Chapters

Investment of Insurance Industry: Regression Analysis and Measures of Some Possible Factors Affecting Investment of Insurance Industry

Chapter 1: Introduction

Why investment important in our economy? This question will lead this study

to measure the impact of some financial factors to investments of insurance industry.

Why should study investment? We determine Gross Domestic Product (GDP) by

adding up all the spending on final goods and services in economy occurring

throughout the year including personal consumption expenditure, domestic

investment, government expenditure and net exports. In simple words, investment is

one of the determinants of GDP which describes the economy with respect to other

factors like price, population and employment, etc. Everyone is affected by changes

in economic condition.

What is the best destination of excess money from income, if there is? It is

important to save money for future purposes. Subjectively, the best way of saving is

the proper spending. We spend money daily, but we do not know exactly when we

have to spend a lot. While you are in a good financial condition, to minimize the risk

that may exist in the future, it is better for you to spend in securities and savings.

Insure yourself, that means spend now consume later when necessary.

What insurance companies do with the money they collect from policy-

holders? Basically, money that is not needed for day-to-day expenses or reserves is

usually invested by insurers. Some years of investing are better than others, but the

industry has always generated positive investment returns. Large volume of their

investments is in government bonds, or else in well-established business.

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1.1 Background of the Study

The concept of insurance is the spreading of risk for an individual or group

among the others. This is through when individuals and group pay a premium to an

insurance company to cover their living and operations in case of disastrous events.

Insurance companies manage risk and make investments in different kind of assets to

earn profits.

Investments fuel the economy by generating income and jobs in various

industries. Same thing about investment is that economic conditions may influence

the expectations of investors. There are several types of investments of insurance

company like bonds (specifically corporate secured bonds), mortgage, stocks

(common stocks and preferred stocks), real estate and other investments.

A bond represents a promise on the part of its issuer to repay the sum of

money (the principal) to the bondholder (the investor or insurance company)

at stated time in the future (maturity date) and to pay interest to the bondholder

at a specified rate. Upon maturity, yield (the interest plus the principal) is

return to the bond holder.

A mortgage is a legal instrument under which the property pledged can be

claimed by the lender if the borrower cannot repay the loan on the due date.

Mortgage investments of insurance company come in the form of first

mortgage or deed of trust of unencumbered real estate. An insurance company

lends money to corporations or persons for building homes, factories or

buying lands.

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The stocks represent a share of ownership in a corporation and therefore a

share in a profit or loss of a corporation. Stocks may be common stocks or

preferred stocks.

o Common stocks confer on its owner the right to vote, share in profits,

and share in the distribution of assets upon liquidation.

o Preferred stocks on the other hand, do not confer on its owner the right

to vote, but first priority rights over dividends and the distribution of

assets upon liquidation.

An insurance company engages in the building and selling of real estate

properties. It may also acquire properties through the foreclosure of properties

of mortgage.

Investments serve to raise the level of output in the future. From the

perspective of an individual, investment is expenditure, usually on a financial asset,

designed to increase the individual’s future wealth. Since investments are durable,

they can be reused. During hard times, firms do not have to buy new capital because

the price is high. Then if firms anticipate a good future, they may buy large volume

of capital now. In other words, depending on expectations for the future, a firm may

choose to fix capital rather than purchase new units, thus spending less. New

advancement in technology can cause a surge in capital investments, but innovation

occurs at irregular times. When a firm is expanding, it invests more and vice versa.

Future expectation is unpredictable and can change quickly as stocks fluctuate greatly.

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1.2 Research Objectives

This research has general and specific objectives.

1.2.1 General Objective

The general objective of this study is to contribute analysis focus on

reasoning, estimation and measuring the impact of selected variables (exchange rate,

savings rate, reserve assets and income tax) to the level of investments of insurance

industry.

1.2.2 Specific Objectives

Specifically it aims to:

Examine the investment mechanism of insurance industry.

Identify the difficulties in economy concerning investments of insurance

industry.

Formulate a significant regression model.

