scholarly journals An Association of Total Health Expenditure with GDP and Life Expectancy

2017 ◽  
Vol 1 (2) ◽  
pp. AU7-AU12 ◽  
Author(s):  
Sojib Bin Zaman ◽  
Naznin Hossain ◽  
Varshil Mehta ◽  
Shuchita Sharmin ◽  
Shakeel Ahmed Ibne Mahmood
Keyword(s):  
Developing Countries ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Health Spending ◽  
Domestic Product ◽  
Fiscal Year ◽  
Total Health Expenditure ◽  
Registration System ◽  
Individual Level

Introduction: Gradual  total health expenditure (THE) has become a major concern. It is not only the increased THE, but also its unequal growth in  overall economy, found among the developing countries. If increased life expectancy is considered as a leverage for an individual’s investment in health services, it can be  expected that as the life expectancy increases, tendency of health care investment will also experience a boost up. Objective: The aim of the present study was to explore and identify the association of healthcare expenditure with the life expectancy and Gross Domestic Product (GDP) in developing countries, especially that of Bangladesh. Methodology: Data were retrospectively collected from “Health Bulletin 2011” and “Sample Vital Registration System 2010” of Bangladesh considering the fiscal year 1996 to fiscal year 2006. Using STATA, multivariable logistic regression was performed to find out the association of total health expenditure with GDP and life expectancy. Results: A direct relationship between GDP and total health expenditure was found through analysing the data. At the individual level, income  had a direct influence on health spending. However, there was no significant relationship between total health expenditure with increased life expectancy. Conclusion: The present study did not find any association between life expectancy and total health expenditure. However, our analysis found out that total health expenditure is more sensitive to gross domestic product rather than life expectancy.

scholarly journals Social Environment Determinants of Life Expectancy in Developing Countries: A Panel Data Analysis

2016 ◽  
Vol 9 (5) ◽  
pp. 105 ◽  
Author(s):  
Fatin Aminah Hassan ◽  
Nobuaki Minato ◽  
Shuichi Ishida ◽  
Norashidah Mohamed Nor
Keyword(s):  
Developing Countries ◽  
Health Status ◽  
Panel Data ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Independent Variables ◽  
Long Run ◽  
Improved Sanitation ◽  
The Relationship

<p>Despite remarkable improvements in health over the past 50 years, there still remain a great number of health challenges around the world. This study examined the relationship between life expectancy rate (as a proxy for health status) with health expenditure, gross domestic product, education index, improved water coverage, and improved sanitation facilities in 108 selected developing countries using annual panel data within the period of 2006–2010. The empirical results from using the panel data approach showed a positive relationship between life expectancy rate and all of those explanatory variables. The relationship between life expectancy with education index and gross domestic product were significant at 1% and 5% significance levels, respectively. Furthermore, the causality finding showed that there is no short-run causality between life expectancy and its determinants. There is a unidirectional causality running from the independent variables of health expenditure, education index, improved water, and improved sanitation to life expectancy at birth. On the other hand, bidirectional causality exists between life expectancy and income in the long-run by employing VECM test.  These independent variables can be considered as important determinants for investment in health status in the long-run. This study could be used as a guideline and may be significant for future researchers and policy makers who aim to improve the life expectancy in developing countries.</p>

scholarly journals Haemorrhage of gross domestic product from disability-adjusted-life-years among 15-59 year olds in Kenya

10.3823/2561 ◽  
2018 ◽  
Vol 11 ◽  
Author(s):  
Joses Muthuri Kirigia ◽  
Germano Mwiga Mwabu
Keyword(s):  
Gross Domestic Product ◽  
Health Expenditure ◽  
Communicable Diseases ◽  
Domestic Product ◽  
Disability Adjusted Life Years ◽  
Total Health Expenditure ◽  
Per Capita Gdp ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Per Capita

Background: This article estimates non-health gross domestic product (GDP) losses associated with Disability-Adjusted Life Years (DALY) lost among 15-59 year olds (most productive age bracket) in Kenya in 2015. Methods: This study employs the lost output or human capital approach (HCA) to convert the DALYs lost from all causes into their monetary equivalents. The magnitude economic haemorrhage from each disease was obtained by multiplying the per capita non-health GDP in International Dollars by the total number of DALYs lost in a specific age group (15-29 years, 30-49 years, 50-59 years). Per capita non-health GDP equals per capita GDP minus total health expenditure in 2015. Data on DALYs and per capita total health expenditure were obtained from the World Health Organization and per capita GDP data was from IMF databases. Results: Kenya lost 9,405,184 DALYs among 15-59 years olds in 2015. That DALY loss caused a haemorrhage in GDP of Int$ 29,788,392,419. Approximately 48.6% of the GDP haemorrhage resulted from communicable diseases and nutritional conditions, 37.4% from non-communicable diseases, and 14.0% from injuries. Conclusion: There is need to augment domestic and external investments into national health systems and other systems that meet basic needs (education, food, water, sanitation, shelter) to reduce disease burden. Key words: Non-health GDP, economic haemorrhage, disability-adjusted life year (DALY)

Effects of Economic and Population Factors on Health Expenditures: Special Case of Pakistan

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Tanzeela Yaqoob ◽  
Rahat Bibi ◽  
Junaid S. Siddiqui
Keyword(s):  
Growth Rate ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Population Growth Rate ◽  
Birth Rate ◽  
Crude Birth Rate ◽  
Health Expenditures ◽  
Total Health Expenditure ◽  
Life Expectancy At Birth

