One high as 11 years. Developed countries are known

One
of the most widely used indicators of the overall development of a country is
life expectancy at birth. It has seen significant increases over the last ten
years in most of the countries of the world. This is of particular significance
for the post-colonial and the developing world since they hope to achieve social
and economic progress through investing substantial amount of resources on
social sectors like health, education, sanitation and social safety nets. Alleviation
of poverty, malnutrition, adult literacy, access to safe drinking water, and
sanitation have also been impressive over the years and it is expected that
they have positively impacted life expectancy.

But
life expectancy has also demonstrated persistently high variability between
countries over the past half-century. As of 2017, the gap in life expectancy
between regions classified by the United Nations (UN) as more developed and
less developed is as high as 11 years. Developed countries are known to have
outpaced developing and under-developed countries in respect to their
demographic structure as well as their economies. It is posited that developed
countries have reached their goals by having an ideal economic structure and
are intending to sophisticate their economies. On the other side, developing
countries are still in their transition phase and thus they can be compared to
with developed countries so as to apply changes to their current models and
hence reach their expected social and economic goals.

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Thus,
it is important to analyse the demographic and economic factors affecting life
expectancy among the developed and developing countries of the world

 LITERATURE
REVIEW

                                        Life
expectancy at birth, is an important function that tell us how well the country
is performing.  Works like Kabir (2008), Shaw, Horrace, and Vogel
(2005), Rodgers (1979) clearly points out the high correlation between GDP per
capita & life expectancy. Adekola
(2002) has shown that life expectancy increases as income per capita
increases.

                                       Apart from these factors like health
expenditure as a portion of total public expenditure of a country, education or
literacy rate have a huge impact on life expectancy in case of developing
nations. In Kabir (2008) it has been
emphasized that life expectancy in developing nations has been increasing due
to significant improvement in public sectors like education, basic health care &
sanitation.

                                       In Rodgers (1979), it has been argued that
increase in per capita income allows an individual to get better medical
facilities and hence improve life expectancy Strulik (2015) found that the cardiovascular revolution led to a
rise in life expectancy by 2 years which further helped to increase higher
education enrolment by 7% per unit in US. Hazen
(2012) has also identified that there is a positive correlation between
life expectancy and average years of schooling.

                                            An important argument has been put forward by
Deaton concerning the relation between Life expectancy and income. He shows
that income does not necessarily have a positive correlation with Life expectancy.
He argues that we should look at the distribution of GDP among the populace. He
says that at lower levels marginal increase in income leads to significant
gains in life expectancy but after a certain threshold variance in improvement
or disimprovement of life expectancy cannot be suitably explained by income. In
this regard Prof. Amartya Sen gives the example of the Indian state of Kerala
which has managed to achieve impressive life expectancy at a relatively low
level of income.

                                      

OBJECTIVES

                              This paper seeks to examine whether
the same factors can explain fluctuation in life expectancy in both high income
economies and low-income economies. We take life expectancy to be a function of
the economic variables incorporate per
capita GDP, per capita public and private health expenditure, urbanization,
fertility rate, and medical care inputs, whereas non-economic variables
incorporate nutritional status, access to safe drinking water, and dummy for
geographical location of a country. We seek to check if the regressors we have
taken are significant for both high income and low-income countries and if
differences arise between high income and low-income countries what measures
should be taken by developing countries so as to enhance the health of the
populace. Thus, we shall do comparative analysis of determinants of life
expectancy in developed and developing countries.