Transcript スライド 1 - Chinese University of Hong Kong

The 1995-2000 interprefectural
migration of foreign residents of Japan:
salient features and multivariate
explanation
Yoshitaka Ishikawa (Kyoto University, Japan)
and
Kao-Lee Liaw (McMaster University, Canada)
The 4th International Conference on Population Geographies
at Hong Kong, China, on 12 July, 2007
1
Existing literature focused on
foreign residents in Japan
◆There has been a proliferation of research
since the mid-1980s, when massive
immigration started.
◆ Foreigner rate is low (1.6%）, but absolute
number is large (approximately 2 million).
◆It is now an important research subject of all
social sciences including geography.
2
Difficulty in studying migration of
foreign residents in Japan
◆ No comprehensive source; general
migration patterns have remained
unknown.
◆ Published Reports of 2000 Census
1) specific origins are unknown both for immigration
and internal migration
2) detailed migrants’ attributes are unknown
⇒special application to Japanese Statistics
Bureau to obtain micro data samples
3
Three perspectives to explain
destination choice
4
Comparison of interprefectural
migration between foreign residents
and total population
Foreign Residents
Groupings of Prefectures
The Three Largest
Metropolitan Areas
Tokyo Area
Nagoya Area
Osaka Area
Metropolitan Fringes
Manufacturing Stronghold
Tohoku Region
Rest of Japan
Netmigration
Total Population
Rate
Netmigration
Rate
(Persons)
(%)
(Persons)
(%)
-570
-0.10
164,912
0.28
354
0.14
235,743
0.74
1,848
2.13
21,893
0.21
-2,772
-1.15
-92,724
-0.53
600
1.21
32,280
0.41
1,894
4.45
-10,552
-0.16
-372
-2.44
-41,423
-0.44
-1,552
-1.52
-145,217
-0.39
5
Net-migration rate of Japanese
interprefectural migration, 1995-2000
6
Major foreign residents in Japan
(2000)
Census
ethnicity
Korean
Chinese
Brazil
Filipino
Others
Alien registration
1,310,545
1,686,444
(1.03%)
(1.33%)
528,904
252,680
188,190
93,352
247,419
635,269
335,575
254,394
144,871
316,335
7
General features by major ethnicity
Groupings of Prefectures
Korean
Chinese
Filipino
Brazilian
interprefectural
migration rate(%)
interprefectural
migration rate(%)
interprefectural
migration rate(%)
interprefectural
migration rate(%)
6.6
14.9
9.5
25.4
net-migration
net-migration
net-migration
net-migration
(Persons)
(%)
(Persons)
-226
-0.07
790
0.90
1,378
-12
-1,592
1.40
-0.03
-0.80
812
116
-138
Metropolitan Fringes
276
3.14
Manufacturing Stronghold
130
Tohoku Region
Rest of Japan
The Three Largest
Metropolitan Areas
Tokyo Area
Nagoya Area
Osaka Area
(%) (Persons)
(%)
(Persons)
(%)
-78
-0.22
-1,126
-2.82
1.39
1.58
-0.62
-170
86
6
-0.63
1.57
0.18
-1,636 -11.14
1,324
6.29
-814 -19.45
230
4.91
82
1.83
-106
-0.78
1.44
-76
-1.67
-16
-0.44
1,510
8.39
-52
-0.72
-218
-6.90
54
2.98
-88
-8.49
-128
-0.20
-726
-5.53
-42
-0.52
-158
-2.49
8
General features
by educational attainment
Groupings of Prefectures
The Three Largest
Metropolitan Areas
Tokyo Area
Nagoya Area
Osaka Area
Metropolitan Fringes
Manufacturing Stronghold
Tohoku Region
Rest of Japan
Less than HS
High School
College
University
interprefectural
migration rate(%)
interprefectural
migration rate(%)
interprefectural
migration rate(%)
interprefectural
migration rate(%)
7.31
net-migration
8.77
net-migration
13.11
net-migration
19.19
net-migration
(Persons)
(%)
(Persons)
(%) (Persons)
(%)
(Persons)
(%)
-698
-0.58
-960 -0.41
0.31
826
0.73
-724 -1.96
536 2.14
-510 -0.87
-1,076 -1.18
1,040 2.81
-924 -0.87
158 0.68
250 3.71
-258 -1.33
1,776
72
-1,022
2.70
0.58
-2.96
280 2.22
504 4.44
-24 -0.77
-62 -0.24
130 0.64
924 5.00
14 0.21
-108 -0.25
-8 -0.23
134 4.02
-78 -6.83
-198 -2.75
186
196
-208
-1,000
2.54
3.54
-6.19
-5.56
150
9
Nested logit model
Departure sub-model:
⇒ dependent variable: choice probability of stay in,
or departure from, the prefecture of usual residence
in 1995
⇒sample size: 69,308 persons
Destination choice sub-model
:
⇒ dependent variable: choice probability of a
particular destination among 46 prefectures
⇒ sample size: 42,301 persons
