Skip to main content

Table 4 Multinomial logit results for urban samplemarginal 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.