tiểu luận kinh tế lượng THE FACTORS EFFECT LIFE EXPECTANCY OF SOME COUNTRIES ALL OVER THE WORLD

However, we have not had an exact answer for the question “How long a person can live?” yet.Despite the fact that we could not calculate the accurate one person’s life span, therewas sti

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATINAL ECONOMICS

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 4

INTRODUCTION 5

SECTION I: OVERVIEW OF THE TOPIC 6

1 Definition 6

1.1 Life expectancy 6

1.2 Current health expenditure per capita 6

1.3 Physician 6

1.4 Alcohol consumption per capita 6

1.5 Lower secondary completion rate 7

2 Economic theories 7

3 Literature review 9

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

1.1 Estimation results 16

1.2 Sample regression model 17

1.3 The coefficient of determination 17

1.4 Explain the meanings of estimated coefficient 17

2 Hypothesis testing 18

2.1 Test an individual regression coefficient 18

2.2 Testing the overall significance 21

3 Recommendations 22

CONCLUSION 24

INDIVIDUAL ASSESSMENT 25

REFERENCES 26

APPENDIX 27

In the today’s world, life expectancy is one of the significant problems that candraw attention to all the world’s citizens Life expectancy is also one of the bestmeasures to evaluate health status of nations The life expectancy for each individual orgroup can be affected by several variables such as gender, genetics, lifestyle, access tohealthcare, economic status, the relevant mortality and morbidity and so on However,

we have not had an exact answer for the question “How long a person can live?” yet.Despite the fact that we could not calculate the accurate one person’s life span, therewas still a lot of researches in the recent decades which have shown that some factorscan affect the life expectancy more than the others are Current health expenditure percapita, Physician, Alcohol consumption per capita and Lower secondary completionrate

Having the awareness of how important the life expectancy is, we decided to findmore about elements affect the life span whether it is a good or bad factor With thetools of econometrics, especially STATA, we set a model with five variables includeddependent variable, which is the life expectancy (LE) and independent variables, whichare current health expenditure per capita (HEC), physician, alcohol consumption percapita and lower secondary completion rate to optimize analysis process

This research could be used as a guideline and may be significant for futureresearchers and policy makers who aim to improve the life expectancy in each countryall over the world Though having tried our best, there are still unavoidable mistakes inevery stage of this study Therefore, please let us know and feel free to discuss if youhave any concern

SECTION I: OVERVIEW OF THE TOPIC

1 Definition

1.1 Life expectancy

Life expectancy, often abbreviated to LEB (for Life expectancy at birth), is a

statistical measure of the average time an organism is expected to live, based on the

year of its birth, its current age and other demographic factors including gender

1.2 Current health expenditure per capita

Health spending measures the final consumption of health care goods andservices including personal health care (curative care, rehabilitative care, long-termcare, ancillary services and medical goods) and collective services (prevention andpublic health services as well as health administration), but excluding spending oninvestments

1.3 Physician

A physician, medical practitioner, medical doctor, or simply doctor, is a

maintaining, or restoring through the study, diagnosis, prognosis and treatment ofdisease, injury and other physical and mental impairments

1.4 Alcohol consumption per capita

Alcohol consumption per capita is annual consumption of pure alcohol in litersper 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 ofsecondary education, regardless of age, expressed as a percentage of the population ofthe age group that officially corresponds to that of graduating from secondary schools.About the lower secondary education completion rate, it is measured as the grossintake 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 secondaryeducation, regardless of age, divided by the population at the entrance age for the lastgrade of lower secondary education

2 Economic theories

Life expectancy is an important research topic that has drawn a lot of attention of scholars in the past decades Therefore, it could be useful to start out by examining how factors was addressed in previous researches.

Health care systems is a problem in each country even it is a developed country

or not Many previous studies have used child mortality and mortality rate indicator as

a proxy for health Anyanwu and Erhijakpor (2007) found that health expenditure had asignificant effect on infant mortality and there was less than five mortality in 47selected African countries between 1999 and 2004 In contrast, some studies thatanalyzed health expenditure did not find any impact on health indicators after adjustingother factors; for instance, Musgrove et al (2005) found that the total spending onhealth did not affect gjhs.ccsenet.org Global Journal of Health Science Vol 9, No 5;

2017 108 the mortality rates In contrast, the present study utilized life expectancy as

an indicator of health outcomes Increased one unit of per person Health ExpenditurePer Capita (HEC) will increase the life expectancy in an average of 8 days in a year

The increased total expenditure on health as a percentage of gross domestic productswill improve expected years of by 8 days It shows that an increase in Healthexpenditure per capita has relevance to an increase in life expectancy.

On the other hand, a country’s drinking habits affect its population’s lifeexpectancy By scraping the World Health Organization’s (WHO) Substance AbuseCountry Profiles, we found each nation’s annual consumption of alcohol per capita.The correlation between life expectancy and alcohol consumption doesn’t seem to be apositive one Drinking wine in moderation may be beneficial for some people’s hearthealth but stopping at just one glass isn’t always as easy as it seems The reality aboutalcohol consumption is that the developed countries are drinking less and, in contrast,consumption in developing countries is increasing Most developing countries do nothave a national policy to reduce alcohol consumption Alcohol consumptionexacerbates poverty then affect life expectancy Drinking costs a nation billions ofdollars While the hidden cost has not been calculated for many countries, the burden

on any nation is bound to be substantial when the cost of medical care, lostproductivity through absenteeism, accidents at work, loss of job skills, salaries forpolice and social workers, court costs, damage to property and cars, insurancepayments and so on are added together