10
Explanatory variables
Individual attributes <De, DC> : age, educational
attainment, sex, ethnicity, family status
Labour market related <De, DC> : employment
opportunity, income level
Co-ethnic attraction <De, DC>
Marital opportunity <De, DC>
Prefectural size <De, DC>
Competition with new immigrants <De, DC>
Spatial separation <DC>: distance, contiguity
Inclusive variable <De>
:
11
Why is international marriage in
Tohoku region important?
● The stem family system is dominant in
such region as Tohoku. To maintain this
system, marriage is essential for
household head’s son as successor.
●Due to imbalanced sex ratio, the issue
of marriage squeeze for male population
is serious in eastern half of Japan.
⇒Tohoku has both the first and second
conditions. Unless household head’s
son find Japanese new bride, he tends
to look for his bride with foreign
nationality.
12
New Immigration and Interprefectural Migration
from oveseas
40000人
10000
1000
net internal migration
（人）
500
100
0
-500
0
400km
13
Application result
of departure submodel
Explanatory Variable
Coef.
t-ratio
-3.4798
-61.2
College Educ.
University Educ.
1.2311
2.6369
4.0
10.5
Male
0.0620
2.2
0.6846
1.1576
1.2404
1.1491
0.9135
0.6441
0.3815
10.1
20.9
24.5
22.9
17.7
11.3
6.0
0.3221
1.2124
-0.2421
6.2
10.7
-3.8
-0.2922
-2.0
Constant
Personal Attributes
Aged
Aged
Aged
Aged
Aged
Aged
Aged
15-19
20-24
25-29
30-34
35-39
40-44
45-49
Chinese
Brazilian
Filipino
Yome
Place Attributes and Interactions
Manufacturing Employment Growth *
Brazilian
-0.0604
-6.7
Income Level * College Educ.
Income Level * University Educ.
-0.2649
-0.5534
-2.9
-6.9
Ethnic
Ethnic
Ethnic
Ethnic
-0.0287
-0.0130
-0.0610
0.0084
-9.2
-4.1
-10.0
2.0
Similarity
Similarity
Similarity
Similarity
*
*
*
*
Korean
Chinese
Brazilian
University Educ.
New Immigration
0.0550
10.1
Bridal Opportunity * Brazilian Tsuma
Stem Family Region * Yome
-0.0239
-2.4630
-2.5
-2.0
Ln(Employment Size)
-0.1853
-5.0
0.0374
1.2
Inclusive Variable
Rho-square
0.1178
14
Application result of destination
choice submodel
Explanatory Variable
Coef.
t-ratio
Manufacturing Employment Growth * Brazilian
Manufacturing Employment Growth * Filipino
Service Employment Growth * Korean
Service Employment Growth * Chinese
Service Employment Growth * Filipino
0.1869
0.0585
0.0295
0.0805
0.0451
22.3
3.3
3.4
7.2
2.0
Income Level * High School Educ.
Income Level * College or University Educ.
0.1999
0.5431
2.6
7.6
0.0376
0.0227
0.0727
0.0258
-0.0114
-0.0160
9.2
5.3
14.8
2.2
-2.0
-3.5
-0.0387
-5.2
Stem Family Region * Yome
0.9704
2.0
Ln(Employment Size)
0.8382
24.1
Ethnic
Ethnic
Ethnic
Ethnic
Ethnic
Ethnic
Similarity
Similarity
Similarity
Similarity
Similarity
Similarity
*
*
*
*
*
*
Korean
Chinese
Brazilian
Filipino
College Educ.
University Educ.
New Immigration * At Most High School Educ.
Distance * At Most College Educ
Distance * University Educ.
Contiguity
Rho-square
-0.7465
-0.5486
0.5774
0.2887
-31.9
-20.9
13.5
15
Conclusion

Major destinations: Nagoya metropolitan area,
manufacturing stronghold (not Tokyo metropolitan
area)

Highly mobile persons: Brazilian, graduates from
university

Application result of nested logit model
<departure sub-model> ethnicity, age, educational attainment,
competition with new immigrants, co-ethnic attraction
<destination choice sub-model> spatial separation, prefectural
size, employment opportunity, co-ethnic attraction
16
Implications of the findings
Comparison of explanatory power of international marraige
between new immigration and interprefectural migration: Role of
international marriage in the former is larger than that in the
latter.
Comparison of migration pattern between foreigner and Japanese:
Net inflow to Tokyo metropolitan area for Japanese is much
larger than that for foreigner.
⇒Interprefectural migration by foreign residents has contributed to a
reduction of “monopolar concentration in Tokyo”.
⇒”hollowization” of manufacturing employment opportunity may lead to
an intensification of “monopolar concentration in Tokyo”.
17