Daya Saing dan Pertumbuhan Ekonomi Negara Berkembang ASEAN

The purpose of this study is to look at the condition of the country's competitiveness and its influence on ASEAN economic growth. The data used consists of panel data consisting of time series data for 2009 - 2019 and a cross section of five ASEAN countries with the highest level of competitiveness. The variables used are economic growth, competitiveness, labor participation, and foreign direct investment. The analysis tool used is panel data regression, the Fixed Effect Model (FEM). The results show that competitiveness, labor participation, and foreign direct investment have a positive and significant effect on economic growth in the five developing ASEAN countries. Keywords: ASEAN, Competitiveness, Economic Growth, and Fixed Effect Model (FEM).

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Influence of Competitiveness, Corruption and Foreign Direct Investment on Economic Growth of Asean Developing Countries

International Journal of Economics Business and Entrepreneurship ◽

10.23960/ijebe.v3i1.62 ◽

2020 ◽

Vol 3 (1) ◽

pp. 80-89

Author(s):

Fadeli yusuf Afif ◽

Ukhti Ciptawaty

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Panel Data ◽

Direct Investment ◽

Random Effect Model ◽

Series Data ◽

Analysis Tool ◽

Corruption Perception Index ◽

Corruption Perception ◽

Asean Countries

The purpose of this study is to look at the condition of the country's competitiveness and its influence on ASEAN economic growth. The data used is panel data consisting of time series data for 2009 - 2019 and cross section of five ASEAN countries with the highest level of competitiveness. The variables used are economic growth, competitiveness, corruption perception index, political risk, and foreign direct investment. The analysis tool used is panel data regression, the Random Effect Model (REM). The results show that competitiveness and foreign direct investment have a positive and significant effect on economic growth, while the corruption perception index has no effect on economic growth in 5 ASEAN countries.

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Determinant of FDI Inflows in OIC Countries

International Journal of Islamic Economics and Finance (IJIEF) ◽

10.18196/ijief.v4i1.9473 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Tania Megasari ◽

Samsubar Saleh

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Exchange Rates ◽

Direct Investment ◽

Trade Openness ◽

Political Stability ◽

Fixed Effect Model ◽

Fdi Inflows ◽

Macroeconomic Variables ◽

Effect Model

This study aims to analyze the determinants of foreign direct investment (FDI) in the Organization of Islamic Cooperation (OIC) country members for the period 2005 to 2018 The determinant variables of FDI are corruption, political stability and macroeconomic variables such as inflation, exchange rates, economic growth, and trade openness. Analysis used in the study is the fixed effect model (FEM) of the OIC data panel.The results showed that economic growth and trade openness had a significant influence on foreign direct investment (FDI), while the effects of corruption, political stability, inflation and the exchange rate have no significant effect on foreign direct investment (FDI).

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DETERMINASI PERTUMBUHAN EKONOMI DI TUJUH NEGARA ASEAN PERIODE TAHUN 1996-2013

Media Ekonomi ◽

10.25105/me.v23i2.3323 ◽

2015 ◽

Vol 23 (2) ◽

pp. 107

Author(s):

Desyana Eka Pramasty ◽

Lydia Rosintan

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Data Analysis ◽

Panel Data ◽

Direct Investment ◽

Panel Data Analysis ◽

Foreign Debt ◽

National Income ◽

Negative Effect ◽

Asean Countries

Economic growth is also one of the most important indicators in determining the standard of living of people in a country, because of an increase in the production capacity of an economy that is manifested in the form of national income. Economic growth is an indication of the success of economic development, measured by comparing, for example, for domestic size, Gross Domestic Product (GDP) in the current year with the previous year. This study aimed to analyze the factors that affect economic growth in seven ASEAN countries period from 1996-2013. This study use panel data analysis. The factors that affect economic growth in seven ASEAN countries, namely foreign debt, foreign direct investment, and the rate of inflation. Based on panel data analysis of the results showed that the foreign debt has negative effect and significant on economic growth, foreign direct investment has positive effect and significant on economic growth and inflation rate has negative effect and significant on economic growth in seven ASEAN countries period from 1996-2013.

