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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.