Estimate and measure the impact of selected factors.

Provide a conclusion and recommendation with respect to the results of

statistical test.

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1.3 Significance of the Study

Hopefully, this paper would help the government to take consider the

estimated effect of financial trade variables to the level of investments of insurance

industry. It is important to determine what factors affect the most to investments of

insurance companies and how these factors influence the level of investments. This is

to insure the economy itself, and to monitor and regulate these factors in order to

obtain the desire level of output.

1.4 Scope and Limitation

The scope of the study is focused on modelling and forecasting the statistical

relationship between investments of insurance industry to exchange rate, interest rate,

reserve assets, and income tax. Exchange rate (market rate), savings rate (interest

rate), reserve assets and income tax were used as determinants of investments of

insurance industry. Employing least squares method of regression analysis to

determine the measurable estimate effect of the model.

The study is limited with 22 observations, data from 1987 to 2008 of selected

variables. The dependent variable for this study is the investment of all private

insurance company in the Philippines. Independent variables used in this research are

exchange rate (market rate), savings rate (interest rate), reserve assets and income tax.

More about the data will discuss on Chapter 2.

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1.5 Statement of the Problem

Generally, insurance companies invest the money they are paid by customers.

Insurers are among the most careful investors in the country. Insurers try to maintain

a portfolio that allows for easy liquidation of investments to pay claims. As with

other industries, insurance companies are not exempt from the financial impact of

challenging economic events. Investment performance that insurance companies

relied on to support products, operations and other vital functions may promptly affect

the overall company feasibility. Assuming the optimization behaviour on behalf of

insurance company (investors) and a positive effect of investment to economy, the

following questions should take and consider by the government to stabilized

investment performance:

What is the effect of higher and lower level of investment to economy?

What factors affecting investments of insurance industry?

What and how is the effect of these factors?

How to diversify these factors in order to attain economic growth?

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1.6 Statement of the Hypothesis

There is a significant direct relationship between exchange rate (price of

dollar in domestic currency) and investment of insurance industry. The

value of domestic currency versus dollar will influence the level of

investment output. When domestic currency depreciates, investment will

tend to increase; when domestic currency appreciates, investment will tend

to decrease. In other words, the level of investment of insurance industry

is determined by the price of dollar.

There is a significant inverse relationship between savings rate (interest

rate on savings) and investment of insurance industry. The rate of interest

on savings will influence the level of investment output. When savings

rate increase, investment of insurance industry will tend to be lower; and

when savings rate is lower, investment is expected to increase.

There is a significant inverse relationship between reserve assets and

investment of insurance industry. When reserve assets increase, level of

investment of insurance industry is expected to be lower. When reserve

assets decrease, level of investment of insurance industry is expected to

increase.

There is a significant direct relationship between income tax and

investment of insurance industry. As income tax increase, total investment

of insurance industry is expected to increase; as income tax decrease, total

investment of insurance industry is expected to be lower.

96.6% of the variability of investment of insurance industry is explained

by exchange rate (market rate), interest rate (savings rate), reserve assets,

and income tax.

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1.7 Framework

Framework illustrates the conceptual and theoretical structure analysis. These

frameworks help you to easy understand the study.

1.7.1 Conceptual Framework

Figure 1.7.1

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1.7.2 Theoretical Framework

Figure 1.7.2

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Chapter 2: Methodology

Data management and collection is necessary to complete this research. After

the assumption that there are several factors affecting the level of investments of

insurance industry I gather some data such as financial and economic indicator like

exchange rate, interest rate, balance of payments, gross domestic product, population,

consumer price index, employment, reserve assets, and total investments and income

tax of insurance industry. I do run these data on E-Views using least squares method

and set total investments of insurance industry as dependent variable to formulate a

model. Fortunately, some of the said variables are significantly related to the level of

investments of insurance industry. Regression analysis comprehend this study with

the interpretation of vital statistics output. In order to precede the analysis of

economic environment, this study will follow a classical methodology.

