Researcher names/ Year
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Objective
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Methodology and Data
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Finding
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Previous Finding/ Discussion
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(Tapia
Granados, 2012)
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Analyzes
the relation between health progress, as measured by annual gains in Life
Expectancy at Birth, LEB (or declines in mortality), and economic growth.
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Using
data for England and Wales during the years 1840-2000 (160 years).
LEB
is the indicator of population health.
LEB
and mortality data were obtained from the Human Mortality Database. GDP and GDP per capita are from Maddison
(2003)
Some
of the data excludes corresponding to war years 1914-1918 and 1939-1945 and
also excludes year 1918 due to flu pandemic.
Augmented
Dickey Fuller (ADF) test
vCointegrating Regression Durbine Watson
(CRDW) test
v Johansen test
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The
negative relation is found between
economic growth- measured by the rate of growth of gross domestic product
(GDP) -and health progress. The lower is the rate of growth of the economy,
the greater is the annual increase in LEB for both males and females.
v No cointegration in long run.
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Harvey
Brenner (1983) recessions caused increases in both infant and adult mortality
in Britain and other countries. Brenner (2005), economic growth has been the
central factor in mortality rate decline in the US over the 20th century. (Positive relation)
Brenner’s
critic Jay Winter (1983), who found infant mortality in Britain falling
quickly during recessions in 1920-1950. (Negative
relation)
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(Huang,
Fulginiti, & Peterson, 2010)
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The
paper focuses on the impacts of health on education and economic growth.
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The theoretical model is a three-period
overlapping generations model where individuals go through three stages in
their lives, namely, young, adult, and old.
The
model extends existing theoretical models by allowing the probability of
premature death to differ for individuals at different life stages.
Potential
endogeneity is addressed by using various strategies, such as controlling for
country-specific time-invariant unobservables and by using the
male-circumcision rate as an instrumental variable for HIV/ AIDS prevalence.
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HIV/AIDS
leads to lower life expectancy or higher probability of premature death in African
countries cause people are less likely to invest in human capital and casue the
country ends up with less human capital and slower economic growth in the
long run. (Positive relation).
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Kalemli-Ozcan
(2002) in the research finds that economic growth is promoted as a result of
declining mortality. (Positive
relation).
Bonnel
(2000) found that the disease resulted in a reduction in per capita growth in
Africa of 0.7 percentage points. (Positive
relation).
Bloom
and Canning (2000, 2005) find that, improvements in longevity lower
fertility, raise educational investment, and raise the long run growth rate
of output. (Negative relation).
Acemoglu
and Johnson (2006) suggest that improving health may have a negative impact
on GDP per capita because increased life expectancies lead to larger total populations
and lower per capita income. (Negative
relation).
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(Tai,
Chao, & Hu, 2015)
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The
purpose of this paper is to consider the growth effect of aid allocation on
healthcare and pollution abatement, and then to investigate the tradeoff between
environmental protection and economic growth in the economy.
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Endogenous
growth model.
Variables:
1. Total expenditure on health as % of GDP,
2. General government expenditure on health as % of total government expenditure,
3. External resources for health as % of total expenditure on health, 4. Per
capita total expenditure on health (US$).
The
data are obtain from World Health Statistics (WHO, 2011).
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Poor
health and worsening pollution are major concerns affecting production
efficiency and economic growth in many developing economies.
During
the 2003 SARS period, GDP fell by 0.25% (NT$22 billion) in Taiwan.. (Positive relation).
Expenditures
on healthcare are lowered for developing countries (4.9–9% of GDP) compared
to devel-oped countries (9.5–18%).
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Cf.
Agénor (2008), when SARS occurred in 2003 in China, consumers avoided going
to public places to engage in leisure activities. This lowered the demand for
goods and services, and thereby had a negative impact on the utility of
consumers. (Positive relation)
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(Gong,
Li, & Wang, 2012)
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This
paper analyzes the effect of health investment, and hence of health capital,
on physical capital accumulation and long-run economic growth.
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Hausman's
specification test (i.e., m-statistic) to test the null hypothesis that all
random effects parameters are zero.
