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Table 6 DID analysis results-based on quantile regression estimations

From: Impact of minimum wage on gender wage gaps in urban China

 

1%

3%

6%

10%

30%

60%

90%

Estimation 1: 1990–2007

 Male

0.4422***

0.2035***

0.2128***

0.1682***

0.1222***

0.1111***

0.1051***

(0.11)

(0.05)

(0.02)

(0.02)

(0.01)

(0.01)

(0.01)

 2002

0.5500***

0.4569***

0.5691***

0.5613***

0.6611***

0.8523***

1.0342***

(0.17)

(0.05)

(0.04)

(0.03)

(0.02)

(0.01)

(0.02)

 The treatment group

−0.7978***

0.0713

−0.1811***

−0.1427***

−0.1868***

−0.2071***

−0.2191***

(0.23)

(0.10)

(0.05)

(0.04)

(0.02)

(0.02)

(0.02)

 Male*2002

0.0314

0.1528**

0.1699***

0.2398***

0.2270***

0.1502***

0.1279***

(0.22)

(0.07)

(0.05)

(0.03)

(0.02)

(0.02)

0.02

 Male*The treatment group

0.9070***

−0.0695

0.1269*

0.0933*

0.1007***

0.1074***

0.1466***

(0.32)

(0.14)

(0.07)

(0.05)

(0.03)

(0.03)

(0.03)

 2002*The treatment group

1.2952***

−0.0884

0.1387

0.1859**

0.2392***

0.1778***

0.0311

(0.49)

(0.16)

(0.11)

(0.08)

(0.05)

(0.04)

(0.05)

 DIDterm

−1.0092 +

0.3830*

0.0767

−0.0594

−0.1357**

−0.1329***

−0.1074*

(0.64)

(0.21)

(0.14)

(0.10)

(0.06)

(0.05)

(0.06)

Estimation 2: 1991–2007

 Male

0.3238**

0.1477***

0.1267***

0.0947***

0.1058***

0.1084***

0.1221***

(0.16)

(0.04)

(0.03)

(0.02)

(0.02)

(0.01)

(0.02)

 2007

0.3839**

0.4934***

0.5300***

0.5603***

0.6992***

0.8726***

1.0636***

(0.19)

(0.05)

(0.04)

(0.03)

(0.02)

(0.02)

(0.02)

 The treatment group

0.4178

0.0951

0.0212

−0.0655

−0.1340***

−0.1794***

−0.1497***

(0.35)

(0.09)

(0.06)

(0.05)

(0.03)

(0.03)

(0.04)

 Male*2007

0.1083

0.1845***

0.2462***

0.3133***

0.2370***

0.1620***

0.0891***

(0.25)

(0.06)

(0.05)

(0.03)

(0.02)

(0.02)

(0.03)

 Male*The treatment group

−0.2488

−0.0211

0.0474

0.0868

0.0848*

0.1194***

0.1394**

(0.47)

(0.12)

(0.09)

(0.06)

(0.05)

(0.04)

(0.06)

 2007*The treatment group

−0.0204

−0.1441

−0.0441

0.1129

0.1796***

0.1606***

−0.0536

(0.56)

(0.14)

(0.10)

(0.07)

(0.06)

(0.05)

(0.07)

 DIDterm

0.2135

0.3710**

0.1540

−0.0571

−0.1155

−0.1542**

−0.0654

(0.74)

(0.19)

(0.14)

(0.10)

(0.07)

(0.06)

(0.09)

Estimation 3: 1992–2007

 Male

0.2417

0.2588***

0.1727***

0.1212***

0.1189***

0.1166***

0.1169***

(0.16)

(0.04)

(0.03)

(0.02)

(0.01)

(0.01)

(0.02)

 2007

0.2376

0.5811***

0.4781***

0.4874***

0.6212***

0.8106***

1.0110***

(0.19)

(0.05)

(0.04)

(0.02)

(0.02)

(0.01)

(0.02)

 The treatment group

0.2146

−0.3440***

−0.0263

−0.0801*

−0.1489***

−0.1802***

−0.1702***

(0.34)

(0.08)

(0.06)

(0.04)

(0.03)

(0.03)

(0.04)

 Male*2007

0.2195

0.0831

0.2087***

0.2808***

0.2264***

0.1512***

0.1060***

(0.24)

(0.07)

(0.05)

(0.03)

(0.02)

(0.02)

(0.03)

 Male*The treatment group

−0.0364

0.3459***

0.0672

0.0678

0.0782*

0.1153***

0.1342***

(0.45)

(0.11)

(0.09)

(0.06)

(0.04)

(0.04)

(0.05)

 2007*The treatment group

0.1879

0.2933*

−0.0157

0.1319*

0.2049***

0.1544***

−0.0319

(0.55)

(0.16)

(0.10)

(0.07)

(0.05)

(0.04)

(0.06)

 DIDterm

0.0100

−0.0103

0.1452

−0.0351

−0.1187*

−0.1429**

−0.0684

(0.72)

(0.21)

(0.14)

(0.09)

(0.07)

(0.06)

(0.08)

  1. Note:
  2. l. The other variables such as education, experience years,han race,married are also estimated
  3. 2. SE values are showed in ( )
  4. 3. +, *, **, *** statistically significant in 15%, 10%, 5%, 1% levels
  5. Source: Calculated using CHIP1995, CHIP2002, CHIP2007