Criminality and economic growth province in Indonesian

The decline in economic growth, which is offset by the increasing number of people and the lack of availability of jobs, has caused more people to be affected and involved in non-crime activities based on the crime rate (CR). This study aims to analyze the effect of crime rates on provincial economic growth in Indonesia in 2011-2020. The variables used are economic growth, crime rates, investment, labor, and initial growth. The method used is the Fixed Effect Model. The results show that the higher the crime rate impacts the decline in economic growth, further increase in investment and labor will encourage economic growth. In contrast, the initial growth shows that the economy of poor provinces grows slower than rich provinces.

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Inequality and Economic Growth: An Analysis of 8-Panels

Journal of Economics and Public Finance ◽

10.22158/jepf.v3n2p173 ◽

2017 ◽

Vol 3 (2) ◽

pp. 173

Author(s):

Khadijah A. Idowu ◽

Yusuf Bababtunde Adeneye

Keyword(s):

Economic Growth ◽

Panel Data Analysis ◽

Random Effect ◽

Random Effect Model ◽

Specific Effect ◽

Developed Countries ◽

Fixed Effect Model ◽

Fixed Effect ◽

Effect Model ◽

The World

Purpose: This paper investigates the effects of inequality on economic growth in the world using continental approach.Design/methodology: Gini Coefficient and Gross Domestic Products (GDP) per capita were used to measure inequality and economic growth respectively. The study conducted a panel data analysis of the relationship between inequality and economic growth. The data span from 1991-2015. Five countries were selected each from seven continents and were also pooled together to constitute a single panel for 35 countries, thus establishing 8 panels. The Hausman test was conducted to determine whether a random or fixed effect model best fit pooled countries analysis or not.Findings: Findings revealed that for the developing countries, high income inequality retards economic growth while for the developed countries such as Europe countries; the situation seems to be different. European countries as revealed in the findings showed that developed countries have benefited from inequality which has significantly and positively affected their economic growth. The results for Panel II (Asia countries) and Panel III (Europe countries) are in line with the study of Forbes (2000) and Li and Zou (1998) that documented that inequality boosts economic growth. Importantly, we found that inequality positively affects economic growth for Panels/Continents with fixed effect model while inequality negatively affects economic growth for Panels/Continents with random effect model.Research Limitation: The study did not control for each continent differences. For African countries, weak institutional settings and environment is a key factor contributing to high inequality.Originality: The paper was able to know the specific effect of inequality on economic growth in each continent in the World. This documents continents that have benefited from inequality and those that inequality has greatly affected their economies negatively.

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ANALISIS:PENGARUH;DEMOKRASI TERHADAP;PERTUMBUHAN;EKONOMI INDONESIA;BAGIAN TIMUR

Jurnal Kajian Ekonomi dan Pembangunan ◽

10.24036/jkep.v1i3.7714 ◽

2019 ◽

Vol 1 (3) ◽

pp. 877

Author(s):

Vina Indriani ◽

Melti Roza Adry

Keyword(s):

Economic Growth ◽

Significant Influence ◽

Fixed Effect Model ◽

Free Variable ◽

Fixed Effect ◽

Analysis Tool ◽

Control Variables ◽

Eastern Indonesia ◽

Effect Model ◽

Educational Variables

The;purpose of;this research is;to;know:and;analyze:>(1);The;influence of;democracy;on;the economic;growth;of;eastern;Indonesia. (2) Investment influence on the economic growth of eastern Indonesia. (3) The influence of education on economic growth in eastern Indonesia. (4) The influence of democracy, investment, and education jointly towards the;economic;growth;of;eastern;Indonesia.The variables used;in;this study were economic growth as a bound variable and democracy as a free variable, as well as investment and educational variables as control variables. The research used the 17 provincial data panel in eastern Indonesia in 2009-2017. Data is obtained from the Central Statistics agency.The analysis tool used in this study is a regression panel with the model chosen is the Fixed Effect Model. The results showed that: (1) democracy is positive and significant to the economic growth of Eastern Indonesia, (2) investments have positive and significant impact on the economic growth of Eastern Indonesia, (3) education Positive and significant influence on the economic growth of Eastern Indonesia, (4) Democracy, investment, and education jointly significantly]influence{the}economic?growth/of/eastern Indonesia.

