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European Journal of Economics, Finance and Administrative Sciences
ISSN 1450-2275 Issue 51 (2012)
© EuroJournals, Inc. 2012
http://www.eurojournals.com/EJEFAS.htm
Relation between Health and Wealth: Is it a Myth or a True
Relationship? Evidence from Egypt
Doaa Mohamed Salman
Associate Professor of Economics, Faculty of Management Sciences
Modern Sciences and Arts University (MSA), Egypt
Tel: +2 -01006179666
E-mail: doaaslman@yahoo.com; dr.doaaslman@gmail.com
Eyad Mohammed Atya
PhD in Economics, Economics Department, Zagazig University, Egypt
Tel: + 201060940600
E-mail: eyadatya@hotmail.com
Abstract
This paper investigates the relationship between health and wealth in the Egyptian economy
during the period 1960-2010. We use life expectancy at birth as a measure for the health
and gross domestic product per capita (constant 2000US$) as a measure for the wealth. We
employ the cointegration analysis and utilize the linear and nonlinear forms. This paper
concluded that for the linear model, the results indicate that there is a positive and
significant relationship between health and wealth. For non-linear model, the results show
that health and wealth have inverse U-shape relationship. This conclusion will help policy
makers and researchers in developing countries with high fertility rate to consider a
strategic health program to achieve impacts on nation's health and human wealth. However,
further work need to be done in order to specify exactly which policies will be effective in
improving economic growth and development in LDCs.
Keywords: Health, Wealth, life expectancy at birth, Cointegartion analysis
1. Introduction
For decades researchers documents the positive links between income and a wide array of health
indicators (see reviews by Deaton, 2001; Robert, 2000b; and Wagstaff and Pamuk, 1998). In lower
income countries, Case et al. (2002) provide evidence that these countries experience higher rates of
asthma, heart conditions, hearing problems, digestive disorders and elevated blood lead levels. While
in high income level countries they witness better health level. On the other side, there is a gap in
literature between the relation between wealth and health. This is a surprising fact because we view
wealth as a basic measurement that affects a person’s health. The question is whether the same
relationship exists between wealth and health.
The relation between wealth and health are interrelated and require decision makers to realize
the core channels to achieve growth and development. Health role is vital for economic growth and the
nation’s wealth. The direct effect of wealth on health occurs via different levels. First, finance
channels, saving provide a direct effect on health. In poor countries with low saving rates face a
challenge to protect ill people. The second channel involved is education, as people with better
127 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
educated level are able to protect their health, and able to use the preventative and curative medical
system. Third, financing agencies represented in: public sector, such as, governmental hospitals and
clinics, and university hospitals, while private sector such as: private insurance companies, unions,
nongovernmental organization (NGO) and household sector. Finally, the quality of the service provider
represented in staff.
Improvement in health based on various macro input factors represented in the quality of
education system, sufficient government expenditure scheme, effective clean environment regulation,
quality of the service providers, and the cost of health service. These factors reflect on the human being
health and the level of productivity in positive trend. We believe that population can be a curse in case
if they are unproductive or a bliss if government invest them to sustain growth and wealth. Changes in
fertility behavior in addition to health and investing in human capital is expected to have to have
effects on life expectancy and economic growth. This paper contributes to literature by investigating
Egypt as one of the developing countries characterized by high population density and volatile
economic growth in the context of demographic transition. Initially, we explore the role of health as
being an intermediate channel affecting wealth. Then we overview the literature and discuss empirical
specifications and result. Finally we draw our conclusion and recommendations.
The Egyptian population started the 20th century with 10 million people and by the end was
almost 70 million. Most of the increase that took place since the end of World War II, was due to an
initial rapid decline in mortality, and decline in death rate. Before World War II, more than 250 out of
every 1,000 Egyptian infants died before reaching their first birthday (Fargues 2000). Since the late
1940s, the infant mortality rate has dropped quite steadily. For at least 20 years this decline in mortality
was not matched by a drop in birth rates. Data from the World Fertility Survey suggest that the total
fertility rate (TFR)1 for all of Egypt was 7.1% in the early 1960s, the TFR declined between from 5.9%
in 1970 to 4.4 % in 1990 and finally to 2.7 % in 2010. United Nations projections suggest that the
population will exceed 127 million by 2050 (United Nations Population Division 2003).
