scholarly journals Influential Factors of Residential Commodity Price Changes in Sanya

2018 ◽  
Vol 10 (12) ◽  
pp. 96
Author(s):  
Ying-Yu Du ◽  
Yong-Qi Huang ◽  
Can-Xu Yao ◽  
Yuan-Biao Zhang
Keyword(s):  
Gross Domestic Product ◽  
Price Level ◽  
Housing Prices ◽  
Commodity Price ◽  
Disposable Income ◽  
Domestic Product ◽  
Land Price ◽  
Residential Land ◽  
Per Capita ◽  
Capita Disposable Income

Residential commodity price is not only an important index of government macro-control, but also an important livelihood topic in society. The purpose of this paper is to take Sanya as an example to make an empirical analysis on the relationship between the factors affecting commodity housing prices, and their effects on housing prices. By using pearson correlation analysis, factor analysis and principal component regression method, it is found that the main factors influencing the housing price in Sanya are the housing sales area, the gross domestic product, the per capita disposable income, and the land price level of residential land. Among them, housing sales area and Sanya city house price changes in the opposite direction, the regional gross domestic product, per capita disposable income, residential land price level plays a positive role in housing prices.

PENGARUH PENANAMAN MODAL ASING, PERDAGANGAN INTERNASIONAL, GDP PER KAPITA, SEKTOR PERTANIAN, DAN URBANISASI TERHADAP PENDUDUK BEKERJA DI INDONESIA

2017 ◽  
Vol 21 (2) ◽  
pp. 85-95
Author(s):  
John Marcell Rumondor
Keyword(s):  
International Trade ◽  
Gross Domestic Product ◽  
Foreign Investment ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Least Square ◽  
Domestic Product ◽  
Working Population ◽  
Ordinary Least Square ◽  
Per Capita

This research aims to understand the influenceof foreign investment, international trade, Gross Domestic Product per capita, agriculture and urbanization of the working population. Country used as an object in this research is Indonesia. This research uses the method of analysis Ordinary Least Square (OLS) and the multiple linear regression analysis method. Research period are from 1997 – 2012. The results showed that the international trade, Gross Domestic Product per capita, agriculture and urbanization have significantpositive influenceon the population work in Indonesia, but foreign investment has no significanteffect on the working population in Indonesia.

Abstract P360: Hypertension Treatment Rates And Health Worker Density: An Analysis Of Worldwide Data

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Rajesh Vedanthan ◽  
Mondira Ray ◽  
Valentin Fuster ◽  
Ellen Magenheim
Keyword(s):  
Gross Domestic Product ◽  
Health Worker ◽  
World Bank ◽  
Domestic Product ◽  
Hypertension Treatment ◽  
Treatment Rate ◽  
Capita Gross Domestic Product ◽  
The World ◽  
Per Capita ◽  
The Relationship

Introduction: Hypertension is the leading global risk for mortality and its prevalence is increasing in many low- and middle-income countries. Hypertension treatment rates are low worldwide, potentially in part due to insufficient human resources. However, the relationship between health worker density and hypertension treatment rates is unknown. Objective: To conduct an econometric analysis of the relationship between health worker density and hypertension treatment rates worldwide. Methods: Hypertension treatment rates were collected from published reports between 1980 and 2010. Data on health worker (physician and nurse) density were obtained from the World Health Organization (WHO). Data for potential confounding variables--per capita gross domestic product, hospital bed density, burden of infectious diseases, land area and urban population--were obtained from WHO and World Bank databases. Potential interaction by per capita gross domestic product was evaluated. Multivariable logistic-logarithmic regression analysis was performed using Stata. Results: Full data were available from 146 countries spanning all World Bank income classification categories. Health worker density was significantly associated with hypertension treatment rate in the unadjusted model (beta = 0.23; p < 0.005). In the fully adjusted model, the association remained positive but was not statistically significant (beta = 0.30; p = 0.078) (Figure). Hypertension treatment rates were more strongly related to physician than nurse density (beta = 0.21 vs 0.08; p = 0.10 vs 0.49). Conclusion: Hypertension treatment rates across the world appear to be related to health worker density, although the relationship does not achieve strict statistical significance. Our results suggest that a 10% increase in health worker density is associated with a 2-3% increase in hypertension treatment rate. Given the global burden of hypertension and other chronic diseases, WHO guidelines for health workforce staffing may need to be reconsidered.

