scholarly journals ANALISIS MIDDLE INCOME TRAP DI INDONESIA

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Asmirawati Asmirawati
Keyword(s):  
Capita Income ◽  
Direct Investment ◽  
Least Square ◽  
High Tech ◽  
Per Capita Income ◽  
Middle Income ◽  
Level Of Education ◽  
Income Per Capita ◽  
Per Capita ◽  
Middle Income Trap

This paper aims to analyze middle income trap in Indonesia where per capita income is the main indicator in determining whether a country is included in the middle income category or not. By looking at the effect of high technology products , education level, direct investment and dependent ratio on per capita income in Indonesia. The results of this model use the ordinary least square method, which shows that the export of high-tech products has a positive and significant effect on per capita income, the level of education has a positive and significant effect on per capita income, direct investment has a negative and significant effect on per capita income, the ratio has a positive and significant effect. income per capita and high-tech product exports, level of education, direct investment, and the ratio have a significant effect on income per capita in Indonesia.

China and the Middle Income Trap

2016 ◽  
Vol 08 (03) ◽  
pp. 78-86 ◽  
Author(s):  
John WONG
Keyword(s):  
Low Income ◽  
Capita Income ◽  
Per Capita Income ◽  
Industrial Upgrading ◽  
Middle Income ◽  
Strong Growth ◽  
Per Capita ◽  
Economic Slowdown ◽  
Middle Income Trap

Is China falling into the “middle-income trap” (MIT) with its current economic slowdown? Extrapolating from its 2015 per capita income of US$8,300 and benchmarking a developed economy at US$16,000, China would become a developed economy within 10 years with a reasonably strong growth of around 6%. China’s impressive R&D efforts and industrial upgrading towards “intensive manufacturing” could help it cross the MIT; however, it may run into a new kind of trap, the “low-income developed-economy trap”.

Film Production And Economic Performance: Should South Africa Invest In Movies?

2021 ◽  
Vol 4 (2) ◽  
pp. 125-144
Author(s):  
Andrew Phiri ◽  
Keyword(s):  
Foreign Direct Investment ◽  
Economic Performance ◽  
Government Spending ◽  
Capita Income ◽  
Direct Investment ◽  
Film Production ◽  
Domestic Investment ◽  
Per Capita Income ◽  
Long Run ◽  
Per Capita

The movie industry is increasingly recognised as a possible avenue for improving economic performance. This study focuses on film production and its influence on South African economic growth (per capita income and employment between 1970 and 2020). Our autoregressive lag distributive (ARDL) estimates on a loglinearised endogenous growth model augmented with creative capital indicate that the production of movies has no significant effects on long-run GDP growth, per capita GDP and employment. The baseline regressions find a short-run positive and significant influence of film production on per capita income and are devoid of long-run effects. However, re-estimating the regressions with interactive terms between movie production and i) government spending ii) foreign direct investment, improve the significance of film regression coefficients which all turn positive and significant, for government spending, and negative for foreign direct investment. Our results indicate that foreign investment crowds out domestic investment whilst government investment in movies is growth-enhancing.

scholarly journals PENGARUH KETIMPANGAN PENDAPATAN, PENDAPATAN PER KAPITA, DAN PENGELUARAN PEMERINTAH DI BIDANG KESEHATAN TERHADAP SEKTOR KESEHATAN DI INDONESIA

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Uswatun Hasanah
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
Health Effect ◽  
Government Expenditure ◽  
Health Sector ◽  
Research Area ◽  
External Factors ◽  
Per Capita Income ◽  
Income Per Capita ◽  
Per Capita

