Changes in the Spatial Population Structure of Japan

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CHANGES I N TH-E S P A T I A L POPUJJATION STRUCTUKE O F J A P A N

T . K a w a s h i m a

J u n e 1 9 7 7

Research Memoranda are interim reports o n research being conducted by the International Institute for Applied Systems Analysis, and as such receive only limited scientific review. Views or opinions contained herein d o not necessarily represent those of the Institute or of the National Member Organizations supporting the Institute.

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P r e f a c e

T h i s p a p e r w a s c o m m i s s i o n e d b y t h e IIASA r e s e a r c h t a s k o n Human S e t t l e m e n t S y s t e m s : D e v e l o p m e n t P r o c e s s e s a n d S t r a t - e g i e s , a n d w a s p r e s e n t e d a t a IIASA C o n f e r e n c e o n Human S e t t l e - m e n t S y s t e m D y n a m i c s h e l d i n December, 1 9 7 6 . I t s e t s f o r t h t h e d e l i n e a t i o n c r i t e r i a f o r J-SMSAs, t h e J a p a n e s e e q u i v a l e n t o f t h e U.S. S t a n d a r d M e t r o p o l i t a n S t a t i s t i c a l A r e a s a n d i t a l s o a n a l y z e s t h e r e c e n t e v o l u t i o n o f t h e J a p a n e s e human s e t t l e m e n t s y s t e m i n t h i s c o n t e x t . T h e w o r k p r e s e n t e d h e r e w i l l b e e x - t e n d e d a t IIASA b y P r o f e s s o r Kawashima t o i n c l u d e a d e l i n e a t i o n o f J a p a n e s e f u n c t i o n a l u r b a n r e g i o n s ( c o m p a r a b l e t o t h o s e b e i n g d e l i n e a t e d f o r c o u n t r i e s i n W e s t e r n a n d E a s t e r n E u r o p e ) a n d e c o n o m i c a n d d e m o g r a p h i c a n a l y s e s u s i n g t h e s e r e g i o n s . T h e r e s u l t s o f t h e s e e f f o r t s w i l l a p p e a r i n f u t u r e r e s e a r c h m e m o - r a n d a i n t h i s s e r i e s .

The r e s e a r c h r e p o r t e d h e r e w a s p a r t i a l l y c a r r i e d o u t w i t h f u n d s p r o v i d e d b y t h e F o r d F o u n d a t i o n a n d t h e J a p a n e s e M i n i s t r y o f E d u c a t i o n . T h e a u t h o r i s p a r t i c u l a r l y g r a t e f u l f o r t h e c o - o p e r a t i o n r e c e i v e d f r o m P r o f e s s o r s Norman G l i c k m a n a n d R o b e r t C. D o u g l a s o f t h e U n i v e r s i t y z ~ f P e n n s y l v a n i a . T h a n k s a r e a l s o d u e t o T a k a s h i N a k a i f o r h i s d i l i g e n t r e s e a r c h a s s i s t a n c e .

P a p e r s i n t h e IIASA S e r i e s o n Human S e t t l e m e n t S y s t e m s : D e v e l o p m e n t P r o c e s s e s a n d S t r a t e g i e s

1 . P e t e r H a l l , N i l e s H a n s e n a n d H a r r y S w a i n , Urban S y s t e m s : A C o m p a r a t i v e A n a l y s i s of S t r u c t u r e , Change a n d P u b l i c P o l i c y , RE{-75-35, J u l y 1 9 7 5 .

2 . N i l e s H a n s e n , A C r i t i q u e of E c o n o m i c R e g i o n a l i z a t i o n s of t h e U n i t e d S t a t e s , RR-75-32, S e p t e m b e r 1 9 7 5 .

3 . N i l e s H a n s e n , I n t e r n a t i o n a l C o o p e r a t i o n a n d R e g i o n ~ l P o l i c i e s W i t h i n N a t i o n s , RE{-75-48, S e p t e m b e r 1 9 7 5 . 4 . P e t e r H a l l , N i l e s H a n s e n a n d H a r r y S w a i n , S t a t u s a n d

F u t u r e D i r e c t i o n s of t h e C o m p a r a t i v e Urban R e g i o n S t u d y : A Summary of Workshop C o n c l u s i o n s , RPJ-75-59, November 19 7 5 .

5 . N i l e s H a n s e n , G r o w t h S t r a t e g i e s a n d Human S e t t l e m e n t S y s t e m s i n D e v e l o p i n g C o u n t r i e s , RM-76-2, J a n u a r y 1 9 7 6 .

6 . N i l e s H a n s e n , S y s t e m s A p p r o a c h e s t o Human S e t t l e m e n t s , RM-76-3, J a n u a r y 1 9 7 6 .

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A l l a n P r e d , T h e I n t e r u r b a n T r a n s m i s s i o n o f G r o w t h i n A d v a n c e d E c o n o m i e s : E m p i r i c a l F i n d i n g s V e r s u s R e g i o n a l P l a n n i n g A s s u m p t i o n s , RR-76-4, March 1 9 7 6 . N i l e s H a n s e n , T h e E c o n o m i c D e v e l o p m e n t o f B o r d e r R e g i o n s ,

RM-76-37, A p r i l 1 9 7 6 .

