Article Type : Research Article
Authors : Athanase Iyakaremye and Atul Pati Tripathi
Keywords : Fertility; Life; Life expectancy; Mortality
Rwanda's economic
progress, spearheaded by a public-sector-driven model, has achieved significant
milestones but faces challenges such as escalating public debt. This study
investigates the relationship between economic growth and life expectancy in
Rwanda, addressing gaps in existing literature regarding the country's unique
socio-economic context. Through quantitative methods encompassing descriptive,
correlation, and causal-comparative analyses, along with econometric
approaches, the research employs Gross National Income (GNI) per capita as a
proxy for economic growth, examining its association with life expectancy while
considering control variables such as education, mortality, and fertility. Data
spanning from 1965 to 2020 were collected from The World Bank's World
Development Indicators. Employing a Vector Error Correction Model (VECM) to
explore the effect of fertility on life expectancy, the study identifies a
significant positive correlation between economic growth and life expectancy,
even amidst challenges like the 1990s genocide and the recent COVID-19
pandemic. External funding, particularly in healthcare, has contributed to
improvements in life expectancy, evidenced by a rise from 26.2 years in 1993 to
68.7 years in 2018, projecting to 71.4 years by 2032. Findings from Ordinary
Least Squares (OLS) regression reveal a statistically significant positive
relationship between economic growth and life expectancy, highlighting the need
for interventions to bolster economic growth for enhanced life expectancy. Additionally,
the study investigates the interplay between Economic Development (ED) and the
Human Development Index (HDI), underscoring the significance of HDI in
fostering sustainable economic growth. Granger causality tests indicate a
reciprocal relationship between ED and HDI, emphasizing the importance of
interventions aimed at enhancing HDI for sustained economic development. In
conclusion, the study provides insights for policymakers to formulate targeted
interventions addressing factors influencing life expectancy, ultimately
promoting population health and well-being in Rwanda.
Rwanda's development trajectory, characterized by a
public-sector-led model, has seen significant achievements alongside challenges
such as rising public debt. Heavy reliance on large public investments has led
to notable budget deficits funded by external borrowing, resulting in a steep
increase in the debt-to-GDP ratio. External financing, including grants and
borrowing, played a crucial role in financing public investment, but the future
necessitates a shift towards greater private sector involvement to sustain
economic growth [1]. The private sector faces obstacles to investment,
including low domestic savings, skill gaps, and high energy costs. Overcoming
these challenges is essential to maintaining high investment rates and
accelerating growth. Additionally, promoting domestic savings alongside
inclusive growth is seen as crucial for efficient resource allocation and
poverty reduction [2]. While Rwanda has made significant progress in reducing
poverty and improving living standards, the COVID-19 pandemic poses a threat to
these gains, particularly in terms of increasing poverty and impacting human
capital development. Rwanda's economic progress has been accompanied by
improvements in living standards, evidenced by reductions in child mortality,
increased school enrollment, and poverty alleviation. However, the pandemic
threatens to reverse these gains, highlighting the urgency of addressing its
impact on poverty and human capital development. Despite these challenges,
Rwanda's Vision 2020 outlined ambitious targets for economic and social
development, including increasing GDP per Capita and life expectancy while
reducing poverty (United Nations Development Programme) [3].
The relationship between economic growth and life
expectancy is a key focus in public health research. Economic development
contributes to improvements in health sectors and overall human well-being.
Understanding the determinants of life expectancy is crucial for national
development, as longer life expectancy contributes to economic productivity
[4]. Empirical studies examine the influence of economic, social, and
environmental factors on life expectancy, emphasizing the importance of
economic growth, globalization, and financial development as key determinants.
Therefore, studying the relationship between life expectancy and economic
growth in Rwanda is essential for guiding policies to enhance economic
performance and human well-being [5].
Research problem
Despite Rwanda's remarkable progress in economic
development, challenges persist in achieving significant improvements in life
expectancy. Factors such as low school participation, illness, poor nutrition,
and poverty continue to hinder the population's overall health and well-being.
While economic growth is often associated with better access to healthcare,
education, and resources, its direct impact on life expectancy in Rwanda
remains unclear. Existing research offers mixed findings, with some studies
suggesting a positive relationship between economic growth and life expectancy,
while others emphasize the importance of healthcare spending, education, and
income distribution. However, limited empirical evidence specifically focuses
on Rwanda's context. Therefore, there is a need for comprehensive research to
explore the contribution of economic growth to life expectancy in Rwanda,
considering the unique socio-economic and healthcare landscape of the country.
