MALAYSIAN JOURNAL OF TROPICAL GEOGRAPHY VOL. 16 DEC. 1987
REGIONAL INEQUALITIES AND DEVELOPMENT IN PENINSULAR
MALAYSIA 1970 — 1980
By Fauza Abdul Ghaffar
Regional inequalities have existed throughout the
development history of Peninsular Malaysia. The major
characteristics of regional inequalities are unequal
economic progress in the different states, differences in
the per capita Gross Domestic Product between the states,
differences in the structure of the state economy,
variations in the rate of urbanization and, in terms of
services, disparities in the standards of living arising from
the uneven distribution of basic household amenities,
particularly water supply, sewerage and electricity.
Three major causes of regional inequalities have been
identified. One of the causes is the impact of relief,
climate and distribution of natural resources as well as
the availability of infrastructure for the development of
these resources and related activities. A second major
cause may be attributed to colonial rule. British colonial
rule had a significant impact on the social, economic and
spatial structure of development which resulted in
regional inequalities. British rule was centred in the
towns, initially in the Straits Settlements (Melaka, Pulau
Pinang, Dindings and Singapore) where the population
was engaged in commercial pursuits and then in the west
coast states especially Selangor, Perak and Negeri
Sembilan where tin mining and rubber cultivation
flourished. These capital-interest enterprises led to the
control of the economy by the metropolitan power which
in turn fostered a powerful economic link of the
Peninsular economy to that of Britain, but at the expense
of internal integration of the economy in the various
states.
Mass immigration of Chinese and Indians was
encouraged by British economic policies. The policy of
economic segregation led to the concentration of the
major ethnic groups in specific economic sectors and
separate areas in the Peninsula. The Chinese concentrated
in industrial and commercial activities in the towns, the
Indians in European-owned plantations, and the Malay
farmers in the poorer, northern and eastern
states. This pattern, although less predominant, persists
until today.
The third cause of regional inequalities may be due to
insufficient attention of development planning on the
special problems of a 'plural society' (Fisk 1962) and the
spatial aspects of resource allocation. Development plans
had focussed largely on sectoral allocation of resources
and on the relatively well-developed areas of the country
(Osborn 1974).
Economic inequalities between states and ethnic
groups led to serious social implications which
constituted an indirect cause of the racial riots in May
1969. The riots forced the government to review the
nature of economic inequalities which culminated in the
introduction of the New Economic Policy embodied in
the Second Malaysia Plan 1971-1975.
The New Economic Policy recognized the deep-rooted
problem of Malay economic inferiority and attempted to
prescribe remedies. The Policy consists of two strategies,
to be achieved over a period of 20 years, namely, to
eradicate poverty by raising income levels and increasing
employment opportunities for all regardless of race, and
to accelerate the process of restructuring society so as to
reduce and eventually eliminate the identification of race
with economic function.
The New Economic Policy thus marks the beginning
of efforts in regional development through various
policies and strategies. The period 1971-80 represented
the first decade of the Outline Perspective Plan (OPP),
1971-1990, within which the objectives of the New
Economic Policy were to be realized. It was also a period
of favourable economic growth with an average per
capita GDP of 7.8 per cent per annum (Fourth Malaysian
Plan 1981-86).
This paper examines the nature, scope and pattern of
regional inequalities at the state level in the decade 19701980. The states provide an appropriate level of study as
they coincide with the characteristics of Richardson's
planning
24
FAUZA ABDUL GHAFFAR
regions (Richardson 1974). The state is the areal unit of
data compilation and for purposes of administration,
planning and resource allocation.
There are 12 states in Peninsular Malaysia which
constitute distinct geographical and administrative entities
(Fig. 1). Due to the problem of data availability, Selangor
and Federal Territory (created in 1972) are considered as
one state. Each state has its own hierarchy of villages and
towns, rural and urban sectors and exhibits a diversity of
income within its boundaries.
Fig. 1 Peninsular Malaysia: States.
An attempt is made to categorise the states in order to
obtain a clear picture of the problem of inequality for
future planning purposes.
