Vol. 15 No.1, Februari 2022


ISSN : 2301-8968


EKONOMI

KUANTITATIF

TERAPAN

JEKT

The Effect of Banks and Cooperatives in Improving Welfare Inayati Nuraini Dwiputri, Lustina Fajar Prastiwi, Grisvia Agustin

ISSN 2301-8968

Denpasar

Februari 2022

Halaman

1-161

The Role of Social Capital with Local Wisdom in Household Food Security in Bali Province Putu Ayu Pramitha Purwanti, Ida Ayu Nyoman Saskara

Middle Income Trap In A Macroeconomic Perspective A Case Study In Indoensia Apip Supriadi

Trade-Environment Triangle in Indonesia: Ecological Footprint Approach Kuratul Aini, Djoni Hartono

Social And Financial Efficiency Of Lembaga Perkreditan Desa Kajeng Baskara

The The Relationship Between Fiscal Policy And Civil Liberty On Per Capita GDP In Indonesia During 1980-2018

Vita Kartika Sari, Malik Cahyadin

The Effect Of Fiscal Decentralization On Economic Growth: A Study Of The Province Level In Indonesia Setyo Tri Wahyudi, Lutfi Kurniawati

The United States’ Monetary Policy Spillover Effect Against Rupiah -Us Dollar Exchange During Usa – China Trade War

Andryan Setyadharma, Anisa Rahmawati, Anisa Rahmawati

Affecting FactorsTrans Land Function In Bali

I Wayan Sudemen, I Ketut Darma

The General Allocation Fund (DAU) Formulation Policy: Incentives or Disincentives to the Fiscal Independence of Local Governments Kun Haribowo, Latri Wihastuti

Impact Of Rural Development Program On Agriculture Production and Rural-Urban Migration In Indonesia Murjana Yasa, Wayan Sukadana, Luh Gede Meydianawathi

Volume 15    Nomor 1


JEKT ♦ 15 [1] : 73-82

eISSN : 2303 – 0186


MIDDLE INCOME TRAP DALAM PERSPEKTIF MAKROEKONOMI : STUDI KASUS DI INDOENSIA

ABSTRAK

Tujuan penelitian ini adalah untuk mengetahui dan menganalisis i) kondisi pendapatan perkapita di Indonesia dilihat dari kriteria Middle income trap serta ii) pengaruh ekspor, penanaman modal asing dan jumlah penduduk baik secara parsial maupun bersama-sama terhadap pendapatan perkapita. Data yang digunakan adalah data sekunder peiode tahun 1991 – 2000, dengan alat analisis menggunakan analisis regresi berganda. Hasil penelitian menunjukkan bahwa perkembangan pendapatan perkapita termasuk kategori lower –middle income. Selanjutnya penanaman modal asing, jumlah penduduk dan ekspor berpengaruh siginifkan terhadap pendapatan perkapita.

Kata kunci : penanaman modal asing, jumlah penduduk, ekspor dan pendapatan perkapita

Klasifikasi JEL : E and P2, P3, or P4

(MIDDLE INCOME TRAP IN A MACROECONOMIC PERSPECTIVE: A CASE STUDY IN INDOENSIA)

ABSTRACT

The purpose of this study is to determine and analyze i) the condition of per capita income in Indonesia seen from the criteria of the Middle income trap and ii) the influence of exports, foreign investment and population, either partially or jointly on per capita income. The data used is secondary data for the period 1991 – 2000, with the analysis tool using multiple regression analysis. The results showed that the development of per capita income was included in the lower-middle income category. Furthermore, foreign investment, population and exports have a significant effect on per capita income.

Keywords         : middle income trap,

and per capita income

Klasifikasi JEL : E and P2, P3, or P4 INTRODUCTION

The World Bank has classified Indonesia into a group of lower-middle income countries for the past 13 years. This shows that Indonesia's economic growth is quite stagnant for a long time and

foreign investment, population, exports

makes Indonesia's potential to enter the Middle Income Trap is very large. This research, among others, aims to identify whether Indonesia has been included in MIT. ECM time series analysis is used at once to find out what actions need to be

taken in the long run to get out or avoid the middle income trap. PNB per capita as the basis for classifying the income groups of countries in the world is used as a variable to look at MIT (Hotmaria Elecktawati Lumbangaol and Ernawati Pasaribu, 2018).

Based on the level of per capita income, countries in the world can be categorized into several groups. Tran (2013) grouped them into four groups; The first is a group consisting of low-income countries that are still struggling out of the poverty trap. Some countries on the African continent fall into this category. Second is a group consisting of countries that have reached middle income levels for a long time (more than fifty years for many cases) but experienced very low income growth after that. Some countries in Latin America fall into this second group. Third, the group consisting of countries that just fall into the middle income category. Indonesia, several Countries association of Southeast Asian Nations (ASEAN) and China are included in this group. The fourth

group consists of high-income countries such as members of the Organisation for Economic Cooperation and Development (OECD).

