Gender Wage Gaps in Hong Kong

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Gender Wage Gaps in Hong Kong

• Junsen Zhang
• Department of Economics
• 2009.11.6

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Review on Gender Wage Gap Literature

• Two problems
• Gender wage gap on a year or between years?
• Considering gender differences in labor
  participation or not?
• Research of four categories
• A Gender wage gap on a specific year, not
  considering gender differences in labor
  participation (many)
• B Gender wage gap between years, not considering
  gender differences in labor participation (many)
• C Gender wage gap on a year, considering gender
  differences in labor participation (several)
• D Gender wage gap between years, considering
  gender differences in labor participation (so
  far, none)

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Examples

• Category A Oaxaca (1973), Liu et al. (2000).
• Category B Blau and Kahn (1997), Zhang et al.
  (2008).
• Category C Hunt (2002).
• The lower gender wage gap is not a good news for
  women. Many low-quality female workers are forced
  to quit labor market.

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What We Do?

• We do the job of category A but on the
  distributional level.
• We do the job of category B but on the
  distributional level.
• We do the job of category D on the mean level.

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Three Papers

• First paper is Gender Wage Gaps in Hong Kong in
  2006 Evidence from the Whole Distribution.
• Second paper is The Effect of Economic
  Restructuring from 1981 to 2006 on Gender Wage
  Gaps in Hong Kong.
• Third paper is Female Labor Participation and
  Gender Wage Gaps from 1991 to 2006 in Hong Kong.

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Paper I Facts
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Paper I Facts

• Figure 1 Gender Wage Gaps at Different
  Percentiles, 2006
• Gender wage gaps are wider at both the lower
  positions and the higher positions. glass
  ceiling and sticky floor both exist.
• This will be hidden at the mean level analysis.

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Paper I Method

• Machado and Mata (2005, Journal of Applied
  Econometrics).
• Step 1 run quantile regression for male sample
  and female sample respectively.
• Step 2 counterfactual analysis--- what will the
  distribution of female wages be like if they were
  paid according to male quantile regression
  coefficients.
• Step 3 counterfactual analysis--- what will the
  distribution of female wages be like if their
  characteristics (edu, exp., etc.) were the same
  with males.
• Step 4 separate coefficient effect and
  characteristics effect.

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Paper I Results

• At lower positions, the gap is mostly explained
  by coefficients.

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Paper I Conclusion Policy Implication

• According to Oaxaca (1973), the part explained by
  coefficients (prices) are regarded as
  discrimination.
• Gender wage gaps are wider at both the lower
  positions and the higher positions. However,
  female workers at the lower positions are more
  discriminated.
• Anti-discrimination effort should be more
  emphasized on females at the lower positions.

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Paper II Facts

• Figure 2 Change of Gender Wage Gap between 1981
  and 2006

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Paper II Method

• Machado and Mata (2005)
• It is useful to manage distributional analysis.
• Lam and Liu (2002)
• It is useful to manage between-year analysis.
• We combine them.

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Paper II Method

• Machado and Mata (2005)
• Already discussed in the first paper.
• Lam and Liu (2002, Journal of Labor Economics)
• M and f denote males and females t and t
  denote two years.
• and denote characteristics and
  coefficients.
• The first term on the right-hand is relative
  price effect and the second term is general price
  effect. The third term is the relative quantity
  effect and the fourth term is general quantity
  effect.

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Paper II Decomposition Results for the Lower
Positions
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Paper II Decomposition Results for the Higher
Positions
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• First, female workers at lower positions and
  higher positions of the wage distribution both
  benefit from economic restructuring.
• Second, female workers at higher positions
  benefit more from economic restructuring. At
  lower positions of the wage distribution,
  economic restructuring reduces gender wage gap by
  0.262 log wage points at higher positions,
  economic restructuring reduce gender wage gap by
  0.880 log wage points.
• Third, female workers at higher positions are
  greatly hindered by effects of the constant term,
  which is often regarded as effects of unobserved
  factors often attributed to discrimination.

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Paper II Policy Implication

• Women at the lower positions do not benefit more
  from economic restructuring.
• We need to give them extra help.

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Paper III Facts

• In Hong Kong, higher female labor participation
  is companied with lower gender wage gap.
• LPR 43.37(1991) , 46.46 (2006)
• Wage ratio (F/M) 0.73(1991), 0.81(2006).
• In other countries, lower female labor
  participation is companied with lower gender wage
  gap.
• East German.
• China Mainland.
• Explanation Low-quality women quit or
  participate in the labor market.
• Why is Hong Kongs story different?

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Paper III Method

• Simpler version of BFL(2002).
• Bourguignon, F., F. Ferreira and P. Leite,
  Beyond Oaxaca-Blinder Accounting for
  Differences in Household Income Distributions
  across Countries.
• Two kinds of counterfactual analyses
• Labor participation counterfactual analysis
• Wage counterfactual analysis.

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Paper III Labor Participation Counterfactual
Analysis

• Step 1 logit model for females of 2006 (t) to
  get labor participation equation
• Step 2 logit model for females of 1991 (t) to
  get labor participation equation
• Step 3 Counterfactual analysis
• If a female of 2006 has the same education as a
  female of 1991, will she participate in labor
  market?
• If a female of 2006 decides her action according
  to the education coefficient of 1991, will she
  participate in labor market?
• Then we can separate different effects on labor
  participation.

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Paper III Wage Counterfactual Analysis

• Four situations
• A present working status is employed, predicted
  is employed
• B present working status is employed, predicted
  is unemployed
• C present working status is unemployed,
  predicted is employed
• D present working status is unemployed,
  predicted is unemployed.
• Her wage will be
• A her actual wage
• B 0
• C predict her wage according to 2006 wage
  equation
• D 0.
• Then we can separate different effects on
  females wages and further on the gender wage gap
  too.

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Paper III Results
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• Education will help a woman to find a job more in
  2006 than 1991.
• Women with higher ages tend to find a job more
  easily in 2006 than in 1991.
• Marriages negative effect is less in 2006 than
  in 1991.

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• From Column 1, we can see four factors can
  explain higher female LPR in 2006.
• Higher education.
• Higher positive effect of education.
• Higher positive effect of age.
• Less negative effect of marriage.
• However, from Column 2, we can see only higher
  education can explain why higher female labor
  participation is companied with lower gender wage
  gap. This factor explains Hong Kongs different
  story. The other three factors show the same
  story with Germany and China mainland.

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Paper III Policy Implication

• Females higher education in Hong Kong is a major
  advantage. Because of this, Hong Kong need not
  worry about the contradiction of policies to
  encourage female labor market participation and
  policies to narrow gender wage gaps.

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• Thank You!