P i o t r K o r c e l l i , T h e Human S e t t l e m e n t S y s t e m s S t u d y :

S u g g e s t e d R e s e a r c h D i r e c t i o n s , RM-76-38, A p r i l 1 9 7 6 . N i l e s H a n s e n , A l s a c e - B a d e n - B a s e l : E c o n o m i c I n t e g r a t i o n

i n a B o r d e r R e g i o n , RM-76-51, J u n e 1 9 7 6 .

Peter N i j k a m p , S p a t i a l M o b i l i t y and S e t t l e m e n t P a t t e r n s : An A p p l i c a t i o n o f a B e h a v i o r a l E n t r o p y , RM-76-45, J u l y 1 9 7 6 .

N i l e s H a n s e n , A r e R e g i o n a l D e v e l o p m e n t Po l i c i e s N e e d e d ? , RM-76-66, A u g u s t 1 9 7 6 .

G a l i n a K i s e l e v a , C o m m u t i n g : An A n a l y s i s o f W o r k s b y S o v i e t S c h o l a r s , RM-76-64, A u g u s t 1 9 7 6 .

K o r e n S h e r r i l l , F u n c t i o n a l U r b a n R e g i o n s i n A u s t r i a , RM-76-71, S e p t e m b e r 1 9 7 6 .

N i l e s H a n s e n , E c o n o m i c A s p e c t s o f R e g i o n a l S e p a r a t i s m , RM-77-10, F e b r u a r y 1 9 7 7 .

K o r e n S h e r r i l l , F u n c t i o n a l U r b a n R e g i o n s and C e n t r a l P l a c e R e g i o n s i n t h e F e d e r a l R e p u b l i c o f Germany and S w i t z e r l a n d , RM-77-17, A p r i l 1 9 7 7 .

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Abstract

This study uses data from the 1960-1975 period to analyze the recent evolution of the Japanese human settlement system. It examines comprehensively the demographic, local government budget and industrial employment aspects of urban and rural spatial dynamics.

The spatial unit of analysis used is the J-SMSA, the Japanese version of the U.S. Standard Metropolitan Statistical Area. The results indicate that before 1970 there were large shifts in population and economic activity from the nonmetropolitan areas to metropolitan areas, and from the southwest to the middle central region. Recently, however, the rate of population loss has decreased significantly in nonmetropolitan areas while the southwest has experienced slight population

increases.

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CHANGES IN THE SPATIAL POPULATION STRUCTURE OF JAPAN

I. Introduction

Before 1970 there were large shifts in population and economic activity from the non-metropolitan areas of Japan to the metropolitan areas, and from the southwestern regions to the middle central region. In the past five years, however, the rate of loss of population has significantly

decreased in the non-metropolitan areas while the southwestern regions have experienced slight increases in population.

The present paper, which is based on data from the 1960- 1975 period summarizes the process which has led to the

recent changes in the Japanese human settlement system. The analysis attempts to investigate comprehensively the spatial, demographic, local-government budget and industrial employment aspects of urban and rural dynamics. It is an extension of previous studies of the development of urban systems in Japan by the author (1974, 1975) as well as joint studies with

N. Glickman (1975) of the University of Pennsylvania.

In this research, we primarily employ the concept of the Japanese version (J-SMSAs) of the U.S. Standard Metropolitan Statistical Areas, which are economically and socially integrated metropolitan units. The criteria for delineating J-SMSAs are discussed in Section 11. Section I11 deals with the nature of the data used in our analysis of J-SMSAs. In section IV we briefly discuss the diversification index which is used in Section V's empirical analysis of changes in the spatial population structure of Japan. Section VI contains some concluding remarks.

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11. The Japanese Version of Standard Metropolitan Statistical Areas

In order to carry out a meaningful analysis of the development of urban sub-systems, the entire area in and around a city (i.e., the area in which activities form an organically integrated economic and social system) needs to be considered as a unit of study. Glickman and I have attempted to delineate the boundaries of the J-SMSAS' according to the following cri- tezia (see Glickman, 1975, pp.2-4 for a more detailed discussion):

1. Criteria for core-cities:

a) Prefectural capitals must be core-cities whether or not they meet the following conditions. Other potential core-cities should satisfy the following three conditions.

b) The minimum population size must have been equal to or greater than 100,000 in 1970.

c) The daytime-nighttime ratio of population must have been greater than 1 .O.

d) Seventy-five percent of the ordinary h-ouseholds must be either "agricultural workers' households"

or "agricultural and non-agricultural workers' mixed households".

e) If the distance between the potential core-cities is no more than 20 kilometers, then the cities compose twin, triple, quadruple,

...,

core-cities.