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Pengaruh Foreign Direct Investment (FDI) Terhadap Pertumbuhan Ekonomi di Nusa Tenggara Barat Tahun 2010-2014

Jurnal Ekonomi dan Bisnis Indonesia ◽

10.37673/jebi.v2i2.9 ◽

2017 ◽

Vol 2 (2) ◽

pp. 18-24

Author(s):

Munyta Mentari ◽

Abdul Ilman ◽

Didi Suwardi

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Panel Data ◽

Direct Investment ◽

Capital Investment ◽

Fixed Effect Model ◽

Domestic Investment ◽

Level Of Education ◽

Domestic Capital ◽

Level 3

This research aims to analyse the effect of Foreign Direct Investment (FDI) on the economic growth of West Nusa Tenggara (NTB) province within 2010-2014. The dependent variable is economic growth, meanwhile the independent variables are : 1) FDI proxied from the percentage of foreign capital investment towards PDRB; 2) Schooling or level of education proxied from the percentage of up to 15 years –old people who complete senior high school education level; 3) Domestic investment proxied from the percentage of domestic capital investment towards PDRB; 4) The interaction of FDI and human capital (level of education) and the control variables which consist of APBD proxied from the percentage of APBD towards PDRB and inflation variable proxied from PDRB deflator. Data analysis used in this study is regression model of panel data. The data is obtained from 10 districts and cities in NTB province from 2010 to 2014. The chow test and hausman test resulted to use fixed effect model in that panel data regression procedure. The results show that FDI has a positive yet unsignificant effect on the economic growth with the confidence level of 95%. It is caused by the low level of technological transfer by the province human resources due to the domination of less educated workers.

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MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA

Jurnal Gaussian ◽

10.14710/j.gauss.v9i3.28925 ◽

2020 ◽

Vol 9 (3) ◽

pp. 355-363

Author(s):

Artanti Indrasetianingsih ◽

Tutik Khalimatul Wasik

Keyword(s):

Panel Data ◽

Random Effect ◽

Random Effect Model ◽

Fixed Effect Model ◽

Fixed Effect ◽

Series Data ◽

Poverty Level ◽

Effect Model ◽

Panel Data Regression ◽

Data Regression

Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

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IMPACTS OF FOREIGN DIRECT INVESTMENT ON POVERTY ERADICATION IN ASEAN-5 COUNTRIES

TRIKONOMIKA ◽

10.23969/trikonomika.v20i2.4085 ◽

2021 ◽

Vol 20 (2) ◽

pp. 62-70

Author(s):

Shania Puteri Azaria ◽

Estro Dariatno Sihaloho

Keyword(s):

Foreign Direct Investment ◽

Panel Data ◽

Financial Development ◽

Direct Investment ◽

Time Series Data ◽

The Philippines ◽

Least Square ◽

Series Data ◽

Middle Income ◽

Asean Countries

This research aims to investigate the relationship between foreign direct investment (FDI) and poverty using panel data of five ASEAN upper and lower middle-income countries for 28 years. The time series data period selected in this study is from 1990 until 2018. The five countries selected to be investigated in this research are presumed as the Tiger Cub Economies, namely Indonesia, Malaysia, Thailand, Vietnam, and the Philippines. This study conducted the Feasible Generalized least Square (FGLS) methods to analyze the statistical panel data. The result from this analysis indicates that foreign direct investment has a negative and significant impact on poverty in five ASEAN countries. Other important results from this study showed that the Gross Domestic Product (GDP), credit provided by the financial sector as the proxy of financial development, and education variables contribute significantly to lower poverty incidence. Policies that focus on attracting foreign direct investment, improving financial development, and support a higher level of education have the potential to reduce poverty in the selected five ASEAN countries.

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PENERAPAN REGRESI DATA PANEL PADA ANALISIS PENGARUH INFRASTRUKTUR TERHADAP PRODUKTIFITAS EKONOMI PROVINSI-PROVINSI DI LUAR PULAU JAWA TAHUN 2010-2014

MEDIA STATISTIKA ◽

10.14710/medstat.11.1.1-15 ◽

2018 ◽

Vol 11 (1) ◽

pp. 1-15

Author(s):

Yosephine Magdalena Sitorus ◽

Lia Yuliana

Keyword(s):

Economic Growth ◽

Panel Data ◽

Fixed Effect Model ◽

Fixed Effect ◽

Seemingly Unrelated Regression ◽

Total Output ◽

Economic Productivity ◽

Effect Model ◽

Panel Data Regression ◽

Data Regression

There is inequality between the economic growth of provinces in Java and outside of Java. The total area of Java is only 6,77% from total area of Indonesia but the Growth Domestic Product (GDP) based on constant price in 2014, Java contributed 57,8% of the GDP total Indonesia. One cause that made this disparity is the development of infrastructure in outside Java is still weak. The development of infrastructure is a basic element for increasing total output production that later will increase the economic growth. However, there are so many problems that occur in developing the infrastructure in outside of Java. This study aimed to analyze the condition of infrastructure provinces outside Java in 2010-2014. The data used is the secondary data for 27 provinces outside of Java 2010-2014 from BPS. The analytical method used is panel data regression with fixed effect model and Seemingly Unrelated Regression (SUR) Model. Based on the results, the infrastructure that affects economic productivity significantly and positively is road infrastructure, health, and budget. Infrastructure that affects economic productivity significantly and negatively is the educational infrastructure. Water and electricity infrastructure did not significantly affect economic productivity.Keywords: Infrastructure, Economic productivity, Panel Data Regression, Fixed Effect Model