METHODOLOGY
Due to the problem of availability, adequacy and
.reliability of data (Ghaffar, 1981), the variables used in
this study are necessarily limited in number. Nevertheless,
23 variables are selected to reflect the multi-dimensional
nature of inequality (Table 1). These variables are divided
into three groups, namely, five economic variables which
show the structure, level of economic activities, output
and income of the state, ten
1The
social variables comprising health, education and
amenities variables, and four demographic and
urbanization variables which generally reflect the total
population and its distribution.
The above variables are subjected to analysis using the
coefficient of spatial variation and Factor Analysis
techniques.
Coefficient of Spatial Variation
The aim of using the coefficient of spatial variation is to
assess the scope of relative variations between the states
for the years 1970 and 1980. For this, the Coefficient of
Spatial Variation (CSV)1 was computed for each of the
variables on the basis of two measures, the mean and the
standard deviation.
The result of the above analysis would be sufficient to
show the general trend of inequalities.
formula for Coefficient of Spatial Variation is (Standard. Deviation) 100
Mean
This ratio is similar to the one proposed by Thomson (1957).
REGIONAL INEQUALITIES & DEVELOPMENT 25
However, although this seems valid in broad terms, the
CSV may conceal important differences among the
individual states. For example, it is not possible to have
an idea of the relative position of individual states within
a hierarchy of regional development. Thus a series of
standard-scores i was computed for the variables to
provide a means to rank and classify the states on a common scale and to ascertain whether or not certain states
had become worse while others had improved their
relative positions.
THE NATURE AND SCOPE OF REGIONAL
INEQUALITIES 1970-1980
To evaluate the nature regional inequalities between
states in the period 1970-1980, the variations in the CSV
between the variables and changes in the CSV of each
variable in 1970 and 1980 are examined.
The Situation in 1970
The 1970 data (Table 2) show that the variables present
fairly high CSV indicating that inter
regional inequalities were quite conspicuous.
The economic indicators, especially variables 2 and 3,
show high CSV indicating the differences in the structure
of the economy of the states and the role of industry and
manufacturing sectors in economic development. The
CSV for variable 5, though considered low, still ranks
higher than five other indicators.
Indicators in the social sector, apart from variables 7
and 8, have uniformly lower CSV, reflecting less
variations in the availability and distribution of such
facilities from state to state. A notable feature is the very
low CSV of the education indicators. This reflects the
even distribution of education facilities and uniformity of
education standard throughout the country, thanks to the
efforts of the government in the provision of education
throughout the country.
An examination of the CSV of the variables shows
that inter-regional inequalities were high in 1970,
especially in the economic sector and the level of
urbanization.
Table 2, The Mean, Standard Deviation and Coefficient of Spatial Variation of Variables for 1970
26 FAUZA ABDUL GHAFFAR
Variables 16, 17, 18 and 19 in the service and
infrastructure sectors also exhibit high CSV. Variables 16
and 17 measure the variations in the extent of motorcar
and motorcycle ownership between the states and
variables 18 and 19 show variations in water and
electricity consumption between the states. These
variables indicate the high level of services available in
the states of the west coast states compared with the east
coast and northern part of the country.
The demographic and urbanization indicators have
high CSV, especially variable 22 (total urban population
in each state). This reflects the concentration of the urban
population in the towns of the west coast states.
Similarly, variable 23 (percentage of population living in
urban areas with a population of 10,000 or more) with
CSV of 61.98, indicates marked variations in the
distribution of population in urban and rural areas. It is
noted that three-quarters of all the towns are found in the
west coast states.
The high CSV for variables 20 and 21 indicate the
uneven distribution of population in the states. These
variables help to identify areas of sparse population
towards which population movements
may be encouraged in regional development policies.
The Situation in 1980
The 1980 data (Table 3) reveal a similar pattern of
regional inequalities as 1970. Although many indicators
point to a progress in the provision of socio-economic
facilities, the level of inequalities still remains high.
Variable 23 still leads the table, followed by three other
variables in the demographic and urbanization sector
indicating the persistence of the lop-sided distribution of
urban population throughout the country. This is followed
by indicators of the service sector which, despite
decreasing in CSV, still remain high. Education facilities
appear to be the least unequally distributed of all the
services.
