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Table 4 Income effects of occupational interaction based on the precise difference model N = 2536

From: Occupational interactions and income level: a social capital study using the first-order difference method

Variable Least square method model First-order difference model
M1 M2 M3
Explanatory variable Monthly income of first job Monthly income of present job Monthly income difference
Internal interaction −.001 −.012 .008*
(.004) (.013) (.003)
Outward interaction .018** .033* .016*
(.004) (.011) (.005)
Seeking job by pulling strings .098*** .014 .034
(.017) (.051) (.036)
Male −.078** −.120**
(.017) (.032)
Age .003 .003 .029**
(.011) (.009) (.007)
Square of age/100 .020 −.017 .029*
(.026) (.014) (.010)
Education level .044*** .059*** .08***
(.004) (.008) (.01)
Party member 089 .133* .269**
(.058) (.046) (.061)
Frequency of job changes .006 .011
(.011) (.013)
State-owned unit −.453*** −.207*** −.178***
(.043) (.037) (.01)
Unit size/100 −.001 .005 .001
(.001) (.005) (.009)
Administrative staff .083* .187** .179***
(.029) (.036) (.032)
Category of employment (10 categories) Yes Yes No
Intercept .091 .789* .884**
(.164) (.247) (.197)
R square .398 .224 .107
Sample size 2536 2536 2536
  1. Note: (1) *p < 0.05, **p < 0.01, ***p < 0.001. (2) Values inside the parentheses are standard errors obtained by taking heteroskedasticity robustness and urban cluster robustness into account. (3) “Yes” means this variable is controlled for in the model. (4) Similar to Table 3, in a different mode, what an explanatory variable corresponds to is the change value. For the conciseness of the table, different numerical values of dummy variables such as unit nature, way of gaining entry to work and occupation, etc. are processed as continuous variables. In a logical sense, they do signify specific meanings. For example, variables for unit nature are −1, 0, and 1, and these represent variation between state-owned and privately owned sectors, which are invariant, and between privately owned and state-owned, respectively. Therefore, if seen as a continuous variable, the difference in the nature of the unit represents the degree of “becoming state-owned” in practice. In robustness analysis, original dummy variables are adopted to perform tests and highly consistent results are achieved