F
statistics
Ordinary
Least Square (OLS).
Genaralized
Least Square (GLS)
Used
a panel data from individual provinces of China, which is 28 Chinese
provinces over 25 years.
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Positive effect of health investment on economic
growth using a panel data from individual provinces in China.
Negative effect of health investment on economic
growth is determined by the ratio of health investment to physical capital
stock and is statistically significant.
In
the short-term, the growth of health improves economic growth. (Positive relation)
In
the long run, the trend of increasing health level as the economy grows leads
to a slowdown in economic growth. (Negative relation)
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Baumol (1967) and van
Zon and Muysken (2001, 2003) if “health” is a normal good, then health level/
health investment/spending will continue to increase in the process of
economic growth and may crowd out physical capital investment and thus harm
economic growth in the long run. (Positive
relation)
Bloom,
Canning, and Jamison (2004); Bloom, Canning, and Sevilla (2004) surveyed the
results of 13 related studies found that a one-year increase in life
expectancy raises output by 4%. (Positive
relation)
Arora
(2001) found a causal relationship between economic growth and health in ten
industrialized countries and the result shows that health contributes to economic
growth permanently but the same does not hold for the effect of economic
growth on health.
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(Assuero,
Freitas, & Stamford, 2013)
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To
analyze the impact of health system in the economic growth based upon three
macroeconomic models.
To
evaluate what is the adequate policy for the allocation of resources for the
optimal economic growth given the explicit presence of the healthcare sector
in the economy.
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Firstly,
model of an economy with only one sector which is the productive sector with
morbidity.
Secondly,
economy is divided into two sectors which are productive sector and health
sector.
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The
presence of the health system increases the life expectancy and the aggregate
product, but does not modify the per capita product.
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Thomas
Malthus (1978) stated who advocated the positive control of the population
suggesting the construction of houses close to mangroves and the narrowing of
streets in order to provoke the return of plagues, saying that……but above all we must repudiate specific
medicine for overwhelming diseases…
but in this research stated that the healthcare sector increase
society’s well-being because aggregate product is greater than the aggregate
product of an economy with morbidity and without a healthcare system.
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(Liang,
Li 2010)
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To
examine empirically the sources of economic growth based on an augmented
Mankiw, Romer, & Weil’s model which considers human capital in the forms
of both health & education for a group of East Asian economics including
China.
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Empirical
results are based on the analysis of a panel data set from 1961-2007.
Sub-sample
estimation for the post-1997 Asian Financial Crisis period is also considered
for comparison purposes.
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The
impact of stock of health & education on economic growth is statistically
significant for both whole sample & sub sample period.
However,
the impact of investment in education on economic growth is a little
“fragile”.
The
statistical results show that statistical impact of health on economic growth
is stronger than of education.
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Based
on the econometric method, there is an argument on Islam (1995) stated that
because there are some unobserved effects obtained in the error terms, for
example the country specific technology shift that is correlated with the
saving rate and the population growth rate, it is more appropriate to use a
fixed-effect model than a random effect model but in this study they
performed the two stage least square estimation as a comparison.
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Nguyen
Thi Minh Thoa et al (2013)
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To
investigate how the health care utilization changes when the economic
condition is changing at a household level.
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They
analyzed a panel data of 11260 households in a rural district of Vietnam.
Of
the sample, 74.4% having an income increase between 2003 & 2007 were
defined as households with economic growth.
They
used a double-differences propensity score matching technique to compare the
changes in health care expenditure as percentage of total expenditure & health utilization
from 2003-2005, from 2003-2007, & from 2005-2007, between households with
& without economic growth.
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Households
with economic growth spent less percentage of their expenditures for health
care, but used more provincial/central hospitals (higher quality health care
services) than household without economic growth.
The
differences were statistically significant.
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This
study provides a different viewpoint of the close link between economic
status and healthcare utilization of households in rural Vietnam.
Unlike
others studies demonstrating a cross-sectional association between economic
status and healthcare utilization, our results demonstrate a longitudinal
relationship showing how healthcare utilization changes when the economic
status is changing.
