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Wage structure ( Borjas chapter 7. Section 7.5 not included .)

Wage structure ( Borjas chapter 7. Section 7.5 not included .). Shape of the earnings/wage distribution Measures of dispersion Geographical dispersion (country/region) Dispersion according to education/skills Age Gender & ethnicity which will be discussed after chapters 9 & 10)

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Wage structure ( Borjas chapter 7. Section 7.5 not included .)

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  1. Wagestructure(Borjas chapter 7. Section 7.5 not included.) • Shape of the earnings/wage distribution • Measures of dispersion • Geographical dispersion (country/region) • Dispersion according to education/skills • Age • Gender & ethnicity which will be discussed after chapters 9 & 10) • Family (marital status, children) • Sector, firm and industry • Long-term vs short term distribution • Intergenerational mmm • Change over time (US, Sweden)

  2. Distribution of wages, earnings and income tend to be log-normal. The logarithm of the wage is normally distributed. The distribution of the wage is skewed to to the right (has a long ”tail” on the right side.) Dispersion has two elements: Between-group-difference Within-group-difference The level and form of wage dispersion depends on both market factors and institutional factors.

  3. Data with lognormal distribution and distribution of the log of the data(borrowed from statisticscompendium for medical students,,,)

  4. Wage distribution in the US

  5. Full-time wages in Sweden 2003, distribution, arithmetic mean (”medellön”) and median for women (- - -) and men (----).Source: Statistics Sweden, Lönestatistisk årsbok 2003

  6. Measures of inequality • Overall measures • (Coefficient of) variation (std. dev./mean) • Gini coefficient • Decile ratios • Gini koefficient is derived from the LORENZ CURVE • The Lorenz curve is based on the distribution over percentiles • n percent of the population have income/wages below the nth percentile • Percentiles, deciles, quartiles, quintiles…

  7. The Lorenz curve (for wages) • List all individuals in order of increasing wage. • Arrange them in this order along the x-axis. • On the y-axis, mark the cumulative percentage of all wages that accrue to the people”to the left” of this person.

  8. Example: • Assume that there are 10 wage earners:

  9. Area I/(Area I+Area II) = 2*Area I = the GINI COEFFICIENT Area I+Area II = 0.5 Area I Area II

  10. Excercise: Calculate the Gini coefficient 65 65 65 43 25 10

  11. Different distributions can have the same Gini-coefficient. • Two alternative measures: • The share of the highest 10 percent/the share of the lowest 10 percent • P90/P10 (Why are these two unequal? Which is largest?) • To see whether there is most inequality at the upper or lower end of the distribution one can use: • P90/P50 and P50/P10 (or P75/P50 and P50/P25) • The shares of the lowest and highest 10 percent.

  12. Lorenz curve for earnings Sweden 2008 in age range 20-64 Source: SCB

  13. Earnings 2008

  14. Gini-coefficents for disposableincome and factorincome per consumptionunit and shareof the top 10 percent.

  15. Basic facts 1Cross country comparison • In the beginning of industrialisation, wage and income disparities tend to get very large. • As industrialisation progresses, historically, inequality has decreased. • Richer countries tend to have smaller income inequality than poorer countries. • But there are large differences between OECD countries and larges differences between developing countries.

  16. Earnings dispersion, some OECD countries 2010 Source: OECD, Employment Outlook 2010

  17. Gini-coefficients (in %) 2010 equivaliseddisposableincome in EU and at-work (fulltime) relative poverty

  18. Total income from employment and business 2009Women and men aged 20- Source: Statistics Sweden,

  19. In the public sector compared to the private: • Less dispersion • Smaller gender differentials • Earlier higher wages for both men and women, both unadjusted and adjusted for education (Level of Living Surveys 1968-1991.) • Now lower average wages than private sector (LLS 2001) • The difference is largest in the highest deciles.

  20. Wages and dispersion in public (- - - ) and private (----) sector 2003

  21. Education and wages (seealsonotestochapter 6) University Sec./ /secondary prim. 1968 1.51 1.31 1974 1.36 1.08 1981 1.20 1.08 1991 1.16 1.15 2001 1.29 1.07 Adjusted for age and gender Source: LNU (from Björklund et. al.)

