employment discrimination & wage discrimination against migrating peasants in urban labor market...
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Employment Discrimination & Wage Discrimination against Migrating Peasants in Urban Labor Market
of China: A Decomposition Method
Zhang Yuan
China Center for Economic Studies, Fudan University
Yiu por Chen
City University of Hong Kong
Structure of This Paper:
1. Institutional Background and Research Motivation
2. Literature Review
3. A New Decomposition Method
4. Data Source and Application of the New Method
5. Conclusion and Policy Implication
1. Background and Motivation
Background: Hukou (household registration) System
Giving priority to heavy industries → Urban biased → Hukou
“Vacate the Cage and Change the Bird”
268 million migrating peasants in 2013 (NBS of China)
Motivation:
A. Urban labor market segregated.
employment discrimination, or wage discrimination?
B. Urban labors are over-paid, and migrating peasants are under-paid
Which part is more important?
C. Wage differential decomposition sheds very little light on the determinants of discrimination against migrating peasants in urban China.
Questions:
Becker(1957), Arrow(1973), Dickens and Kevin(1985), Cotton(1988)
Minorities suffer unfair treatment on both employment and wages only because of different gender or racial. We call them employment discrimination, and wage discrimination.
Minorities are paid less than their marginal product, while majorities are paid more than their marginal product. We call them under-paid, or over-paid, respectively.
A. To what extent that total discrimination index is attributable to employment discrimination or wage discrimination?
B. To what extent that total discrimination index is attributable to over-paid index or under-paid index?
C. What are the trends of them over time in urban China?
2. Literature Review
A. Segregated labor market
Doeringer and Piore(1971):
Dual labor market (primary and secondary labor market)
Two-tier labor market in urban China:
Meng and Miller(1995); Wang and Zuo (1999); Knight et al. (1999); Meng(2000); Meng and Zhang(2001)
B. Migrating peasants have less opportunities to get jobs in the formal sectors, and even in the same sector, other things being equal, migrating peasants are paid less than their counter parts in urban labor market
Meng and Miller (1995); Knight et al. (1999); Meng (2000); Meng and Zhang (2001); Yang and Chen (2000); Cai et al. (2000; 2003); Dong and Bowles (2002); Wang (2003; 2005); Yan (2006; 2007); Li and Li (2008); Démurger et al. (2009); Zhang et al. (2013).
In the segmented urban labor market of China, urban labors are over-paid, and migrating peasants are under-paid.
Knight et al. (1999); Meng (2000); Meng and Zhang (2001).
C. Decomposing wage-differentials between migrating peasants and urban labors, proposed by Blinder-Oaxaca-Cotton, Brown et al..
Blinder (1973) defines D=C+U as a measure of that portion of the total differential attributable to discrimination.
Brown et al. (1980) Decomposition
Discrimination= I+WD
Using Brown et al. (1980) decomposition method, Meng and Zhang (2001), finds that a significant difference in occupational attainment and wages exists between rural migrants and urban residents. Most of the difference cannot be explained by productivity-related differences between the two groups, implying that urban residents are favorably treated while their migrant counterparts are discriminated against.
Employing a similar decomposition, Démurger et al. (2009) finds that, the impact of sector allocation on earnings differences between migrating peasants and urban labors is neither strong nor robust. And also, they find a stronger, but only partly robust within sector earnings discrimination effect between urban residents and rural migrants.
Using Oaxaca (1973) and Brown et al. (1980) decomposition method, Wang (2003; 2005) finds that more than 43 per cent of wage differentials is attributable to discrimination against migrating peasants and other un-observables.
Employing Blinder-Oaxaca-Cotton method, Xie and Yao (2006) arrives at similar conclusions.
Blinder-Oaxaca-Cotton-Brown-Neumark decomposition,
First, the discrimination component from these methods is not an accurate measure of discrimination (Meng and Zhang, 2001; Liu et al. 2004; Jann, 2008;).
Second, these methods reveal nothing about the role of job discrimination and wage discrimination, or the role of under-pay and over-pay in the total discrimination index.
Third, these methods cannot be applied to a segregated labor market, because the wage equations in two sub-labor markets are different.
Zhiming Cheng, Fei Guo, Graeme Hugo, Xin Yuan, 2013, “Employment and Wage Discrimination in the Chinese Cities: A Comparative Study of Migrants and Locals,” Habitat International, 39, pp.246-255.
Liu Pak-Wai, Junsen Zhang, Shu-Chuen Chong, 2005, “Occupational Segregation and Wage Differentials between Natives and Immigrants: Evidence from Hong Kong,” Journal of Development Economics, Vol. 73, pp. 395-413.
