The Typology of Human Development and Factors That

Influence It in West Sumatera

Erni Febrina Harahap, Ayudia Pratiwi, and Kasman Karimi

Development Economic, Economic Faculty and Business,

Universitas Bung Hatta, Padang, Indonesia

kasman_karimi@yahoo.com

Abstract. Human development is one of important indicators for the progress of

a country if it has the quality. The concept of human development includes 4

important components, namely equality in gaining access to economic and

political resources, productivity which is an effort to increase economic activity,

empowerment which is an effort to build the quality of society by increasing the

potential and ability of them, and sustainable which means that in managing

human development capital, it must be able to be utilized in subsequent periods.

Human development is a process of improving human ability to develop choices

and opportunities. The purpose of this study is to analyze the typology of human

development in West Sumatra, and the effect of poverty levels, economic growth,

government spending on education and health sectors to the human development

index. The analytical method used in this research is using Klassen typology and

panel data regression analysis, covering 19 districts and cities in West Sumatra

for 7 years of observation, (2010-2016) so that the total number is 133. The data

used in this study are secondary data sourced from the Central Statistics Agency

(BPS), the Directorate General of Fiscal Balance (DJPK), literature, and articles

related to this study.

Keywords: Human development index ꞏ Klassen typology ꞏ Economic growth ꞏ

Poverty ꞏ Government expenditure

1 Introduction

Development is a multidimensional process that includes changes in social structure,

attitudes of society, national institutions, pursuing accelerated economic growth,

addressing income inequality, and alleviating poverty (Todaro and Smith, 2006; Erni

Febrina, 2018). As a process, development is of course carried out by looking at existing

needs while responding to changes that occur in society and the demands of time shift

due to the development of civilization, social systems, and more advanced technology.

The development paradigm that is currently developing is economic growth as

measured by human development as seen by the level of quality of human life as

measured through the quality of the level of education, health and purchasing power.

Poverty can be a serious effect on human development because the problem of

poverty is a complex problem that actually starts from the inability of people's

purchasing power to meet their basic needs and other needs such as education and

health. Another factor affecting the human development index is economic growth.

Harahap, E., Pratiwi, A. and Karimi, K.

The Typology of Human Development and Factors That Inﬂuence It in West Sumatera.

DOI: 10.5220/0010524000002900

In Proceedings of the 20th Malaysia Indonesia International Conference on Economics, Management and Accounting (MIICEMA 2019), pages 619-629

ISBN: 978-989-758-582-1; ISSN: 2655-9064

619

Economic growth shows the extent to which economic activity can generate additional

income in a given period. The economy is considered to experience growth when all

real service rewards for the use of factors of production in a certain year are greater

than the previous year. Government expenditure in the education and health sector is

very important in improving the quality of human resources. The better health services

and increasing government attention to the quality and quantity of education

opportunities for citizens will improve the quality of human resources. And this will

increase the value added of the production of goods and services which will also

increase economic growth in a region.

2 Literature Review

2.1 Human Development

Human development is a process of enlarging people’s choices. The concept or

definition of human development basically covers a very broad dimension of

development. In the concept of human development, development should be analyzed

and understood from its human standpoint, not just from its economic growth. Human

development includes the development of population as the center of attention where

not only the development of the population in the economic field, but as a whole

includes the ability to optimize productivity, equity, sustainability and empowerment.

2.2 Poverty

Poverty is the inability to meet minimum living standards. The problem of low standard

of living is related to the amount of income, inadequate housing, poor health and health

services, low level of education of the community so that it results in low human

resources and increased unemployment (Kuncoro, 2000). The cause of poverty in

economic terms is a result of the low quality of human resources, which is caused by

low education, and results in low productivity so that wages are also low. This also

results in hunger, malnutrition, discrimination, low participation in the decision making

process and ultimately the quality of human resources will also be low.

2.3 Economic Growth

Economic Growth is one indicator used to measure a country's economic performance.