The rapid population growth was the result of a substantial decline in mortality triggered by the
increased use of antibiotics and vaccinations, and by the spread of disease control and sanitation
programs. These improvements substantially increased life expectancy at birth. But achieving “Good
health” is obviously a multidimensional aspect and the impulsive need to pull off good health relies on
complex factors. Egypt Human Development Report 2010 (EHDR) recorded values for the progress of
the income index indicating a noticeable improvement in its income level, the increase in average GDP
per capita between the 2008 and 2010 EHDRs took place despite the rise in the percentage of the poor
from 19.6% to 21.6%, and the increase in the absolute number of poor.
Egyptian government health policy increased health expenditure remarkably during the period
1995 to 2010, figure one records the increase in per capita government expenditure on health (PPP int.
$) in Egypt from 50 percent in 1995 to 108 percent in 2010. However, the increase in health
expenditure did not meet the needs of the population demands and the demand of human resources for
health. In Egypt, the Ministry of Education and Ministry of Higher Education control the supply of
human resources for health (e.g. doctors and nurses) from a side, while the Ministry of Health controls
a large part of the demand of human resources for health; as the government is committed -by law- to
hire graduates of the faculties of Medicine and Nursing and schools of nursing. The main concern of
the Ministry of education is to tune the balance between the demand required by health foundations
and the available capacity of educational institutions rather than the quality of the population health.
The demand for human resources for health in Egypt is influenced by many things other than
population needs.
1 The total fertility rate (TFR) is a useful measure for examining the overall level of fertility. It can be interpreted as the
number of children a woman would have by the end of her childbearing years if she were to pass through those years
bearing children at the currently observed rates. The TFR is calculated by summing the age-specific fertility rates. It is
presented for women age 15-44 and women 15-49 to facilitate comparisons with other surveys in which the age range of
interviewed women may differ from that in the 2005 EDHS.
128 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
Figure 1: Egypt per capita government expenditure on health (PPP int. $) during 1995- 2010
Source: World Health Organization 2011
In addition, the progress in Egypt total expenditure on health as a percentage of gross domestic
product during 2000 record was 5.6%, that increased to 6.3 % in 2006, thendroped to 4.7 in 2010 (
WHO, 2011). Although, the Egyptian government expenditures on health as a % of total expenditure
on health was not maintaining a stable increase in this level, it recorded 40.7 % as a percent of the total
expenditure on health during 2000 to drop to 37.4% by 2010, (see figure 2). These values is considered
to be low percentages compared with the Egyptian population.
Figure 2: General government expenditure on health as a % of total expenditure on health during 2000 to
2010
Source: World Health Organization 2011
It is worth noting that despite improvements in life expectancy rate at birth total ( years) from
70 to 73 there is still a significant number of Egyptians live in slums, with poor and overcrowded
housing, limited food supply, and inadequate access to clean water, good quality health care, and
education. The poorest 20 percent of the Egyptian controlled only 9 percent of wealth during year
2008, while the wealthiest 20 percent controlled 40 percent of the country’s wealth with a drop 2
percent in year 2000, (WDI, 2011). This inequality in income rooted to the government policies as it
focuses on the Northern cities e.g. Cairo and Alexandria in its investment plans more than the south
rural areas.
Inequality also spread to a certain extent to the education sector as the household wealth level is
a major determinant of higher education enrollment. However, we found that almost half of those who
129 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
are or have been to university came from the richest wealth quintile (richest 20%); only 4% came from
the poorest wealth ones (poorest 20%). In 2008, United Nation Population Division report reasoned
this to the free higher level of education that the government adopted since 1962. Resulting in an
urban/rural differential where 39% of rural youth compared to 61% of urban youth finish higher
education2. Consequently, youth in rural area with limited capacity for learning and working endure
higher limitation in human developments that is transmitted to their children. Egyptian Government
efforts to raise the human level of development focusing on the education, health and income are not
sufficient as it is still facing continuous inherited problems.
2. Literature Review
From the theoretical point of view, the standard neoclassical model of the limits of improvement in
health and life expectancy highlights that increased life expectancy increases the population number
while reducing the capital-labor ratios and decreasing the per capita income. However, endogenous
growth models in the tradition of Becker and Barro (1988) propose that human capital investment and
fertility responses may offset the severe predictions of the neoclassical model. Other researchers
provide a strong relationship between initial levels of health and economic growth, using life
expectancy at birth as their basic measure of overall health of the population. They conclude that
improved health is associated with faster economic growth and supported the positive relationship
between health and economic growth (Gallup, Sachs and Mellinger, 1999).
Nora Lustig (2006) conducted in Mexico during 1970-95 to study the relationship between
health and growth using life expectancy and mortality rates of different age groups as health indicators.
It was observed that health is responsible for approximately one-third of long term economic growth.
