Journal of Geographical Sciences >
Study on the synergy between intra-urban resident’s migration and job change in Beijing
*Corresponding author: Zhang Wenzhong, PhD and Professor, E-mail:zhangwz@igsnrr.ac.cn
Author: Yu Jianhui (1983-), PhD, specialized in residential space distribution and its evolution mechanism. E-mail:yujh@igsnrr.ac.cn
Received date: 2014-01-14
Accepted date: 2015-03-05
Online published: 2015-07-17
Supported by
National Natural Science Foundation of China, No.41201169;No.41230632
Key Program of Chinese Academy of Sciences, No.KZZD-EW-06
National Science and Technology Support Program, No.2012BAJ- 15B02
Copyright
People’s decisions of residential mobility in housing market and decisions of job change in labor market play an essential role in the formation and dynamics of urban spatial structure. This paper investigates the relationship between residential relocation and job change and its heterogeneity using a large-scale survey of residential living satisfaction and preferences in Beijing. Several conclusions are drawn as follows: 1) People’s decisions of residential mobility are significantly positively correlated with their decisions of job change, indicating that these two-dimensional decisions are in fact a correlated decision process rather than two independent decision processes. 2) There is heterogeneity in the correlated decisions of residential mobility and job change. More specifically, the interrelationship between the decisions of residential mobility and job change among people without Beijing hukou, renters and single-worker households is more intensive than people with Beijing hukou, homeowners and multi-worker households. In addition, there is heterogeneity in the determinants of residential relocation and job change between groups with different types of housing tenure, household registration status and family employment structure. 3) For renters, commuting time can significantly increase the probability of residential relocation, which indicates that residents of different socioeconomic attributes have very different responses to commuting time costs.
YU Jianhui , DONG Guanpeng , ZHANG Wenzhong , LI Jiaming . Study on the synergy between intra-urban resident’s migration and job change in Beijing[J]. Journal of Geographical Sciences, 2015 , 25(8) : 978 -990 . DOI: 10.1007/s11442-015-1214-7
Figure 1 The distribution of samples in Beijing |
Table 1 Statistical descriptions of the data and variables |
Variables | Percentage/Mean |
---|---|
Residential move | 20.73% |
Job change | 10.90% |
Age | |
30-40 | 34.43% |
40-50 | 22.37% |
50-60 | 5.64% |
Family income (104 yuan/month) | |
0.3-0.5 | 26.42% |
0.5-1 | 41.37% |
1-1.5 | 15.62% |
> 1.5 | 6.08% |
Education | |
High school | 22.76% |