In actual economic activity, economic growth means physical economic development.

Some physical economic developments that occur in a country are the increased

production of goods and services, and the development of infrastructure. All of this is

usually measured from the development of real national income achieved by a country

in a certain period. With the increase in economic growth, it will increase the income

per capita of the community so that the HDI in one region actually also increases.

Where the higher the national or regional income, the greater the hope for opening new

production capacities which of course will absorb new labor. High income is reflected

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in high per capita income and positive and meaningful growth. Then the relatively

better economic growth, the greater the hope not to be unemployed so that it will

encourage the distribution of per capita income so as to encourage an increase in the

human development index (Ranis and Steward (2000); Oluwatobi and Olurinola

(2011); Erni Febrina, (2017)).

2.4 Government Expenditures in the Education and Health Sector

Investment in terms of education is absolutely necessary, the government must be able

to build a means and a good education system. The budget allocation for government

expenditure on education is a tangible manifestation of investment to increase

community productivity. Development spending on the development sector can be

allocated to provide educational infrastructure and provide educational services to the

entire population of Indonesia equally. The education budget of 20 percent of the state

budget is a form of government realization to improve education (Anisa, et all, 2018).

Government spending on the education sector will affect developments in the education

sector by increasing the number of students who are able to complete their education to

a higher level. The higher the average level of knowledge and skills possessed by the

community, the easier it is for every individual of working age to understand, apply and

get results from technological advancements and ultimately improve the nation's

economic and living standards. A nation must increase investment in education and

health to achieve development (Tun Lin Moe, 2008).

Government expenditure on the health sector is an effort to fulfill one of the basic

rights of the people, namely the right to obtain health services in accordance with the

1945 Constitution Article 28 H paragraph (1) and UU No. 23 concerning Health

(Kuncoro, 2013). Human quality can also be seen from the side of health where health

is one of the factors that influence human resources, in other words health aspects also

influence human quality. Lack of calories, nutrition, or low health status for the

population will result in low human quality with mental retardation. Government

expenditure in the health sector seeks to fulfill one of the basic rights in obtaining health

services in the form of health facilities and services which are also a prerequisite for

increasing community productivity.

3 Methodology

3.1 Klassen Typology

Each region has different economic progress and growth. There are regions that are able

to spur economic activities so that they can grow rapidly and there are also regions

where the economic cycle has stagnated at one point or even grown negatively. To be

able to compare the level of progress of an area with other regions in the same scope of

reference, it can be used Klassen Typology as an analysis tool.

The Typology of Human Development and Factors That Inﬂuence It in West Sumatera

621

yi > y yi < y

ri > r

uadrant 1

Fast-Forward and

Fast-Growing Areas

uadrant 2

The Fast Developing Areas

ri < r

uadrant 3

Depressed Areas

uadrant 4

relatively disadvantaged area

where: ri = Economic growth rate of region i

yi= IPM region i

r = Economic growth rate of reference region

y = IPM reference region

Fig. 1. Regional Classification According to Klassen Typological Analysis.

3.2 Unit Root Test

The basic idea of the unit root test in the panel data is the development of the unit root

test in times series, which can be explained in the model:

𝑌



 𝜌



𝑌



 𝑋



𝜎



 𝜀



(1)

i = 1, 2, ...., n (number of individu)

t = 1, 2, ...., t (number of time)

The ADF root unit test formula is:

∆𝑌



 ∝ 𝑌



1 𝛴𝛽𝐹



1𝑡𝑓 ∆𝑌



 𝑋



𝜀



(2)

Assumed that α = ρ - 1 with lag pi and varies between cross sections.