This study aims to fill this gap by examining the relationship between economic
growth and life expectancy in Rwanda, identifying key determinants, and
providing insights for policymakers to develop targeted interventions aimed at
improving overall population health and well-being.
The causal effect of economic growth on life
expectancy has been a topic of extensive research, with scholars aiming to
understand the relationship between these two variables. Sen, employs an
identification strategy based on the epidemiological transition as an
instrument to estimate this effect [6]. Using predicted mortality change as an
instrument for life expectancy, Davies and Kuhn, find a significantly negative
average effect of increased life expectancy on GDP per capita. Additionally,
highlight that while an increase in life expectancy leads to population growth,
its impact on aggregate GDP remains weak and insignificant [7,8]. Preston, also
notes that the effect of life expectancy on income per capita is significantly
negative [9]. The link between health outcomes and economic growth has
attracted significant attention from theorists and policymakers, seeking to
understand why healthier populations might lead to higher economic prosperity.
Economic growth theories, dating back to classical economists have evolved to
consider health as a crucial component of human capital formation, alongside
education and innovation. While early growth models overlooked the role of
health, modern theories emphasize its importance in facilitating productivity
growth and technological innovation [10]. Grossman developed a model of demand
for health, viewing health as a form of capital that generates healthy time,
further integrating health into growth models [11]. Empirical studies examining
the relationship between life expectancy and economic growth provide mixed
results. While some find a positive correlation between life expectancy and
economic growth, others suggest a negative or negligible impact [12].
Additionally, studies differ in their findings regarding the nature of this
relationship, with some suggesting a U-shaped pattern, while others argue for a
linear association. These disparities underscore the complexity of the
relationship between health and economic growth, influenced by various
contextual factors and methodological approaches. In the context of Rwanda,
significant progress has been made in improving living standards and health
outcomes, including reductions in child mortality, increased primary school
enrollment, and improvements in life expectancy and maternal mortality rates.
However, the COVID-19 crisis poses challenges to sustaining these gains,
highlighting the importance of continued investment in human capital and
healthcare infrastructure. As Rwanda strives for further economic development,
understanding the intricate relationship between economic growth and life
expectancy becomes essential for informed policy decisions aimed at promoting
sustainable and inclusive growth while ensuring the well-being of its
population [12].
Research gap
Despite extensive research on the causal relationship
between economic growth and life expectancy, there remains a gap in
understanding the specific dynamics of this relationship in the context of
Rwanda. Existing literature predominantly focuses on global or generalized
trends, with limited empirical evidence from Rwanda itself. Moreover, while
some studies suggest a positive correlation between economic growth and life
expectancy, others indicate contradictory or inconclusive findings. Thus, there
is a need for empirical research tailored to Rwanda's socio-economic and
healthcare context to elucidate the nuanced relationship between economic
development and life expectancy within the country, informing targeted policy
interventions and investment strategies [13].
Keynesian theory
By Keynesian theory, the increase of saving rate due
to the improvement of life expectancy results in a depressive effect on
economic growth by decreasing aggregate demand. In empirical ways, the impact
of health on economic growth may be at the micro and macroeconomic levels. At
the macro level and from the seminal article of Barro and Sala-i-Martin,
several studies analyzed the life expectancy on economic growth [14]. Barro
conducted a study in eighty-four countries that show how life expectancy has
improved to 10% leading to a GDP growth of 0.52% to 0.62% [15]. From one
hundred and four countries' panel data using a convergence approach, present
that an increase in life expectancy in one year leads to the economic growth of
2.6 to 4% of GDP [16]. Lorentzen highlighted that an increase in life
expectancy has a positive effect on economic growth [17]. Reveal a positive and
significant relationship between life expectancy and economic growth [18]. The
three authors reach the conclusion that an initially high level of life
expectancy and quick improvement of the latter has a significantly positive
impact on the GDP per capital.