scholarly journals Geographical Indication and Regional Development: Cause or Consequence

2019 ◽  
Vol 11 (3) ◽  
pp. 535
Author(s):  
Alan Malacarne ◽  
Liaria Nunes da Silva ◽  
Camila Souza Vieira ◽  
Ricardo Fontes Macedo ◽  
Andreia Malacarne ◽  
...  
Keyword(s):  
Gross Domestic Product ◽  
Regional Development ◽  
Agricultural Sector ◽  
Intrinsic Value ◽  
Domestic Product ◽  
Geographical Indication ◽  
Starting Point ◽  
Per Capita

The Geographical Indication is an instrument of protection to products and services that have intrinsic value. The cities of Bento Gon&ccedil;alves, Flores da Cunha, Monte Belo do Sul, Farroupilha, Paraty, Urussanga, Salinas and Aba&iacute;ra are highlights in the Brazilian agricultural sector. These regions have territorial demarcations with a Geographical Indication certification, where the producers live in the same region and can sell their own products with this seal of quality. An analysis has as a starting point the following study problem: Is the success of the implementation of a Geographical Indication linked to the development of the region? The results showed that only the Gross Domestic Product per capita is not sufficient to prove a record of Geographic Indication was actually implemented successfully in a certain region or not, however it can be observed that in the developed regions the trend is much higher.

scholarly journals REGIONAL GROSS DOMESTIC PRODUCT OF GEORGIA. METHODOLOGICAL CHANGES

World Science ◽  
2019 ◽  
Vol 3 (11(51)) ◽  
pp. 9-12
Author(s):  
Inga Benashvili ◽  
Mamuka Benashvili
Keyword(s):  
Gross Domestic Product ◽  
Domestic Product ◽  
National Accounts ◽  
Regional Structure ◽  
New Classification ◽  
System Of National Accounts ◽  
National Rate ◽  
Per Capita ◽  
Municipal Level ◽  
Constant Prices

The paper is devoted to the methodological changes in the calculation of regional Gross Domestic Product (GDP), mainly due to the introduction of the 2008 version of the System of National Accounts in Georgia. Other changes are related to the transition to a new classification system of economic activity (NACE rev2). Because of this, the regional structure of GDP has changed significantly.Regional GDP on a per capita basis, in 2018 Tbilisi ranks first (6122,5 USD). Then it will be followed by Adjara (5514.3 USD). Their rate is significantly higher than the national rate (4722.0 USD).The priority directions for calculating regional GDP in Georgia are as follows: •Receiving data directly from local units (local KAUs) by improving information sources;•More detailing of regionalization. In particular, at the municipal level; •Calculate regional GDP at constant prices.

The Optimum Level of Income Inequality in South Asia: An Econometric Analysis

2021 ◽  
pp. 139156142110390
Author(s):  
Fahmida Khatun ◽  
Syed Yusuf Saadat
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Gross Domestic Product ◽  
South Asia ◽  
Gini Coefficient ◽  
Econometric Analysis ◽  
Domestic Product ◽  
Optimum Level ◽  
Capita Gross Domestic Product ◽  
Per Capita

Inequality in the distribution of income can be beneficial or detrimental for economic growth depending on the level of inequality. This study advocates that when income inequality is low, increase in income inequality increases economic growth, whereas when income inequality is high, increase in income inequality decreases economic growth. The level of inequality that maximizes economic growth is defined as the optimum level of income inequality. This article attempts to determine the optimum level of income inequality for South Asia through an econometric analysis. It uses panel data from Bangladesh, India, Nepal, Pakistan and Sri Lanka, over a 34-year period to undertake a systematic investigation using panel instrumental variables techniques. The results of this study confirm that an optimum level of income inequality does exist, and occurs at a Gini coefficient value of 0.4492. Thus, this research empirically confirms that the relationship between income inequality and economic growth is non-linear. Further calculations show that for an economy that is at the optimum level of income inequality, the per capita gross domestic product can be expected to double within approximately 13 years, provided all other factors are held constant. However, a change in the Gini coefficient by 0.10 units in either direction—higher or lower—away from the optimum level, can increase the number of years for the per capita gross domestic product to double by 55 to 57 years, depending on the method of approximation. JEL: D31, D63, O15, O40

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