Results showed that low health levels are linked to poverty trap. There is a clear imperative to focus on
improving the health status of the population to unleash higher economic growth and lower poverty
rates. Moreover, Acemoglu (2006), in a study entitled "impact of life expectancy on economic growth"
investigated the recent agreement in scientific assemblies and policy making bodies that disease
environment and health status at present have been created through high income differences among the
countries. The study discussed that health status improvement does not only improves the quality of
life but also stimulates rapid economic growth. The conclusions drawn from this study was that the
increase in life expectancy led to a considerable increase in population, however considerable birth rate
was not controlled to compensate increased life expectancy
A recent paper by Acemoglu and Johnson (2007) further investigated the changes in life
expectancy with dates of global health interventions to combat 15 major diseases. They studied 47
countries at various levels of development, during period 1940 to 1980, they offer little evidence for
the causal effect of life expectancy on income per capita differs during different phases of
development. Cervellati and Sunde (2009) argue that the increase in life expectancy reduces income
per capita in countries that did not go through the demographic transition. In post-transitional countries
the gains in life expectancies leads to an increase in per capita income. Additionally, Bloom, Canning
and Fink (2009) argue that Acemoglu and Johnson’s results are based on the assumption that initial
health and income do not affect the subsequent economic growth. The healthiest nations in 1940 are
those that benefitted least from the health interventions and also the ones that grew the most, giving a
negative relationship between health interventions and growth. Furthermore, Cervellati and Sunde
(2011) studied 47 countries showing that wealth exhibits a V-shaped relation with health. Thus, they
argue that only after the onset of the demographic transition, life expectancy had a causal positive
effect on wealth.
2 This high unemployment can be explained by the fact that young people in poor households have a lower reservation
wage, and hence accept any possible form of employment. While, young graduates from the highest socio-economic
classes rely on their parents to remain unemployed until a suitable job is found.
130 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
On the other side, Zachary Zimmer (2008) studied the relation between wealth and disability in
one of the world's poorest regions – rural Cambodia. The research presents a U shape relation but the
paper speculates on possible causal directions (both from wealth to health and vice-versa). Moreover,
Hansen C. (2012) used panel data from 119 countries during the period 1940 to 1980. He discovered
that wealth traces a U-shaped path as a function of the level of national health and that excluding the
possibility of a nonmonotonic path might lead to wrong conclusions about the wealth–health nexus.
Therefore, the main message is that when studying this relationship over time, a form of nonlinearity
for health should be included in the empirical model. Scholars’ results using panel data to identify the
relation between health and wealth either presents a U – shape or V- Shape relation. The reasons rely
on the stage of development and the demographic transition for each country. In an early stage of
development, the effect of health improvements on wealth is negative because, at this stage, the only
effect is to increase the size of the population which possibly has an adverse effect on wealth.
3. Empirical Specifications and Results
We investigate the relationship between health and wealth in the Egyptian economy during the period
(1960-2011). The basic empirical specification is given by the following reduced form relationship
between wealth and health.
3.1. Model and Data
We employ linear and nonlinear models so we estimate the following two models.
01
GDP ββLife (Model 1)
2
01 2
GDP Life Life
(Model 2)
GDP represents the level of wealth measured by the log of Gross Domestic Product per capita
(constant 2000 US$). Life represents level of health which is measured by log of life expectancy at
birth3. We collect data for Gross Domestic Product (GDP) and life expectancy at birth from the World
development indicator.
3.2. Empirical Results
Our methodological approach in this paper is structured as follows: first, we test for stationarity in the
time series for all the variables using the augmented Dickey–Fuller (ADF) test (Dickey and Fuller,
1979). The results indicate that the variables are non stationarity as we see from table (2).
Table 1: Augmented Dickey-Fuller unit root tests
Variables Lags Constant lags Constant and trend
LGDP 1 -0.4636 1 -2.7009
DLGDP 0 -4.104277*** 0 -4.0604**
LLife 3 -2.1289 3 -0.116317
D(Llife) 2 -0.252436 2 -0.436988
DD(LLife) 1 -0.943081** 1 -0.685901**
LLife2 3 -0.010527 3 -0.873052
D(LLife2) 2 -0.711936 2 -0.389649
DD(LLife2) 1 -2.924523* 1 -0.3.657034**
(*), (**) and (***) indicate 10 %, 5% and 1% level of significant, respectively.