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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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Impact of Military Expenditures on the Globalization Process: A Spatial Econometric Analysis for African Region

Journal of Asian and African Studies ◽

10.1177/00219096211010324 ◽

2021 ◽

pp. 002190962110103

Author(s):

Saima Sarwar ◽

Alvina Sabah Idrees

Keyword(s):

Economic Growth ◽

Negative Relationship ◽

Fixed Effect Model ◽

Fixed Effect ◽

Spatial Econometric ◽

Effect Model ◽

The World ◽

Spatial Autoregressive ◽

Military Expenditures ◽

The Impact

With modernization, ideological shifts and economic interdependency, the concept of globalization has expanded vastly. Though the world is unipolar, still the international competition remains prevalent that poses serious threats to regional conflicts. The great powers of the world are still competing with each other for influence over other countries. Thus, the role of militarization cannot be ignored in this context. Thus, it would be interesting to examine the impact of military expenditures on the globalization process through the spill-over effects, along with their relationship with economic growth. The study employed panel data consisting of African countries, covering the time period from 2001 to 2014. The econometric estimation is done through the application of spatial econometric techniques, that is, the spatial autoregressive fixed effect model and spatial Durbin fixed effect model. The study has found a positive relationship between economic growth and globalization but a negative relationship was found between military expenditures and economic growth.

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The impact of corruption on the economic growth in Bangladesh, India and Pakistan: An ARDL approach

Independent Journal of Management & Production ◽

10.14807/ijmp.v12i8.1470 ◽

2021 ◽

Vol 12 (8) ◽

pp. 2079-2093

Author(s):

Md. Mamun Miah ◽

Tahmina Akter Ratna ◽

Shapan Chandra Majumder

Keyword(s):

Economic Growth ◽

Correction Term ◽

Negative Relationship ◽

Secondary Data ◽

Fixed Effect Model ◽

Positive Influence ◽

Fixed Effect ◽

Ardl Model ◽

Effect Model ◽

The Impact

Purpose of the study: Main purpose of the paper is to find out the impact of corruption on the economic growth of Bangladesh, India, and Pakistan. At the same time, our other objectives are to find the long and short-run effects of corruption on growth in these countries. Methodology: For conducting the study, we have taken the data from Bangladesh, India, and Pakistan. For this study necessary secondary data have been collected from 1990 to 2016 based on countries like Bangladesh, India, and Pakistan. Data for economic growth (dependent) and trade (independent) are collected from World Development Bank and data for corruption are taken from International Country Risk published by the PRS Group. The study has used ECM ARDL Model and the Fixed Effect Model. Findings: The result of the fixed effect model shows a 1percent increase in corruption decreases GDP by 0.07 units and shows a negative relationship with economic growth. Again if trade increases by 1 percent then growth will increase by 0.09 units on average and shows a positive relationship with economic growth. ECM ARDL Model shows the positive coefficient of corruption but not significant but trade has a long-run positive influence on economic growth. The error correction term indicating that the adjustment is corrected by 70% in these three countries. Contributions: This paper may be helpful for existing literature gap and also for further research. It will be helpful for policy makers to control corruption in three countries.

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Peran Pertumbuhan Ekonomi Dalam Menurunkan Kemiskinan di Tingkat Provinsi di Indonesia Tahun 2004-2012

MODUS ◽

10.24002/modus.v28i1.669 ◽

2016 ◽

Vol 28 (1) ◽

pp. 91

Author(s):

Denni Setiawan Jayadi ◽

Aloysius Gunadi Brata

Keyword(s):