3.3 Cointegration Test

Cointegration is a long-term relationship between variables which although not

individually stationary, but the linear combination between these variables becomes

stationary

𝑌



 ∝



 𝛿



 𝛽



𝑋



 𝛽



𝑋



 … 𝛽



𝑋



 𝜀



(3)

Residual:

𝜀



 𝜌



𝜀



𝑈



(4)

𝜀



 𝜌



𝜀



𝛴





𝜑



∆𝜀



𝑈



(5)

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622

3.4 Panel Multiple Regression

Model: 𝐼𝑃𝑀



= 𝛽



+ 𝛽



𝑇𝐾𝑀



+ 𝛽



𝑃𝐸



+ 𝛽



𝑃𝑃𝑃



+ 𝑃𝑃𝐾



 𝜀



where: IPM = Human Development Index

TKM = Poverty Rate

PE = Economic Growth

PPP = Government Expenditure on Education Sector

PPK = Government Expenditure on Health Sector

i = regency / city i

t = year of observation (2010-2016)

𝛽



= Constants

𝛽



, 𝛽



, 𝛽



, 𝛽



= Coefficients of independent variables

𝜀



= Error term

4 Result and Discussion

4.1 Klassen Typology

Klassen's typology classifies regions based on two characteristics possessed by the area,

namely the human development index and the rate of economic growth (Tun Lin Moe,

2008). The results of the Klassen typology calculation can be seen in Table 2 below.

yi > y yi < y

ri > r

Quadrant 1

Fast-Forward and

Fast-Growing

Areas

(Padang, Solok

City, Payakumbuh,

Padang Panjang,

and Bukittinggi)

uadrant 2

The Fast Developing Areas

(Limapuluh Kota,

Dharmasraya, Pasaman Barat)

ri < r

Quadrant 3

Depressed Areas

(Sawahlunto, Pariaman)

uadrant 4

Relatively Disadvantaged

Area

(Mentawai islands, Pesisir

Selatan, Solok Regency,

Sijunjung, Tanah Datar,

Padang Pariaman, Agam,

Pasaman, Solok Selatan)

Fig. 2. Regional Classification According to Klassen's Typological Analysis.

The Typology of Human Development and Factors That Inﬂuence It in West Sumatera

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4.2 Unit Root Test

In the unit root test at level (Table 1) there are still not stationary, the unit root test is

done with the first difference in table 2.

Table 1. Unit Root Test Results at Level.

Variable Probability Description

LIPM 0.0604 Not Stasionary

LTKM 0.0000 Stasionary

LPE 0.0000 Stasionary

LPPP 0.0000 Stasionary

LPPK 0.5289 Not Stasionary

Table 2. Unit Root Test Results at First Difference.

Variable Probability Description

LIPM 0.0000 Stasionary

LPPK 0.0000 Stasionary

4.3 Cointegration Test

The next test is Kao Residual Cointegration Test to conclude whether or not there is

cointegration.

Table 3. Kao Cointegration Test Results.

Based on the results of Kao Test (Baltagi, 2005) shows the equation model has a

probability of 0.0006 which is smaller than the value of α 0.05. Therefore, based on

these values it can be concluded that all the variables tested in this study are

cointegrated or have a long-term equilibrium relationship.

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Table 4. Estimation Results of Panel Multiple Regression Equation.



4.4 Chow Test

To compare or choose which model is best between Common Effect and Fixed Effect

then Chow test is done.

Table 5. Chow Test Result.

Based on the above estimate result note the probability value (Prob.) For cross-section

Chi-square. If the value > 0.05 (specified at the beginning as the level of significance

or alpha) then the selected model is Common Effect, but if < 0.05 then the selected

model Fixed Effect. In the above estimation results show that the value of Prob. Cross-

section Chi-square of 0.0000 whose value < 0.05 so it can be concluded that the Fixed

Effect model is more appropriate than the Common Effect model.

The Typology of Human Development and Factors That Inﬂuence It in West Sumatera

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4.5 Hausman Test

Haustman Test aims to compare or choose which model is the best between Fixed

Effect and Random Effect. Then Hausman test with the following estimation results:

Table 6. Hausman Test Result.