Akaike Information Criteria (AIC) is used to select the lag length
DX represents the first difference of variable x
DDX represents the second difference of variable x
3 The total life expectancy at birth is the average number of years a child would live if prevailing patterns of mortality of
the total population at the time of his/her life. This also is expected to have direct relationship with the rate of economic
growth in the economy. This is because as the living condition improves, human longevity is expected to be enhanced
and vice-versa. This is achieved when there is improvement in health expenditure.
131 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
The second step is to test for cointegration using the Johansen technique (Johansen, 1995),
which is carried out in a context of a vector auto regression (VAR) model. Whether or not the variables
included in the VAR model they are cointegrated. It has implications for the form of that model and for
the type of causality test supporting it is the appropriate technique. If the Johansen tests support the
conclusion that the variables are not cointegrated, then causality tests must be based on a VAR model
in first differences. If, however, the variables are cointegrated, then causality tests should be based on
an error correction model (ECM). So, the third step is to test for causality by employing the appropriate
types of causality tests. Table (2) shows that we have long –run relationship among the variables. So
we will proceed to estimate the Error Correction Model (ECM).
Table 2: Johansen cointegration tests (1995)
Model 1
Rank Eigen value Trace statistic 5% Critical value
0 . 22.1454 15.41
1 0.36174 1.0421* 3.76
2 0.02193
Model 2
0 . 88.7028 29.68
1 0.81221 8.4263* 15.41
2 0.12718 1.8973 3.76
3 0.03876
We proceed to estimate error correction model (ECM) for the models. Table (3) presents the
results of error correction model for both models. The first model (linear model) shows positive and
significant correlation between health and wealth at 1 % level of significance. This means that the
improvements in the health will lead to an increase in the wealth of the Egyptian economy. We use the
non-linear model to estimate the shape between the health and wealth. Column (2) shows a positive B1
and negative B2 – both statistically significant at the 1 % level of significance. This means that the
curve which describe the relationship between wealth and health take an inverse U-shaped relationship
for the Egyptian economy and the turning point is 69 years.
To explain the inverse relation between wealth and health it passes through two stages. In the
first stage, the improvements in the wealth (measured by life expectancy) will lead to improvement in
wealth. i.e.: the worker will be healthier and so productivity is expected to be high. In the second stage,
we have two opposite effects. The first is an increased productivity of the labour (positive effect). The
second effect is increased population size (as a result of the improvement of the health). Consequently,
this will make pressure on the economic growth and exhaust the benefits seen from improving the
health. In the second stage the negative effect was higher than the positive effect and this will lead to a
negative relationship between health and wealth.
Table 3: Error Correction Model
GDP GDP Turning point
LLife 3.2789*** 12.12516*** -
(0.118732) (2.6985)
LLife2 -1.429004*** 69
(0.34728)
*** indicate 1 % level significant. Standard errors (SE) in parentheses
6. Summary and Concluding Remarks
This research adds to the literature of the relation between health and wealth via empirical analysis to
the Egyptian economy, during the period 1960-2010. We try to focus on one country using time series
132 European Journal of Economics, Finance and Administrative Sciences - Issue 51 (2012)
data and apply cointegration analysis. Previous work relied on panel data but in this study we tried to
focus on one country using time series data and apply cointegration analysis. We estimated linear and
non-linear models. For the linear model, the results indicated that there is a positive and significant
relationship between health and wealth. For non-linear model, the relationship between health and
wealth follows an inverse U-shape relationship, Egypt witness an inverse relationship with a
turnaround value of about 69 years of life expectancy, i.e., this means that improving the health in the
long run put more pressure on the economic growth and consumes it, and health problems is an
obstacle ahead of enjoying the growth in economic growth.
Improving health in Egypt among all governorates is a challenge the government is facing,
especially with present of high inequality among governorate. The unavailability of data among
governorate over a long time posed a limitation in the present work for a deep analysis in each
governorate. And, to achieve better government expenditure allocation in the health sector must be
parallel with higher quality of the service provider. The issue that required a new perspective to
restructure insurance health program to be a tool for investment not consumption approach.
For policy implication, we believe that the way to improve the economic growth is to improve
the skills of the labour via education to prevent transmission of poverty across generation. This is in
agreement with previous reports supporting the direct effect of education on poverty. Furthermore, the
ministry of education and higher education need to match the market needs with the supply from the
educational institutions. This is expected to be one of the effective policies that can be implemented in
the health and wealth sectors which will results in improved economic growth and development. We
think that if the population exceeds 127 million by 2050, as it is estimated to be, while the government
adopting their insufficient policies to deal with health expenditure, then the health measurement will
deteriorates pressure and will have severe negative impacts on economic growth in the near future.
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