2. Criteria for localities to be combined with the core- cities:

a) The number of commuters from the localities to the core-city must be greater than 500.

b) The ratio of commuters (from each locality to the core-city) to total employment in each locality must be greater than five percent.

C) A locality is combined with a core-city to which most commuters go if the locality is eligible to

'we sometimes refer to the J-SMSA as the Regional Economic Cluster (REC)

.

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be combined with more than one potential core-city.

d) Seventy-five percent of the ordinary households must be either "non-agricultural workers' households" or "agricultural and non-agricultural workers' mixed households".

In accordance with these conditions, and using 1970 Popu- lation Census data, the first phase of delineating the J-SMSAs was carried out. After making some boundary adjustments in the

light of relevant functional criteria, the definitive J-SMSA map was drawn (see Map 1). The total population of the J-SMSAs

amounts to about 70 percent of the total national population.

Table 1 gives the name list of the J-SMSAs as well as information on code numbers, sequential numbers, numbers of member localities including core-cities, and the region where each J-SMSA is locatedS2 The 8 4 J-SMSAs include a total of

1021 localities (given in Appendix 1 , which is available separately)

.

111. Data for the J-SMSAs

The data bank for the J-SMSAs now includes more than one hundred variables. Data on the locality level were hand tabu- lated and then aggregated to the J-SMSA level by computer.

Data on both levels are now stored on magnetic tape for the use of persons interested in doing empirical research on the Japanese urban system. Tables 2, 3 and 4 show some basic J-SMSA data retrieved from our data bank for purkxes of our analyses; data for Japan as a whole also are given. Table 2 gives the population levels in 1960, 1965, 1970 and 1975, the five-year growth rates for each of these time-spans, and the ten-year growth rates for the period from 1960 to 1970 (GR4) and from 1965 to 1975 (GR5). In the last column are shown the values of the ratio

20kinawa Prefecture is excluded since its reversion took place in 1972.

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T a b l e 1 J-SMSA N a m e

List

J- SMSA

c o d e

S e q . N u m b e r

J-SMSA N a m e S A P P O R O FIAKODATE ASAHIKAWA MURORAN K U S H I R O O B I H I R O AOMORI H I R O S A K I HACHINOHE MORI OKA

S E N D A I I S H I N O N l A K I A K I T A

YAMAGATA FUKUSHIMA A I ZU WAKAMAT SU KORIYAMA

IflITO H I T A C H I UTSUNOMIYA M A E B A S H I T A K A S A K I K I R W TOKYO YOKOHAMA ODAWARA N I I G A T A NAGAOKA TOYLMA TAKAOKA KANAZAWA F U K U I KOFU NAGANO MATSUMOTO G I N S H I Z U O K A HAMAMAT SU NUMAZU F U J I NAGOYA TOYOHASHI TOYOTA T SU I S E OT SU KYOTO OSAKA KOBE HIlVlEJ I

N o . o f M e m b e r L o c a l i t i e s

R e g i o n

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T a b l e 1 ( c o n t i n u e d )

J-SMSA Seq. J-SMSA

code N u m b e r

NARA WAKAYAMA T O T T O R I YONAGO MAT S U E OKAYAMA K U R A S H I K I HIROSHIMA KURE

FUKUYAMA SHIMONOSEKI U B E

YAMAGUCHI IWAKUNI TOKUSHIMA TAKllMATSU MAT SU YAMA

IMABARI N I IHAMA KOCHI

KITAKYU SHU FUKUOKA OMUTA KURUNlE SAGA NAGASAKI

SASEBO KUMAhriOTO YATSUSHIRO O I T A

M I Y A Z A K I MIYAKONOJO NOBEOKA KAGOSIIIMA

N o . o f M e m b e r R e g i o n L o c a l i t i e s

N o t a t i o n s f o r R e g i o n s : A

-

H o k k a i d o ( 6 J - S M S A s )

B

-

H o n s h u ( 1 ) : Tokaido-Sanyo-Megalopolis ( 2 5 J-SMSAs )

C

-

H o n s h u ( 1 1 ) : Non-Tokaido-Sanyo-Megalopolis ( 3 3 J - S M S A s )

D

-

S h i k o k u ( 6 J-SMSAs) E

-

K J - U S ~ U ( 1 4 J-SMSAS)

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k k k k k c d d c d c d c d Q , Q , a Q , m

3 3 w 3

L n m m o 0

A rl

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f 0 ? Z d F C : C Z C C X . C l m P . - ^t-

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+I I-' ;3

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4 4 d d

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which is equivalent to

population in 1975 population in 1965 population in 1970 population in 1960

This value indicates the population growth rate observed during the period from 1970 to 1975 as compared with that

during the period from 1960 to 1965. If this growth rate ratio (GRR) is less than one for a specific J-SMSA, it means that the J-SMSA's growth rate declined in the last five years.