Based on the above estimation we can see the probability value (Prob.) Cross-section

random if the value > 0.05 then the selected model is Random Effect, but if < 0.05 then

the selected is Fixed Effect Model.

5 Classic Assumption Test

5.1 Normality Test

Normality test to test whether in the regression model, the data used has a normal

distribution or not. The good data are those with normal or near-normal distributions.

Where if the probability is greater than the specified alpha then the residual is normally

distributed. If the probability is small from the specified alpha then the residual is not

normally distributed, Baltagi (2005). Normality Test Results. Based on Jarque-Bera

statistic test, the statistic value is 6,186374 with probability that is 0,045357 < alpha

0,05 hence can be concluded that the residual is normally distributed.

Fig. 3. Normality Test.

5.2 Multicollinearity Test

Multicollinearity test is the situation of correlation of independent variables among

each other. Multicollinearity test aims to test whether in the regression model found a

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correlation between independent variables. A good regression model should not be

correlated between independent variables.

Based on the estimation with multicollinearity test can be seen that the correlation

coefficient value is smaller than 0.80 while the rule of thumbs rough rule if the

correlation coefficient < 0.80 is assumed there is no multicollinearity. So in this study

can be concluded that all independent variables used in this study there is no problem

multicollinearity in the model.

Table 7. Multicollinearity Test Results.

5.3 Heteroscedasticity Test

In this study heteroscedasticity test using Glejser method with the result is as follows

(table 8), Based on the estimation with heteroscedasticity test by looking at the t test

the coefficient of LTKM, LPE, LPPP, LPPK individually did not significantly affect

the dependent variable RESABS, with probability value > alpha = 0.05. Based on these

results, it can be concluded that in the model used there is no problem of

heteroscedasticity.

Table 8. Heteroscedasticity Test Results.

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6 Conclusion

1. Typology Klassen classifies Regencies and Cities in West Sumatera there are four

characteristics, namely, First, Fast-Forward and Fast-Growing Areas (Quadrant I):

Padang, Solok City, Padang Panjang, Bukittinggi, and Payakumbuh. Second, the

Fast Developing Areas (Quadrant II): Limapuluh Kota, Dharmasraya, and Pasaman

Barat. Third, Depressed Areas (Quadrant III): Sawahlunto and Pariaman. And

Fourth, Relatively Disadvantaged Areas (Quadrant IV) include the Mentawai

Islands, Pesisir Selatan, Solok, Sijunjung, Tanah Datar, Padang Pariaman, Agam,

Pasaman and Solok Selatan.

2. Based on the result of regression equation of panel data of independent variable of

poverty level have negative and significant influence to index of human

development. If the level of poverty declines, will increase the human development

index. This is in accordance with Bauer's theory in Ifionu & Nteegah (2013).

Likewise, government health expenditure variables that have a positive and

significant impact on the human development index. If public health spending

increases, will be reflected in an increase in the human development index. This is

in accordance with the theory of Strauss and Thomas in Todaro (2003). While the

variable of economic growth have negative and significant effect to human

development index. The results of this analysis do not fit with Harrod-Domar's

theory in Todaro (2015). This is because the increase in the index of human

development is not solely on economic growth. In order for economic growth in

line with human development, economic growth must be accompanied by equitable

development. With equity of development there is a guarantee that all residents can

enjoy the results of development.

Government expenditures on education sector have a negative and significant

impact on the human development index. If government spending in the education

sector increases then the human development index will decline. The results of this

analysis do not match the theory put forward by Ejiogu, (2011). This is caused by

the poor education system and the ineffectiveness of the government budget

allocation in the education sector, especially related to the high number of

corruption. Where there is a tendency for corruption to occur on the side of school

facilities and infrastructure. (ICW, 2015).

3. From F-Statistic test result of regression Probability F-Statistic 0,000000 and this

result compared with alpha 5% (0.05) so it can be concluded as a whole independent

variable have significant effect to index of human development.

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