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Table 3 M ulti-level event history models of African immigration to Guangzhou

From: The causal mechanism of migration behaviors of African immigrants in Guangzhou: from the perspective of cumulative causation theory

Variables

Model 1

Model 2

Model 3

Model 4

Before 2008

After 2008

Before 2008

After 2008

Before 2008

After 2008

Before 2008

After 2008

Time variables

Length of time spent in China

0.136***

0.148***

0.1336***

0.146***

0.1309***

0.142***

0.147***

0.125***

Square of length of time in China

−0.00236***

−0.00300***

−0.000532***

−0.00295***

−0.000478***

−0.00293***

−0.00017***

−0.00251***

Cube of length of time in China

9.34e06***

1.23e05***

2.25e06***

1.21e05***

1.88e06***

1.20e05***

−7.03e06***

1.02e05***

Background variables

Age

−0.00188

0.00459

0.00157

0.0102

0.007

0.00989

−0.0263

0.0102

Gender (male = 1)

0.532

0.253

0.334

0.429

0.42

0.403

2.670**

0.469

General human capital

Education level

−0.0791

−0.117

−0.182

−0.0308

−0.193

−0.0705

0.0127

−0.0986

Conducted business before coming to China

−0.428

−0.157

−0.292

−0.247

−0.403

−0.324

−1.035*

−0.38

Economic-specific human capital

Come from big city (= 1)

0.646

−0.402

0.513

−0.329

0.53

−0.318

0.405

−0.283

Have house in sending country (= 1)

−0.422

−0.357

−0.463

−0.26

−0.511

−0.244

−0.792

−0.208

Have investment in sending country (= 1)

−0.939***

−0.397

−0.814**

−0.328

−0.906**

−0.246

−0.685***

−0.267

GDP per capita of sending country

−0.000769*

−0.00022

−0.000813*

−0.00025

−0.000797*

−0.000224

−0.000423**

−0.000337*

Migration-specific human capital

Chinese language level

  

0.00197

−0.139

0.00823

−0.144

0.464

−0.111

Number of countries visited before China

  

−0.169*

−0.257***

−0.167*

−0.226***

−0.277**

−0.150*

The number of cities been to before Guangzhou in China

  

0.213***

−0.098**

0.210**

−0.0724**

0.216**

−0.043**

Social capital at individual level

Whether family members have oversea working or living experience

    

0.448

−0.0765

0.0023

−0.208

Whether family members have working or living experience in China

    

0.039

−0.538**

0.0719*

−0.370**

The number of Cantonese you know in China

    

−0.00312

0.00167

−0.0014

0.00241

The number of compatriot you know in China

    

−0.000723

0.00732***

0.00251

0.00889***

The number of non-compatriot Africans you know in China

    

−0.000319

0.00741**

0.0945

0.659***

Have acquaintances help with the reception

    

0.317*

0.0579*

0.448**

0.252**

Social capital at the community level

The proportion of illegal Migrants among your compatriots

      

3.48**

1.062**

Are there many people from your homeland coming to China

      

0.327***

−0.600**

Whether immigration to China has improved the lives of people at your homeland or not

      

1.461***

0.0311

Number of Africans in the community you live

      

0.00406

0.00893**

Number of compatriot in the community you live

      

0.00351

0.440***

Constant

−2.350**

−4.90***

−2.885**

−4.20***

−2.884***

−4.85***

−3.641***

−4.001***

Random effects

Recruit group level

1.027***

1.371***

0.9623***

1.257***

0.9877***

1.318***

0.651***

1.248***

Individual residual

1.541***

1.446***

1.2445***

1.368***

1.050***

1.196***

0.949***

1.022***

Log likelihood

−265.48

−726.05

−243.99

−718.07

−242.72

−710.8

−211.87

−623.719

Observations (individual × month)

6,867

7,924

6,867

7,924

6,867

7,924

6,867

7,924

Number of groups

51

108

51

108

51

108

51

108

Number of observing sample

116

511

116

511

116

511

116

511

  1. ***p<0.01, **p<0.05, *p<0.1.