The indicators in the economic sector reveal almost
identical patterns as in 1970 with variables 2 and 3
showing the highest variations. Nevertheless, though the
CSVs are high, the economic and social development
levels have improved and inter-regional inequalities have
consequently decreased in the economic sector.
Table 3. The Mean, Standard Deviation and Coefficient of Spatial Variation of the Variables for 1980
REGIONAL INEQUALITIES & DEVELOPMENT
Certain variables have recorded an increase in
inequality among which variable 5 (per capita GDP ratio
to average GDP in Malaysia), most of the demographic
and urbanisation variables and, surprisingly, the
education variables. The increase in inequality of
education facilities might be due to the growing-number
of children of school-going age in the population and the
inability in the states to match the number of teachers
with the growing enrolment in schools.
CHANGING PATTERN OF INEQUALITIES
1970-1980
Changes in the CSVs of variables in 1970 and 1980 show
that, despite remaining high, there has generally been a
decrease in the variation of most indicators. Changes in
the CSVs of the variables can be seen in Figure 2 and
Table 4.
In the economic sector, there is a relatively moderate
decrease in variables 1, 2 and 3 but substantial in variable
4. More important is the increase in variation in the
income indicator (variable 5) which clearly shows that
although there is a slight restructuring of the economy in
the states, income inequality has increased (Fig 2A).
In the demographic and urbanization sectors, the
variables yield extremely high CSVs. Except for variable
23, all the other variables register an increase in CSV
reflecting greater uneven distribution of population and
the level of urbanisation in the country (Fig. 2B).
Most of the social and infrastructure variables (Fig.
2C) show a decrease in the CSV. However, the CSV of
the service and infrastructure variables are high. In the
health sector there is also a slight decrease in CSV, and
although there is an increase in the CSV of the education
sector it is still the most widespread service available.
Fig. 2 Changes In the Economic, Demographic and Social Variables, 1970 — 1980.
28
FAUZA ABDUL GHAFFAR
Table 4 shows several features in the relative
variations of the variables. Firstly variables which record
high CSVs may register a decrease in CSV as in
variables 16, 17, 18 and 19 or an increase in CSV as in
variables 20 to 23. On the other hand there was also a
decrease in the CSV among social indicators with
moderate CSVs. Do these features have any impact on
the policy of regional development, more specifically
have government efforts in regional development been
concentrated in a limited area of socio-economic
development ?
The nature of regional inequalities is related to the
multi-dimensional aspect of development. The decade of
overall economic growth in the 1970s has indeed led to a
decrease in economic inequalities. To have a clearer
picture of the situation it would be appropriate to look at
the performance of the individual states.
RANKING AND CLASSIFICATION OF
THE STATES
The ranking and classification of individual states can
show the relative position of each state in 1970 and 1980
and how each fared in socio-economic development
during the decade. Following the work of Nacer (1979)
two methods have been used, the first one consisted of a
mere ordering of the states according to the individual
variables and the summation of their ranks. The second
and more common method applies basically the same
principles as the first one but uses all the information
available and thus allows for the cumulative effects of
the previously standardized scores.
Table 5 shows the rank of each of the states for both
the years 1970 and 1980. Several important features are
discernible. Selangor remains first on the rank for both
years with scores far ahead of the others.
Table 4. Changes in the Coefficient of Spatial Variation of Variables between 1970 and 1980
The second to sixth ranked states are formed by states in
the west coast states from Pulau Pinang in the north to
Johor in the south. The remaining states at the bottom of
the ranks are those of the north and east coast states.
Based on the ranking of the Z-scores, a classification of
the states can be made. Generally the conventional eastwest dichotomy of development levels in Peninsular
Malaysia is clearly revealed with the west coast states
being more developed than the east coast states.
The Developed States
The 1970 data show that the developed states, ranked first
to sixth, form a contiguous zone along the west coast of
the Peninsula. Based on the socio-economic indicators
used in this study, these states can be further divided into
groups according to their relative rank scores.
(i) Leading all other states by a wide margin is
Selangor/Federal Territory. This state is well
provided with social services and infrastructure and
has a high level of urbanisation, especially the
Kelang Valley where Kuala Lumpur is situated, and
forms the most industrialised state in the country.