Table 3 gives the percentage distribution of local- government public expenditures by expense category. The eleven categories used are: assembly arrangement, general affairs, social welfare, health, unemployment matters, agro- forestry-fishery projects, commerce and industrial activities, construction projects, fire service, education, and public bonds. For all J-SMSAs, outlays for construction projects account for 27.16 percent of the total, followed by education, general affairs, and social welfare, which account for 21.27 percent, 13.57 percent, and 12.41 percent respectively.

In the second column of Table 3 are shown the diversification indices of the Public Expenditure Pattern, denoted by

DI(11). The values were calculated on the basis of modifica- tions made in turn by Isard (1960, pp.270-277) and Douglas

(1967, pp.11 ff.), of Rodgers (1957) initial work in this area.

The higher the value of the index (which will be discussed briefly in the next section) the more similar is the structure to the average degree of diversification.

Table 4 shows the percentage distribution of employment by industry sector for the following sectors: agriculture; forestry and hunting; fishery and agriculture; mining; construction;

manufacturing; wholesale and retail trade; finance and insurance;

real estate; transport and communication; electricity, gas and water; services; and government. For all J-SMSAs, manufacturing accounts for the highest share of employment (29.70 percent), followed by wholesale and retail trade, services, and agriculture, with 21.87 percent, 15.55 percent, and 10.28 percent

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respectively. The Industrial Employment Pattern diversification indices--denoted by DI(13)--are given in the second

column so that the employment structure of each J-SMSA can be compared with the average of all the J-SMSAs. In the last column are shown the values of the ratio which indicates the diversification of the budgetary structure in relation to the diversification of the employment structure of each J-SMSA.

IV. Diversification Index

The diversification index is calculated by comparing each J-SMSA's budget-expense structure with the average structure of all 84 J-SMSAs. In order to obtain the diversification index, we calculate a concentration index for each budget-expense category in each J-SMSA and then rank the categories in terms of this index. The concentration index for budget-expense category j in J-SMSAi is the percentage share of J-SMSAils budget-expense for category j divided by the percentage share of budget-expense in all 84 J-SMSAs accounted for by category

j . Accordingly,

BEi. / L ^BEi.

- S

CI,; = - ij

where

'Iij ⁼Concentration index for J-SMSAils busget- expense for category j.

BEij ⁼J-SMSAils budget-expense for category j.

The construction of a Lorenz curve for each J-SMSA requires the ranking of budget-expense categories by concentration index.

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That is, the points representing the cumulative values of the numerator (S ) on the vertical axis and of the denominator

ij

(TSj) on the horizontal axis are plotted in the decreasing order of the concentration index. This means that the point for the budget-expense category whose Sij is largest relative to its TS (i.e., the item with the highest value of

crij) will be closest to the vertical axis, the second largest will j come next, and so forth. If one connects these points in order by lines from the point (0, 0) to the point (100, loo), one gets a curve (strictly, kinked-line) which is convex upwards and which tends to rise rapidly from the point (0, 0) and then flatten with its end at the point (100, 100). This Lorenz curve is contained in a quadrate box; the diversification index is defined as the difference between the total area of this box and the area under the Lorenz curve, divided by the area above the 4 5 degree line.

In view of the nature of the diversification index, if a J-SMSA's budget-expense structure is completely diversified in the sense that all of its concentration indices are equal to one, then its Lorenz curve falls on the 4 5 degree line, i.e.

the diversification index is equal to one. If, at the other extreme, all the public expenditures in a J-SMSA are concentrated on only one budget-expense category, then one gets an

extremely low diversification index for the J-SMSA.

The diversification index is useful for research in

which one wants to compare the structure (not only the budget- expense structure but also almost any type of structure) of each J-SMSA with the typical average structure of all the J-SMSAs. However, it should be noted that the significance of the diversification index can only be determined in

relation to other socio-economic variables because of the fact that there is nothing inherently good or bad about a particular level of diversification (Douglas, 1967, p.13).

V. Changes in the Spatial Population Structure of Japan

As shown in Table 1, Japan can be divided into four geo- graphic regions: Hokkaido, Honshu, Shikoku and Kyushu, each

(25)

of which corresponds to one of the country's four major islands. The Honshu region is divided, in turn, into two regions: Honshu (I) and Honshu (11)

.

The Honshu (I) region is identical with the Tokaido-Sanyo-Megalopolis, along which various types of activities are highly concentrated. The Honshu (11) region covers the rest of the area of Honshu

Island, the Non-Tokaido-Sanyo-Megalopolis region. The Hokkaido, Honshu (I), Honshu (111, Shikoku and Kyushu regions have 6 , 25,

33, 6 , and 14 J-SMSAs respectively.

Table 2 shows the population levels, growth rates, and growth rate ratios for the J-SMSAs. The 1970 populations of the ten largest J-SMSAs are as follows:

TOKYO OSAKA NAG3YA YOKOHAMA KYOTO KOBE

KITAKYUSHU FUKUOKA SAPPORO SENDAI

POPULATION = 18897712 POPULATION = 9521577 POPULATION = 4248982 POPULATION = 3558172 POPULATION = 1809412 POPULATION = 1740999 POPULATION = 1501563 POPULATION = 1348113 POPULATION = 1310693 POPULATION = 1019991 It should be noted that the six largest J-SMSAs in

terms of population size are located in region B, the Tokaido- Sanyo-Megalopolis.