Next,
we used a similar analytical approach as the one used in Thanh et al. but with different groups of the treated and
controls (poor vs. non-poor in that study and EG vs. non-EG in our study).
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Kuan-Ming
Wang (2011)
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To
determine whether long-term relationship between the increase in health care
expenditure and the economy growth is stable, and investigate the short-term
causal relationship and influence.
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Used panel regression analysis and quantile
regression analysis.
Panel regression analysis including unit
root and panel cointegration test, and Fully Modified OLS (FMOLS) to estimate
the VECM model-type panel.
Wald coefficient test to examine the causes
among the variables of health care spending and the economic growth.
The quantile regression analysis is to
examine the causality between an increase in health care expenditure and
economic growth under different quantile levels of economic growth.
The yearly data includes 31 sample countries
from 1986 to 2007 obtained from OECD Health Data.
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There cointegration relationship between
health care expenditure and GDP and they are complementary.
The estimation of the panel type error
correction model indicates that in the short-run, health care expenditure
growth will stimulate economic growth. However, economic growth will reduce
health care expenditure growth.
The results of quantile regression indicate
that in countries with a low level of economic growth, health care
expenditure growth will reduce economic growth.
In countries with medium and high levels of economic growth, the
influence of health care expenditure growth on economic growth is positive.
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This paper found that health care
expenditure and GDP that involve cointegration are different from Hansen and
King (1996) and Culyer (1990) that there is no long-run relationship between
health care expenditure and GDP.
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Habib Nawaz Khan et al (2015)
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The
aim of the paper is to investigate the relationship between health care
expenditure (HCE) and economic growth.
The
causality between HCE and economic growth in the Selected South Asian
Association for Regional Cooperation (SAARC) countries.
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Used panel data from 1995 to 2012.
Panel unit root test to determine the order
of integration of each variable.
Panel cointegration tests to examine the
long run relationship between HCE and economic growth.
Panel Dynamic Least Squares (PDOLS) and
Seemingly Unrelated Regression (SUR) technique to estimate the long-run and
short-run coefficients.
The data obtained from WDI, SESRIC, WHO, and
HRC.
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They found a significant long run
relationship between HCE and economic growth in the South Asian countries.
There exists short-run relationship between
HCE and per capita income in the SAARC countries.
There is presence of bi-directional causality
between HCE and economic growth in the short run.
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In
this study, the findings support that there is bi-directional causality
between HCE and economic growth in short-run. However, Dumitrescu and Hurlin
(2012) non-homogeneous panel causality result supports the presence of
unidirectional causality running from per capita income to HCE in South Asian
countries in the short run.
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Wen-Yi Chen (2015)
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The aim of this paper is to investigate the
dynamic relationship between health progress and economic growth in USA.
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The data in this study covered the period
from 1934 to 2010.
Data were collected from Human Mortality
Database, Williamson (2013) and Chantrill (2012).
This study adopts the continuous wavelet
analysis and discrete wavelet analysis to investigate the dynamic
relationship between health progress and economic growth.
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The sign of correlation between health
progress and economic growth relies on the strength of the positive (or
negative) correlation in the short and medium runs, and negative (or positive)
correlation in the long run.
The findings from continuous wavelet
analysis reconcile a pro-cyclical pattern in life expectancy at birth in the
long run with the opposite pattern in life expectancy at birth in the short
run with respect to the economic growth.
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In this study, health progress and economic
growth depend on the strength of the positive (or negative) correlation in
the short and medium run, and negative (or positive) correlation in the long
run. Previous studies such as Tapia Granados and Diez Roux (2009), Tapia
Granados (2005), Brenner (2005), and Ruhm (2007), (2005), (2003), (2000)
investigating the relationship between health and economic growth in the USA
never found positive (negative) relationship between health progress and economic
growth in the short (long) run.
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*Notes
WDI- World Development Indicator
SESRIC- Statistical, Economic and Social
Research Training Centre for Islamic Countries
WHO-
World Health Organization
HRC-
Human Resource Centre
REFERENCES
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Gong, L., Li, H., & Wang, D. (2012). Health investment, physical
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