Agriculture, on the other hand, plays a relatively
minor role in the economic development of this
state.
(ii) The west coast state of Pulau Pinang in the north and
Negeri Sembilan south of Selangor. Pulau Pinang in
recent years has grown rapidly in industrial and port
facilities.
(iii) The states of Perak, Melaka and Johor.
The Less Developed States
The states which show low values in most of the variables
constitute the less developed states. These states are found
in the northern and eastern parts of Peninsular Malaysia
where agricultural activities constitute the major economic
activity and the population is predominantly rural and
Malay. These states may be divided into two groups.
(i)
The states of Pahang and Trengganu which possess
natural resources such as forests, agricultural land and
petroleum. These states form the resource frontier
region of the country with substantial development
potentialities. Several urban centres may become
potential growth centres.
(ii) The states of Kedah, Perlis and Kelantan which form the
bottom rank of the table are rice-growing areas.
Besides relying heavily on traditional agriculture, these
states are deficient in social and infrastructure
facilities.
In 1980, the developed and less-developed states remain
identical but with Pahang joining the rank of the former.
Selangor/Federal Territory still dominates, followed by
Pulau Pinang, Negeri Sembilan, Melaka, Perak, Johor,
Pahang, Kelantan, Kedah and Perlis. Pulau Pinang in
particular has experienced rapid growth. Despite certain
improvements, Kelantan, Kedah and Perlis remain the
least developed of the states. Figure 3 reveals the increase
or decrease in the absolute scores of each state and the
gradient of inequality over the decade 1970-1980.
THE-SENSITIVE INDICATORS' AND THEIR
EVOLUTION
Improvement in the level of development in the less
developed states has not reduced the extent of regional
inequalities. This is because the developed states have
also undergone development. This section will identify
certain sensitive indicators which are common to the
less developed states and consequently to specify the
sectors which need particular efforts in development
planning.
Several methods can be used to determine the most
sensitive indicators in the less developed states. A
method is used by Nacer (1979) where concentration is
made on the grouping of the regions and look at the
variables which record the lowest rank. This is then
expressed as a percentage of the lowest theoretical
mark. In this study however, the method employed is
by examining the ranks of the Z-scores of each of the
indicators in the four less developed states. The rank of
each indicator is noted, from which indicators which
forms the lowest rank in the 4 states are recorded. If an
indicator is ranked 8th, 9th, 10th and llth in each of the
states, then it is considered a sensitive indicator.
Fig. 3 Gradient of Regional Inequalities, 1970— 1980.
One important feature depicted in Figures 3 and 4 is that there is
no state belonging to the class -5.00 to -9.99 in 1980. This is the
second group of the less-developed states which in 1970 consisted
of the states of Kedah and Perlis. In 1980, Kedah is placed in a class
higher and Perlis slips into a class lower than the class - 5.00 to 9.99.
The performance of the states based on the set of socio-economic
indicators shows significant spatial inequalities in the level of
development. Although there have been several shifts in the rank of
some states in the 1970s, these occur within a given category of
development status. Despite a decrease in variation in most of the
indicators, regional inequalities are still consi derable in 1980.
Several indicators in almost every sector are very
useful in defining the less developed states. The 1970
Z-scores reveal that variables 2. 3 and 5 of the
economic sectors, and variables 6, 7, 8, 9, 16. 17 and
23 of the social, infrastructure and urbanisation
indicators are found to be sensitive. Variables relating
to education are the least sensitive of all because of the
fairly equal level of provision of educational facilities
in all the states. In 1970, variable 8 (the number of
person per registered dentist) is found to be the most
sensitive indicator in the less developed states.
The 1980 Z-scores reveal almost similar numbers
and type of sensitive indicators. Other than variable 8.
which shows an improvement, the income and
urbanization indicators are the most sensitive of all.
Some indicators become more sensitive, for example,
variable 6 (infant mortality rate) and the infrastructure
variables, while variables 7 and 9 become less
sensitive. However the impact of these changes is of
little consequence.