Quantitative analysis is present to estimate and measure how is the impact of

selected factors affecting the total investments of insurance industry. Given the

assumption, some statistical test supporting the model and equation will determine the

significant relationship of independent variables to dependent variable.

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2.1 Data Management and Collection

This study consisting annual data from 1987 to 2008 of selected variables that

may affect investments of insurance industry, and data comprises total investments of

insurance companies in the Philippines including domestic and foreign insurance

companies of composite, life, non-life, and professional reinsurer. Data of total

investments of insurance industry as dependent variable and total income tax as one

of independent variables is gathered from the Annual Report of Insurance

Commission, Statistics and Research Division Office located at 1071 United Nations

Avenue, Manila. While exchange rate (market rate) ends of period, reserve assets,

and savings rate (interest rate), data of independent variables is from the database of

United Nations Organization (data.un.org).

2.2 Variables

Relationships between economic variables are generally inexact. To allow the

inexact relationship between variables, it should be modify deterministic function

with probabilistic property or disturbance. The disturbance represents all those

factors that affect the outcome but are not taken into account explicitly. Multiple

regression analysis is concerned with the study of the dependence of one variable, the

dependent variable, on more other variables, the explanatory variables or independent

variables. In this paper, you will find a multiple regression model consisting one

dependent variable and four independent variables.

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2.2.1 Dependent Variable

The dependent variable is assumed to be statistical, random, or stochastic, that

is, to have a probability distribution. It represents a quantity that varies from

individual to individual throughout the population, and is the primary focus of

interest. The dependent variable used in this research is the total investments of

insurance industry every year in unit peso, including investments from all types of

insurance company that were registered and licenced to operate in the Philippines.

Philam Life, on their Pre-Contract Training Course manual (2013), investments fuel

the economy by generating income and jobs in various industries. There are three

major considerations made before an insurance company decides to invest. First, an

insurance company must consider the risk associated with the investment it makes.

Second, an insurance company must consider the ease by which the investment can be

converted to cash. Lastly, an insurance company must consider the rate of return the

investment will provide. Insurance industry makes investments in well-established

business.

The total investments is impart to the total output in economy. The

mechanism of insurance explained the importance of investments of insurance

company in developing economy. It is important to determine what factors affect the

most to investments of insurance companies and how these factors influence the level

of investments. This is to insure the economy itself, and to monitor and regulate these

factors in order to obtain the desire level of output.

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Dependent Variable:

Investments of Insurance Industry = INVESTMENTS_INS

Investments - amount of money or other resources measured in terms of money

placed on activities or other forms of assets for the purpose of earning profits.

2.2.2 Independent Variables

The explanatory or independent variables vary from one individual to the next,

and are thought to be related to dependent variable. One of the problems arising in

making a regression model is that many of independent variables are highly collinear.

Assumption 10 of the classical linear regression model (CLRM) is that there

are no perfect linear relationships among the explanatory variables. Model in this

study consisting four independent variables namely exchange rate (market rate) ends

of period, total income tax (of insurance companies), reserve assets (total as of end of

year), and savings rate (annual percentage of interest rate).

Independent Variables:

Exchange Rate = EXCHANGE_RATE_MR

Income Tax = INCOME_TAX_INS

Reserve Assets = RESERVE_ASSETS

Savings Rate = SAVINGS_RATE

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Exchange Rate – price of one currency in terms of another. Most commonly,

exchange rates are expressed as the number of units of domestic currency that will

purchase one unit of foreign currency (e.g. units of currency per U.S. dollar). An

exchange rate may also be defined as the inverse: the number of units of foreign

currency that one unit of domestic currency will purchase.

Income Tax – A tax that governments impose on financial income generated by all

entities within their jurisdiction. Income tax is a key source of funds that the

government uses to fund its activities and serve the public.

Reserve Assets – consist of those external assets that are readily available to and

controlled by monetary authorities for direct financing of payments imbalances, for

indirectly regulating the magnitude of such imbalances through intervention in

exchange markets to affect the currency exchange rate and/or for other purposes.

