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IZA Journal of Labor & Development

Table 3 Multinomial logit results for migrant 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

0.0144***

0.0783***

-0.0928***

0.0126***

0.0738***

-0.0864***

 

(0.00453)

(0.00884)

(0.00861)

(0.00462)

(0.00898)

(0.00863)

Married

-0.00446

0.0904***

-0.0860***

-0.00155

0.0915***

-0.0899***

 

(0.00509)

(0.0115)

(0.0113)

(0.00521)

(0.0113)

(0.0109)

Age

0.00100***

-0.00510***

0.00410***

0.00120***

-0.00398***

0.00278***

 

(0.000246)

(0.000574)

(0.000569)

(0.000252)

(0.000568)

(0.000558)

Years of education

-0.000748

-0.00473***

0.00548***

-0.000751

-0.00518***

0.00593***

 

(0.000811)

(0.00179)

(0.00177)

(0.000857)

(0.00182)

(0.00178)

Ownership-type firm last job

SOE

-0.00239

-0.0947***

0.0971***

-0.00241

-0.0749***

0.0773***

 

(0.00564)

(0.0127)

(0.0129)

(0.00569)

(0.0129)

(0.0129)

Industry

      

Construction

   

-0.0229***

0.0352**

-0.0124

    

(0.00386)

(0.0144)

(0.0143)

Low-level service

   

-0.0272***

-0.00363

0.0308

    

(0.00515)

(0.0190)

(0.0189)

Wholesale and retail trade

   

-0.0290***

-0.0450***

0.0740***

    

(0.00378)

(0.0160)

(0.0160)

Hotel and catering services

   

0.00114

0.0449***

-0.0460***

    

(0.00738)

(0.0159)

(0.0153)

High-level service

   

-0.0149**

-0.0223

0.0372*

    

(0.00729)

(0.0210)

(0.0208)

Occupation

      

Clerk and relevant personnel

   

0.0819***

0.0692***

-0.151***

    

(0.0214)

(0.0200)

(0.0135)

Commercial and service personnel

   

0.0270**

0.0634***

-0.0904***

    

(0.0130)

(0.0157)

(0.0132)

Manufacturing and relevant personnel

   

0.0723***

0.0524**

-0.125***

    

(0.0209)

(0.0210)

(0.0160)

City

      

Shenzhen

   

-0.00201

0.0132

-0.0112

    

(0.00849)

(0.0221)

(0.0220)

Dongguan

   

-0.0227***

0.0162

0.00653

    

(0.00702)

(0.0221)

(0.0221)

Zhengzhou

   

-0.00587

-0.0116

0.0175

    

(0.00889)

(0.0215)

(0.0215)

Luoyang

   

0.0252*

-0.132***

0.107***

    

(0.0143)

(0.0242)

(0.0250)

Hefei

   

-0.0251***

-0.173***

0.198***

    

(0.00653)

(0.0200)

(0.0205)

Bengbu

   

-0.0360***

-0.0939***

0.130***

    

(0.00580)

(0.0242)

(0.0245)

Chongqing

   

0.000241

-0.0604***

0.0601***

    

(0.00842)

(0.0193)

(0.0196)

Shanghai

   

-0.0280***

-0.185***

0.213***

    

(0.00565)

(0.0181)

(0.0186)

Nanjing

   

-0.0358***

-0.291***

0.327***

    

(0.00437)

(0.0157)

(0.0164)

Wuxi

   

-0.0341***

-0.382***

0.416***

    

(0.00549)

(0.0149)

(0.0159)

Hangzhou

   

-0.00813

0.0474**

-0.0393**

    

(0.00708)

(0.0184)

(0.0182)

Ningbo

   

0.0140

0.0891***

-0.103***

    

(0.0114)

(0.0239)

(0.0233)

Wuhan

   

-0.00610

-0.0663***

0.0724***

    

(0.00743)

(0.0186)

(0.0188)

Chengdu

   

-0.0176**

-0.00988

0.0275

    

(0.00713)

(0.0200)

(0.0200)

Pseudo R2

0.0113

  

0.0730

  

Observations

4388

4388

4388

4381

4381

4381

  1. Notes: Source: RUMIC data set wave 2009;
  2. # Retirees and early retirees are excluded from the subsample of quitters. 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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