The above analysis shows certain indicators are
discriminatory in defining the less developed states. In
the decade 1970-1980 the same indicators are
responsible for the low level of development in the less
developed states. These indicators are represented by
almost all sectors, reflecting again the multidimensional aspect of regional inequalities. The
implication is that there is a need to adopt an
intergrated approach in regional development in order
to reduce the nature and scope of inequalities between
the developed and less developed states.
REGIONAL INEQUALITIES & DEVELOPMENT 31
Fig. 4 Regions based on Z-Scores A. 1970 and B. 1980.
.
FACTOR ANALYSIS: THE TREND AND
PATTERN OF INEQUALITIES
In this study, Factor Analysis is used to identify patterns of
relationship between variables and to gain an idea of regional
variations in socio-economic development in the country.
The Situation in 1970
The correlation matrix in Table 6 shows a relatively large
number of high and positive coefficients, particularly variables 5,
16, 17, 18, 19 and 23 which are highly correlated with each
other. These variables refer to income, infrastructure, services
and the level of urbanisation. Note that variable 13 and 14
(education variables) show weak correlation with all other
variables.
The factor analysis produces three factors as the more significant
ones in that they have eigen values of more than 1.0. These
factors account for 83.7 per cent of the total variance.
Table 7 shows that Factor 1 loads heavily on almost every
variable except 9, 13 and 14 which are social indicators. Factor 1
explains 57.3 per cent of the total variance with an eigen value of
5.2, Factor 2 loads heavily on variable 14 and accounts for 14.5
per cent of total variance with an eigen value of 1.3 and factor 3
loads heavily on variable 13 and explains 12 per cent of total
variance
with
an
eigen
value
of
1.0
Since Factor 1 represents a major proportion of the total
variance and appears to some extent to capture at least the
interlocking nature of socio-economic development, focus of
attention is concentrated on the interpretation of this particular
factor. From Table 8 it is obvious that there is wide variation in
the factor loadings. Variables 5, 16. 17. 18, 19 and 23 have the
highest factor loadings and these are the variables with high
CSVs, indicating the high degree of variation of these variables
between the states. The least sensitive variables are 13 and 14
(the education variables) which describe the second and third
factors and do not reveal the same regional pattern as the other
indicators.
Factor scores on the Factor 1 are computed (Table 9) to gain
some idea of the regional variations in Malaysian socioeconomic development. It can be seen that regional inequalities
at the beginning of the decade was high. Generally, the ranking
and grouping of the states are identical with those derived from
the earlier analysis, with the west coast states occupying the top
of the table and the northern and east coast states at the bottom.
Based on the factor scores four major regions are demorcated for
1970, with Selangor forming the most developed region. The
next region of moderate development comprise Pulau Pinang,
Perak. Negri Sembilan, Melaka, Johor and Pahang. Of the two
less developed regions, one comprises Trengganu and Kedah and
the other, the least developed region of all. comprises Perils and
Kelantan. The results of factor analysis again emphasize the eastwest dichotomy in the level of socio-economic development in
Peninsular Malaysia (Figure 5).