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ANALISIS REGRESI DATA PANEL TERHADAP INDEKS PEMBANGUNAN MANUSIA (IPM) JAWA TIMUR TAHUN 2006-2015

Majalah Ilmiah Matematika dan Statistika ◽

10.19184/mims.v18i2.17250 ◽

2018 ◽

Vol 18 (2) ◽

pp. 69

Author(s):

Muhammad Jamil Hidayat ◽

Alfian Futuhul Hadi ◽

Dian Anggraeni

Keyword(s):

Time Series ◽

Panel Data ◽

Cross Section ◽

Fixed Effect Model ◽

Fixed Effect ◽

Series Data ◽

Cross Section Data ◽

Section Data ◽

Effect Model ◽

Per Capita

Panel data is a combination of time series and cross section data. Panel data regression is used because in a time there is time researchers can’t perform analysis only by using time series data and cross section data only. This is because the number of factors used in the analysis phase, so that if the researcher only uses cross section data then the researcher can’t see the influence of factors that affect as well as on the growth of HDI that occurs from time to time in a certain period. Whereas it is quite possible that the conditions between one year and another will be different. Based on the model estimation, it is used with fixed effect model (FEM) approach. Modeling HDI with FEM in 2006-2015 period resulted in R2 value of 94.23%. The results showed that from 2006-2015 the ratio of student-teacher (RST), health facilities (HF), percentage of expenditure per capita by group of food (PPF) and regional per capita expenditure (PPE) have significant effect to HDI. Keywords: HDI, Panel, Fixed Effect Model

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Environmental regulation, Industrial structure upgrading and Economic growth in Beijing Tianjin Hebei region

E3S Web of Conferences ◽

10.1051/e3sconf/202123502021 ◽

2021 ◽

Vol 235 ◽

pp. 02021

Author(s):

Menglu Li

Keyword(s):

Economic Growth ◽

Economic Development ◽

Panel Data ◽

Environmental Regulation ◽

Industrial Structure ◽

Fixed Effect Model ◽

Fixed Effect ◽

Effect Model ◽

The Relationship ◽

Industrial Structure Upgrading

This paper selects the panel data of 13 cities in Beijing Tianjin Hebei region from 2008 to 2016, and uses the fixed effect model to study the relationship between environmental regulation, industrial structure upgrading and economic growth in Beijing Tianjin Hebei region. The results show that: strengthening environmental regulation can promote the upgrading of industrial structure in Beijing Tianjin Hebei region by reducing the emission of pollutants; the upgrading of industrial structure is conducive to promoting the economic development of Beijing Tianjin Hebei region.

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The impact of institutions on economic growth in selected developing countries: An analysis based on Bayesian panel estimation

Journal of Applied Economics and Business Studies ◽

10.34260/jaebs.4412 ◽

2020 ◽

Vol 4 (4) ◽

pp. 251-272

Author(s):

Qasim Shah ◽

Seema Zubair ◽

Sundus Hussain

Keyword(s):

Economic Growth ◽

Developing Countries ◽

Panel Data ◽

Fixed Effect Model ◽

Data Models ◽

Fixed Effect ◽

Estimation Methods ◽

Panel Data Models ◽

Effect Model ◽

The Impact

This paper presents an empirical analysis of the impact of institutions on the economic growth of 27 developing countries during the period 1990-2014. Many creative models of panel data allow variations in slope coefficients both across time and cross-sectional units. All models were established in a Bayesian structure and their performance was tested by using an interesting application of the effect of institution on GDP. Technical details of all these models are given and tools are presented to compare their performance in the Bayesian system. Besides, panel data models and posterior model pools are provided for an insight into the institution's relationship with economic development. The derivation of Bayesian panel data models is included. The previous data has been used in this study and normal gamma prior is used for the models of panel data. 2SLS estimation technique has been used to analyze the classical estimation of panel data models. In the paper, developing countries were viewed as a whole. The study's evaluated results have shown that panel data models are valid Bayesian methodology models. In the Bayesian approach, the results of all independent variables affect the dependent variable significantly and positively. Based on all model standard defects, it is necessary to say that the Fixed Effect Model is the best in Bayesian panel data estimation methods. It was also shown that in comparison to other models, the fixed-effect model has the lowest standard error value.

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