This (Outreville 1996) and (Ward and Zurbruegg 2000)

This section
summarizes the past literature on life insurance and its relationship to the
economic growth of various countries. We look at similar studies, comparisons
of various countries and regions throughout the past years.

2.1 Similar studies

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In this section we will show the importance of what the past literature
has studied with regards to the relationship of life insurance and its effects
on the economy of various countries.

It is important to note that researcher in the field such as (Campbell 1980),(Outreville 1996) and (Ward and Zurbruegg 2000) have all identified the significant positive impact that the level of
income has on the economy of a country. For instance, (Campbell 1980) claims that the force that drives consumers to purchase life insurance
is because they feel the need to protect the life of dependents.

If we look at comparison of specific
countries, for instance the study by (Truett 1990) whereby they compare the consumption growth pattern of life insurance specifically
in Mexico and United States during the periods of 1964 to 1984. There
assumptions were based on the argument that abstract level demand depends on
factors such as insurance prices, level of individual
income, availability of substitutes, among other individual and environmental characteristics.
They even further investigated with demographic variables such as education
level, age of individuals and size of population with age ranging from 25 to
64. They were able to conclude that the higher income inelasticity of demand
for life insurance was present in Mexico at low income levels. As a matter of
fact, age, income and level of education were important factors to be
considered as they affect the demand for life insurance in both Mexico and
United States.

(Outreville
1996)
on the other hand, considers a wide array of countries and analyses data from
1986 covering a range of 48 countries in order to examine the relationship
between financial development and the development of the life insurance sector.
Outreville indicates that there is a significant positive relationship between
the development of the life insurance market and financial development. His
findings also indicate that the relationship becomes negative in the case of
another financial development variable for instance GDP.

Furthermore, studies reveal that there is a negative
relationship between life expectancy and life insurance. Hence, higher
mortality rate should result in higher life insurance activity. On the other
hand, (Outreville 1996)
and (Ward and
Zurbruegg 2000)
studies reveal that there is a positive relationship between life expectancy
and life insurance premiums.

(Beck, Levine, and Loayza 2000) used cross-country instrumental variables and found a
link between using
instrumental variables, the exogenous component of financial intermediary
development and long-run economic growth. They proved that exogenous components
of financial improvements are connected not only to capital accumulation but
also to productivity growth

 

(Beck and
Webb 2002),
states that banking sector development assists in the development of life
insurance and its contractual savings function. While an efficient banking
system can contribute in the development of the life insurance sector by
offering payment services and increasing confidence in financial institutions,
life insurance among other forms of contractual savings can raise the
development of capital markets through the demand for long-term financial
investment. Therefore, we can determine that life insurance is affected by
financial markets and other financial products.

(Arena 2008)
tested the causality
relationship between
insurance market activity (life and non-life insurance) and economic
growth. The author gathered panel data for 55 countries and implemented the generalized method of moments from the period of 1976-2004. His results reveal
that there is causal relationship between insurance
market activity and economic growth.
The results showed that both life and non-life insurance on economic growth
were positive and statistically significant.

(Chen, Lee, and Lee 2011)
focused on the relationship between life insurance market development as well
as stock market operations and the implication for economic growth using data
from 1976 to 2005 for 60 countries. A derivative of the endogenous growth model
was employed to analyse the relationship. The generalized method of moments
(GMM) technique was used in estimating the equations that link life insurance
and stock market with growth. The result from the study shows that the
development of the life insurance market leads economic growth. The results
further showed some evidence that stock market and the life insurance market
are substitutes rather than complements. The results imply that causality runs
from life insurance market to economic growth.

(C. C. Lee, Lee, and Chiu
2013) focused
on 41 countries from 1979 to 2007
in order to analyse the relationship between
activities in the life insurance and economic
growth. Whereby their outcomes
point out that the long-run equilibrium relationship between real GDP and real life insurance premiums occurs when heterogeneous country effect is allowed.

(Pradhana, Arvinb, and Norman  2015)
studied 34 OECD countries for a period of 24 years from 1988 to 2012. Their
focus was on the causal relationships between insurance market development,
financial development, and economic growth. Their results reveal that both
insurance market and financial market development are long-run instrumental
factors of economic growth. On the other hand, short-run causality whereby
results reveal that patterns vary in the short-run and require adjustments
between variables with feedback being required between them in several
instances. Therefore, close relationship between insurance
market development, financial development, and economic growth illustrates that
in the longer run the OECD countries can keep up with economic growth. In order
to achieve economic growth however, rather than just pursuing financial
development as a whole they need to consider developing their insurance sectors.

 

 

 

 

 

 

(C. Lee et al. 2016) took a different
approach from extensive literature that studies insurance development on
economic growth and direct impact that institutions have on insurance and
economic growth. By applying the newest dynamic panel threshold model, they further
investigated how institutional environments influence the relation that
insurance development and economic growth have. Their results reveal that
relatively unhealthier institutional environments resulted in a negative
relationship between life insurance and economic growth. They noted that, after
a particular level or threshold of institutional quality has been attained this
significantly negative effect turns out to be insignificant. Therefore, unhealthy
institutional conditions could prevent the growth and development effect of
life insurance sectors.

 

 

The above literature of related research
topics with regards to life insurance and economic growth indicates that indeed
the life insurance industry contributes to economic growth.