AbstractHuman resource is one of capital importance in the development of a nation. One of the important aspects that affect human resources are a public health level, where health sector has an important role. The status of one's health is the result of the interaction of various factors, namely internal and external factors. Internal factors consist of physical and psychological factors, while external factors consist of economic factors, education, environment and cultureThis research aims to examine and analyze the effect of income inequality as measured by the Gini Ratio against the health sector as measured by life expectancy in Indonesia in 2005-2013. On the research of regression equation using data panels with Random Effects Model approach. The results of this research is the inequality of income, per capita income, and Government expenditure in the health effect simultaneously against health sector in Indonesia in 2005-2013 and is partial, inequality of income, per capita income, and Government expenditure in the health sector impact health sector in Indonesia in 2005-2013. Keywords : Health sector, income inequality, income per capita, Government expenditure in health sector. Research Area: Indonesia

scholarly journals Analysis of Factors Affecting Economic Growth in Bangka Belitung Province, Indonesia with LSDV And FGLS Methods

2018 ◽  
Vol 2 (1) ◽  
pp. 24
Author(s):  
Darman Saputra
Keyword(s):  
Panel Data ◽  
Local Governments ◽  
Capita Income ◽  
Oil And Gas ◽  
Random Effect ◽  
Least Square ◽  
Per Capita Income ◽  
Processing Industry ◽  
Factors Affecting ◽  
Per Capita

The Least Square Dummy Variable (LSDV) method can be used to estimate parameters in the panel data regression model incomplete one-way fixed effect. To produce the best model with GDP data of GRASB. Variables that do not occur heteroscedasticity and models that meet the smallest sum square of error is the variable Mining and Processing Industry, this variable affects the per capita income. The Feasible Generalized Least Square (FGLS) method can be used to estimate the regression parameters for incomplete panel data for a one-way random effect. In this model produce the best model with non-oil and gas GRDP data. The variables that fulfill it are the processing Industry, service, and agriculture of Forestry and Fishery.  Therefore looking at the above model can be concluded non-oil and Gas GRDP has three factors that affect per capita income in Bangka Belitung. This should be a reference of local governments to further improve the quality or production in agriculture and services because this potential is more promising for the future. Software used to analyze data in this paper is with R.

scholarly journals Socio-Economic and Demographic Factors of Poverty Alleviation in Pakistan: A Case Study of Southern Punjab

2020 ◽  
Vol 6 (2) ◽  
pp. 525-538
Author(s):  
Rashid Ahmad ◽  
Muhammad Zahir Faridi
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Capita Income ◽  
Household Head ◽  
Rural Poverty ◽  
Least Square ◽  
Per Capita Income ◽  
High Dependency ◽  
Per Capita ◽  
Dependency Rate

This study aims to explore the socio-economic and demographic determinants of poverty in Southern Punjab by using the cross sectional data consisting of 785 household heads. Binary logistic regression  and ordinary least square method are used for estimation. The findings exhibit that the variables like family system, household size, presence of disease and status of employment of household head are positively and significantly related to  poverty whereas household head age, rural-to-urban migration,  years of schooling,  number of earners, women status of work, remittances, the physical assets value and ownership of house significantly and negatively influence the likelihood of poverty and positively influence the per capita income of the households in Southern Punjab. The study also provides the comparison of regional and division level. It is concluded that DG Khan division is the poorest among all the divisions of the southern Punjab. In DG Khan Division, the households have less education, high dependency ratio. In rural areas of southern Punjab, there is more poverty as compare to urban areas. The rural poverty is due to many factors like high dependency rate, lower level of education, adoption of profession, lower per capita income, dissaving. It is suggested that education should be promoted, employment opportunity should be provided so that dependency rate may be reduced, rural areas should be restructured by provision of basic necessities of life.

scholarly journals Relationship between income inequality, socioeconomic development, vulnerability index, and maternal mortality in Brazil, 2017

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maria do Socorro Candeira Costa ◽  
Francisco Winter dos Santos Figueiredo
Keyword(s):  
Maternal Mortality ◽  
Capita Income ◽  
Gini Index ◽  
Socioeconomic Development ◽  
Maternal Mortality Ratio ◽  
Socioeconomic Indicators ◽  
Per Capita Income ◽  
Socioeconomic Determinants ◽  
Income Per Capita ◽  
Per Capita

