FOREIGN TRADE UNIVERSITY
FACULTY OF INTERNATINAL ECONOMICS

********

GROUP REPORT
THE FACTORS EFFECT LIFE EXPECTANCY OF
SOME COUNTRIES ALL OVER THE WORLD
Group 4
Class: Econometrics 1 – KTEE218
Lecturer: M.S. Nguyen Thuy Quynh
Members : 1. Tran Xuan Giang – 1814450027
2. Pham Ngo Quynh Giao – 1814450028
3. Nguyen Thi Minh Hoa – 1814450193
4. Nguyen Quynh Trang – 1814450069
5. Le Ngo To Uyen – 1814450104
Ha Noi, 9/2019


ABSTRACT .............................................................................................
INTRODUCTION ...................................................................................

4
5

SECTION I: OVERVIEW OF THE TOPIC .......................................

6

1. Definition ...........................................................................................................


4. Research hypotheses ............................................................................................ 11

SECTION II: MODEL SPECIFICATION ........................................ 11
1.

Methodology .................................................................................................... 11

2.

Theoretical model specification ..................................................................... 12

3.

Describe the data ............................................................................................ 12
3.1

Specify the source of data ......................................................................... 12

3.2

Descriptive Statistics and interpretation for each variable ..................... 13

3.3

Correlation matrix between variables ...................................................... 15

SECTION III: HYPOTHESIS ............................................................. 16
1.

Estimated model ............................................................................................. 16

CONCLUSION......................................................................................24
INDIVIDUAL ASSESSMENT............................................................. 25
REFERENCES......................................................................................26
APPENDIX............................................................................................ 27


ABSTRACT
Our research has been conducted with a view to examining the relationship
between each of the four factors affecting the life expectancy and life expectancy. First
of all, the research relates four elements which have the impacts on the life expectancy
are Current health expenditure per capita, Physician, Alcohol consumption per capita
and Lower secondary completion rate. Besides, the multiple regression analysis was
conducted with the data of some countries all over the world collected from World
Bank database. Regression specification error test (RESET) was also conducted to
ensure that the regression model specified is adequate. After that, the findings have
shown there are positive relationship between life expectancy and current health
expenditure per capita, Physician and Lower secondary completion rate, whereas,
Alcohol consumption per capita and life expectancy have a negative relationship.
Therefore, we can have a better awareness of the factors which can have good or bad
effects on our life expectancy. If we spend more on our health expenditure or have the
higher secondary education rate and physicians in a country, we can expand our life
expectancy. In the contrast, our life expectancy can suffer severe impacts if we
consume alcohol too much.


INTRODUCTION
In the today’s world, life expectancy is one of the significant problems that can
draw attention to all the world’s citizens. Life expectancy is also one of the best
measures to evaluate health status of nations. The life expectancy for each individual or
group can be affected by several variables such as gender, genetics, lifestyle, access to

services including personal health care (curative care, rehabilitative care, long-term
care, ancillary services and medical goods) and collective services (prevention and
public health services as well as health administration), but excluding spending on
investments.

1.3 Physician
A physician, medical practitioner, medical doctor, or simply doctor, is a
professional who practices medicine, which is concerned with promoting,
maintaining, or restoring through the study, diagnosis, prognosis and treatment of
disease, injury and other physical and mental impairments.

1.4 Alcohol consumption per capita
Alcohol consumption per capita is annual consumption of pure alcohol in liters
per person. In addition, recorded alcohol per capita consumption of pure alcohol


is calculated as the sum of beverage specific alcohol consumption of pure alcohol
(beer, wine, spirits, other) from different sources.