Savings Rate – is the rate charged on all interest-bearing deposits of banks, which are

withdraw-able anytime. It is derived as the ratio of interest expense on peso deposits

of reporting commercial banks to the total outstanding level of these deposits.

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2.3 Regression Analysis

The statistical technique of regression analysis is the main tool used to obtain

the estimates. Using this technique and the data given in Table 2.3.1, we obtain the

estimates of coefficients.

2.3.1 Data

Table 2.3.1

Total Investments of Insurance Industry = INVESTMENTS_INS(Total, Ph. Peso)

Exchange Rate = EXCHANGE_RATE_MR(End of period, Ph. Peso/U$ Dollar)

Income Tax = INCOME_TAX_INS(Total, Ph. Peso)

Reserve Assets = RESERVE_ASSETS(Total, Ph. Peso)

Savings Rate = SAVINGS_RATE(Annual, Percentage)

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2.3.2 Method

The statistical method of least squares has produced these estimates. The

regression model is correctly specified as this study used least-squares estimator

which satisfies the assumption that there is no specification bias or error in the model

of empirical analysis. This method also follows probability distribution.

2.3.3 Model

Investments of Insurance Industry = f (Exchange Rate, Savings Rate, Reserve Assets and Income Tax)

2.3.4 Equation Output

Figure 2.3.4

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2.3.5 Estimation Equation

The equation output on Figure 2.3.4 gives the estimated equation:

Variables Coefficient

Y = INVESTMENTS_INS C1 = -75,800,000,000X1 = EXCHANGE_RATE_MR C2 = 5,550,000,000X2 = SAVINGS_RATE C3 = -10,700,000,000X3 = RESERVE_ASSETS C4 = -14.03X4 = INCOME_TAX_INS C5 = 182.30

u = disturbance

INVESTMENTS_INS = -75,800,000,000 + 5,550,000,000(EXCHANGE_RATE_MR) –

10,700,000,000 (SAVINGS_RATE) – 14.03 (RESERVE_ASSETS) + 182.30

(INCOME_TAX_INS)

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Y = C1 + C2X1 +C3X2 + C4X3 + C5X4 + u


2.3.6 Coefficient

The coefficient (partial regression coefficient) measures the marginal

contribution of the independent variable to the dependent variable, holding all other

variables fixed. The column labelled "Coefficient" depicts the estimated coefficients. The

least squares regression coefficients are computed by the standard OLS formula:

b = (Xˈ X)-1 Xˈ у

If “C” is included in the list of regressors, the corresponding coefficient is the

constant or intercept in the regression. It is the base level of the prediction when all of

the other independent variables are zero. The other coefficients are interpreted as the

slope of the relation between the corresponding independent variable and the

dependent variable, assuming all other variables do not change. We do not interpret

the constant since the dataset does not include the data of variables with zero value.

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The regression coefficients are interpreted with tables and graph to illustrate

the effect of each factor to investments of insurance industry:

Graph 2.3.6a

- For every one peso per dollar

increase of market exchange

rate every year (e.g. Year1

₱10:$1, Year2 ₱11:$1), total

investments of insurance

industry is estimated to

increase, on the average, by

₱5,550,000,000.00 holding

other factors constant.

Table 2.3.6a

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Investments

Exchange Rate


Graph 2.3.6b

- For every 1% increase in

savings rate (interest rate), total


industry is estimated to be

lower, on the average, by

₱10,700,000,000.00 holding

other factors constant

Table 2.3.6b

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Investments

Savings Rate


Graph 2.3.6c

- For every ₱1.00 increase in

value of reserve assets, total


industry is estimated to be

lower, on the average, by

₱14.03 holding other factors

constant.

Table 2.3.6c

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Investments

Reserves Assets


Graph 2.3.6d

- For every ₱1.00 increase on

income tax, total investments of

insurance industry is estimated

to increase, on the average, by

₱182.30 holding other factors

constant.

