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IZA Journal of Labor & Development

Table 4 Multinomial logit results for urban sample – marginal effects

From: The costs of worker displacement in urban labor markets of China

 

Only demographic and ownership controls

All controls

 

Displaced

Quitters#

Stayers

Displaced

Quitters#

Stayers

Demographics

      

Male

-0.0775***

-0.0314***

0.109***

-0.0723***

-0.0228***

0.0951***

 

(0.00732)

(0.00788)

(0.00976)

(0.00704)

(0.00800)

(0.00942)

Married

-0.0336**

0.0802***

-0.0467***

-0.0304**

0.0921***

-0.0616***

 

(0.0153)

(0.0156)

(0.0162)

(0.0144)

(0.0157)

(0.0152)

Age

0.0115***

-0.00538***

-0.00613***

0.0108***

-0.00534***

-0.00547***

 

(0.000546)

(0.000529)

(0.000636)

(0.000523)

(0.000529)

(0.000615)

Years of education

-0.0229***

-0.00108

0.0239***

-0.0109***

0.00202

0.00885***

 

(0.00153)

(0.00142)

(0.00171)

(0.00158)

(0.00152)

(0.00174)

Ownership-type firm last job

Working in SOE in last job

0.146***

-0.146***

0.000392

0.137***

-0.130***

-0.00650

 

(0.0120)

(0.00448)

(0.0118)

(0.0113)

(0.00514)

(0.0110)

Industry

      

Construction

   

-0.0996***

0.0303

0.0694***

    

(0.0123)

(0.0185)

(0.0196)

Low-level service

   

-0.153***

-0.00408

0.157***

    

(0.00743)

(0.0131)

(0.0139)

Wholesale and retail trade

   

-0.0653***

0.0279*

0.0375**

    

(0.0127)

(0.0160)

(0.0181)

Hotel and catering services

   

-0.115***

0.0370

0.0775***

    

(0.0171)

(0.0245)

(0.0277)

High-level service

   

-0.173***

-0.0247**

0.198***

    

(0.00663)

(0.0116)

(0.0124)

Occupation

      

Professional technicians

   

0.0377

0.136***

-0.174***

    

(0.0300)

(0.0377)

(0.0259)

Clerk and relevant personnel

   

0.0369

0.114***

-0.151***

    

(0.0298)

(0.0372)

(0.0270)

Commercial and service personnel

   

0.107***

0.163***

-0.269***

    

(0.0343)

(0.0391)

(0.0214)

Manufacturing and relevant personnel

   

0.114***

0.124***

-0.239***

    

(0.0327)

(0.0379)

(0.0228)

Other practitioner (difficult to classify)

   

0.0601*

0.152***

-0.213***

    

(0.0349)

(0.0416)

(0.0272)

City

      

Shenzhen

   

0.0436

-0.0369*

-0.00671

    

(0.0313)

(0.0211)

(0.0301)

Dongguan

   

0.0515*

-0.0396**

-0.0119

    

(0.0284)

(0.0201)

(0.0281)

Zhengzhou

   

0.0498*

-0.144***

0.0947***

    

(0.0260)

(0.0140)

(0.0264)

Luoyang

   

0.0887***

-0.132***

0.0433

    

(0.0332)

(0.0216)

(0.0346)

Hefei

   

0.0152

-0.102***

0.0865***

    

(0.0242)

(0.0161)

(0.0255)

Bengbu

   

0.120***

-0.0976***

-0.0229

    

(0.0297)

(0.0191)

(0.0298)

Chongqing

   

-0.000614

-0.0804***

0.0810***

    

(0.0226)

(0.0156)

(0.0236)

Shanghai

   

0.0738***

0.113***

-0.187***

    

(0.0242)

(0.0235)

(0.0228)

Nanjing

   

-0.00453

-0.110***

0.115***

    

(0.0239)

(0.0155)

(0.0252)

Wuxi

   

0.0554**

-0.0344

-0.0210

    

(0.0281)

(0.0215)

(0.0286)

Hangzhou

   

0.0255

-0.0742***

0.0486*

    

(0.0240)

(0.0168)

(0.0249)

Ningbo

   

0.0405

-0.000688

-0.0398

    

(0.0288)

(0.0237)

(0.0294)

Wuhan

   

0.0785***

-0.108***

0.0298

    

(0.0247)

(0.0149)

(0.0245)

Chengdu

   

0.0675***

-0.0295*

-0.0380*

    

(0.0228)

(0.0168)

(0.0221)

Pseudo R2

0.1089

  

0.1853

  

Observations

5953

5953

5953

5943

5943

5943

  1. Notes: # Retirees and early retirees are excluded from the subsample of quitters.
  2. Default categories are: private or mixed firm for ownership-type of firm, manufacturing for industry, principals in governments, parties, enterprises and institutions for occupation, and Guangzhou for city.
  3. *Significant at 10%;**significant at 5%;***significant at 1%. Standard errors in parentheses.
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