College | 65.04% |
Postgraduate | 8.44% |
Occupation | |
Skill intensive | 36.16% |
Labor intensive | 36.31% |
Freelance | 8.10% |
Household employment structure | |
Multiworkers | 77.48% |
Household registration | |
Non-migrator | 90.12% |
Housing tenure | |
Buy | 77.48% |
Commuting time (min) | 35.02 |
Table 2 Estimate results of bivariate probit models among all households, owners and renters |
Variables | All samples (Model 1) | Owners (Model 2) | Renters (Model 3) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Residential move | Job change | Residential move | Job change | Residential move | Job change | |||||||
β | Std.error | β | Std.error | β | Std.error | β | Std.error | β | Std.error | β | Std.error | |
Constant | 0.5378* | 0.3246 | -0.7314 | 0.2924 | -0.1768 | 0.4738 | -1.3496 | 0.4752 | 0.3768 | 0.5475 | -0.7175* | 0.4386 |
Age | ||||||||||||
30-40 | -0.0521 | 0.0756 | -0.0922 | 0.0877 | 0.0811 | 0.0929 | -0.1037 | 0.1096 | -0.3169** | 0.1371 | -0.0881 | 0.1522 |
40-50 | -0.3365*** | 0.0959 | -0.2838** | 0.1132 | -0.2406** | 0.1110 | -0.2258* | 0.1289 | -0.6201*** | 0.2154 | -0.5957** | 0.2700 |
50-60 | -0.3814** | 0.1721 | -0.0852 | 0.1858 | -0.2232 | 0.1926 | -0.2146 | 0.2252 | -0.9816** | 0.4165 | 0.2253 | 0.3716 |
Family income (104 yuan/month) | ||||||||||||
0.3-0.5 | -0.0934 | 0.1229 | 0.1027 | 0.1399 | -0.1078 | 0.1733 | 0.1872 | 0.2072 | 0.0121 | 0.1862 | 0.1036 | 0.2007 |
0.5-1 | -0.0553 | 0.1221 | -0.0304 | 0.1419 | 0.0005 | 0.1712 | 0.0698 | 0.2096 | -0.1075 | 0.1866 | -0.0851 | 0.2037 |
1-1.5 | -0.0355 | 0.1421 | 0.1136 | 0.1630 | 0.1225 | 0.1886 | 0.3830* | 0.2243 | -0.4477* | 0.2513 | -0.7118** | 0.3155 |
> 1.5 | 0.2729 | 0.1724 | -0.0168 | 0.2104 | 0.3423 | 0.2114 | 0.0413 | 0.2703 | 0.1394 | 0.4408 | 0.2056 | 0.4427 |
Education | ||||||||||||
High school | 0.2608 | 0.1993 | 0.0796 | 0.2161 | 0.3661 | 0.3138 | 0.3258 | 0.3479 | 0.0842 | 0.2884 | -0.2539 | 0.3027 |
College | 0.3836** | 0.1953 | 0.2250 | 0.2117 | 0.5029 | 0.3101 | 0.4149 | 0.3449 | 0.1965 | 0.2801 | -0.0046 | 0.2923 |
Postgraduate | 0.3689* | 0.2251 | 0.2384 | 0.2510 | 0.4692 | 0.3340 | 0.3448 | 0.3786 | 0.2539 | 0.3907 | 0.2174 | 0.4192 |
Occupation | ||||||||||||
Skill intensive | -0.0975 | 0.0926 | 0.2025* | 0.1155 | -0.0851 | 0.1032 | 0.1675 | 0.1307 | -0.1116 | 0.2213 | 0.4028 | 0.2692 |
Labor intensive | -0.1457 | 0.0957 | 0.1663 | 0.1188 | -0.1825* | 0.1097 | 0.1229 | 0.1374 | -0.0134 | 0.2177 | 0.3992 | 0.2659 |
Freelance | -0.3010** | 0.1431 | 0.2663* | 0.1594 | -0.4501** | 0.1910 | 0.2370 | 0.1981 | -0.1504 | 0.2677 | 0.4230 | 0.3131 |
Household employment structure | ||||||||||||
Multiworkers | -0.2263** | 0.0999 | -0.1437 | 0.1126 | -0.2589** | 0.1322 | -0.2333 | 0.1500 | -0.2238 | 0.1600 | -0.0201 | 0.1743 |