1.5 Lower secondary completion rate
Secondary completion rate is the total number of graduates from the last grade of
secondary education, regardless of age, expressed as a percentage of the population of
the age group that officially corresponds to that of graduating from secondary schools.
About the lower secondary education completion rate, it is measured as the gross
intake ratio to the last grade of lower secondary education (general and pre-vocational).
It is calculated as the number of new entrants in the last grade of lower secondary
education, regardless of age, divided by the population at the entrance age for the last
grade of lower secondary education.
2. Economic theories
Life expectancy is an important research topic that has drawn a lot of attention of

productivity through absenteeism, accidents at work, loss of job skills, salaries for
police and social workers, court costs, damage to property and cars, insurance
payments and so on are added together.
Interestingly, not all countries who drank below the average liters of alcohol
experienced higher life expectancies, which may point to other contributing factors for
lower life expectancies. But it can be easily understood that a rise in alcohol
consumption could decrease the life expectancy.
Life expectancy grows when there are more primary care physicians in the field.
According to a study led by researchers at Stanford and Harvard, it shows us just how
important primary care physicians are in prolonging our lives. Every 10 additional
primary care physicians per 100,000 people in the United States was associated with a
51.5-day increase in life expectancy during the decade from 2005 to 2015. “Greater
primary care physician supply was associated with improved population mortality,


suggesting that observed decreases in PCP supply may have important consequences
for population health,” the study said.
When countries develop economically, people live longer lives. Development
experts have long believed this is because having more money expands lifespan, but a
massive new study suggests that education may play a bigger role. The finding has
huge implications for public health spending. Schooling develops basic cognitive
functioning, such as reading, writing, and communicating, and teaches individuals how
to think logically, critically analyze data, solve problems, and implement plans. Higher
education is the key to stable and well-paid jobs, and increased income helps to pay for
nutritious food, better-quality housing, and high-quality medical care. In addition,
education promotes healthy lifestyles through the development of effective human
agency. Highly educated people use their knowledge, information, and past
experiences to avoid health-related risk factors and engage in health-enhancing
behaviors, such as smoking cessation, alcohol abstinence, and frequent physical
exercise. Moreover, education provides socio-psychological resources that can

regression analysis. This study showed that there is a positive, strong correlation
between life expectancy as an independent variable and per capita income, health
expenditures, literacy rate and daily calorie intake. Also, it revealed that there is a
negative strong correlation between life expectancy and the number of people per
doctor in African countries.
A study led by researchers at the Stanford University School of Medicine and
Harvard Medical School published Feb. 18 in JAMA Internal Medicine has shown that
Greater primary care physician supply was associated with lower mortality.
From the review of literature, we can see that alcohol consumption, health
expenditure, education and the number of physicians, all of them are the factors that
have effect on people’s life expectancy. However, there is no current study including


impact of all these factors, so we decided to conduct this research to find out how they
affect on the life expectancy of 136 countries all over the world.
4. Research hypotheses
In this research, we expected that there is a positive relationship between health
expenditure, lower secondary education completion rate, the number of physician and
life expectancy. If we increase our health expenditure or have the higher secondary
education rate or have more physicians in a country, we can expand our life
expectancy.
We also predicted that the total alcohol consumption would have negative effect
on people’s life span. The result of the study is supposed to prove that our life
expectancy can suffer severe impacts if we increase our alcohol consumption too
much.

SECTION II: MODEL SPECIFICATION
1. Methodology
Thank for using the multiple regression analysis that shall be conducted in order
to observe what relationship each variable has with life expectancy. STATA shall be

physician: Physicians (per 1000 people)

•

alcohol: Total alcohol consumption per capita (liters of pure alcohol,
projected estimates, 15+ years of age)

•

secondary: Lower secondary completion rate, total (% of relevant age
group)

•

ui: The disturbance of observation i, represents other factors that affect
consumption.

➢

Dependent variable is LE.

➢

Independent variables are HEC, physician, alcohol, secondary. Basing on the theoretical above,

the total alcohol consumption per capita has negative relationship with life expectancy. On the other
hand, the current health expenditure per capita, physicians (per 1000) and lower secondary
completion rate have positive one with life expectancy.