  22. To summarise: • Returns to secondary education • dropped sharply from 1968 to 1974 • have varied a little but no distinct trend afterwards • Returns to university education: • Gradual (and large) decline from 1968 to some point in the 1980s • From mid-1980s new increase but not to the levels of the 1960s

  23. Another way of measuring: • The returns per year of schooling estimated in wage equations (controlling for experience, industry, sector etc.) each year 1993-2002 • There is a steady increase, from 5 to 6 percentage points for men, 3 ½ - 4 ½ for women. • For education which is at the right level for the job returns are somewhat higher. Source: Johansson and Katz (2007)

  24. In the US (see Borjas fig. 7-5) the wage differential between college and high school graduates decreased in the 1970s but increased from about 50 percent to 90 percent from 1980 to 2000. • The wage differential between those with and without full high school education also increased to but less dramatically.

  25. Does this agree with economictheory? • Demand: We think that there has been a general increase in demand for highly educated workers but it is hard to measure. • Supply: There was a large increase of workers with long university schooling in the 1970s and first half of the 1980s but slower afterwards. The share with 3-yr sec. school increased through the whole period.

  26. Stylised model of market for university educated workers: S1 • Shift in supply dominates. w ,E  • Shift in demand dominates, w , E  S2 S3 D3 D2 D1

  27. Supply of university/college educated increased through the whole period. Agrees with decrease in returns to schooling in the earlier period but not with increase afterwards. • There must have been a shift in demand with effects that dominated over those of increased supply. • (to be continued below)

  28. Trends in dispersion 1980-2000 Earnings dispersion according to the LLS

  29. Both Sweden and the US saw big increases in dispersion over the 1980s and 1990s. • Larger increase in the US and from a higher level. • In both countries dispersion increased in both ends of the distribution but more in the upper part. • Both differentials between skill groups (returns to schooling and to experience) and within them (residual distribution) increased.

  30. The sharp increase in earnings inequality was not a uniform international development. • Big increases also in UK (at least to the mid-1990s), Australia, New Zealand and others. • BUT • Very little change or even decreases over either the 80s, 90s or both in Germany, France, Japan, Norway and other countries.

  31. Why the changes in dispersion? • Decreasing returns to education shifted to increasing. • In Sweden the decrease in gender differentials slowed down or stopped. • Increasing relative wages for youth in the 1970s and 1980s, falling in the1990s. (Can be due to selection effects – fewer young people work and more of them have part-time ”extra” jobs.)

  32. Could there be a “market explanation” of the increased skill differentials? • That requires a strong increase in demand. Candidates: • Increased international specialisation. • Through trade – imports have higher content of low skilled labour and exports lower • Through capital movements – production which requires a lot of unskilled labour moves where it is cheapest. (But today highly skilled work, like programming is moved too.) • Technological change biased towards skilled labour – the IT revolution. But these affected all OECD countries – yet the increase in dispersion wasn’t uniform.

  33. Institutional reasons • Sweden: • 1950s-70s – a strong union movement which tried to limit inequality, particularly among blue-collar workers (the solidaristic wage policy). • Highly centralised bargaining and agreements until 1983. After that more decentralised and individualised wage bargaining. Agrees in time with increase in dispersion. • Research shows connection between egalitarian ambitions of unions and wage compression, particularly for blue-collar workers. • There were cut-backs in the public sector and public sector wages declined relative to those in the private sector. • US: • From the 1980s, both (many) employers tried to restrict unionisation and union influence and so did government policies in the Reagan period. • The minimum wage decreased substantially in real terms in the 1980s.

  34. The institutional changes have probably had more impact on the lower part of the wage distribution and demand shifts more on the upper. • A lot of research with sometimes conflicting results – and a lot more that remains to be done.

  35. Short- and long-term dispersion • Wages change over the workers life-time. • They increase with experience and according to human capital theory they start from the lowest level and increase fastest in job with educational content. • Dispersion of life-time earnings is smaller than dispersion in one particular year. • This has been shown with panel data in many countries but some country differences remain – the US wage distribution is particularly unequal both in the long- and short term.

  36. The intergenerationalcorrelation: • The children of high earners earn more than the children of low earners. • High earner parents make sure their children get a good education • But given education, there is still an effect. • Biological explanations • Social explanations (cultural and social capital)

  37. The elasticity of the son’s wage with respect to the father’s in US studies is often 0.3 – 0.4 • Comparable studies in Sweden and the US found an elasticity of 0.4 in the US, 0.25 in Sweden. (Jäntti & Björklund) • Public funding of education and periods of expansion of education tend to lower the intergenerational coefficient (increase social mobility).

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