The middle income trap is a scourge for developing countries, both in Asia, Oceania, Africa, and Latin America. The World Bank itself classifies the income (income) of countries in the world into 4 (four) categories, namely: low income (low income), lower middle income (lower middle income), upper middle income (upper middle income), and high income (high income).

The World Bank revealed that the economy is still concentrated in countries with high incomes, which is 38.1 percent and only 13.3 percent is felt by low income countries. Indonesia itself officially rose to upper middle income since mid-2020 ago. However, will Indonesia always be at the middle income level and could Indonesia be able to rise to the rank of a high-income country. Based on the description above, this study will focus on analyzing whether Indonesia has entered into MIT in macroeconomic

research, with the title middle income trap in macroeconomic perspective:   case studies in

Indoensia.

Research objectives

  • 1. 1. To find out and analyze

the condition of per capita income in Indonesia judging from the Middle income trap criteria

  • 2.    To find out and analyze the influence of exports, foreign investment (PMA) and population both partially and together on per capita income

Theoretical Studies

Simply put, the Middle Income Trap is a condition in which a country that has managed to reach a middle income  level, but stuck and

restrained to develop into a high-income  country.  This  happens

because  at some  level  middleincome  countries  will  become

uncompetitive in the value added industries sector, such as manufacturing.     Labor-intensive

industries will also begin to move to low-wage countries so that

economic growth in middle income countries will tend to stagnate or even decline. Middle income countries (MIC) not only have difficulty competing with Low-Wage Countries, but also difficulty competing with High-Technology Countries.

Definisi Middle Income Trap

The middle-income trap (MIT) refers to a condition in which middle-income countries are unable to maintain a stable enough rate of economic growth to achieve a new income group as high-income countries. So trapped in the middle income group (Aviliani et al, 2014).

How to Measure MIT

The World Bank (2014) in its research used the variable Gross National Income (PNB) per capita as a proxy for MIT. PNB per capita is measured from Gross National Income which is the total value added income of all residents of a country, both domestically and abroad (World Bank, 2014). PNB per capita is used as one of the benchmarks for determining how

successful a country is in managing its economy.

Jesus Felipe (2012) in an ADB working paper entitled: Tracking Middle Income Trap: What is it, Who is in it, and Why provides an approach to how a country can be called a country trapped in MIT.

Felipe (2012) classifies all countries of the world into four income groups based on GDP per capita. These countries fall into the category: (1) low-income countries; (2) lower-middle-income countries; (3) upper-middle-income countries; and (4) high-income countries.

Table 2. Income category based on PNB per capita

Kategori

PNB per kapita 2013

Low Income

< US $ 1.045

Lower Middle Income

US $ 1.045 - US $ 4.125

Upper Middle Income

US $ 4.125 - US $ 12.746

High Income

> US $ 12.746

Source:World Bank, 2014 (diolah)

Previous Research

Aprisal W. Malale, Maung Agus Sutikno, 2014. Stating that variables in exports of goods and services, added value of agriculture, and foreign assistance and assistance (with lag or without lag) significantly negatively affect pnb per capita. Gross Capital Formation variables significantly positively affect (in the current year) and have an effectnegatif (in the previous 2 and 3 years) against PNB per capita in the current year. Inflation variables have no significant effect on PNB per capita.

Iskandar A.A, 2014. Stating that quantitatively the regression model of variable PDRB ADHB and PDRB ADHK and population has a significant effect on per capita income. The number of residents against per capita income in a negative direction, means that the number of residents has a negative and significant effect on per capita income, per capita income in 2014 Rp. 6,002,891 if converted to the World Bank category 2014 lower income < US $ 1,045. Based on the results of the analysis it can be concluded that Lampung is still in the Lower Income category.

RESEARCH METHODS

The methods used in this study use quantitative descriptive methods. Descriptive research according to Kuncoro (2013: 10) includes the

collection of data for hypothesis testing or to answer questions regarding the final status of the research subject. The data in this study is a sequence data with time series from 1991 to 2020. The data processing in this study used eviews and looked for correlation coefficient values using multiple regression data analysis.