32 FAUZA ABDUL GHAFFAR
Table 6. Correlation Matrix for Selected Variables for
1970
VARIABLE
5
9
13
14
16
17
18
19
23
5
9
1.00
0.50
-0.06
0.16
0.90
0.79
0.81
0.92
0.82
13
0.50
1.00
0.01
-0.21
0.52
0.51
0.32
0.57
0.14
-0.6
0.01
1.00
0.10
0.07
0.04
0.09
-0.11
-0.15
14
0.16
-0.21
0.10
1.00
0.27
0.30
0.14
-0.01
0.18
16
0.90
0.51
0.07
0.27
1.00
0.91
0.79
0.75
-0.77
17
18
0.79
0.32
0.04
0.31
0.91
1.00
0.52
0.70
0.62
19
0.81
0.32
0.09
0.14
0.79
0.52
1.00
0.63
0.86
23
0.92
0.57
-0.11
-0.01
0.75
0.70
0.63
1.00
0.71
0.82
0.14
-0.15
0.18
0.77
0.62
0.86
0.71
1.00
Table 7. Rotated Factor Loadings for Selected Variables
for 1970
FACTOR 1
VARIABLES
V5
% Per capital GDP ratio to Malaysian
V9
V13
V14
V16
V17
V18
V19
V23
average
Persons/acute hospital bed
Transitional rate primary/Form I
Transitional rate lower secondary/Form V
Motocars/1000 population
Motocycles/1000 population
Per capita electricity consumption
Per capita water consumption
% of urban population
0.99
0.49
0.04
0.25
0.96
0.86
0.85
0.87
0.89
Table 8. Factor Loadings
on Factor 1 for Selected
Variables for 1970
VARIABLES
V5
LOADINGS ON
FACTOR 1
% Per capita GDP ratio to
Malaysian average
Persons/acute hospital bed
0.97
V13 Transitional rate primary/ Form 1
0.04
V14 Transitional rate lower
secondary/Form V
V16 Motocars per 1000 population
0.24
0.96
V17 Motocycles per 1000 population
0.86
V18 Per capita electricity consumption
0.85
V19 Per capita water consumption
V23 % of urban population
0.87
0.88
V9
FACTOR 2
0.49
FACTOR 3
-0.09
-0.718
0.07
0.80
-0.00
-0.02
0.08
-0.29
0.20
-0.45
0.22
0.93
0.22
0.16
0.19
0.00
-0.10
-0.26
The Situation in 1980
To provide comparative results with the 1970 data, a matrix
of correlation coefficients is computed for the nine selected
variables based on the 1980 data.
The correlation matrix in Table 10 shows a number of
high and positive correlation. Variables 16, 17. 18, 19 and 23
are highly correlated with one another reflecting the interrelationship between the economic, infrastructure and
services and the urbanisation indicators. Variable 23
(level of urbanisation) shows a weak and decreasing
correlation with most other variables except variables 5
(income)and 18 (per capita electricity consumption). This
might be due to the improvement in the distribution and
provision of facilities and services in parts of the country outside the highly urbanised areas.
As in 1970, three significant factors account for 86.4 per
cent of the total variance. Factor 1 loads heavily on most
variables except 9, 13, 14 and 17 and accounts for 52.7 per
cent of the total variance. Factor 2 loads heavily on variables
9 and 17 and Factor 3 on variables 13 and 14 (Table11).
An analysis based on the interpretation of Factor 1 shows
that there are wide variations in the factor loadings. Variable
5 has the highest factor loadings followed by variables 18,
23, 19 and 16. The loadings on variable 17 felled from 0.86
to 0.40, possibly caused by an increase in the ownership of
motorcycles especially in rural areas in all the states. The
variables with the highest factor loadings are those having a
high CSV in the earlier analysis and those with low factor
loadings coincide with those of low CSVs (Table 12).
Factor scores computed on Factor 1 (Table 13) to facilitate
comparison with 1970 show that, although not quite similar
to the rankings based on the Z-scores, the regions obtained are
identical. Selangor and the rest of the west coast states form the
developed regions and the north and east coast states the less
developed ones. Perlis replaces Kelantan as the least developed
state. An improvement in relative position of Trengganu is
notable, a fact attributed to the production of petroleum off-shore
which
began
in
the
late1970s
REGIONAL INEQUALITIES & DEVELOPMENT 33
Table 9. Factor Scores for
the States, 1970
STATES
FACTOR SCORES
Selangor/Federal Territory
+2.26
Negeri Sembilan
Pulau Pinang
Perak
Pahang
Johor
Melaka
Terengganu
Kedah
Perlis
Kelantan
+0.57
+0.44
+0.38
+0.31
+0.12
+0.69
-0.69
- 0.86
-1.19
•-1.25
DISCUSSION
Although the techniques of CSV and factor analysis do not
produce exactly similar results, they do provide a common
understanding to the nature and scope of the regional-inequality
problem in the states in Peninsular Malaysia and the grouping of
these states into regions according to the level of socio economic development.
An examination of the regional inequality problem in the early
stage of national development in Peninsular Malaysia has led to
the hypothesis that regional inequalities, unless checked by
strong government intervention are likely to increase in the
course of development.
