Analysis of Determinants Human Development Index in ASEAN

Countries

Khubbi Abdillah

, Alfin Maulana

and Aminatuzzuhro

Department of Economic Development, Faculty of Economics and Business, Universitas Wijaya Putra, Indonesia

Departement of Accounting, Faculty of Economics and Business, Universitas Wijaya Putra, Jl. Raya Benowo 1-3

Surabaya, Indonesia

Keywords: Human Development Index, ASEAN Countries, Panel Regression.

Abstract: The Human Development Index (HDI) is an important variable in improving people's quality of life, measured

by the level of education, health, and income per capita. This research considers aspects of economic

variables, such as foreign direct investment (FDI), unemployment, and economic growth, with the aim of

analyzing the determinants of HDI in 11 ASEAN countries from 2018 to 2021. The analysis technique of this

study uses panel data regression with the help of eviews software version 12. The results of the study

concluded that economic growth, FDI have a significant positive effect on HDI. while the unemployment rate

has no significant effect on HDI. The policy recommendation in this study is that the government should

increase employment opportunities by opening new jobs through foreign direct investment, which will

increase GDP and subsequently improve HDI.

1 INTRODUCTION

Human development index (HDI) is an indicator used

to measure the progress of a country in terms of social

and economic dimensions (Shah, 2016). The social

and economic success of a country's development

hinges on human development. Human development

is not only about increasing human choices such as

human rights, freedom of speech, ability to work, and

the opportunity to live longer with good health, and

think creatively. UNDP developed the HDI concept

to assess human well-being from a broader

perspective, beyond the income generated by society

(Sofilda et al., 2015).

Previous studies have been conducted by previous

researchers on the Human Development Index in

several journals. With the existence of previous study

so that authors make rationale for compiling this

study. The results of studies by Handalani (2018),

Fadillah & Setiartiti (2021), and Dzulqornain & Iriani

(2022) conclude that economic growth has a

significant impact on the human development index.

According to study Rohmah & Wicaksana (2021), to

increase the human development index, it is

necessary to identify the problems faced and make

policies to increase the human development index by

encouraging higher economic growth. The study of

Sumiyarti and Handayani (2022) revealed various

outcomes. the research results show that economic

growth has not been able to drive growth in 34

provinces in Indonesia. Sumiyarti & Handayani

(2022) adds that the success of building welfare

(HDI) is determined by how much the government's

commitment as a regulator and provider of

infrastructure to achieve a modern economy, improve

the quality of life and human resources.

The results of the study conducted by Sumiyarti

and Handayani (2022) concluded that foreign

investment has a positive and significant impact on

the human development index. while studies

Sumiyarti & Handayani (2022), Arisman (2018),

show that the unemployment rate has significant

negative effect on the human development index. But,

Sofilda et al., (2015) conclude that the unemployment

rate has no significant effect on the human

development index. according to Sangaji (2016),

public policies implemented by the government must

be able to reduce the poverty rate by creating jobs

through pro jobs so that the unemployment rate

decreases.

The findings from Elistia & Syahzuni (2018)

show that economic growth as measured by GDP per

capita has a very strong positive correlation above 0,8

142

Abdillah, K., Maulana, A. and Aminatuzzuhro, .

Analysis of Determinants Human Development Index in ASEAN Countries.

DOI: 10.5220/0012649100003798

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd Maritime, Economics and Business International Conference (MEBIC 2023) - Sustainable Recovery: Green Economy Based Action, pages 142-146

ISBN: 978-989-758-704-7

and significant at the α = 1% level with the Human

Development Index which is an indicator of welfare

in 10 ASEAN countries from 2010 to 2016, except

Brunei Darussalam which has a strong positive and

significant correlation of 0,76. In contrast to

Simamora et al., (2022) who conducted research on

the relationship between HDI and economic growth

in districts/cities of East Kalimantan Province in 2010

– 2021 using the Klassen Typology approach,

cointegration, and Granger causality relationships.

The research results concluded that only 3 regions

consisting of 1 district and 2 cities were in quadrant I

of the Klassen Typology, namely the correlation

between growth and HDI was positive. The long-term

relationship between economic growth and HDI is

evident. In addition, the Granger causality results

show a one-way relationship, namely that HDI has an

impact on growth.

Source: UNDP (2023), Processed Data.

Figure 1: Human Development Index in ASEAN 2018 –

2021.

Based on Figure 1, the Human Development

Index in ASEAN countries varies and increases

yearly, except for 2021. Almost all ASEAN countries

experienced a decline in Human Development Index

(HDI), except for Singapore. Singapore is an ASEAN

country that has the highest average HDI score,

followed by Brunei Darussalam, Thailand, Malaysia,

and Indonesia. While the lowest HDI is owned by

Timor Leste.

