1 / 11

IP602 – Measuring discrimination

IP602 – Measuring discrimination. November 30. Source: Fortin and Schirle (2006). Source: Goldin (2006), US data. Source: Baker and Drolet (2009) “A New View of the Male/Female Pay Gap”. ‘Productive’ characteristics. Indicators or human capital Education levels / years of schooling

edolie
Download Presentation

IP602 – Measuring discrimination

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. IP602 – Measuring discrimination November 30

  2. Source: Fortin and Schirle (2006)

  3. Source: Goldin(2006), US data

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

  5. ‘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)

  6. Average wages • Among men, • Wagemi = am + bmXmi + ui • Average wages among men, given X are: • Wagem = am + bmXm • Among women, • Wagefi = 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

  7. Wages of men and women bm Higher average wages for men are due to more experience on average, higher pay with zero experience, and a higher return to their experience wagem bf wagef am af Xf Xm

  8. 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 )

  9. 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.

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

  11. 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.

More Related