Skip to main content

Table 2 Effects of Non-Local Hukou on the probability of employer contact, linear probability models

From: Do employers prefer migrant workers? Evidence from a Chinese job board

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Non-Local Hukou (NLH)

0.0138*** (0.0029)

0.0124*** (0.0026)

0.0111*** (0.0026)

0.0098*** (0.0025)

0.0113*** (0.0024)

0.0081*** (0.0019)

0.0079*** (0.0019)

Education less than requested1

 

−0.0070 (0.0052)

−0.0104* (0.0058)

−0.0107* (0.0056)

−0.0096* (0.0056)

−0.0092*** (0.0027)

−0.0090*** (0.0026)

Education more than requested1

 

−0.0018 (0.0034)

0.0017 (0.0039)

0.0006 (0.0039)

−0.0001 (0.0039)

0.0009 (0.0017)

0.0011 (0.0017)

Age less than requested2

 

−0.0018 (0.0059)

−0.0027 (0.0060)

−0.0030 (0.0060)

−0.0005 (0.0054)

−0.0103*** (0.0033)

−0.0125*** (0.0033)

Age more than requested2

 

−0.0304*** (0.0090)

−0.0289*** (0.0090)

−0.0274*** (0.0086)

−0.0176** (0.0076)

−0.0228*** (0.0074)

−0.0279*** (0.0079)

Experience less than requested3

 

−0.0064 (0.0057)

−0.0068 (0.0057)

−0.0077 (0.0054)

−0.0106** (0.0053)

−0.0108*** (0.0025)

−0.0109*** (0.0025)

Experience more than requested3

 

0.0000 (0.0033)

0.0005 (0.0028)

−0.0001 (0.0027)

0.0005 (0.0026)

−0.0017 (0.0017)

−0.0017 (0.0017)

Sex differs from requested

 

−0.0120** (0.0052)

−0.0119** (0.0052)

−0.0092* (0.0049)

−0.0065 (0.0045)

−0.0063* (0.0034)

−0.0054* (0.0032)

Number of positions advertised (/100)

    

0.5598** (0.2309)

0.2842 (0.2106)

 

Number of applicants (/100)

    

−0.0141*** (0.0028)

−0.0097*** (0.0024)

 

Detailed CV controls

No

No

Yes

Yes

Yes

Yes

Yes

Occupation fixed effects

No

No

No

Yes

Yes

No

No

Occupation*Firm fixed effects

No

No

No

No

No

Yes

No

Ad fixed effects

No

No

No

No

No

No

Yes

Observations

221,135

221,135

221,135

221,135

221,135

221,135

221,135

R-squared

0.0002

0.0050

0.0053

0.0172

0.0278

0.2749

0.2981

  1. Education matching based on five ordered categories in the ad and resume: primary (6 years), junior middle (9 years), technical or high school (11–12 years), college (15 years), and university (16 years). Age matching variables refer to whether the applicant’s age is below, within, or above the requested age range. Experience matching variables refer to whether the applicant’s experience is below, 0–2 years above, or more than 3 years above the requested experience level. In addition to the covariates shown, columns 2–7 include the following: the job’s requested education level (5 categories), requested experience level (quadratic), requested age level (quadratic in midpoint of range), requested gender (male, female, not specified), advertised wage (quadratic in midpoint of bin; 8 bins). Also included are dummies for and whether the worker is female, whether a new graduate is requested, for whether the worker is a new graduate, for whether the worker’s new graduate status matches the employer’s request. We also control for whether technical school is specifically requested, whether the worker attended technical school, and the match between these. Indicators for missing age and wage information for either the ad or the worker are also included, where relevant. Columns 3–7 add controls for the following worker (CV) characteristics (these characteristics are not mentioned in job ads very often): the applicant’s Zhicheng rank (6 categories), whether the CV is in English, the number of schools attended, number of job experience spells, number of certifications reported, applicant height (interacted with applicant gender), an indicator for myopia (interacted with applicant gender), and marital status (interacted with applicant gender). Standard errors in parentheses are clustered by ad. ***p < 0.01, **p < 0.05, *p < 0.1
Back to article page