The following J-SMSAs had the highest values of 10-year population growth rates from 1960 to 1970 (GR4) and from 1965 to 1975 (GR5)

,

respectively.

1410 YOKOHAMA B GR4 = .59 110 SAPPORO A GR4 = .48 2710 OSAKA B GR4 = -43 2330 TOYOTA B GR4 = .43 291 0 NARA C GR4 = .38

(26)

291 0 NARA C GR5 = . 4 8

1 4 1 0 YOKOHAMA B GR5 = . 4 8

1 1 0 SAPPORO A GR5 = . 4 5

2330 TOYOTA B GR5 = . 4 4

3320 KURASHIKI B GR5 = . 3 7

The Nara J-SMSA h a s d r a s t i c a l l y i n c r e a s e d i t s p o p u l a t i o n s i z e i n t h e p a s t f i f t e e n y e a r s b e c a u s e o f i t s s t r o n g t e n d e n c y t o become a d o r m i t o r y c o m m u n i t y f o r p e o p l e who w o r k i n e i t h e r t h e O s a k a o r t h e K y o t o J-SMSA d u r i n g t h e d a y t i m e . The Yokohama J-SMSA s t i l l c o n t i n u e s t o g r o w r a p i d l y , a s d o e s t h e S a p p o r o J-SMSA, w h i c h a t t r a c t s p e o p l e f r o m t h e n e i g h b o r i n g a r e a s i n H o k k a i d o I s l a n d . 3

T h e T o y o t a J-SMSA's boom i s d u e t o t h e e x i s t e n c e o f a c t i v e a u t o m o b i l e m a n u f a c t u r i n g i n d u s t r i e s . T h e K u r a s h i k i J-SP4SA r o s e t o t h e f i f t h p o s i t i o n d u r i n g t h e l a s t f i v e y e a r s a s a c o n s e - q u e n c e o f r e c e n t s u b u r b a n i z a t i o n a r o u n d t h e Okayama J-SMSA.

W i t h r e g a r d t o t h e g r o w t h r a t e r a t i o ( G R R ) shown i n t h e l a s t c o l u m n o f T a b l e 2 , i t i s i n s t r u c t i v e t o e x a m i n e t h e J-SMSAs w i t h a r a t i o l e s s t h a n o n e :

OSAKA P?U RORAN YOKOHAMA TOKYO ISE O B I H I R O ODAWARA KUSHIRO WAKAYAMA SAPPORO NUMAZU GIFU

GRR ⁼ . 8 5 3 2 GRR = . 9 0 6 8 GRR = . 9 2 4 5 GRR = . 9 2 5 9 GRR = . 9 4 1 8 GRR = . 9 4 9 6 GRR ⁼ . 9 5 0 4 GRR = . 9 6 6 7 GRR = . 9 7 4 1 GRR = . 9 7 9 7 GRR ⁼ . 9 8 4 3 GRR = . 9 9 1 6

3 F o r t h e j u s t i f i c a t i o n o f t h i s s t a t e m e n t see T a b l e 5-b.

(27)

The Osaka J-SMSA had the largest reduction in growth, mainly because it grew by 43 percent during the ten-year period

from 1960 to 1970, but only by 22 percent from 1965 to 1975.

It also is interesting that no J-SMSAs from the Shikoku and Kyushu regions had ratios less than one and that only two

J-SMSAs out of the 33 J-SMSAs located in the non-Tokaido-Sanyo- Megalopolis region had a ratio less than one.

Table 3 gives the percentage distribution of local government public expenditures by budget-expense category and the diversification index for the budget-expense structure. Con- cerning the expenses for construction projects, DI(11, 8), which accounts for the highest percentage share (27.16 percent) for all J-SMSAs, the J-SMSAs with the five highest values are as follows:

2810 KOBE B DI(11, 8) = 41.07 1710 KANA Z AWA C DI(11, 8) = 37.04 110 SAPPORO A DI(11, 8) = 34.43 271 0 OSAKA B DI(11, 8) = 32.69 141 0 YOKOHAMA B DI(11, 8) = 31.82

It is remarkable that except for the Kanazawa J-SMSA, whose 1970 population was 540,268, each of the other four

J-SMSAs had 1970 populations over one million. One would n ~ t necessarily expect to find a high correlation between 1970

population and the percentage distributjor of expenses for construction projects, but the relevant correlation coefficients (Table 6) are 0.82, 0.55, 0.70 and 0.50 for t.he J-SMSAs in Hokkaido, Shikoku, Kyushu and Japan as a whole, respectively.