Analytical Techniques

Data analysis techniques use multiple regression analysis, with the following research models:    Data analysis

techniques use multiple regression analysis, with the following research models:

Log Y = βθ + β1 log X1 + β2 log X 2 + β3 log X 3 + e

Keterangan:

Log Y = Pendapatan per Kapita

Log X1 = Investasi

Log X2 = Jumlah Penduduk

Log X3 = Ekspor

β1, β 2, β 3 = koefisien regresi dari setiap variabel independen β0 = konstanta

e = Variabel Penggangu (error term)

Classic Assumption Test

Analysis requirements testing is used as a requirement in the use of multiple linear regression analysis models. In linear regression, to ensure that the model is BLUE (Best Linear Unbiased Estimator) tests are carried out, among others: linearity test, normality test, multicollinearity                test,

heteroskedasticity     test     and

autocorrelation test.

RESULTS AND DISCUSSIONS Per capita Income Conditions in Indonesia Seen From Middle Income Trap Criteria

Tabel 1. Development of Per Capita Income in Indonesia in 1991-2020

Tahun

Klasifikasi

Tahun

Klasifikasi

1991

Lower-Middle Income

2006

Lower-Middle Income

1992

Lower-Middle Income

2007

Lower-Middle Income

1993

Lower-Middle Income

2008

Lower-Middle Income

1994

Lower-Middle Income

2009

Lower-Middle Income

1995

Lower-Middle Income

2010

Lower-Middle Income

1996

Lower-Middle Income

2011

Lower-Middle Income

1997

Lower-Middle Income

2012

Lower-Middle Income

1998

Lower-Middle Income

2013

Lower-Middle Income

1999

Lower-Middle Income

2014

Lower-Middle Income

2000

Lower-Middle Income

2015

Lower-Middle Income

2001

Lower-Middle Income

2016

Lower-Middle Income

2002

Lower-Middle Income

2017

Lower-Middle Income

2003

Lower-Middle Income

2018

Lower-Middle Income

2004

Lower-Middle Income

2019

Lower-Middle Income

2005

Lower-Middle Income

2020

Lower-Middle Income

Sumber : Hasil olah data,BPS


Furthermore, from the results of data processing with the E-Views 10 application obtained the following regression equation.

Y = 6.066663 + 0. 082869 X1 –     0.

337476 X2 + 0.037852 X3

Information:

Y = Pendapatan per Kapita

  • X1 = Penanaman Modal Asing

(PMA)

  • X2 = Jumlah Penduduk

  • X3 = Ekspor

Based on the equation above, it can be explained as follows: The coefficient value of foreign investment (PMA) (X1) has a coefficient of 0. 082869 means that if there is an increase in foreign investment of US $ 1 and when other factors are considered fixed, it

will increase per Capita Income by US $ 0. 082869 or any (PMA) of US$ 10,000, will increase per Capita Income by US $ 828.

The population coefficient (X2) has a coefficient of -0. 337476, meaning that if there is an increase in the population by 1 percent and when other factors are considered fixed, it will decrease per Capita Income by US $ 0. 337476 or any population of 10 percent, will decrease per Capita Income by US $ 3,374. This shows the effect on the increasingly higher gdp per capita

divide, so that it will reduce per capita income.

The value of the export coefficient (X3) has a coefficient of 0.037852, meaning that if there is an increase in exports of US $ 1 and when other factors are considered fixed, it will increase per Capita Income by US $ 0.037852 or each export by US $ 10,000, will increase per Capita Income by US $ 378.

Classic Assumption Test

Normality Test

Jarque-Bera's normality test result that probability amounted to 4.301149 > 0.05 means that the data in this study is normal distribution. Linearity Test

The test results obtained the probability number F-statistic of 0.4875  >  0.05 means that the

relationship of the free variable with the bound variable is linear.

Multicollinearity Test

There is no variable whose Centered VIF value is more than 10, so it can be concluded that all free

variables in this model are free from multicollinearity problems.

Heteroskedasticity Test

The white test results obtained Prob-Chi Square 0.0679, it can be concluded that probability chisquare 0.0679 > 0.05 means that

there is no problem of heteroskedastisity in the analysis data studied.

Autocorrelation Test

Prob-Chi Square test results 0.1489, it can be concluded that the value of Prob-Chi Square 0.1489>0.05, meaning that there are no autocorrelation problems in the data in the analysis studied. Furthermore, to find out the influence of foreign investment, the number of residents and exports can be seen in the table below.

Tabel 2 Hasil Uji t

Variabel

t-statistic

Prob       t-

statistic

Signifikansi 5%

Penanaman  Modal

Asing (PMA)

8.296405

0.0000

Signifikan

Jumlah Penduduk

-

2.464443

0,0206

Signifikan

Ekspor

3.499111

0,0017

Signifikan

Sumber: Hasil Pengolahan E-Views 10


Based on table 2 above, the decision taken from the test results can be known that:

Static value of foreign investment variable (PMA) (X1) of 8.296405 > t Table of 1.70562 in other words the probability value of 0.0000 < 0.05 then H0 is rejected, meaning there is a positive and significant relationship between pmdn free variable (X1) to variable bound income per capita in Indonesia.