3. A New Decomposition Method
Measure of discrimination (Oaxaca,1973)
ofm
ofmfm
WW
WWWWD
)/(
)/(/
r
or
ou
u
W
W
W
WD *1
)(*)(1r
ro
u
ou
W
UnderpW
W
OverpWD
u: urban labors
r: rural migrants
overp: over_paid
underp: under_paid
o: no discrimination
ro
uro
u W
Underp
W
Overp
W
Underp
W
OverpD *
Two-tier labor market without discrimination
Two-tier labor market with discrimination
Assumption: labor supply and individual characteristics are fixed (Neumark, 1988; Butler, 1982)
Gross over-pay for U1+U2 urban labors
over-pay attributable to wage discrimination;
over-pay attributable to employment discrimination;
Gross under-pay suffered by R1+R2 rural migrants
under-pay attributable to wage discrimination; under-pay attributable to employment discrimination;
)9()()(
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2,1,2,1,2,1,2,21,1
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or
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WRWRUWRUWRUnderp
1,12,2 rr URUR
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Take averages and substitute them into the measure equation,
)__
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(
____2,1
rro
uo
u
rro
uo
u
W
punderWage
W
punderEmp
W
poverWage
W
poverEmp
W
punderWage
W
punderEmp
W
poverWage
W
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)/()(_ 212,21,1 UUOUOUpoverWage uu
)/()(_ 212,1, UUWWpoverEmp ou
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)/()(_ 212,21,1 RRURURpunderWage rr
)/()(_ 212,1, RRWWpunderEmp or
or
)/()( 212,21,1 RRWRWRW rrr
)/(])()[( 212,21,1 UUWUWUW ou
ou
ou
4. Data Source and Application
China Household Income Project, 2002-2007
Urban samples+Migrating peasants
Market 1 Market 2Ownership SOEs or state controlling enterprises othersSector Supply of electronic, gas, and water;
Transportation, warehouse, postal service;Finance and insurance;Real estate;Culture, education, health, sports, broadcast television;State organs;
(Most of public sectors)
others
Definition of Two-tier Labor Market
2002 2007Market 1 Market 2 Market 1 Market 2
Migrating peasants 21.64% 78.36% 33.55% 66.45%Urban labors 78.31% 21.69% 75.10% 24.90%
2002 2007Market 1 Market 2 Market 1 Market 2
Migrating peasants 3.11 2.35 6.63 5.33Urban labors 6.33 4.37 13.61 9.29
Employment distribution in two-tier labor market
Mean hour wage in two-tier labor market (RMB Yuan)
Oaxaca(1973)
A. Estimate the wage function using male samples, substitute characters of female into the wage function;
B. Estimate the wage function using female samples, substitute characters of male into the wage function;
Index Number Problem
Cotton (1988); Reimers (1983); Neumark (1988)
C. Estimate the wage function using male and female samples, respectively, weight these two functions with their shares in the labor market, and get the weighted average wage function, then, substitute their characters into this weighted average wage function.
How to deduce the wage level without discrimination?
How to deduce the employment distribution without discrimination?
Urban labors Migrating peasants
Market 1 Market 2 Market 1 Market 2
Without discrimination 50 50 50 50
Probability 50% 50%
With discrimination 50+5 50-5 50-5 50+5
Probability 50%+5% 50%-5%
Gap of probability attributable to discrimination
55%-45%=10%
2121
21
21 RRUU
RR
UU
2121
21
21 RRUU
UU
RR
Urban labors Migrating peasants
Market 1 Market 2 Market 1 Market 2
Without discrimination 100 100 50 50
Probability 50% 50%
With discrimination 100+10 100-10 50-10 50+10
Probability 50%+5% 50%-10%
Gap of probability attributable to discrimination (β)
β=55%-40%=15%
A. Run Probit (or Logit) model using full sample, controlling a dummy variable for migrating peasants, and other characters.
The marginal effect of the dummy variable measures the probability gap attributable to discrimination, i.e. β, other things being equal.
B. Restore the probabilities of entering Market 1 without discrimination according the above equations.
C. Move Δ urban labors in Market 1 with the lowest probabilities into Market 2, move Δ rural migrants in Market 2 with the highest probabilities into Market 1.