Table 2.3.6d

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Investments

Income Tax


2.3.7 Standard Error

In statistics the precision of an estimate is measured by its standard error. The

standard errors measure the statistical reliability of the coefficient estimates-the larger

the standard errors, the more statistical noise in the estimates.

2.3.8 T-Statistics

The t-statistic is computed as the ratio of an estimated coefficient to its

standard error, is used to test the hypothesis that a coefficient is equal to zero. To

interpret the t-statistic, we should examine the probability of observing the t-statistic

given that the coefficient is equal to zero.

Table 2.3.8

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Coefficient Standard Error T-Statistics

-75,800,000,000.00 23,700,000,000.00 -3.195,550,000,000.00 404,000,000.00 13.74

-10,700,000,000.00 1,960,000,000.00 -5.46-14.03 2.10 -6.70182.30 29.51 6.18


2.3.9 Probability

The last column of the output shows the probability of drawing a t-statistic as

extreme as the one actually observed, under the assumption that the errors are

normally distributed, or that the estimated coefficients are asymptotically normally

distributed. This probability is the marginal significance level.

Table 2.3.8

Performing the test at 5% significance level means that probability lower than

0.05 is taken as evidence to reject the null hypothesis of a zero coefficient. The above

output, on Table 2.3.8, the hypothesis that the coefficient on exchange rate (market

rate), interest rate (savings rate), reserve assets and income tax is zero is rejected at

the 5% level of significance. This is referred to as a highly significant relationship

between dependent variable and independent variables of our model.

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2.4 Summary Statistics

This study used vital statistics to explain the meaning of this regression

analysis including R-Squared (R2) to measures the success of the regression in

predicting the values of the dependent variable within the sample, Durbin-Watson

Statistics to measures the serial correlation in the residuals, probability of F-Statistics

to state the hypothesis within the marginal significance level of F-test and Histogram

of residual for normality test.

Table 2.4

2.4.1 R-Squared (R2)

The R-squared (R2) statistic measures the success of the regression in

predicting the values of the dependent variable within the sample. In standard

settings, R2 may be interpreted as the fraction of the variance of the dependent

variable explained by the independent variables. The statistic will equal one if the

regression fits perfectly, and zero if it fits no better than the simple mean of the

dependent variable.

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Table 2.4 shows that 96.6% of the variability of investments of insurance

industry is explained by exchange rate (market rate), interest rate (savings rate),

reserve assets, and income tax.

2.4.2 Durbin-Watson Statistics

The Durbin-Watson statistic measures the serial correlation in the residuals.

The statistic is computed as:

The Durbin-Watson statistic is a test for first-order serial correlation. More

formally, the DW statistic measures the linear association between adjacent residuals

from a regression model. The Durbin-Watson is a test of the hypothesis ρ = 0 in the

specification:

If there is no serial correlation, the DW statistic will be around 2.

Figure 2.4.2

The DW statistic will fall below 2 if there is positive serial correlation

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(In the worst case, it will be near zero).

If there is negative correlation, the statistic will lie somewhere between 2 and 4.

2.4.3 F-Statistics and the Probability of F-test

The F-statistic reported in the regression output is from a test of the hypothesis

that all of the slope coefficients (excluding the constant, or intercept) in a regression

are zero. For ordinary least squares models, the F-statistic is computed as:

Under the null hypothesis with normally distributed errors, this statistic has an

F-distribution with numerator degrees of freedom and denominator degrees of

freedom.

The p-value given just below the F-statistic denoted Prob. (F-statistic) is the

marginal significance level of the F-test. If the p-value is less than the significance

level of 0.05 reject the null hypothesis that all slope coefficients are equal to zero. In

Table 2.4, the Probability of F-statistic is essentially zero, so we reject the null

hypothesis that all of the regression coefficients are zero. Note that the F-test is a joint

test so that even if all the t-statistics are insignificant, the F-statistic can be highly

significant.

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2.4.4 Histogram and Normality Test

This view displays a histogram and descriptive statistics of the residuals,

including the Jarque-Bera statistic for testing normality. If the residuals are normally

distributed, the histogram should be bell-shaped and the Jarque-Bera statistic

(Probability) should not be significant.

