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Table 2 Statistical descriptions

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

  1995 2002 2007
  Male Female F-M Male Female F-M Male Female F-M
Monthly wage 536 462 86.2% 1045 852 81.5% 1722 1271 73.8%
Education
 Elementary school or less 3.6% 5.6% 1.9% 2.2% 2.5% 0.4% 2.2% 2.2% 0.0%
 Junior high school 28.1% 32.7% 4.6% 24.3% 21.7% −2.7% 20.4% 17.0% −3.4%
 Senior high school 38.9% 44.2% 5.3% 37.7% 45.1% 7.4% 35.3% 40.4% 5.1%
 College 18.7% 12.5% −6.2% 23.0% 23.0% 0.0% 24.5% 27.7% 3.2%
 University 10.7% 5.1% −5.6% 12.8% 7.7% −5.1% 17.6% 12.7% −5.0%
Years of experience 28 27 −2 30 27 −3 31 28 −3
Han 95.4% 95.3% 0.0 96.0% 95.9% −0.1% 97.4% 96.9% −0.5%
Married 87.1% 87.9% 0.8% 89.1% 86.6% −2.5% 88.4% 86.4% −2.0%
Ownership
 SOE 86.2% 76.9% −9.3% 70.0% 64.5% −5.5% 59.4% 49.7% −9.7%
 COE 12.0% 20.7% 8.7% 5.5% 9.0% 3.5% 5.1% 7.0% 1.9%
 Foreign/Private Firm 1.5% 1.7% 0.2% 23.4% 23.9% 0.5% 29.3% 30.3% 1.0%
 Others 0.2% 0.7% 0.5% 1.2% 2.6% 1.4% 6.2% 13.1% 6.8%
Occupation
 Manager 17.3% 6.3% −11.0% 19.8% 9.3% −10.5% 6.7% 2.8% −4.0%
 Engineer 19.5% 22.2% 2.6% 17.8% 23.8% 6.0% 33.3% 37.5% 4.2%
 Clerical staff 22.5% 23.4% 0.9% 20.4% 22.8% 2.4% 20.5% 19.1% −1.4%
 Manufacturingl worker 37.7% 41.4% 3.7% 32.6% 23.1% −9.4% 23.9% 11.7% −12.2%
 Others 2.9% 6.7% 3.8% 9.4% 21.0% 11.5% 15.6% 28.9% 13.3%
Industry
 Agriculture, forestry, fisheries 2.1% 1.3% −0.8% 1.3% 1.3% 0.0% 1.0% 0.7% −0.3%
 Manufacturing 43.3% 41.7% −1.6% 26.4% 23.3% −3.1% 22.5% 15.1% −7.4%
 Mining 1.2% 0.9% −0.3% 2.1% 0.8% −1.3% 1.5% 0.6% −1.0%
 Construction 3.3% 2.7% −0.6% 4.2% 2.2% −2.0% 4.1% 1.8% −2.3%
 Transportation/communication 5.9% 4.3% −1.6% 10.2% 5.1% −5.1% 13.6% 6.5% −7.1%
 Wholesale,retail and catering 12.1% 17.3% 5.2% 9.9% 15.4% 5.5% 11.1% 18.6% 7.5%
 Real estate 3.3% 4.0% 0.7% 6.0% 4.4% −1.6% 7.7% 5.3% −2.4%
 Health and Social Welfare 3.6% 5.8% 2.3% 4.0% 6.7% 2.7% 3.2% 5.6% 2.4%
 Education Arts and Culture 6.4% 8.0% 1.6% 8.4% 9.8% 1.3% 8.4% 10.8% 2.4%
 Technical Services 2.7% 2.1% −0.6% 9.3% 15.6% 6.4% 2.6% 1.6% −1.0%
 Financial Industry 1.8% 2.1% 0.3% 2.4% 3.0% 0.6% 2.9% 4.0% 1.1%
 Public administration and social organizations 13.6% 9.1% −4.5% 13.6% 10.2% −3.4% 15.1% 15.9% 0.8%
 Others 0.7% 0.5% −0.1% 2.1% 2.2% 0.1% 6.4% 13.5% 7.1%
Samples 5002 4629   5473 4398   8272 6703  
  1. Source: Calculated using CHIP1995, 2002 and 2007
  2. Notes:
  3. 1) the gender wage gaps = female wage mean values/male wage mean values
  4. 2) the gender gaps of another variables = female variable mean values-male variable mean values