Economic Growth ◽

Poverty Reduction ◽

Secondary Data ◽

Data Bank ◽

Fixed Effect Model ◽

Negative Influence ◽

Fixed Effect ◽

Mining Sector ◽

Effect Model ◽

Panel Data Regression

Abstrak Penelitian ini bertujuan untuk mengetahui dan menganalisis peran pertumbuhan ekonomi terhadap penurunan kemiskinan dilihat dari sektoral tahun 2004–2012. Variabel yang digunakan adalah jumlah penduduk miskin sebagai variabel dependen dan Produk Domestik Regional Bruto (PRDB) di sembilan sektor sebagai variabel independen. Data yang digunakan dalam penelitian ini merupakan data sekunder yang diperoleh dari terbitan world data bank. Metode analisis yang digunakan adalah regresi data panel dengan pendekatan model fixed effect. Dalam mengolah data, penulis menggunakan bantuan software Eviews 8.1. Berdasarkan hasil estimasi di peroleh bahwa secara keseluruhan pertumbuhan ekonomi berpengaruh negatif dan signifikan terhadap kemiskinan di tingkat Provinsi di Indonesia. Selanjutnya dilihat dari segi sektoral ditemukan bahwa variabel sektor per-tambangan memiliki pengaruh yang negatif dan signifikan terhadap penurunan kemiskinan. Hal itu disebabkan adanya commodities boom terhadap komoditi hasil tambang. Sehingga sektor pertambangan bukanlah sektor yang menjadi kunci dalam penurunan kemiskinan namun terjadinya commodities boom memiliki pengaruh terhadap penurunan kemiskinan di Provinsi di Indonesia. Kata Kunci : Fixed Effect, Kemiskinan, PDRB sektoral, pertumbuhan ekonomi, commodities boom. AbstractThis study aims to identify and analyze the role of economic growth on poverty reduction seen from sectors in 2004-2012. The variables used were the number of poverty as the dependent variable and the Gross Regional Domestic Product (GRDP) in nine sectors as independent variables. The data used in this research is secondary data obtained from the data published by the World Bank. The analytical method used is the panel data regression with fixed effect model approach. In processing the data, the authors using statistical software Eviews 8.1.Based on estimates obtained that overall economic growth is negative and have significant effect on poverty at the provincial level in Indonesia. Furthermore, in terms of sectoral found that variable per-mining sector has a negative influence and significant impact on poverty reduction. It was caused by the commodities boom of the commodity mined. So that the mining sector is not a sector that is key in reducing poverty, but the commodities boom have an impact on poverty reduction in the province in Indonesia. Keywords: Fixed Effect, poverty, the GDP sectoral, economic growth, commodities boom.

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IMPACT OF INVESTMENT, LABOR, AND INFRASTRUCTURE ON JAVA ISLAND ECONOMIC GROWTH 2011-2017

EFFICIENT Indonesian Journal of Development Economics ◽

10.15294/efficient.v1i3.35151 ◽

2018 ◽

Vol 1 (3) ◽

pp. 230-241

Author(s):

Maya Aprilia Sari

Keyword(s):

Economic Growth ◽

Local Governments ◽

Secondary Data ◽

Fixed Effect Model ◽

Fixed Effect ◽

Least Square ◽

Clean Water ◽

Domestic Investment ◽

Central Java ◽

Effect Model

The study aims to determine and analyze the effect of investment, labor, and infrastructure on economic growth in Java in 2011-2017. This research is a quantitative study using secondary data from six provinces in Java (DKI Jakarta, West Java, Central Java, Special Region of Yogyakarta, East Java and Banten) obtained from the Central Statistics Agency. Analysis of the data used in this study is panel regression of fixed effect model data using the General Least Square (GLS) method. The results showed that individually the domestic investment variable, labor, clean water infrastructure had a significant influence on economic growth while foreign investment had no significant effect on economic growth. Suggestions: 1) local governments are expected to increase the potential of each region to attract investors; 2) local governments are expected to create a conducive investment climate and facilitate investment licensing; 3) local governments are expected to increase the allocation of education funds and provide training in foreign languages and skills to the workforce; 4) local governments should make better plans for the distribution of clean water and improve the efficiency of the use of clean water.© 2019, Universitas Negeri Semarang Penelitian bertujuan untuk mengetahui dan menganalisis pengaruh investasi,tenaga kerja, dan infrastruktur terhadap pertumbuhan ekonomi di Pulau Jawa tahun 2011-2017. Penelitian ini merupakan penelitian kuantitatif menggunakan data sekunder enam provinsi di Pulau Jawa (DKI Jakarta, Jawa Barat, Jawa Tengah, Daerah Istimewa Yogyakarta, Jawa Timur, dan Banten) yang diperoleh dari Badan Pusat Statistik.Analisis data yang digunakan pada penelitian ini adalah regresi data panel model fixed effect menggunakan metode General Least Square (GLS). Hasil penelitian menunjukkan bahwa secara individu variabel penanaman modal dalam negeri, tenaga kerja, infrastruktur air bersih memiliki pengaruh signifikanterhadap pertumbuhan ekonomi sedangkanpenanaman modal luar negeri tidak berpengaruh signifikan terhadap pertumbuhan ekonomi. Saran: 1) pemerintah daerah diharapkan meningkatkan potensi setiap daerah agar menarik para investor; 2) pemerintah daerah diharapkan menciptakan iklim investasi yang kondusif dan mempermudah perizinan investasi; 3) pemerintah daerah diharapkan meningkatkan alokasi dana pendidikan dan memberikan pelatihan bahasa asing dan ketrampilan kepada tenaga kerja; 4) pemerintah daerah hendaknya membuat perencanaan distribusi air bersih yang lebih baik lagi dan meningkatkan efisiensi penggunaan air bersih.