Figure 2.4.4

All of the statistics are calculated using the observations in the current sample.

Mean is the average value of the series, obtained by adding up the

series and dividing by the number of observations.

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Median is the middle value (or average of the two middle values) of

the series when the values are ordered from the smallest to the largest.

The median is a robust measure of the center of the distribution that is

less sensitive to outliers than the mean.

Max and Min are the maximum and minimum values of the series in

the current sample.

Std. Dev. (standard deviation) is a measure of dispersion or spread in

the series. The standard deviation is given by:

Where N is the number of observations in the current sample and is

the mean of the series.

Skewness is a measure of asymmetry of the distribution of the series

around its mean. Skewness is computed as:

Where is an estimator for the standard deviation that is based on the

biased estimator for the variance . The skewness

of a symmetric distribution, such as the normal distribution, is zero.

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Positive skewness means that the distribution has a long right tail and

negative skewness implies that the distribution has a long left tail.

Kurtosis measures the peakedness or flatness of the distribution of the

series. Kurtosis is computed as:

Where is again based on the biased estimator for the variance. The

kurtosis of the normal distribution is 3. If the kurtosis exceeds 3, the

distribution is peaked (leptokurtic) relative to the normal; if the

kurtosis is less than 3, the distribution is flat (platykurtic) relative to

the normal.

Jarque-Bera is a test statistic for testing whether the series is normally

distributed. If the residuals are normally distributed Jarque-Bera

statistic (Probability) should not be significant. The test statistic

measures the difference of the skewness and kurtosis of the series with

those from the normal distribution. The statistic is computed as:

Where S is the skewness, and K is the kurtosis.

Under the null hypothesis of a normal distribution, the Jarque-Bera

statistic is distributed as X2 with 2 degrees of freedom. The reported

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Probability is the probability that a Jarque-Bera statistic exceeds (in

absolute value) the observed value under the null hypothesis-a small

probability value leads to the rejection of the null hypothesis of a

normal distribution. For the LWAGE series displayed above, we reject

the hypothesis of normal distribution at the 5% level but not at the 1%

significance level.

Chapter 3: Review of Related Literature

3.1 Local Literature

“A look into the insurance industry and its relation to the economy: A panel data

analysis on the possible financial, economic and demographic factors that affect

insurance density”

By: Bernadette H. Marquez

Significance of this study

The importance of this study lies on the reason that this would emphasize the

role of insurance industry in transferring risks that that contributes to the society and

to the economy as well. Furthermore, this would help the government officials to

responsibly take into consideration the condition of the insurance industry in planning

for the economy, and take actions on the economic indicators that would significantly

affect the insurance per capita expenditure. As well as for the insurance regulators to

have an idea about the factors and determinants that affects insurance density, also for

them, to implement stricter regulations to the insurance companies that would

eventually promote further development of the insurance market through the

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encouragement of spending on insurance protection and insurance consumption. This

would also provide substantial information for the general public to be informed of

the role the insurance industry plays as well as the factors affecting insurance

consumption.

3.2 Foreign Literature

“Analysis of Insurance Practice and Economic Growth in Nigeria: using co-integration test and error correction model”

By: Eze Onyekachi Richard and Okoye Victor

Abstract:

The study examines the impact of insurance practice on the growth of

Nigerian economy. Insurance premium income, total insurance investment and

income of insurance development was used as determinants of insurance practice. We

employ unit root tests, Johansen co-integration test and error correction model in data

analysis and to determine the short and long run effect of the model. The study

observed that the insurance premium capital has significantly impacted on economic

growth in Nigeria; that the level of total insurance investment has significantly

effected on economic growth in Nigeria; and that there is causal relationship between

insurance sector development and economic growth in Nigeria. The implication of

these findings is that insurance industry would contribute meaningful to the growth of

Nigeria economy in long run. The study concludes that there is a significant positive

effect of insurance practice on the growth of Nigerian economy. We therefore

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recommend that having seen that there is long-run relationship between insurance

industry practice and economic growth in Nigeria. There is need that more efforts

should be made to increase transparency and efficiency in insurance industry through

adequate legislation and policy formulation targeted at providing institutional

improvement, especially in risk management and product innovations in insurance

industry.

