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Table 4 Cross-classified multilevel model with cross-level interactions for individual monthly income (Log), CFPS2010

From: Regional segregation or industrial monopoly? Dual labor market segmentation and income inequality in China

  Male Urban resident Education Party member Occupational ISEI State/collective unit
(Model 4) (Model 5) (Model 6) (Model 7) (Model 8) (Model 9)
Main effect
 Main effect for each column variable .127 .650 .098* .068 −.002 .289
(.404) (.484) (.044) (.645) (.014) (.479)
 County GDP per capita .044*** .035* .052*** .033** .041* .036***
(.012) (.016) (.014) (.011) (.017) (.011)
 County average education .103* .154** .140* .111** .130* .126**
(.046) (.053) (.053) (.042) (.062) (.043)
 % of female employees −.702 .222 .776 .121 −1.115 −.115
(.539) (.450) (.600) (.320) (.732) (.341)
 % of employees with higher education .756† .298 −.629 .396 .987 .499
(.441) (.490) (.711) (.418) (.771) (.453)
 % of state-owned entities 1.048 .533 1.333 1.687 −4.599* −.093
(1.605) (1.612) (1.629) (1.597) (2.025) (1.644)
Cross-level interaction with region variable
 GDP per capita −.019* −.0001 −.002† .0004 −.0002 −.011
(.009) (.014) (.001) (.017) (.0003) (.010)
 Average education .014 −.044 −.003 .002 −.001 −.059
(.036) (.051) (.004) (.060) (.001) (.046)
Cross-level interaction with industry variable
 % of female employees .421 .013 −.085 −.335 .031† .895
(.587) (.526) (.060) (.813) (.018) (.639)
 % of employees with higher education −.656* .062 .081† −.062 −.011 −.458
(.314) (.335) (.042) (.409) (.011) (.386)
 % of state-owned entities 2.202*** 1.904*** .066* 1.582** .164*** 5.611***
(.251) (.278) (.030) (.508) (.030) (.884)
  1. Numbers in brackets are estimated standard errors. The corresponding sample sizes for individual, region, and industry are 14,698, 162, and 19, respectively. These models also control for the main effects of other variables shown in model 3 of Table 3
  2. p < .1; *p < .05; **p < .01; ***p < .001