Static value of population variable (X2) of -2.464443 < t Table of 1.70562 in other words the probability value of 0.0206 < 0.05 then H0 is rejected, meaning there is a negative and significant relationship between the free variable of population number (X2) to variables bound to Income per Capita in Indonesia.

Static value variable population number (X3) of 3.499111> t Table of 1.70562 in other words the probability value of 0.0017 < 0.05 then H0 is rejected, meaning there is a positive and significant relationship between export-free variables (X3) to variables bound to Income per Capita in Indonesia.

Based on the above description that foreign investment, population and exports have a significant effect on per capita income, this is in line with previous research.

Furthermore, the statistical test F is conducted to find out if all the free variables contained in the model have a mutual influence on the bound variable. To know this can be seen from the magnitude of the probability value of its significance.

If the probability value of its a significant effect together on the

significance is less than 0.05 then dependent the independent variable will have

variable.


Tabel 3 Hasil Uji F

F-statistic

76.74529

Prob(F-statistic)

0,000000

Sumber: Hasil Pengolahan E-Views 10

In table 3 the F-statistical value of this test result is 76.74529 and the F-table value of 0.000000 at α = 0.05. It can be concluded together, that foreign investment variables (PMA), population and exports have a significant effect on Per Capita Income in Indonesia.

CHAPTER V CONCLUSIONS AND SUGGESTIONS

  • 5.1    Conclusion

Based on the results of the analysis that has been discussed in the previous chapter. So in this study can be concluded as follows:

  • 1.    Based on the results of the criteria of income classification parameters according to the World Bank and according to Felipe et al (2012) it can be stated that Indonesia throughout 2019 to 2020 has been in the trap of middle income trap Or

  • 2.    Foreign capital security, population and exports have a significant effect on per capita income

5.2. Suggestion

With respect to foreign investment, population and exports are related to per capita income, the government needs to pay close attention, so that per capita income can be maintained even more, so that Indonesia can get out of the Middle-Income trap.

DAFTAR PUSTAKA

Aviliani, Siregar, H., Hasanah, H., 2014. Addressing the MiddleIncome Trap: Experience of Indonesia. Asian Social Science Volume 10 No.7 p 163- 172.

Aprisal W. Malale, Maung Agus Sutikno, 2014.    Analisis

Middle-Income Trap di Indonesia. Jurnal BPPK, Volume 7 Nomor 2

Aviliani, Hermanto Siregar & Heni Hasanah, 2014. Addressing the Middle-Income Trap : Experience of Indonesia. Asian Social Science Vol. 10 No. 7

Asmirawati, 2017. Analisis Middle Income Trap di Indonesia, Jurnal Ecosains Vol 6 No1

Felipe,  J.,  2012. Tracking the

Middle-Income Trap: What is it, Who is in It, and Why? ADB Economics Working Paper Series Part 1 No.306 p 1-38.

Felipe,  J.,  2012. Tracking the

Middle-Income Trap: What is it, Who is in It, and Why? ADB Economics Working Paper Series Part 2 No.307 p 1-24.

Hotmaria Elecktawati Lumbangaol dan Ernawati Pasaribu, 2018. Eksistnesi dan Determinan Middle Income Trap di Indonesia, Jurnal Ekonomi dan Kebijakan Publik Vol 9. No.2

Iskandar A.A,   2014. Analisis

Kualitas       Pertumbuhan

Ekonomi Di Tinjau dari Pendekatan Middle Income Trap Provinsi Lampung. Jurnal Manajemen dan Bisnis, Vol. 4 No.2

Raisal Fahrozi Lubis, 2015. The

Middle Incoem Trap: is there a way out for ASIAN countries. Journal of Indonesia Economy and Business Vol. 30 No. 3

Sigit Setiawan, 2017. Middle Incoem Trap and Infrastructure issues in Indonesia:  A Strategic

Persefective.     Internasional

Journal of Economics and Financial Issues ISSN ; 21464138

Tran, V.T. (2013). The MiddleIncome Trap:  Issues for

Members of the Association of Southeast Asian Nations.

ADBI Working Paper 421. Tokyo: Asian Development Bank Institute.

Wibowo, Tri, 2016. Ketimpangan Pendapatan dan Middle Income Trap, Kajian Ekonomi Keuangan, Vol 20 No 2 (Agustus 2016)

World Bank, World Bank Country and Lending Groups. Angka di dalam tanda kurung menunjukkan perubahan dari tahun sebelumnya.

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