With regard to the diversification index of the budget- expense structure, the five highest-ranking J-SMSAs are as follows :

2210 SHIZUOKA B DI(11) = .89076 2110 GIFU B DI(11) = -88443 371 0 TAKAMATSU D DI (1 1) = .88345 1510 NI I GATA C DI(11) = .88136 2320 TOYOHASHI B DI(11) = .88072

(28)

The Shizuoka J-SMSA has the most typical structure of

public expenditures. On the other hand, the Yatsushiro J-SMSA, in the Kyushu region, has the lowest diversification index

(0.66237), indicating that its budget-expense structure is unique when compared with the average structure of all 84 J-SMSAs

.

Table 4 gives the diversification index of the industrial employment pattern for each J-SMSA. The five highest-ranking J-SMSAs are:

2230 NUMAZU B DI(13) = 0.94445 1710 KANAZAWA C DI(13) = 0.93399 2210 SHI ZUOKA B DI(13) = 0.93064 3410 HIROSHIMA B DI(13) = 0.91890 131 0 TOKYO B DI(13) = 0.91825

The Numazu J-SMSA has the most typical structure with respect to the industrial employment pattern. The Shizuoka J-SMSA, which has the highest diversification index for the budget-expense structure, is ranked third in this instance.

Table 4 also indicates that among the J-SMSAs with the smallest diversification indices are Hirosaki (0.55809),

Miyakonojo (0.61741)

,

Yamaguchi (0.62240)

,

Morioka (0.66025)

,

and Miyazaki (0.66988). They are located at some distance from the Tokyo-Osaka industrial belt.

The argument is sometimes made that a J-SMSA with a high level of employment diversification is economically healthy because of the fact that the magnitude of its local economic activities need not depend on the success or failure of one or two major industrial sectors. On the other hand, it could be argued that the rapidly-growing J-SMSAs will generally tend to have their employment concentrated in high-growth industrial sectors, and thus they would tend to have lower diversification indices. The data in Table 6 indicate that this last hypothesis is plausible concerning both the Shikoku region's metropolitan system and the J-SMSAs in the 1,000,000

-

4,999,999 population- size group; the respective correlation coefficients are -0.78 and -0.51 for the 5-year population growth rate and the employment structure diversification index.

(29)

A third argument is that there is a tendency for larger J-SMSAs to be more diversified. This hypothesis seems to be reasonable for the metropolitan systems in the Shikoku, and Kyushu regions regarding the budget-expense structure, and for the Kyushu regions regarding the employment structure.

The relevant correlation coefficients (Table 6) are 0.69, 0.73, and 0.51, respectively.

Table 4 also gives the percentage distribution of employment by industry. For all J-SMSAs manufacturing accounts for the highest share of employment, 29.70 percent. The five highest-ranking J-SMSAs for manufacturing industry DI(13,6) are :

1030 KIRYU C DI(13,6) = 49.15 2330 TOYOTA B DI(13,6) = 48.26 820 HITACHI C DI(13,6) = 40.69 2240 FUJI B DI(13,6) = 40.36 3320 KURASHIKI B DI(13,6) = 40.19

Each of these five J-SMSAs is located in the Honshu

region, and each has its own particularly specialized industrial sectors; textile mill products for the Kiryu and Kurashiki J-SMSAs; motor vehicles and motor vehicle equipment for the Toyota J-SMSA; ordinary and electrical machinery, equipment and supplies for the Hitachi J-SMSA; and pulp, paper and finished allied products for the Fuji J-SMSA.

The last column of Table 4 compares the budgetary structure and the employment structure for each J-SMSA. The J-SMSAs with the five highest values of this diversification index

ratio (DIR) and those with the five lowest values are:

220 HIROSAKI C DIR = 1.52135 310 MORI OKA C DIR = 1.33159 150 KUSHIRO A DIR = 1.30829 3530 YAMAGUCHI B DIR = 1.25540 230 HACHINOHE C DIR = 1.21486

(30)

3 8 3 0 NIIHAMA D DIR = 0 . 8 5 7 8 7

2 4 1 0 TSU C D I R = 0 . 8 6 2 2 2

1 7 1 0 KANAZAWA C DIR = 0 . 8 6 6 5 6

4530 NOBEOKA E DIR = 0 . 8 6 8 6 4

3 4 2 0 KURE B DIR = 0 . 8 8 3 4 9

T h e J-SMSAs i n t h e f i r s t g r o u p ( e x c e p t f o r t h e Y a m a g u c h i J-SMSA) a r e l o c a t e d i n t h e n o r t h e r n p a r t o f J a p a n , w h i l e a l l t h o s e i n t h e s e c o n d g r o u p a r e i n t h e s o u t h - w e s t e r n p a r t . I n t h e - o r r e l a t i o n c o e f f i c i e n t m a t r i x i n T a b l e 6 , o n e sees a h i g h c o r r e l a t i o n ( 0 . 7 5 ) b e t w e e n D I R a n d 1 9 7 0 p o p u l a t i o n i n t h e S h i k o k u r e g i o n , w h i l e a s i g n i f i c a n t n e g a t i v e c o r r e l a t i o n