Feriyanto (2016) examined how labor, growth,

and investment (both domestic and foreign) affect

HDI in 33 provinces from 2006 to 2013 using a fixed-

effect model. The research results concluded that

labor, domestic investment, FDI have a positive effect

on HDI. Meanwhile, economic growth hasn’t effect

on HDI. Furthermore, Anindhita and Hasbi (2022)

examined the causality relationship and multiple

regression between economic growth and HDI in

Gorontalo Province between 2011 and 2022 using 40

samples. The findings conclude that economic growth

and HDI are stationary at the 1

difference level and

have a cointegration relationship at the α = 5% level.

The results of the causality test show that economic

growth and HDI have a two-way relationship or

influence each other.

The aim of this study is to examine the factors that

affecting the Human Development Index in 11

ASEAN countries in 2018 – 2021. For this aim, panel

data regression can be used, along with a combination

of time series and cross-sectional data. Independent

variable in this study, include economic growth,

foreign direct investment, and unemployment rate.

2 RESEARCH METODOLOGY

The data secondary used taken from World

Development Indicators (WDI) and United Nations

Development Programme (UNDP). Research objects

taken from 11 countries namely: Indonesia, Malaysia,

Singapore, Philippines, Thailand, Brunei

Darussalam, Vietnam, Laos, Myanmar, Cambodia,

Timor Leste. The data required include: Human

Development Index (HDI) from UNDP (2023), GDP

per capita growth (annual %), Foreign Direct

Investment (FDI) net inflows (% of GDP),

unemployment rate (% of total labor force) (World

Bank, 2023).

Panel data regression was used to analyze

relationships between dependent and independent

variables using pooled data. HDI was the dependent

variables. While the independent variables in this

study were economic growth, FDI, and

unemployment. This study sample from 2018 until

2021. Panel data regression has three model stages:

common effect model (CEM), fixed effect model

(FEM), and random effect model (REM). CEM has

explanatory variables that are not influenced by error

term. Meanwhile, FEM assumes different intercepts

and REM has error term that are not correlatied with

each other and more consistent than CEM.

However, in panel data regression, there are two

tests, namely Chow test (to select CEM nad FEM)

and Hausman test (to select FEM and REM). The best

model is chosen to interpret the analysis results based

on the existing test results. The mathematical

equation that used in this study as follow:

HDI

= α

+ β

GDP

+ β

FDI

+ β

UNEMP

+ ε

(1)

Where:

HDI = Human development index

0,2

0,4

0,6

0,8

2018 2019 2020 2021

Indonesia

Malaysia

Singapore

Philippines

Analysis of Determinants Human Development Index in ASEAN Countries

143

GDP = Economic Growth

FDI = Foreign direct investment

UNEMP = Unemployment rate

3 RESULTS AND DISCUSSION

According to Figure 2, economic growth in ASEAN

countries tends to fluctuate, and even decline,

especially during the COVID-19 outbreak. Almost all

countries experienced minus (-) growth during covid

in 2020, except Brunei Darussalam and Vietnam.

Timor Leste has the highest average economic growth

of 29,93 percent. The reason for this is that the

country is considered a new country and is currently

in the process of development.

Figure 2: FDI in ASEAN 2018 – 2021.

Based on Figure 2, Foreign Direct Investment

(FDI) in ASEAN tends to increase. The country with

the highest average FDI is Singapore, with 26.17

percent. Then, followed by Cambodia, Lao, and

Vietnam. The remaining 8 countries have an average

FDI below 4 percent. The country that has the lowest

average FDI is Thailand. FDI is an important

component in encouraging an increase in HDI.

According to Todaro and Smith (2020), the

Human Development Index (HDI) is a proxy for

social welfare and has a positive relationship with

income per capita. This means that the higher GDP

per capita, the higher the social welfare. The increase

in job opportunities and income will be accompanied

by more capital inflows into the country. Because of

the production goods and services increases, social

welfare increases.

Todaro and Smith (2020) added that economic

growth only results in improvements in income

distribution if two conditions are met, namely

expanding employment opportunities and increasing

productivity. The more job opportunities expand, the

greater the opportunity for people to get a job. In

order for people to earn more income, in this case

workers must continue to increase productivity by

increasing working hours rather than leisure time.

Source: World Bank (2023), Processed Data.

Figure 3: Foreign Direct Investment in ASEAN 2018 –

2021.

This study uses panel data regression to analyze

the relationship between independent variables and

the dependent variable in panel data. Panel data is

combination of time series dan cross-section. The

first step in this study we estimate using common

effect model. We can see empirical results common

effect model in Table 1. The result shows that

economic growth, foreign direct investment had

impact on human development index (HDI) at α=1%.

