Presentation on theme: "Changes in Wage Inequality Paul Gregg and Stephen Machin, Bristol UCL Dec 3-4 2004."— Presentation transcript:
Changes in Wage Inequality Paul Gregg and Stephen Machin, Bristol UCL Dec 3-4 2004
Issues Big shifts in the structure of wages in the UK since the late 1970s. In international context UK, US are countries with biggest changes in wage structure. Returns to formal Education/Skills and returns to other soft skills.
Subjects to be Covered Trends in wage inequality Wage Inequality and Intergenerational Mobility Shifts in relative demand Skill-biased technological change Demand for Low Skill Labour Returns to Other skills/traits Policy
Trends in Wage Inequality What to Look for The Tilt The Spike The Flat Bottom
Trends in Male Wage Inequality, UK Family Expenditure Survey
Trends in Male Wage Inequality, UK Family Expenditure Survey PercentilesRatios 10 th 20 th 30 th 40 th 50 th 60 th 70 th 80 th 90 th 90-1050-1090-50 Men 19753.894.765.395.946.477.107.838.8410.892.801.661.68 19803.924.945.666.327.037.828.679.8412.103.081.791.72 19853.995.146.036.807.638.559.6911.3714.143.541.911.85 19904.145.546.557.468.449.6111.0713.1516.433.972.041.95 19954.295.526.607.638.719.8611.2413.1816.543.862.031.90 20004.355.566.577.698.9010.3312.0714.2218.094.162.052.03 Women 19752.472.963.393.764.154.525.025.747.282.941.681.75 19802.663.243.563.874.254.685.236.097.872.961.601.85 19852.853.373.704.124.605.215.977.079.173.221.611.99 19903.153.764.214.765.4126.96.36.19911.413.621.722.11 19953.353.884.455.115.886.627.749.2611.943.571.762.03 20003.664.204.835.576.517.629.0610.8913.863.791.782.13
Longer Run Trends in Male Wage Inequality Year90-10 Wage RatioYear90-10 Wage Ratio 1886 2.0719792.19 1906 2.3419822.25 1938 2.0619882.45 1970 2.2119902.48 1976 2.0719972.61 Source: New Earnings Survey, British Labour Statistics
Wage Inequality and Intergenerational Mobility 1 Decompose Wage inequality into: Changing returns to education Inequality within education group - unmeasured education - other soft skills/traits
Wage Inequality and Intergenerational Mobility 2 Intergenerational link - Degree to which family background influences education (or soft skills etc) - The pay off to having that education level, skill or trait in later life Research present in previous conferences highlighted increasingly strong and causal role of family income on educational attainment
Changes in Educational Wage Differentials Percent Log(Weekly Wage) Differences (Base: No Educational Qualifications) 197519801985199019951998 Men Degree or higher54.247.554.962.867.171.7 Higher vocational39.331.639.042.029.533.5 Teaching and nursing 30.825.226.436.241.438.4 Intermediate188.8.131.523.123.623.8 Women Degree or higher70.364.166.078.381.779.4 Higher vocational59.145.452.361.367.161.5 Teaching and nursing 59.558.659.367.456.342.2 Intermediate19.419.125.732.129.033.1 Notes: Calculated from General Household Surveys. For 1975 through 1995, statistics are based on three pooled years with the central year reported in the Table. Derived from statistical regressions holding constant age and age squared.
Changes in Relative Demand and Supply Race between supply and demand. Key question for explaining rising wage inequality is why has the relative demand for more educated/skilled workers gone up? Supply responses – shift in intermediate levels with move to GCSE in 1989 knock- on to graduate expansion approx. 5 years later
Hypotheses About What Lies Behind the Relative Demand Shift Skill-biased technological change Increased international competition Decline in importance of labour market institutions
Skill-Biased Technological Change Basic idea: New technologies lead to higher productivity, but only some (more skilled) workers possess the necessary skills to operate them. Therefore employers raise demand, and wages, for highly skilled workers who are complements with the new technologies. Lower wages, or lay off, less skilled workers who do not possess the skilled to use the new technologies.
SBTC - Evidence Requires that skill demand shifts vary systematically with the adoption and introduction of new technologies. More indirect evidence looking at shifts in relative demand within and between firms and industries. More direct evidence looking at the relationship between changes in skill demand and observable measures of technology.
Longer Run Changes The 1970s, 1980s and 1990s are a case in point. In 1970s relative supply fast, slower in 1980s, then faster in the 1990s. Consistent with pattern of relative wage shifts.
Rising demand for the least skilled jobs Goos and Manning (2003) paper. SBTC matters for the top, but right at the bottom of the skill spectrum there is increasing demand for the lowest skilled jobs. Polarisation between top, middle and bottom
Low Skilled only Benefit in Tightest Labour Markets High Employment Areas Middle Employment Areas Low Employment Areas 19932002 % point change 19932002% point change 19932002% point change Area Employment Rate 76.681.1 +3.5 70.973.5+3.6 64.670.3+5.7 Men Low quals. 73.979.5+5.6 61.6 62.4+0.8 52.851.6-1.2 Low quals. 25-49 79.684.9+4.7 69.870.6+0.8 58.953.5-5.4 Low quals. Social housing 57.665.0+7.4 38.735.7-3.0 32.225.3-6.9 Women Low quals 59.164.8+5.7 52.450.8-1.6 46.150.3+4.2 Low quals. 25-49 61.864.5+2.2 55.753.7-2.0 47.850.2+2.4 Low quals. Social housing 41.745.5+3.8 32.029.1-2.9 29.832.9+3.1
Changes at the Top End of the Wage Distribution There are decade differences in the evolution of wage inequality. The 1980s was clearly the decade of rapid changes, at all points of the wage distribution In the 1990s the distribution widened out, but the action is at the top.
Returns to Other Skills/Traits Research has also highlighted growing intergenerational transmission not occurring through education Intergenerational link - Degree to which family background influences education (or soft skills etc) - The pay off to having that education level, skill or trait in later life
Evidence of positive returns to other skills/traits 1 Those related to cognitive ability - IQ - literacy and numeracy Soft skills/personality -Communication -Behavioural maladjustment -Machiavelli score
Evidence of positive returns to other skills/traits 1 Physical Attributes -Height (1cm = 0.5% on wages, more in LDC) -Physical beauty -Obesity Conclusion – Bowles Gintis and Osbourne JEL Wide range of personality and physical traits have been found to influence earnings, however, no one factor is very powerful.
Policy Summary Policy relevant area where: a) research need to establish the facts of top end, returns to other skills/traits b) amass body of evidence of what interventions change transmission of family background to education and other attainments c) assess potential to reduce returns to transmitted traits (scarring or investments) d) redistribution to both reduce penalties and reduce transmission in next generation