( - 0 . 5 0 ) e x i s t s b e t w e e n D I R a n d 1 9 7 0 p o p u l a t i o n f o r t h e J-SMSAs i n t h e 7 5 0 , 0 0 0

-

1 , 0 0 0 , 0 0 0 p o p u l a t i o n s i z e - c l a s s . I t c a n a l s o b e s e e n t h a t i n t h e S h i k o k u r e g i o n t h e r e i s a r a t h e r h i g h c o r - r e l a t i o n c o e f f i c i e n t b e t w e e n t h e g r o w t h r a t e r a t i o (GRR) a n d d i v e r s i f i c a t i o n i n d e x r a t i o ( D I R ) . T h e s e f i n d i n g s s u g g e s t t h a t i t w o u l d b e w o r t h w h i l e t o a t t e m p t t o c a r r y o u t f u r t h e r e x p l o - r a t o r y r e s e a r c h o n s p a t i a l p o p u l a t i o n s t r u c t u r e b y u s e o f t h e D I R .

T h e d a t a i n T a b l e s 5 - a t h r o u g h 5-9 p e r m i t a b r i e f i n t e r - r e g i o n a l c o m p a r a t i v e i n v e s t i g a t i o n . E x a m i n i n g t h e g r o w t h r t t e s o f p o p u l a t i o n f c r a l l J-SMSAs i n e a c h r e g i o n i n T a b l e 5 - a , i t i s s e e n t h a t t h e f a s t e s t - g r o w i n g r e g i o n s f r o m 1 9 6 0 t o 1 9 7 0 e x - p a n d e d l e s s r a p i d l y d u r i n g t h e p e r i o d f r o m 1 9 6 5 t o 1 9 7 5 . T h e H o k k a i d o r e g i o n g r e w b y 30 p e r c e n t i n t h e f o r m e r p e r i o d a n d b y 29 p e r c e n t i n t h e l a t t e r p e r i o d . T h e Tokaido-Sanyo-Megalopolis g r o w t h r a t e w a s r e d u c e d f r o m 30 p e r c e n t t o 26 p e r c e n t . On t h e o t h e r h a n d , t h e s l o w l y - g r o w i n g r e g i o n s d u r i n g t h e f o r m e r p e r i o d - - s u c h a s t h e non-Tokaido-Sanyo-Megalopolis, S h i k o k u a n d K y u s h u r e g i o n s - - i n c r e a s e d t h e i r g r o w t h r a t e s i n t h e l a t t e r p e r i o d f r o m 8 p e r c e n t t o 1 3 p e r c e n t , 6 p e r c e n t t o 1 3 p e r c e n t a n d 5 p e r c e n t t o 11 p e r c e n t r e s p e c t i v e l y . A s i m i l a r t e n d e n c y c a n b e s e e n i n t h e s i m p l e a v e r a g e g r o w t h r a t e s s h o w n i n T a b l e 5 - a . T h e K y u s h u r e g i o n h a d a f o u r - f o l d i n c r e a s e i n i t s g r o w t h r a t e w h i l e t h e S h i k o k u r e g i o n ' s g r o w t h r a t e m o r e t h a n d o u b l e d .

I t i s i m p o r t a n t t o k e e p i n m i n d t h a t t h e c o m p a r i s o n s j u s t made i n v o l v e d a s o r t o f " m o v i n g - a v e r a g e " g r o w t h r a t e s o t h a t a

(31)

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22063387 19481 50 6100924 33161728

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5039206 71354357 4121423 1290357 5 93418501 5171800 76757913 3975058 123701 90 98274961

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(33)

Table

3-d

Population 2nd Diversification Index for J-SMSAs by Population Size (8 Classss) Size

XI

For notations and remarks, see Tables 5-a and

5-g.

(34)

Table 2-e Population and Divers5ficztion Index for J-SMSAs by Population Size (3-Clzsses)

Table 5-f PT, .~~~.nber . r of J-SMSAs by Population Size and Region

POP.\

- Size.

I

A

B c D

E Total For notations and remarks, see Tables 5-a and 5-g. Total for Each Category 6 25

33

6

14 84

(35)

Table

5-g

Notations and Remarks for Tables 5-a,b,c,d,e and f A - - B

- - C - -

D

- -

E - - BC

r a t h e r " s m o o t h e d " g r o w t h t e n d e n c y was o b t a i n e d . I t s h o u l d b e n o t e d i n a d d i t i o n t h a t w e a d o p t e d t h e g r o w t h r a t e r a t i o ( G R R ) r a t h e r t h a n t h e g r o w t h r a t e f o r t h e f o r m e r p e r i o d d i v i d e d by t h a t f o r t h e l a t t e r p e r i o d i n o r d e r t o a v o i d t h e l o g i c a l con- f u s i o n f r e q u e n t l y c a u s e d b y t h e e x i s t e n c e o f n e g a t i v e g r o w t h r a t e s .