Abstract Background Public health recognizes that health conditions depend on factors related to the development patterns income distribution, degree of poverty, working conditions, among other social determinants. The objective of this study was to analyze the association of maternal mortality with the Human Development Index (HDI), Gini Index, Income per capita, and the Social Vulnerability. Method The study analyzed the relationship between MMR and socioeconomic indicators in the 26 federative units and the Federal District of Brazil, in 2017. The socioeconomic indicators used in the study were: HDI, Gini Index, Income per capita, and SVI. Crude and adjusted linear regression were performed between maternal mortality and socioeconomic indicators. Results When analyzing which socioeconomic determinants that are related to maternal mortality ratio rates, a higher per capita income positive effect was observed for lower MMR (β = − 150.8; CI 95% -289.9 to − 11.7; r2 = 0.17; p = 0.035), as well as a trend of higher MMR in relation to the SVI (β = 97.7; CI 95% -12.2 to 207.6; r2 = 0.12; p = 0.079). In model found by the stepwise forward selections, only the per capita income was um index related to less RMM (β = − 0.02; CI 95% -0.05 to − 0.002; r2 = 0.15; p = 0.028). Conclusion The findings showed that the per capita income has a negative association MMR in the different states of Brazil, but seems canceled because of the other socioeconomic determinants related to the poor live conditions.

E. ANALISIS PEMBENTUKAN MODAL TETAP BRUTO, INVESTASI ASING LANGSUNG, DAN EKSPOR TERHADAP PENDAPATAN NASIONAL PERKAPITA INDONESIA (DALAM MENGHINDARI MIDDLE INCOME TRAP)

2021 ◽  
Vol 4 (1) ◽  
pp. 47
Author(s):  
Mega Zahira Virtyani ◽  
Dr. Ignatia Martha Hendrati,S.E.,M.E. ◽  
Kiki Asmara,S.E.,MM
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
National Income ◽  
Capital Formation ◽  
Fixed Capital ◽  
Middle Income ◽  
Goods And Services ◽  
Fixed Capital Formation ◽  
Per Capita ◽  
Middle Income Trap

Abstrak Pendapatan Nasional Per Kapita merupakan pendapatan rata-rata semua penduduk di suatu negara. Penelitian ini bertujuan untuk menganalisis pengaruh Pembentukan Modal Tetap Bruto, Investasi Asing Langsung, dan Ekspor Barang dan Jasa terhadap Pendapatan Nasional Per Kapita Indonesia dalam menghindari Middle Income Trap. Metode yang digunakan dalam penelitian ini adalah metode regresi linier berganda dengan menggunakan data Indonesia periode tahun 2008-2019. Hasil penelitian menunjukkan secara bersama-sama variabel Pembentukan Modal Tetap Bruto, Investasi Asing Langsung, dan Ekspor Barang dan Jasa berpengaruh secara signifikan. Tetapi secara parsial, hanya Pembentukan Modal Tetap Bruto yang memiliki tingkat signifikan. Sedangkan, Ekspor Barang dan Jasa dan Investasi Asing langsung tidak berpengaruh secara signifikan. Upaya yang dapat dilakukan dalam menghindari Middle Income Trap yaitu Pembentukan Modal Tetap Bruto, Investasi Asing Langsung, dan Ekspor Barang dan Jasa meningkat secara bersama-sama agar dapat memberikan nilai tambah produktivitas terhadap Pendapatan Nasional Indonesia. Kata Kunci : Pembentukan Modal Tetap Bruto, Investasi Asing Langsung, Ekspor, Pendapatan Nasional Per Kapita, Jebakan Pendapatan Menengah. Abstract National Income Per Capita is the average income of all residents in a country. The purposes of this research are determine the effect of Gross Fixed Capital Formation, Foreign Direct Investment, and  Exports of Goods and Services on Indonesia's National Income Per Capita in avoiding Middle Income Trap. The method that used in this research is multiple linear regression method using Indonesian data for 2008-2019. The results of this research show that the variables of Gross Fixed Capital Formation, Foreign Direct Investment, and  Exports of  Goods and Services have a significant effect at the same time. Partially, only Gross Fixed Capital Formation has a significant level. Meanwhile, Exports of Goods and Services and Foreign Direct Investment do not have a significant effect. The efforts that can be made to avoid Middle Income Traps, are Gross Fixed Capital Formation, Exports of Goods and Services, and Foreign Direct Investment can be increase at the same time to give extra value for the productivity to Indonesia's National Income. Key Word : Gross Fixed Capital Formation, Foreign Diret Investment, Gross National Income Per Capita, Middle Incom Trap.