Research design
The following quantitative research methods were
employed such as descriptive research (it requires a very large sample size and
is used to describe a population), correlation research (it explores the
relationship between two or more variables), and causal-comparative (it seeks
to establish the difference in variables between groups). The methodological
approach adopted the descriptive and econometric approaches. The Gross National
Income (GNI) per capita is presented as a function of life expectancy and other
control variables such as education, mortality, and fertility [19]. The time
series were indulged with the unit root problem that makes the error of the
time series nonstationary. Co-integration test plays a big role in finding the
relationship between variables [20-23]. The vector error correction model
(VECM) was used to investigate the effect of fertility on life expectancy in
Rwanda from 1965 to 2020. The general assumption in the suggested model is that
there is at least one long-run co-integration vector for the variables and the
value of the dependable variable can be meant as a function of past values of
the dependent variable, past values of the independent variable, and error
term.
Population and sample
The life expectancy indicator mostly relies on the
number of years of life expectancy at birth. For instance; among the past
studies conducted, employed the life expectancy at birth, utilized the total
number of years that an individual has to live in a country to gauge the life
expectancy variable. The researcher used the number of years of life expectancy
at birth (total in men and women) to measure life expectancy in Rwanda. To
obtain this measure and annual GDP growth rate, data were collected from the
World Bank Database.
Data collection procedures
The data were retrieved from The World Bank’s World
Development Indicators from 1965 to 2020. The data on fertility were used to
test the co-integration and causality relationship between life expectancy and
fertility in panel data. The researcher used the variable of life expectancy as
an indicator of health and employed real per capita GDP as a criterion of
economic growth. The study used the annual data and covers the period from 1965
to 2020. The logarithms of variables were employed for empirical analyses. The
researcher adopted an empirical specification that allows for different effects
of life expectancy on population. To figure out problems of reverse causality
and to investigate the causal effect of fertility on life expectancy. The base
sample was relevant to the predicted fertility instrument and life expectancy.
In further investigations of the human capital, the channel was tracked based
on the population share without schooling and on the average years of schooling
in the population of working age constructed by Cohen and Soto.
Data analysis
Effect of economic
growth on life expectancy
The research examined the relationship between
economic growth and life expectancy. The increase in population size reduces
wages and decrease the incentive to work as well as the income per capita.
LFPRart = ? + ?LE15rt + ?r
+ ?t + eart, (3) where this refers to age group, r relates to Rwanda
and t refers to the year. GDP per capita reflects a nation's standard of
living. LE15rt is the life expectancy, r: Rwanda, and t: Year. The regression includes the year and country
fixed effects. The data collected was analyzed in STATA 17 to get results.
In the early 1990s, Rwanda met the tragedy of a
100-day genocide where a million Innocent Tutsis were killed. This destroyed
all infrastructure and left millions in deeper poverty. In this period, the
life expectancy reached a low of 26.2 years in 1993 at the height of the
genocide. However, it has risen in 2018 to 68.7 years. Rwanda's projection in 2032, life expectancy
was 71.4 years. Many factors have been put into place to increase life expectancy
and social welfare. Hence, in 2022, Rwanda has reached the global average. In
fact, the VIH/AIDS case and death rates have potentially slowed down. The
external funds have improved Rwandans ‘health. In the year of 1995, Rwanda
received $0.50 per person for healthcare, less than any other country in the
continent of Africa. Many organizations like Partners in Health (PIH) played in
the increase of the population’s access to healthcare and supported Rwanda to
rebuild community health systems.
OLS between economic growth
and life expectancy
Life expectancy (P=0.0000) demonstrates a robust and
statistically significant positive correlation with economic growth at the 5%
level of significance. The coefficient indicates that a one-unit increase in
life expectancy corresponds to a minute uptick of 6.65E-11 in economic growth.
Thus, elevating life expectancy by one unit is associated with an incremental
enhancement in economic growth. This underscores the imperative of implementing
strategies to bolster economic growth as a means to augment life expectancy in
Rwanda, emphasizing the interdependence between socio-economic development and
population health outcomes. Such insights are pivotal for informing policy
decisions aimed at fostering holistic societal advancement (Table 1).
Vector autoregressive
model for economic growth and life expectancy
The autoregressive model, as depicted in Table 10,
elucidates the temporal evolution of each variable through its respective
equation. Notably, the equation incorporates variables lagged by one year, such
as life expectancy (p=0.000) and economic growth. Essential prerequisites for
understanding this model include a comprehensive list of variables and
covariates, along with hypothesized relationships (Null and Alternative
hypotheses) that may influence each other dynamically over time. This
structured approach enables researchers to discern the intricate interplay
between different factors and their cumulative impact on the variables under
examination, facilitating informed analysis and decision-making processes.