“The Effect of Insurance Business on Economic Development in Nigeria”

By: Anthony Adekunle Owojori and Luke Olusola Oluwagbuyi

Abstract

This study investigates the contribution of insurance to economic development

in Nigeria. As a descriptive survey, the study comprised all the 50 insurance

companies in Lagos State, Nigeria out of which a sample of 10 companies were

selected. Out of the 20 life and 30 non-life insurance in the sample, 4 life and 6 non-

life insurance were selected using random sampling techniques. The instrument used

for the study was a questionnaire designed, validated and found reliable for the study.

The findings showed that problem among insurance companies were lack of funds

which leads to claim avoidance. There was no significant difference between

performance of insurance policy in urban and rural areas. The findings also revealed

insurance companies provide financial services to some substantial number of people

in the economy. The findings further revealed that insurance helps in capital

accumulation than payment of reparation of loses. Based on findings, it was

recommended that there should be a cheap means of handling risks to the insured in

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view of the fact that the principle of large number is brought to bear in the practice

and operations of insurance. The state government should enhance the participation of

individuals and corporate bodies by generating incentives strategy, upgrading

infrastructures enhance human capital development and creating a favourable climate

for insurance investment.

Chapter 4: Summary, Conclusion and Recommendation

4.1 Summary

Chapter 1 of this research introduces the importance and concept of

investment in economy. Giving the background, objectives, significance of the study,

problem statement, hypothesis, and framework support our immediate knowledge. As

a component of GDP, it is important to determine what factors can affect the level of

investment. Insurance is also introduced; prior to investing, insurance companies

understand well the concept of risk and return to manage their financial situation.

Risk management is associated to insurance, and return is expected on investment.

Insurance companies provide financial services and transfer risk through the premium

invested in specified term of financial assets which increase the rate of aggregate

investment in the economy and thus promoting economic development.

Methods and findings in this study are shown in Chapter 2. Using least

squares method and regression analysis, with data from 1987 to 2008 ( 22

observations) of total investments of insurance industry as dependent variable;

exchange rate (market rate), interest rate (savings rate), reserve assets, and income tax

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of insurance companies as independent variables, the model is formulate to estimate

and measure the impact of independent variables to dependent variable. The result of

statistical tests indicates the significant relationship on our model.

On Chapter 3, this paper review local and foreign literature: literary work of

Miss Bernadette H. Marquez entitled “A Look into the Insurance and Its Relation to

the Economy: A Panel Data Analysis on the Possible Financial, Economic and

Demographic Factors That Affect Insurance Density” (local), “Analysis of Insurance

Practice and Economic Growth in Nigeria: using co-integration test and error

correction model” by Eze Onyekachi Richard and Okoye Victor (foreign), and “The

Effect of Insurance Business on Economic Development in Nigeria” by Anthony

Adekunle Owojori and Luke Olusola Oluwagbuyi (foreign).

Chapter 4 is the summary, conclusion and recommendation. Summary

contains brief discussion of all chapters. Conclusion is the inference assumption of

analysis. Recommendation provides subjective solution and suggestions.

Chapter 5, bibliography is the list of writing used in this study as reference and

guide, including the “Annual Report of Insurance Commission” reference for data.

Chapter 6 contains reference for definition of terms, tables and graphs.

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4.2 Conclusion

In view of this study, it is important to monitor and regulate the performance

of investment of insurance industry. Stabilizing the financial settings of international

and domestic environment will help insurance company to make a good investment.

The public, as primary concern of insurance, is said to be aware about insurance

consumption. It is important to all level of income earner to spend for insurance

necessarily.

4.3 Recommendation

Government should enhance the contribution of individuals and

corporate organizations by generating encouragements strategy,

constructive climate for insurance investment, improvement

infrastructures and increase human capital development.