scholarly journals PERILAKU DANA PIHAK KETIGA DALAM MERESPON PERUBAHAN VARIABEL EKONOMI MAKRO PADA BANK UMUM SWASTA NASIONAL (BUSN) PROVINSI JAWA TIMUR PERIODE 2000-2012

2013 ◽  
Vol 11 (2) ◽  
pp. 184
Author(s):  
Dhurotus Sangadah
Keyword(s):  
Interest Rates ◽  
Capita Income ◽  
Least Square Method ◽  
Equation Model ◽  
Least Square ◽  
Third Party ◽  
Per Capita Income ◽  
Dependent Variables ◽  
Per Capita ◽  
Saving Deposit

The purpose of this reserach is to knowing of responbility of dependent variabel to exchange of makro economics variable at Excahage Commercial Bank province of East Java. The model analysis is Doubled Linear Regression with  employs the OLS (Ordinary Least Square) method. In this research will be used four regression with four dependent variables. In the equation model Saving Deposits, Demand Deposits, Tme Deposits, Third Party Funds are dependent variables and per capita income, interest rate, inflation are independent variables. Result of regression was showed that Saving Deposit more sensitive to respon change of inflations variable that showed by its probability is 0,0024. Time deposit moere sensitive to respon change of interest rates variable taht  showed by its probability was 0,0012. Per capita income  has same respon of all dependent variable that swowed by its probability was 0,0000

scholarly journals Faktor-faktor Yang Mempengaruhi AHH Provinsi Bali

2019 ◽  
Vol 8 (2) ◽  
pp. 71-83
Author(s):  
Luh Dita Darmayanti ◽  
Surya Dewi Rustariyuni
Keyword(s):  
Life Expectancy ◽  
Government Spending ◽  
Capita Income ◽  
Linear Regression Analysis ◽  
Government Expenditure ◽  
Health Sector ◽  
Per Capita Income ◽  
Income Per Capita ◽  
Education And Health ◽  
Per Capita

The degree of public health can be measured by looking at the amount of Life Expectancy (AHH). AHH is the result of calculating projections often used as one of the People's Welfare Indicators (IKR). Assuming a declining trend in infant mortality rates (IMR) and changes in the population's age composition, the objectives in this study are: 1) to analyze the effect of income per capita, government spending in education, and health simultaneously affect life expectancy in Bali Province / City in the 2011-2017 period and 2) to analyze the effect of per capita income, government spending the education and health sector influences the life expectancy in the Regency / City of Bali Province in the 2011-2017 period. The data used in this study is secondary data in 2011-2017. This study uses Multiple Linear Regression analysis techniques used to process classical assumption test data using Eviews 9. The results of this study stated that the variable income per capita (X1), government expenditure in education (X2), and government expenditure in health (X3) simultaneously affected the life expectancy (Y) in districts/cities in Bali Province. Partially per capita income has a positive and significant impact on life expectancy. Government expenditure in education and government expenditure in health does not affect life expectancy in Bali Province districts/cities.  

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