Granger causality Wald tests for economic growth and
life expectancy
Life expectancy (p?=?0.000) does significantly cause
GDP at 5% in (Table 2)
Economic development (ED)
and human development index (HDI)
HDI (P=0.0000) is positive and statistically
significant on mortality at 5% in (Table 3). The coefficient term tells the
change in Birth rate for a unit change in HDI this means that if the HDI
decreases by 1 unit, then the ED decreases by -10.08. In other words, we need
to implement interventions to increase the HDI to keep the economic growth of
Rwanda.
Vector autoregressive
model for ED and HDI
(Table 4) presents the autoregressive model,
elucidating the temporal dynamics of each variable through individual
equations. Notably, the equation incorporates variables lagged by one year,
such as ED (p=0.001) and HDI (p=0.000), indicating their significant impact.
Understanding this model necessitates prior familiarity with a comprehensive
list of variables and covariates, along with hypothesized relationships (Null
and Alternative hypotheses) that may influence each other dynamically over
time. This structured approach facilitates in-depth analysis of the interplay
between various factors and their evolving effects, aiding researchers in
discerning patterns and trends essential for informed decision-making and
policy formulation (Table 5,6).
Economists widely argue that health plays a pivotal
role in fostering human capital and driving economic growth. This study delves
into the relationship between Rwanda's economic development and life expectancy
spanning from 1969 to 2020. Employing Vector Autoregression (VAR) and causality
analysis methods, it unveils a statistically significant correlation between GDP
and life expectancy, echoing findings from prior research. Granger causality
tests further affirm GDP's profound influence on shaping life expectancy
outcomes. Notably, GDP emerges as a critical determinant of life expectancy in
Rwanda. The study unveils that enhanced life expectancy is positively
influenced by GDP through various channels, including increased female labour
force participation, favourable changes in fertility rates, and advancements in
education, which collectively bolster the labour supply. While the nexus
between health and economic growth is extensively explored in developed
nations, this study's focus on Rwanda offers unique insights into their nuanced
interplay within a developing context. The observed causal relationship between
GDP and life expectancy underscores the pivotal role of economic development in
improving health outcomes, and conversely, the importance of health in driving
sustainable economic growth. This highlights the imperative for targeted policy
interventions aimed at promoting both economic prosperity and public health in
Rwanda, thereby fostering comprehensive and inclusive development strategies
tailored to the country's specific socio-economic landscape.
Comprehensive Investigation: Future research should
delve deeper into various aspects of economic development and their impact on
life expectancy in Rwanda. Specifically, attention should be given to analyzing
the correlation between economic growth and the political climate, considering Rwanda's
historical experiences of both stability and instability.
Focus
on foreign direct investment (FDI):
Recognizing the potential influence of FDI and economic growth on life
expectancy, Rwanda should actively seek to attract foreign investments to bolster
its economic climate. This entails fostering an environment conducive to
foreign investment while prioritizing strategies to enhance economic
performance.
Investment
in human capital: It is imperative for the
Rwandan government to prioritize investment in human capital development. This
includes initiatives such as comprehensive training programs, improving
healthcare infrastructure, generating employment opportunities, and ensuring
affordable access to healthcare services. Such investments not only enhance the
quality of the labour force but also contribute to increased productivity and
economic growth.
Healthcare
access and quality: Addressing the high
mortality rate requires the implementation of policies aimed at providing
accessible and high-quality healthcare services. This involves ensuring access
to essential healthcare facilities and affordable medications to mitigate
preventable deaths. By prioritizing healthcare accessibility and quality,
Rwanda can effectively reduce mortality rates and promote overall well-being.
Mitigating
economic impact on mortality: The study highlights the
short-term relationship between economic variables and mortality rates. Given
this insight, policymakers should be cognizant of the impact of economic
factors such as inflation on essential goods and purchasing power. Measures
should be taken to mitigate the adverse effects of economic fluctuations on
population health, including initiatives to alleviate poverty, improve
nutrition, and reduce maternal and infant mortality rates.
Continuous
monitoring and research: Continuous monitoring
and further research are essential to understand the dynamic relationship
between economic development and mortality rates in Rwanda. By staying abreast
of emerging trends and conducting rigorous research, policymakers can make
informed decisions to address health disparities and promote sustainable
development.