W i t h r e s p e c t t o t h e d i v e r s i f i c a t i o n i n d e x r a t i o ( D I R ) , t h e H o k k a i d o r e g i o n h a s t h e h i g h e s t v a l u e ( 1 . 1 3 1 1 1 ) w h i l e t h e

S h i k o k u r e g i o n h a s t h e l o w e s t ( 0 . 9 8 5 8 4 ) . F u r t h e r r e s e a r c h would b e r e q u i r e d t o e x p l a i n t h e s e r e g i o n a l c h a r a c t e r i s t i c s .

I n T a b l e 5 - b , t h e g r o w t h r a t e s o f p o p u l a t i o n f o r non-J- SMSA a r e a s a r e p r e s e n t e d . The t h r e e r e g i o n s o t h e r t h a n t h e Honshu r e g i o n show n e g a t i v e g r o w t h r a t e s i n r o w s ( i ) a n d ( j ) . I n t e r e s t i n g l y , a l l t h e r e g i o n s e x c e p t t h e H o k k a i d o r e g i o n

( w h i c h h a s e x p e r i e n c e d a n i n c r e a s e i n t h e r a t e o f p o p u l a t i o n l o s s ) h a v e h i g h g r o w t h r a t e r a t i o s ; t h e y a r e 1 . 0 8 4 , 1 . 0 7 3 a n d 1 . 0 7 4 f o r t h e Honshu, S h i k o k u a n d Kyushu r e g i o n s , r e s p e c t i v e l y . The o v e r a l l non-J-SMSA t e n d e n c y i s s i m i l a r t o t h a t f o r t h e s e t h r e e r e g i o n s . The r a t e o f l o s s o f p o p u l a t i o n h a s s i g n i f i c a n t l y d e c r e a s e d i n t h e n o n - m e t r o p o l i t a n a r e a s i n t h e p a s t f i v e y e a r s .

T a b l e 5-c s u m m a r i z e s t h e p o p u l a t i o n g r o w t h p a t t e r n i n e a c h r e g i o n i n b o t h m e t r o p o l i t a n a n d n o n - m e t r o p o l i t a n a r e a s . One c a n see t h a t t h e S h i k o k u a n d Kyushu r e g i o n s , w h i c h u s e d t o b e l a g g i n g i n t e r m s o f p o p u l a t i o n g r o w t h r a t e , h a v e r e c e n t l y e x p e r i e n c e d p o s i t i v e g r o w t h r a t e s e v e n t h o u g h t h e s e r a t e s a r e

s t i l l l o w e r t h a n t h e n a t i o n a l a v e r a g e o f 7 p e r c e n t f o r t h e p e r i o d f r o m 1970 t o 1 9 7 5 .

O v e r a l l , T a b l e s 5 - a , 5-b a n d 5-c i n d i c a t e t h a t t h e momen- tum o f t h e t r e n d o f l a r g e s h i f t s i n p o p u l a t i o n f r o m n o n - m e t r o - p o l i t a n a r e a s t o m e t r o p o l i t a n a r e a s a n d f r o m t h e S h i k o k u a n d Kyushu r e g i o n s t o t h e Honshu r e g i o n h a s b e e n g r a d u a l l y r e d u c e d i n t h e p e r i o d s t u d i e d .

T a b l e s 5-d a n d 5-e show p o p u l a t i o n - g r o w t h c h a r a c t e r i s t i c s by p o p u l a t i o n - s i z e c l a s s a n d T a b l e 5-f shows t h e number o f J-SMSAs i n t h e p o p u l a t i o n s i z e - r e g i o n m a t r i x . The d a t a i n T a b l e 5-d show t h a t J-SMSAs w i t h t h e h i g h e s t g r o w t h - r a t e r a t i o s

(37)

are found in the 400,000

-

499,999 (XU) and 1,000,000

-

^4,999,999

(X7) population-size classes.

The data in Table 5-e indicate that, as a rough tendency, the larger the J-SMSA, the lower will be the population growth- rate ratio. Similarly, the larger the J-SMSA, the lower will be the diversification index ratio. Further research is required

to gain a better understanding of the reasons for these phenomena, and thus a better understanding of the dynamics of the spatial population structure in Japan.

Table 6 gives the correlation coefficient matrix for the main variables discussed in this paper. Interestingly, the Shikoku region has a number of relatively high correction coefficients. Also, there are high correlation coefficients between the growth-rate from 1970 to 1975 and the employment share of wholesale and retail trade,

and

between this growth rate and the employment share of the services sector.

VI. Concluding Remarks

In this paper an attempt has been made to draw a profile of Japanese population growth on the basis of data collected for the J-SMSAs. Research of this kind is difficult in Japan because of the need to collect and tabulate data by hand. Clearly, further research is needed in order to make a reasonable plan for utilizing the nation's limited land more efficiently. There is an urgent need to have data for J-SMSA-type statistical units collected and published by the government. This will encourage more scholars to undertake studies of human settlement and

related problems, as well as of fundamental agglomeration pro- cesses that influence the evolution of urban systems.

Changes in the Spatial Population Structure of Japan

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^{- . I 3} ^- ⁰⁶