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IMPLEMENTASI DATA PANEL SPASIAL TERHADAP TINGKAT PRODUK DOMESTIK REGIONAL BRUTO DI PROVINSI BALI

E-Jurnal Matematika ◽

10.24843/mtk.2021.v10.i02.p319 ◽

2021 ◽

Vol 10 (2) ◽

pp. 46

Author(s):

NI MADE ARY DHARMA WIDYA ASTUTI ◽

MADE SUSILAWATI ◽

NI LUH PUTU SUCIPTAWATI

Keyword(s):

Economic Growth ◽

Random Effect ◽

Random Effect Model ◽

Economic Indicator ◽

Fixed Time ◽

Fixed Effect Model ◽

Fixed Effect ◽

Spatial Lag ◽

Effect Model ◽

Spatial Panel Data

Gross Regional Domestic Product (GRDP) is an economic indicator to see the economic movements of a region during a certain period, whether based on current and constant price. Economic activities in a region use the GRDP calculation based on current prices by industrial base year 2010. In 2019, Bali's economic growth increased by , exceeding national economic growth of . Using spatial panel data in analysis consists of common effect model, fixed individual effect model, fixed time effect model, random effect model, and spatial lag fixed effect model. The best model to modeling GRDP Bali Province is spatial lag fixed effect which has a difference in constant values ??at any time, with of 99.41 percent, the remaining is explained by other variables not examined

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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 EFFECT OF ECONOMIC GROWTH AND DEMOGRAPHIC CONDITION ON CRIMINALITY IN EAST JAVA PROVINCE

Jurnal Ekonomi dan Bisnis Airlangga ◽

10.20473/jeba.v31i12021.28-39 ◽

2021 ◽

Vol 31 (1) ◽

pp. 28

Author(s):

Fani Novi Hariyantia ◽

Rafael Purtomo S ◽

Regina Niken Wilantari

Keyword(s):

Economic Growth ◽

Population Density ◽

Significant Relationship ◽

Crime Rate ◽

Secondary Data ◽

Fixed Effect Model ◽

Poor People ◽

Analysis Method ◽

Effect Model ◽

Demographic Condition

Introduction: This study aims to determine how much the effect of economic growth and demographic conditions on the crime rate in East Java Province. This study is using secondary data for 6 years from 2013-2018.Methods: The data analysis method used in this study is panel data regression analysis method with the Fixed Effect Model (FEM) approach. The dependent variable used in this study is the crime rate, while the independent variables are economic and demographic growth, which includes population density and the number of poor people.Results: Based on the results of this study, it can be concluded that economic growth has a positive but insignificant relationship to the crime rate in East Java Province. Population density has a positive and significant relationship to the crime rate in East Java Province. Meanwhile, the number of poor people has a negative and significant relationship with the crime rate in East Java Province. The results of the study also show that economic growth, population density and the number of poor people have an effect and significant relationship on the crime rate in East Java Province.Conclusion and suggestion: This needs an equitable distribution of income and empowerment of human resources through improving educational facilities and infrastructure as well as skills so that productivity and community income increase. In addition, it is necessary to have equitable development and the provision of employment opportunities in each region so that population density is not concentrated in one or several areas.

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