But, GDP hadn’t impact on HDI.

Table 1: Empirical Results Common Effect.

Variable

Coefficient

Prob

0.616647

0.0000*

GDP

-0.002573

0.1907

FDI

0.006758

0.0012*

UNEMP

0.021718

0.0032*

R-squared

0.342141

Adjusted R-squared

0.292801

Prob (F-statistic)

0.000723*

Durbin-Watson stat

0.143300

Source: Eviews 12, Processed.

Table 2 show the results of Chow Test. The Chow

test is utilized to determine which common effect or

fixed effect model is the most suitable for estimating

panel data. The results of chow test indicated that the

probability of cross-section chi-square is 0,000 less

than α=1% so that Ho is rejected and H1 is accepted.

Moreover, chow test produces the chosen model,

-30,000

-20,000

-10,000

0,000

10,000

20,000

30,000

40,000

2018 2019 2020 2021

Indonesi

Malaysia

Singapor

-20,0000,000 20,00040,000

2018

2019

2020

2021

Timor Leste

Cambodia

Myanmar

Lao

MEBIC 2023 - MARITIME, ECONOMICS AND BUSINESSINTERNATIONAL CONFERENCE

144

namely fixed effect model than common effect

model.

Table 2: The Results of Chow Test.

Effect Test

Statistic

Prob

Cross-section F

1812,9156

0,0000*

Cross-section Chi-square

281,8522

0,0000*

Source: Eviews 12, Processed.

Hausman test is a test used to determine whether

a fixed effect model or a random effect model is.

Based on Table 3, the results of Hausman test show

that probability of cross-section random is equal to

0,0784 less than α=10% so that H0 is rejected and H1

is accepted. So, the best model used is fixed effect

model in this study.

Table 3: The Results of Hausman Test.

Test Summary

Chi-square Stat

Prob

Cross-section random

6,805564

0,0784**

Source: Eviews 12, Processed.

Based on the test results and selection of the best

estimator then the model which is more precise in

estimating the analysis of determinant variables for

the human development index in ASEAN countries

by using fixed effect model. This model will then be

selected, interpreted, and analyzed in research. It can

be seen in Table 4. The fixed effect model equation

in this study can be explained as follow:

HDI

= 0,7193 + 0,0279 GDP

+ 0,0336 FDI

0,0142 UNEMP

+ ε

(2)

Table 4: Empirical Results Fixed Effect.

Variable

Coefficient

Prob

0,7193

0,0000*

GDP

0,027997

0,0002*

FDI

0,033615

0,0122**

UNEMP

0,014232

0,9592

R-squared

0,999786

Adjusted R-squared

0,999693

Prob (F-statistic)

0,0000*

Durbin-Watson stat

2,392593

Source: Eviews 12, Processed.

Table 4 show that fixed effect estimated model is

exists with probability or empirical statistical

significance F of 0,0000 less than α=1%,

simultaneously independent variables significant on

dependent variable. Coefficient of determination (R-

squared) which indicates that the variation of

independent variable can be explained by 99,9786%

of the dependent variable and the rest is influenced by

other variables outside the model by 0,0214%.

Economic growth (GDP) variable has a

regression coefficient value of 0,0279 with p-value of

0,0002 at significant effect on Human Development

Index (HDI) at α=1%. It means that if GDP increased

by 1%, the HDI will increase by 0,0279 or 2,79%. The

high level of economic growth will increase the

Human Development Index in ASEAN. The results

of this study is in line with previous study Handalani

(2018), Fadillah & Setiartiti (2021), Dzulqornain &

Iriani (2022) and rejected by Feriyanto (2016).

Based on from panel data regression results

with Eviews 12, coefficient of 0,0336 with p-value of

0,0122 at a significance α=5% then H1 is accepted

and Ho is rejected, which means that Foreign Direct

Investment (FDI) partially has a positive and

significant effect on Human Development Index

(HDI) in ASEAN period 2018 – 2021. It means that

if FDI increased by 1%, the HDI will increase by

0,0336 or 3,36%. It is consistent with the studies of

Feriyanto (2016), Handalani (2018), and Sumiyarvi

& Handayani (2022). On the other hand, with p-value

of 0,9592 less than α=10% then Ho accepted and H1

is rejected, which means unemployment rate

(UNEMP) has no significant on Human Development

Index (HDI). It is also in line with study conducted by

study Sofilda et al., (2015) and rejected by Feriyanto

(2016).

-0.006 -0.004 -0.002 0.000 0.002 0.004 0.006

Series: Standardized Residuals

Sample 2018 2021

Observations 44

Mean -3.01e-18

Median 3.68e-05

Maximum 0.005310

Minimum -0.006176

Std. Dev. 0.003527

Skewness -0.242376

Kurtosis 1.876252

Jarque-Bera 2.745954

Probability 0.253352

Source: Eviews 12, Processed.