Household registration | ||||||||||||
Nonmigrator | -0.3910*** | 0.1061 | -0.3234*** | 0.1164 | -0.3970** | 0.1710 | -0.4392** | 0.1879 | -0.3502** | 0.1425 | -0.2122 | 0.1547 |
Housing tenure | ||||||||||||
Buy | -0.6826*** | 0.0788 | -0.4233*** | 0.0900 | ||||||||
Commuting time | 0.0045 | 0.0523 | -0.0259 | 0.0592 | -0.0100 | 0.0688 | 0.0027 | 0.0807 | 0.0488** | 0.0217 | -0.0397 | 0.0899 |
N | 2074 | 1607 | 467 | |||||||||
Log likelihood | -1622.2713 | -1087.7912 | -508.92 | |||||||||
Correlation coefficient (ρ) | 0.2461***(0.0507) | 0.1519** (0.0671) | 0.3788*** (0.0783) | |||||||||
Likelihood test of independence (P) | 22.1563 (0.0000) | 5.0216 (0.0250) | 20.0436 (0.0000) |
Table 3 Estimate results of bivariate probit models among nonmigrators and migrator |
Variables | Non-migrator (Model 4) | Migrant (Model 5) | ||||||
---|---|---|---|---|---|---|---|---|
Residential move | Job change | Residential move | Job change | |||||
β | Std.error | β | Std.error | β | Std.error | β | Std.error | |
Constant | 0.0856 | 0.3900 | -0.91862** | 0.35946 | 1.1040 | 0.8250 | -0.695022 | 0.607114 |
Age | ||||||||
30-40 | 0.0652 | 0.0822 | -0.0898 | 0.0966 | -0.7233*** | 0.2176 | -0.2361 | 0.2259 |
40-50 | -0.2427** | 0.1002 | -0.2638** | 0.1186 | -0.9058** | 0.4391 | -0.6947 | 0.4515 |
50-60 | -0.3200* | 0.1790 | -0.1258 | 0.1949 | -0.6286 | 0.8218 | -0.1125 | 0.7947 |
Family income (104 yuan/month) | ||||||||
0.3-0.5 | -0.1596 | 0.1367 | 0.0462 | 0.1590 | 0.1900 | 0.2952 | 0.4321*** | 0.1546 |
0.5-1 | -0.1365 | 0.1357 | -0.0105 | 0.1604 | 0.2586 | 0.2981 | -0.1899 | 0.3179 |
1-1.5 | -0.1005 | 0.1551 | 0.1394 | 0.1807 | 0.3583 | 0.4081 | 0.0130 | 0.4279 |
> 1.5 | 0.1245 | 0.1885 | -0.0611 | 0.2382 | 1.2338** | 0.5055 | 0.1893 | 0.4846 |
Education | ||||||||
High school | 0.2628 | 0.2565 | 0.0157 | 0.2655 | 0.2798 | 0.3640 | 0.0349 | 0.3783 |
College | 0.4071* | 0.2529 | 0.1238 | 0.2622 | 0.4317 | 0.3513 | 0.2653 | 0.3589 |
Postgraduate | 0.4078 | 0.2786 | 0.1947 | 0.2973 | 0.1043 | 0.5451 | -0.0948 | 0.5792 |
Occupation | ||||||||
Skill intensive | -0.0436 | 0.0979 | 0.1673 | 0.1235 | -0.7525** | 0.3301 | 0.4245 | 0.3596 |
Labor intensive | -0.1364 | 0.1010 | 0.1839 | 0.1256 | -0.4463 | 0.3522 | 0.0762 | 0.3846 |
Freelance | -0.2457* | 0.1369 | 0.2756* | 0.154467 | -0.7395* | 0.4264 | 0.2641 | 0.4494 |
Household employment structure | ||||||||
Multiworkers | -0.2249** | 0.1116 | -0.21439* | 0.1267 | -0.1829 | 0.2426 | 0.0797 | 0.2553 |
Housing tenure | ||||||||
Buy | -0.6894*** | 0.0852 | -0.4398*** | 0.0975 | -0.6518*** | 0.2341 | -0.2544 | 0.2448 |
Commuting time | 0.0186 | 0.0586 | -0.0174 | 0.0673 | -0.0200 | 0.1278 | -0.1184 | 0.1313 |
N | 1869 | 205 | ||||||
Log likelihood | -1389.1763 | -210.7548 | ||||||