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Exchange rate, interest rate, reserve assets and income tax should be

restrained a target by the government since these considered as factors

that may influence the investment of insurance industry.

Chapter 5: Bibliography

“A look into the insurance industry and its relation to the economy: A panel data

analysis on the possible financial, economic and demographic factors that affect

insurance density”

By: Bernadette H. Marquez

“Analysis of Insurance Practice and Economic Growth in Nigeria: using co-

integration test and error correction model”

By: Eze Onyekachi Richard and Okoye Victor

“The Effect of Insurance Business on Economic Development in Nigeria”

By: Anthony Adekunle Owojori and Luke Olusola Oluwagbuyi

The Insurance Code of 1978 (AS Amended): Published by the Insurance Commission 1979

ASEAN Report of the Fifth Meeting of the ASEAN Insurance Regulators: 17-19 December 2002 Chiang Mai, Thailand

Insurance Company Investments, S. Davidson Herron, Jr.

NTRC Tax Research Journal Volume IX.1 Philippines January-February 1997

Glossary of Terms (Commonly Used in Statistical Work) Statistical Coordination Office – National Economic and Development Office

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Overview by: Governor Rafael Carlos B. Buenaventura Edited by: Dr. Vicente B. Valdepeῆas, Jr. – The Banko Sentral & the Philippine Economy

Key Financial Stability Issues in Insurance – An account of the Geneva Association’s ongoing dialogue on systemic risk with regulators and policy-makers

Theories of Investment: A Theoretical Review with Empirical Applications, Johan E. Eklund

Basic Econometrics Fourth Edition, Damodar N. Gujarati

Microfinance Consumer Protection Guidebook

Pre-Contract Training Course Manual, Philam Life (2013)

Insurance Commission 1988 Annual Report











Insurance Commission Annual Report (1998 Figures)









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Chapter 6: Definition of Terms, Tables and Graphs

6.1 Definition of Terms

Bond – represents a promise on the part of its issuer to repay the sum of money (the

principal) to the bondholder (the investor or insurance company) at stated time in the

future (maturity date) and to pay interest to the bondholder at a specified rate. Upon

maturity, yield (the interest plus the principal) is return to the bond holder.

Common Stocks – confer on its owner the right to vote, share in profits, and share in

the distribution of assets upon liquidation.

Exchange Rate – price of one currency in terms of another. Most commonly,

exchange rates are expressed as the number of units of domestic currency that will

purchase one unit of foreign currency (e.g. units of currency per U.S. dollar). An

exchange rate may also be defined as the inverse: the number of units of foreign

currency that one unit of domestic currency will purchase.

Investments – amount of money or other resources measured in terms of money

placed on activities or other forms of assets for the purpose of earning profits.

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Mortgage – is a legal instrument under which the property pledged can be claimed by

the lender if the borrower cannot repay the loan on the due date. Mortgage

investments of insurance company come in the form of first mortgage or deed of trust

of unencumbered real estate. An insurance company lends money to corporations or

persons for building homes, factories or buying lands.

Preferred Stocks – on the other hand, do not confer on its owner the right to vote, but

first priority rights over dividends and the distribution of assets upon liquidation.

Real Estate – an industry of development of non-residential buildings, apartment

buildings and dwelling.

Reserve Assets – consist of those external assets that are readily available to and

controlled by monetary authorities for direct financing of payments imbalances, for

indirectly regulating the magnitude of such imbalances through intervention in

exchange markets to affect the currency exchange rate and/or for other purposes.

Savings Rate – is the rate charged on all interest-bearing deposits of banks, which are

withdraw-able anytime. It is derived as the ratio of interest expense on peso deposits

of reporting commercial banks to the total outstanding level of these deposits.

Stocks – represent a share of ownership in a corporation and therefore a share in a

profit or loss of a corporation. Stocks may be common stocks or preferred stocks.

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6.2 Figures, Tables and Graphs

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Documents

Chapters