgetown University and William Jack Georgetown.

Heckle and Chide: Empowering matatu passengers to enforce better driving behavior in Kenya James Habyarimana Georgetown University and William Jack Georgetown.
1 Nikolai Kiselev and Vera Rosenbush Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv Calibration Workshop Zurich, Switzerland,

1 Nikolai Kiselev and Vera Rosenbush Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv Calibration Workshop Zurich, Switzerland,
The latest products and tools provided by JMA Kenji KISHIMOTO National Typhoon Center JMA.

The latest products and tools provided by JMA Kenji KISHIMOTO National Typhoon Center JMA.
1 National Pollutant Discharge Elimination System Permit United States Steel Gary Works NPDES Permit IN0000281.

1 National Pollutant Discharge Elimination System Permit United States Steel Gary Works NPDES Permit IN
Summative Math Test Algebra (28%) Geometry (29%)

Summative Math Test Algebra (28%) Geometry (29%)
GT3 Overview The Globus Project Argonne National Laboratory USC Information Sciences Institute Copyright (C) 2003 University of Chicago and The University.

GT3 Overview The Globus Project Argonne National Laboratory USC Information Sciences Institute Copyright (C) 2003 University of Chicago and The University.

Similar presentations

Ads by Google