<p>This paper aims to explore the factors affecting the health care expenditures of Pakistan by employing the Multivariate techniques for the annual data series from 1960 to 2010 .The variables we considered are Gross Domestic Product (GDP) as an economic indicator, Population of age 65 and above (P≥65), Population of age 0 to 14 (P(0-14)), Life expectancy at Birth (LE), Crude Birth rate (CBR) and population growth rate (GR) as population indicator and Total Health Expenditure (THE) as an influencing factor. Multiple regression considering Total Health Expenditure (THE) is applied as dependent on the variables mentioned above. Since Variance Inflation Factor (VIF) for all independent variables are very high, the smallest VIF is around 11 goes up to 65. The results obtained by Principal components reveal the effect of population structure and the age factor effect oppositely on Total Health Expenditures (THE). Factor Analysis suggests that the behavior of Health Expenditures is common with Gross Domestic Product (GDP), population of age 65 and above (P≥65) and life expectancy at Birth (LE) in Pakistan while population of age 0 to 14 (P (0-14)), population growth rate (GR) and Crude Birth rate (CBR) are moving in opposite direction i.e. as GDP, P≥65 and LE of Pakistan increases P (0-14), GR and CBR will decreases.</p>

scholarly journals Economic interventions to ameliorate the impact of COVID-19 on the economy and health: an international comparison

2020 ◽  
Author(s):  
Shaun Danielli ◽  
Raman Patria ◽  
Patrice Donnelly ◽  
Hutan Ashrafian ◽  
Ara Darzi
Keyword(s):  
Life Expectancy ◽  
Gross Domestic Product ◽  
International Comparison ◽  
Real World ◽  
Domestic Product ◽  
Real World Data ◽  
Economic Collapse ◽  
Available Information ◽  
The Impact ◽  
Second Wave

Abstract Background The COVID-19 pandemic continues to challenge governments and policymakers worldwide. They have rightfully prioritised reducing the spread of the virus through social distancing interventions. However, shuttered business and widespread restrictions on travel and mobility have led to an economic collapse with increasing uncertainty of how quickly recovery will be achieved. Methods The authors carried out a review of publicly available information on the economic intervention’s countries have put in place to ameliorate the impact of COVID-19. Results The strategies and scale of economic interventions have been broad, ranging from 2.5% to a reported 50% of Gross Domestic Product. Conclusions Numerous countries are beginning to ease lockdown restrictions and restart economies in different ways. There is therefore evolving, real-world data that should be used dynamically by governments and policymakers. The strategies on restarting the economy must be balanced against the uncertainty of a possible second wave of COVID-19. A nuanced approach to easing restrictions needs to take into account not only immediate risk to life but longer-term risks of widening inequalities and falling life expectancy.

scholarly journals Impact of Trade Liberalization on Economic Growth of Nepal

2019 ◽  
Vol 8 ◽  
pp. 136-148
Author(s):  
Ramesh Bahadur Khadka
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Gross Domestic Product ◽  
Trade Liberalization ◽  
World Bank ◽  
Trade Balance ◽  
Trade Openness ◽  
Domestic Product ◽  
Total Trade ◽  
The Impact

Trade openness has been considered as an important determinant of economic growth. It has been witnessed during the past couple of decades that international trade openness has played a significant role in the growth process of both developed and developing countries. International organizations such as Word Trade Organization, International Monetary Fund and World Bank are constantly advising, especially developing countries, to speed up the process of trade liberalization to achieve high economic growth. In this context, this paper aims to analyze the impact of trade liberalization on economic growth of Nepal. For this purpose, all the data regarding gross domestic product, export, import, total trade, trade balance of Nepal from 1980 A.D. to 2013 A.D. published by World Bank (2014) were used. Both descriptive as well as inferential statistics were used to analyze the data. Correlation analysis was used to find the correlation between the selected variables. Multiple linear regression analysis was carried out to analyze the impact of the trade liberalization in economic growth of Nepal. Trade cost does not explain any influence in gross domestic product, export, import, total trade and trade balance. The impact of trade openness is positive for all variables except trade balance. Trade openness has influenced economy significantly; import increased with purchasing power, export also increased but service only. Therefore, there is gap in export and imports.

scholarly journals Association of Gross Domestic Product with Under-Five Mortality Rate and Life Expectancy During 1990 - 2015 in Iran: An Ecological Study

2019 ◽  
Vol 20 (12) ◽  
Author(s):  
Firooz Esmaeilzadeh ◽  
Manijeh Alimohammadi ◽  
Mojtaba Sepandi ◽  
Farzad Khodamoradi ◽  
Yousef Alimohamadi
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Ecological Study ◽  
Domestic Product ◽  
Under Five

scholarly journals Kesejahteraan, pengeluaran pemerintah sektor kesehatan dan harapan hidup di Provinsi Aceh: Sebuah pendekatan data panel

2019 ◽  
Vol 17 (1) ◽  
pp. 31-37
Author(s):  
Nanda Rahmi ◽  
Afdhal Putera
Keyword(s):  
Linear Regression ◽  
Life Expectancy ◽  
Regression Model ◽  
Linear Regression Model ◽  
Significant Relationship ◽  
Health Spending ◽  
Quantitative Approach ◽  
Domestic Product ◽  
Analysis Method

This study to investigate the effect of health spending and Gross Regional Domestic Product (GRDP) on life expectancy in Aceh. The data are collected for 23 districts in Aceh over 4 years from 2012-2016. The analysis method uses a quantitative approach with applying a linear regression model with data panel. The findings of this study indicated that health spending and GRDP have a positive and significant effect on life expectancy. Furthermore, GRDP has a positive and significant relationship with life expectancy.

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