Although plagued with problems in implementation, several
of the regional development policies can be considered to have
attained some success in increasing the economic as well as
social development level in most of the states in Peninsular
Malaysia. This shows that government policies, to a certain
extent have been decisive in contributing towards overall
development and at the same time arrested further widening of
economic inequalities between the states.
Despite this relative success, the level of inequalities is still
gloring and, more important, part of the improvement may be
due to different rates of population growth between the states.
The latter may imply that relative decrease in the inter-regional
level of inequalities may have been achieved at the expense of
corresponding deterioration of the intra-regional and rural-urban
levels.
Over the decade of overall economic growth and
government intervention, there-has been a decrease in the level
of economic inequalities. Inequalities were already conspicuous
since the beginning of modern economic development in
Peninsular Malaysia and future widening in inequalities were,
arguably,
difficult
to
continue
indefinitely.
Fig. 5 Regions based on Factor Scores A. 1970 and B. 1980.
REGIONAL INEQUALITIES & DEVELOPMENT 35
Table 13. Factor Scores for
the States, 1980
STATES
FACTOR SCORES
Selangor
+2.21
Negeri Sembilan
Pulau Pinang
Perak
Pahang
Johor
Melaka
Terengganu
Kedah
Perlis
Kelantan
-0.15
+1.30
-0.22
-0.16
+0.09
-0.01
-0.01
-0.82
-1.38
-0.84
Moreover, investments made to reduce the gap between the
developed and less developed states since independence in 1957
had inevitably improved the overall socio-economic level of all the
states. Additionally, various programmes had been designed to
distribute as wide as possible basic amenities and facilities to improve living standards and the quality of life. Over the decade,
these had cumulative impacts on improving socio-economic
conditions in the less developed states. Finally official intervention
in regional development in favour of the less developed states
provided a sufficient base for further development and
improvement in socio-economic conditions leading to a reduction
in the gap in development between the states in the late 1970s.
CONCLUSION
This study shows that while development has been achieved in the
less developed states, equal or even more rapid development has
occurred in the developed states to sustain a disturbing level of
regional inequalities.
It is argued that although regional development planning has
increasingly become an important part of national planning, there
seems to be an inherent conflict between transferring resources to
poorer regions and the national development goals of political and
social integration. While different kinds of projects are
implemented in different states, a more comprehensive policy
framework is needed for regional planning. Regional plans in the
country have drawn on data on the distribution of natural and
human resources but generally in an ad hoc manner. It is seen that
while the national plan recognizes the goal of general economic
and regional balance to overcome such difference the planning
process is still geared towards the sectoral rather than a regional
approach.
Furthermore, the ad hoc nature of regional development
planning has led to several problems in regional plan
formulation and implementation. For example, development
plans tend to compete with one another often resulting in the
neglect of opportunities for geographic specialisation and the
disregard for development in certain regions. These problems
and the fact that several of the •sensitive' indicators were highly
discriminatory with regard to the less-developed states, support
the need for an intergrated approach to regional development
planning.
The adoption of the intergrated approach requires the
establishment of a regional planning machinery and the
introduction of certain strategies applicable to both national
and regional planning. There is a need for a policy aimed at
achieving a strong and favourable growth of the national
economy to benefit the entire population. This implies a
regional approach to planning rather than the sectoral
approach. To achieve the stated goals in the New Economic
Policy, it is relevant that spatial aspects of development be
taken into proper account. This will in turn necessitate an
adequate spatial framework in the planning process. This
spatial framework may be in the form of areal division of the
country into various homogeneous regions according to the
level of or potentiality for development.
The identification of the 'development areas' and the
grouping of the states into developed and less-developed ones
are based on the per capita GDP of each state. It is stressed that
a wider range of socio-economic indicators be used to delineate
these groupings. An important measure in moving towards an
intergrated approach of regional development planning
involves the reorganisation and strengthening of the planning
machinery in the form of a Regional Planning Department.
This would replace the present structure of regional planning
involving- many agencies at different levels but where the
power of decision-making rests with the Federal level. Policies
on regional development will be decided by a council
consisting of members of the highest political authority from
both the Federal and state governments. Active involvement of
both Federal and state authorities will allow decentralisation of
the regional planning process and a wider participation of
different interests to work towards the stated goals of national
development.
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