Interestingly, not all countries who drank below the average liters of alcoholexperienced higher life expectancies, which may point to other contributing factors forlower life expectancies But it can be easily understood that a rise in alcoholconsumption 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 howimportant 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 a51.5-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 consequencesfor 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 Highereducation is the key to stable and well-paid jobs, and increased income helps to pay fornutritious 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

contribute to health and longevity through emotional and instrumental support That well-educated people are more likely to be and remain married also contributes to the relationship between education and health

3 Literature review

Life expectancy is an important index that reflects the standard of living and thesocial situation as well as the economic development level of a country Therefore, inrecent decades, there are a lot of studies carried out that research about life expectancyand the potential factors affecting it

According to an article released by the Lancet on April 14, 2018 about “Riskthresholds for alcohol consumption”, it has shown that the association between alcoholconsumption and total cardiovascular disease risk

According to research from the National Institute on Alcohol Abuse andAlcoholism, women are especially vulnerable to the negative medical effects ofexcessive alcohol use.

Besides the alcohol consumption, there is an irrefutable positive correlationbetween education and longevity A study by the Washington University School ofMedicine suggests there are both direct and indirect health benefits of education Thedirect benefits include adopting healthier lifestyles, an increased ability to cope withstress, and more effective management of chronic diseases In terms of indirectbenefits, scientists point to a, generally, better social position, a bette r paying job, andaccess to better medical care

Another research was published on The Journal of Medical Research andInnovation has shown an association of total Health Expenditure with GDP and lifeexpectancy

According to Asian Economic and Financial Review “DETERMINANTS OFLIFE EXPECTANCY: A PANEL DATA APPROACH”, Yavari and Mehrnoosh (2006)analyzed the effects of socio- economic factors on life expectancy using multipleregression analysis This study showed that there is a positive, strong correlationbetween life expectancy as an independent variable and per capita income, healthexpenditures, literacy rate and daily calorie intake Also, it revealed that there is anegative strong correlation between life expectancy and the number of people perdoctor 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, healthexpenditure, education and the number of physicians, all of them are the factors thathave 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 theyaffect 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 healthexpenditure, lower secondary education completion rate, the number of physician andlife expectancy If we increase our health expenditure or have the higher secondaryeducation rate or have more physicians in a country, we can expand our lifeexpectancy

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 lifeexpectancy can suffer severe impacts if we increase our alcohol consumption toomuch

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 beused for analysis

The model also use the Ordinary Least Squares Regression to estimate therelationship between 4 independent variables and a dependent variable; the methodestimates the relationship by minimizing the sum of the squares in the differencebetween the observed and predicted value of the dependent variables configured as astraight line

2 Theoretical model specification

Whereas:

projected estimates, 15+ years of age)

group)

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

3.1 Specify the source of data

Based on data of current health expenditure per capita, physicians, total alcohol

databank, multiple regression analysis shall be conducted in order to observe whatrelationship each variable has with life expectancy The data range in the year 2016 ofsome countries over the world

3.2 Descriptive Statistics and interpretation for each variable

Based on what has been observed above, each of 4 factors has an association withlife expectancy, each one at a different level This research shall draw on somecountries around the world, collected from World Bank databank and observe arelationship between each factor and life expectancy Four specific variables employedhere are current health expenditure per Capita, PPP (current international $); Physicians(per 1000), total alcohol consumption per capita (liters of pure alcohol, projected

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 theoverall mortality level of a population and summarizes the mortality pattern thatprevails across all age groups in a given year It is calculated in a period life tablewhich provides a snapshot of a population’s mortality pattern at a given time In ourmodel, we take the data about life expectancy in 2015 of some high-incomecountries

2 Current health expenditure per capita, PPP (current international $)

Data used in this report consists of current health expenditures, which are both ofhealthcare goods and services consumed during each year They include healthservices (preventive and curative), family planning activities, nutrition activities, andemergency aid designated for health but does not include provision of water andsanitation Data are in current U.S dollars The health expenditure estimates havebeen prepared by the World Health Organization under the framework of the System

of Health Accounts 2011 (SHA 2011)

3 Physicians (per 1000 people)

Physicians include generalist and specialist medical practitioners Health systemdata includes physicians are increasingly being recognized as key to combatingdisease and improving the health status of populations The data is estimated number

of physicians per 1,000 people The WHO compiles data from household and laborforce surveys, censuses, and administrative records

4 Total alcohol consumption per capita

This indicator measures the sum of both recorded and unrecorded adult percapita consumption (15 years of age or older) over a calendar year, in litres of purealcohol, adjusted for tourist consumption Data on recorded alcohol per capitaconsumption of adults (15+ years) are for 2016 and were obtained from the WHOGlobal Information System on Alcohol and Health Recorded alcohol per capita

consumption of adults reflects the consumption of pure alcohol per person percountry in a given year, and is computed from government records (taxation),industry publications for the production and sales of alcohol as well as data from the

UN Food and Agricultural Organization

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

This rate is measured as the percentage of pupils who completed the last year oflower secondary schooling, regardless of age It is calculated as the number of newentrants in the last grade of lower secondary education divided by the total number

of children of official completing age Country-specific definition, method andtargets are determined by countries themselves Data were collected from nationaland other publicly available sources and validated by the Local Education Group(LEG) in each country

3.3 Correlation matrix between variables

SECTION III: HYPOTHESIS

1 Estimated model

1.1 Estimation results

OLS results – Linear Regression Model

1.2 Sample regression model

LE=61.41307+0.0011434*HEC+1.914654*physician-0.2216016*alcohol+0.0997977*secondary+ ̂

1.3 The coefficient of determination

The coefficient of determination measures the goodness of fit

model and the remains is due to other factors

1.4 Explain the meanings of estimated coefficient

independent variables equal 0 then the expected mean value of the dependentvariable is the intercept

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