2121
21,, RRUU
RRPP ir
oir
2121
21,, RRUU
UUPP iu
oiu
Determinants of Probability of Entering Market 12002 2007
Logit Probit Logit ProbitMigrant -1.650*** -1.002*** -1.174*** -0.723***
(0.062) (0.036) (0.061) (0.037)Age -0.089*** -0.049*** -0.006 -0.002
(0.024) (0.014) (0.019) (0.011)Age_sq 0.001*** 0.001*** 0.000 0.000
(0.000) (0.000) (0.000) (0.000)Male 0.355*** 0.201*** 0.069 0.039
(0.046) (0.026) (0.049) (0.029)Married 0.135 0.068 -0.063 -0.036
(0.099) (0.057) (0.082) (0.049)Education 0.151*** 0.086*** 0.115*** 0.069***
(0.008) (0.005) (0.009) (0.005)Experience 0.113*** 0.068*** 0.028*** 0.020***
(0.009) (0.005) (0.010) (0.006)Experience_sq -0.001*** -0.001*** 0.001*** 0.000**
(0.000) (0.000) (0.000) (0.000)Provincial Dummy YES YES YES YES
ObservationPseudo R2
129450.2740
129450.2733
90420.1671
90420.1669
2002 2007
Migrating peasants +0.24492 +0.16857
Urban labors -0.07930 -0.08392
Δ 775 515
Wage equation in two-tier labor market - 2002Market 1 Market 2
Migrating peasants Urban labors Migrating peasants Urban laborsMale 0.891*** 0.423*** 0.618*** 0.395**
(0.200) (0.135) (0.202) (0.172)Age 0.208*** 0.248*** -0.110 0.287***
(0.080) (0.081) (0.097) (0.088)Age_sq -0.002** -0.002** 0.002 -0.003***
(0.001) (0.001) (0.001) (0.001)Married -0.416 0.557* 0.453 -0.263
(0.345) (0.325) (0.441) (0.373)Schooling year 0.092** 0.305*** 0.143*** 0.194***
(0.040) (0.026) (0.043) (0.031)Experience -0.027 0.037 0.106 0.047
(0.055) (0.032) (0.083) (0.035)Experience_sq 0.002 -0.001 -0.002 -0.001
(0.003) (0.001) (0.006) (0.001)Constant -2.266 -4.724*** 8.985** -0.043
(2.088) (1.781) (3.517) (1.661)Industrial dummies YES YES YES YES
Ownership dummies YES YES YES YESProvincial dummies YES YES YES YES
ObservationAdjusted R2
14600.0897
68830.1899
17060.0848
28960.1815
Market 1 Market 2Migrating peasants Urban labors Migrating peasants Urban labors
Male 0.794*** 0.112 1.036*** 0.009(0.249) (0.456) (0.258) (1.090)
Age 0.339*** -0.080 0.210** 0.429(0.100) (0.195) (0.102) (0.428)
Age_sq -0.005*** 0.000 -0.003** -0.006(0.001) (0.002) (0.001) (0.005)
Married -0.194 1.373 0.203 1.766(0.347) (0.886) (0.369) (1.912)
Schooling year 0.315*** 0.141* 0.193*** 0.395**(0.053) (0.077) (0.062) (0.193)
Experience 0.272*** 0.299*** 0.358*** 0.432*(0.063) (0.072) (0.094) (0.223)
Experience_sq -0.010*** -0.005*** -0.017** -0.013*(0.003) (0.002) (0.007) (0.007)
Constant -2.752 8.226* 0.479 0.048(2.596) (4.324) (5.061) (9.430)
Industrial dummies YES YES YES YESOwnership dummies YES YES YES YESProvincial dummies YES YES YES YES
ObservationAdjusted R2
15280.1241
40070.1267
14710.1143
20160.0288
Wage equation in two-tier labor market - 2007
Urban labors Migrating peasantsNumber Hour wage Number Hour wage
2002Market 1 7658-775=6883 6.33-0.36=5.97 685+775=1460 3.11+0.27=3.38
Market 2 2121+775=2896 4.37-0.42=3.95 2481-775=1706 2.35+0.20=2.55
2007Market 1 4604-515=4089 13.61-1.68=11.93 1024+515=1539 6.63+2.77=9.40
Market 2 1527+515=2042 9.29-1.29=8.00 2028-515=1513 5.33+0.81=6.14
Two-tier labor market without discrimination
Total discrimination index and its components
%60.27
%56.1%04.26
%73.16%31.9%76.8%97.7%89.6%42.2
)51.2
22.0
51.2
20.0()
37.5
37.0
37.5
13.0(
51.2
22.0
51.2
20.0
37.5
37.0
37.5
13.020022,1
D
%4.59
%31.6%09.53
%10.35%99.17%48.25%53.9%88.14%11.3
)77.5
47.1
77.5
55.0()
62.10
58.1
62.10
33.0(
77.5
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77.5
55.0
62.10
58.1
62.10
33.020072,1
D
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punderWage
W
punderEmp
W
poverWage
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poverEmp
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punderWage
W
punderEmp
W
poverWage
W
poverEmpD
5. Conclusion and Policy Implication
A. Total discrimination index more than doubled from 2002 to 2007, which is mainly attributable to increasing of wage discrimination.
B. In 2002 and 2007, total discrimination index is mainly composed of wage discrimination, rather than employment discrimination.
C. In 2002 and 2007, total discrimination index is mainly composed of under-pay which is suffered by migrating peasants, rather than over-pay which is related to urban labors.
So,
Future anti-discrimination legislation should be directed more at promoting equal pay, and at eliminating the under-pay suffered by migrating peasants without urban Hukou.