3. Describe the data


Max

Min

Life
expectancy

LE

73.04522

74.65537

7.533

84.22683

51.593

HEC

1549.943

934.0632

1784.483

9869.742


86.945

27.400

156.934

10.025

Current
health
expenditure
per capita
Physicians
Total
alcohol
consumption
Lower
secondary
completion
rate

1. Life expectancy


The number of years that a person can expect live. The life expectancy is based
on the year of its birth, its current and other factors including gender. It reflects the
overall mortality level of a population and summarizes the mortality pattern that
prevails across all age groups in a given year. It is calculated in a period life table
which provides a snapshot of a population’s mortality pattern at a given time. In our
model, we take the data about life expectancy in 2015 of some high-income

entrants in the last grade of lower secondary education divided by the total number
of children of official completing age. Country-specific definition, method and
targets are determined by countries themselves. Data were collected from national
and other publicly available sources and validated by the Local Education Group
(LEG) in each country.

3.3 Correlation matrix between variables
LE

HEC

physician

alcohol

Secondary

1.0000
HEC

0.6658

1.0000

physician

0.7040

0.6844


Linear Regression model
OLS results – Linear Regression Model
Observations 1-136
Dependent variable: LE
Coefficient

Std. Error

t-ratio

p-value

Const

61.41307

1.303709

47.11

0.000

HEC

0.0011434

0.0003062

3.73


0.000

Mean
dependent var

73.04522

S.D. dependent var

56.7573

Sum squared
resid

2654.75358

S.E. of regression

4.5017

R-squared

0.6535

Adjusted R-squared

0.6429

F(4,131)


∑

=1

2

R measures the proportion of the total variation in LE explained by the
regression model.
2

R =0.6535: 65.35% of the total variation in LE is explained by the regression
model and the remains is due to other factors.
1.4 Explain the meanings of estimated coefficient
➢

The interpretation of the intercept term in the regression equation: If the
independent variables equal 0 then the expected mean value of the dependent
variable is the intercept.
It means: If HEC=0
physician =0
alcohol=0
secondary=0
→ LE=61.41307
➢
The interpretation of the slope terms in the regression equation:
▪
HEC=0.0011434: If current health expenditure per capita increases by 1 dollar→
Life expectancy will rises 0.0011434 year given other factors in the model are
constant.


a.

βHEC
{

0:
1:

=0
≠0

➢
Method 1: Confidence interval approach
Based on STATA table the confidence interval of = [0.00054; 0.00175]
βHEC=0 doesn’t belong to [0.00054; 0.00175]→ reject
̂

➢

Method 2:Test of significant

0

→βHECis significant.


̂̂

−



p- value of HEC =0.000

ℎ

̂

= [1.0678; 2.7614]


➢

Method 3: P – value approach

p- value of physician =0.000
➢

:

Method 1: Confidence interval approach

Based on STATA table the confidence interval of
→βalcohol is significant.

ts=

0

c

⁄2

0.05⁄2 0.025

|>tc→ reject Ho

Method 3: P – value approach

p- value of alcohol=0.048

➢

c

⁄2

0.05⁄2 0.025

|>tc→ reject Ho

we see that |

Method 3: P – value approach

p- value of secondary=0.000
2

= 61.77

p- value = P (F > F0) = 0.0000
→

p-value < 0.05 → Reject H0
The model statistically is fitted. Because variables are not significant at the

5% level and only 1 variable is significant at the 5% level.
3. Recommendations
According to the findings of the study, we can enhancing health outcomes
through improved educational attainment, lower alcohol consumption, more healthcare
expenditure and increased primary care physicians.
Governments of countries should establish a national program that forgives the
student-loan debt of any newly trained doctor who agrees to two or three years of


primary-care service in underserved areas. The cost to the government would be offset
long-term by improved community health and reduced hospitalizations.
They also have to reduce the affordability, availability and promotion of alcohol
to improve national life expectancy. A minimum unit price for alcohol is one of the
best ways to reduce drinking in the heaviest drinkers and tackle the alcohol related
health inequalities.
Governments should subsidy of secondary education and encourage the spend of
citizen for health care services.


CONCLUSION

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Quynh Trang

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To Uyen

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Evaluator