Correlation coefficient (ρ) | 0.1886*** (0.0571) | 0.5397*** (0.1096) | ||||||
Likelihood test of independence (P) | 10.5122 (0.0012) | 17.4117 (0.0000) |
Table 4 Estimate results of bivariate probit models among single worker and multi-worker households |
Variables | Single worker household (Model 6) | Single worker household (Model 7) | ||||||
---|---|---|---|---|---|---|---|---|
Residential move | Job change | Residential move | Job change | |||||
β | Std.error | β | Std.error | β | Std.error | β | Std.error | |
Constant | 1.1412 | 0.7533 | -1.1286 | 0.6464 | 0.3151 | 0.3764 | -0.8269 | 0.3572 |
Age | ||||||||
30-40 | 0.0409 | 0.1989 | -0.4047* | 0.2373 | -0.0710 | 0.0824 | -0.0454 | 0.0956 |
40-50 | -0.6708** | 0.3333 | -0.3976 | 0.3497 | -0.3056*** | 0.1014 | -0.2535** | 0.1209 |
50-60 | -0.5666 | 0.6146 | 1.1108 | 1.4833 | -0.3643** | 0.1809 | -0.3086 | 0.2193 |
Family income (104 yuan/month) | ||||||||
0.3-0.5 | -0.0590 | 0.2255 | 0.2575 | 0.2479 | -0.1942 | 0.1545 | 0.0116 | 0.1794 |
0.5-1 | 0.1525 | 0.2703 | -0.0938 | 0.3168 | -0.1806 | 0.1490 | -0.0737 | 0.1748 |
1-1.5 | 0.3728 | 0.4446 | 0.0810 | 0.4876 | -0.1664 | 0.1659 | 0.0777 | 0.1918 |
> 1.5 | 0.9112* | 0.5337 | -0.0667 | 0.6866 | 0.1165 | 0.1958 | -0.0599 | 0.2383 |
Education | ||||||||
High school | 0.4681 | 0.3751 | 0.3398 | 0.3185 | 0.1941 | 0.2432 | 0.2442 | 0.2800 |
College | 0.5969* | 0.3645 | 0.0726 | 0.3303 | 0.3209 | 0.2387 | 0.3245 | 0.2750 |
Postgraduate | 0.5822 | 0.4955 | 0.1976 | 0.3982 | 0.3091 | 0.2684 | 0.3301 | 0.3134 |
Occupation | ||||||||
Skill intensive | 0.0493 | 0.2754 | 0.3398 | 0.3185 | -0.1083 | 0.0996 | 0.2043* | 0.1265 |
Labor intensive | -0.1495 | 0.2968 | 0.0726 | 0.3303 | -0.1291 | 0.1023 | 0.2111* | 0.1296 |
Freelance | -0.3561 | 0.3804 | 0.1976 | 0.3982 | -0.2709* | 0.1585 | 0.3396** | 0.1773 |
Household registration | ||||||||
Nonmigrator | -0.2355*** | 0.2445 | -0.1105 | 0.2678 | -0.4252*** | 0.1197 | -0.3972*** | 0.1312 |
Housing tenure | ||||||||
Buy | -0.8493 | 0.2036 | -0.5286** | 0.2277 | -0.6512*** | 0.0868 | -0.4062*** | 0.0997 |
Commuting time | 0.2601 | 0.2369 | 0.0651 | 0.1515 | 0.0552 | 0.0577 | -0.0526 | 0.0652 |
N | 274 | 1800 | ||||||
Log likelihood | -240.8636 | -1362.95 | ||||||
Correlation coefficient(ρ) | 0.3633*** (0.1229) | 0.2330*** (0.0560) | ||||||
Likelihood test of independence (P) | 7.5433 (0.0060) | 16.4065 (0.0001) |
The authors have declared that no competing interests exist.
1 |
|
2 |
|
3 |
|
4 |
|
5 |
|
6 |
|
7 |
|
8 |
|
9 |
|
10 |
|
11 |
|
12 |
|
13 |
|
14 |
|
15 |
|
16 |
|
17 |
|
18 |
|
19 |
|
20 |
|
21 |
|
22 |
|
23 |
|
24 |
|
25 |
|
26 |
|
27 |
|
28 |
|
29 |
|
30 |
|
31 |
|
32 |
|
33 |
|
34 |
|
35 |
|
36 |
|
37 |
|
38 |
|
39 |
|
40 |
|
41 |
|
42 |
|
43 |
|
44 |
|
45 |
|
46 |
|
47 |
|
48 |
|
49 |
|
/
〈 | 〉 |