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IP602 – Measuring discrimination

IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

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Page 1: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

IP602 – Measuring discrimination

Page 2: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Source: Fortin and Schirle (2006)

Page 3: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Source: Goldin(2006), US data

Page 4: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Source: Baker and Drolet (2009) “A New View of the Male/Female Pay Gap”

Page 5: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

‘Productive’ characteristics

• Indicators or human capital– Education levels / years of schooling– General experience in the labour market– Job-specific training and experience (tenure)

• Industry and occupation categories• Union status, public or private sector

W = f(S, X, T, I, O, U, P)

Page 6: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Average wages

• Among men, – Wagem

i = am + bmXmi + ui

• Average wages among men, given X are:– Wagem = am + bmXm

• Among women, – Wagef

i = af + bfXfi + ui

• Average wages among women, given X are:– Wagef = af + bfXf

• 3 parts to the average wage – average level of experience, the return to experience, intercept

Page 7: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Wages of men and women

af

am

bm

bf

Xf Xm

wagef

wagem

Higher average wages for men are due to more experience on average, higher pay with zero experience, and a higher return to their experience

Page 8: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Oaxaca decomposition

• Simplified• Wagem– Wagef

= (am + bmXm)- (af + bfXf) = am + bmXm- af - bfXf + bmXf - bmXf

Rearrange:• Wagem– Wagef

= (am - af )+ (bm - bf )Xf + bm (Xm - Xf )

Page 9: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Explained vs. Discrimination

• Explained portion:= bm (Xm - Xf) / (Wagem– Wagef)

• Unexplained portion: = (am - af )+ (bm - bf )Xf / (Wagem– Wagef)

If we account for enough productive characteristics, we would describe the unexplained portion as being discrimination against women.

Page 10: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Explained vs. unexplained – US, 1998Source: table 7-1, Blau, Ferber and Winkler

Characteristics Percent explainedEducational attainment -6.7Labour force experience 10.5Race 2.4Occupational categories 27.4Industry category 21.9Union status 3.5Total explained 58.9%

Total unexplained 41.1%

Wage differential (%) 20.3%

Page 11: IP602 – Measuring discrimination. Source: Fortin and Schirle (2006)

Explained vs. Discrimination

• Restate the previous results:• Female – male wage ratio = 80%• unadjusted wage differential = 20%• 53% of the 20% is explained by differences in

productivity characteristics (11%)• productivity adjusted wage ratio = 91%• Ie. If comparing equally qualified men and

women, women’s wages are 91% of men’s.