Figure 4: The Results of Normality Test.

Normality tes result can be seen in figure 2,

which shows that data has been estimated is normally

distributed. The probability for Jarque Berra is

0.253352, which exceeds 10%, so H0 is accepted and

H1 is rejected, as shown in Figure 2. So, it can be

concluded that error term in this model is normally

distributed.

Analysis of Determinants Human Development Index in ASEAN Countries

145

4 CONCLUSION

The dependent variable used in the study results of 11

countries in ASEAN is Human Development Index

(HDI). Economic growth, Foreign Direct Investment

( FDI), unemployment are independent variables.

Panel data regression used in this study with fixed

effect model. The results of the study can be

summarized as follows: economic growth and foreign

direct investment have a positive and significant

impact on the Human Development Index (HDI) in

ASEAN. But, unemployment rate has no significant

effect on HDI. Policy recommendation in this study

is that the government needs to increase employment

opportunities by opening new jobs through FDI to

improve HDI. Apart from that, an increase in GDP

which is influenced by the size of output can result in

additional labor and better productivity. GDP that

continues to grow will increase people’s per capita

income and encourage the state to provide education

and health facilities through large tax collections from

the society so that HDI increases.

REFERENCES

Anindhita, F., & Hasbi, M. (2022). The Analysis of

Economic Growth and Human Development in

Gorontalo Province. Jurnal Ekonomi Pembangunan,

20(01), 1–9.

Arisman. (2018). Determinant of Human Development

Index in ASEAN Countries. Signifikan: Jurnal Ilmu

Ekonomi, 7(1), 113–122.

Bank, W. (2023). World Development Indicators.

databank.worldbank.org

Dzulqornain, R., & Iriani, R. (2022). The Effect of

Economic Growth, Regional Expenditures, and Poverty

Levels in East Kalimantan Province. Jurnal Ekonomi

Akuntansi, 7, 27–37.

Elistia, E., & Syahzuni, B. A. (2018). The correlation of the

human development index (HDI) towards economic

growth (GDP per capita) in 10 ASEAN member

countries. Jhss (Journal of Humanities and Social

Studies), 2(2), 40–46.

Fadillah, N., & Setiartiti, L. (2021). Analysis of Factors

Affecting Human Development Index in Special

Regional of Yogyakarta. Journal of Economics

Research and Social Sciences, 5(1).

https://doi.org/10.18196/jers

Feriyanto, N. (2016). The effect of employment, economic

growth, and investment on HDI: In provinces in

Indonesia. Journal of Economics, Business &

Accountancy Ventura, 19(1), 1.

Handalani, R. T. (2018). Determinan Indeks Pembangunan

Manusia di Asia Tenggara. Jurnal Kebijakan

Pembangunan Daerah, 2(2).

Rohmah, C., & Wicaksana, E. J. (2021). Factors Affecting

Inter-Regional Human Development Index in Jambi

Province. Jurnal Ekonomi Pembangunan,

19(December), 193–206. https://doi.org/10.29259/jep

Sangaji, J. (2016). The Determinants of Human

Development Index in Several Buddhist Countries.

Journal of Buddhist Education and Research, 2(1), 48–

60.

Shah, S. (2016). Determinants of Human Development

Index : A Cross-Country Empirical Analysis. SSRG

International Journal of Economics and Management

Studies (SSRG - IJEMS), 3(7), 40–43.

Simamora, J. P., Fahrulaji, F., & Martha, S. (2022).

Analysis of Relation Human Development Index and

Economic Growth Regency/City in the Province of

West Kalimantan: Analysis of Relation Human

Development Index and Economic Growth

Regency/City in the Province of West Kalimantan.

Jurnal Forum Analisis Statistik (FORMASI), 2(2), 72–

82.

Sofilda, E., Hermiyanti, P., & Hamzah, M. Z. (2015).

Determinant Variable Analysis of Human Development

Index in Indonesia (Case For High And Low Index At

Period 2004 – 2013). OIDA International Journal of

Sustainable Development, i.

Sumiyarti, S., & Handayani, K. (2022). Determinants of

Human Development Index : Case Study of Provinces

in Indonesia. LePALISSHE.

https://doi.org/10.4108/eai.3-8-2021.2315091

Todaro, M. P., & Smith, S. C. (2020). Economic

development. Pearson UK.

UNDP. (2023). Human Development Index Report.

data.undp.org

MEBIC 2023 - MARITIME, ECONOMICS AND BUSINESSINTERNATIONAL CONFERENCE

146