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

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATINAL ECONOMICS ******** GROUP REPORT THE FACTORS EFFECT LIFE EXPECTANCY OF SOME COUNTRIES ALL OVER THE WORLD Group Class: Econometrics – KTEE218 Lecturer: M.S Nguyen Thuy Quynh Members : Tran Xuan Giang – 1814450027 Pham Ngo Quynh Giao – 1814450028 Nguyen Thi Minh Hoa – 1814450193 Nguyen Quynh Trang – 1814450069 Le Ngo To Uyen – 1814450104 Ha Noi, 9/2019 ABSTRACT INTRODUCTION SECTION I: OVERVIEW OF THE TOPIC Definition 1.1 Life expectancy 1.2 Current health expenditure per capita 1.3 Physician 1.4 Alcohol consumption per capita 1.5 Lower secondary completion rate Economic theories Literature review Research hypotheses 11 SECTION II: MODEL SPECIFICATION 11 Methodology 11 Theoretical model specification 12 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 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 Hypothesis testing 18 2.1 Test an individual regression coefficient 18 2.2 Testing the overall significance 21 Recommendations 22 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 healthcare, 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, there was still a lot of researches in the recent decades which have shown that some factors can affect the life expectancy more than the others are Current health expenditure per capita, Physician, Alcohol consumption per capita and Lower secondary completion rate Having the awareness of how important the life expectancy is, we decided to find more about elements affect the life span whether it is a good or bad factor With the tools of econometrics, especially STATA, we set a model with five variables included dependent variable, which is the life expectancy (LE) and independent variables, which are current health expenditure per capita (HEC), physician, alcohol consumption per capita and lower secondary completion rate to optimize analysis process This research could be used as a guideline and may be significant for future researchers and policy makers who aim to improve the life expectancy in each country all over the world Though having tried our best, there are still unavoidable mistakes in every stage of this study Therefore, please let us know and feel free to discuss if you have any concern SECTION I: OVERVIEW OF THE TOPIC 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 and 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 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 a significant effect on infant mortality and there was less than five mortality in 47 selected African countries between 1999 and 2004 In contrast, some studies that analyzed health expenditure did not find any impact on health indicators after adjusting other factors; for instance, Musgrove et al (2005) found that the total spending on health 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 Expenditure Per Capita (HEC) will increase the life expectancy in an average of days in a year The increased total expenditure on health as a percentage of gross domestic products will improve expected years of by days It shows that an increase in Health expenditure per capita has relevance to an increase in life expectancy On the other hand, a country’s drinking habits affect its population’s life expectancy By scraping the World Health Organization’s (WHO) Substance Abuse Country 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 a positive one Drinking wine in moderation may be beneficial for some people’s heart health but stopping at just one glass isn’t always as easy as it seems The reality about alcohol consumption is that the developed countries are drinking less and, in contrast, consumption in developing countries is increasing Most developing countries not have a national policy to reduce alcohol consumption Alcohol consumption exacerbates poverty then affect life expectancy Drinking costs a nation billions of dollars 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, lost 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 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 Literature review Life expectancy is an important index that reflects the standard of living and the social situation as well as the economic development level of a country Therefore, in recent decades, there are a lot of studies carried out that research about life expectancy and the potential factors affecting it According to an article released by the Lancet on April 14, 2018 about “Risk thresholds for alcohol consumption”, it has shown that the association between alcohol consumption and total cardiovascular disease risk According to research from the National Institute on Alcohol Abuse and Alcoholism, women are especially vulnerable to the negative medical effects of excessive alcohol use Besides the alcohol consumption, there is an irrefutable positive correlation between education and longevity A study by the Washington University School of Medicine suggests there are both direct and indirect health benefits of education The direct benefits include adopting healthier lifestyles, an increased ability to cope with stress, and more effective management of chronic diseases In terms of indirect benefits, scientists point to a, generally, better social position, a bette r paying job, and access to better medical care Another research was published on The Journal of Medical Research and Innovation has shown an association of total Health Expenditure with GDP and life expectancy According to Asian Economic and Financial Review “DETERMINANTS OF LIFE EXPECTANCY: A PANEL DATA APPROACH”, Yavari and Mehrnoosh (2006) analyzed the effects of socio- economic factors on life expectancy using multiple 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 ➢ Method 3: P – value approach p- value of physician =0.000tc→ reject Ho Method 3: P – value approach p- value of alcohol=0.048tc→ reject Ho we see that | Method 3: P – value approach p- value of secondary=0.000 F5%, (4, 131)→ Reject H0 F0= 21− Method 2: P – value approach ( −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 variable is significant at the 5% level 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 In brief, life expectancy has been one of the most significant issues worldwide In our report, even though there is a model that has statistically significant and possibly economically significant independent variables, we have to emphasize that the variables chosen are probably not the best measures of the life expectancy because life expectancy can be influenced by many other factors such as gender, genetics, lifestyle and so on This is the biggest drawback that we could not avoid Besides, data collecting is manual from different sources in the Internet so that mistakes could not be avoided, this is also a limitation On the other hand, we have some recommendations concluded from the model If possible, we should add more other variables such as gender, genetics, marital status and so on to this model in order to have a better overview about the research INDIVIDUAL ASSESSMENT Minh Hoa Quynh Trang To Uyen Quynh Giao Xuan Giang Minh Hoa 10 10 10 10 10 Quynh Trang 10 10 10 10 10 To Uyen 10 10 10 10 10 Quynh Giao 10 10 10 10 10 Xuan Giang 10 10 10 10 10 Average score 10 10 10 10 10 Evaluator REFERENCES https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)30134X/fulltext#seccestitle70 https://pubs.niaaa.nih.gov/publications/arh24-1/05-11.pdf https://www.healthaffairs.org/doi/full/10.1377/hlthaff.2011.0746 https://jmrionline.com/jmri/article/view/72 http://www.aessweb.com/pdf-files/aefr-2015-5(11)-1251-1257.pdf https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2724393 http://www.who.int/gho/alcohol/en/ https://databank.worldbank.org/source/health-nutrition-and-populationstatistics?fbclid=IwAR3D2iXLXZQIgmfIWMCtRuN4LST587ZZS7CdTMmqe2zk1DH9vr9s9WLu6I https://databank.worldbank.org/source/health-nutrition-and-populationstatistics?fbclid=IwAR3D2iXLXZQIg- mfIWMCtRuN4LST587ZZS7CdTMmqe2zk1DH9vr9s9WLu6I https://databank.worldbank.org/source/health-nutrition-and-populationstatistics?fbclid=IwAR3D2iXLXZQIg- mfIWMCtRuN4LST587ZZS7CdTMmqe2zk1DH9vr9s9WLu6I https://databank.worldbank.org/source/health-nutrition-and-populationstatistics?fbclid=IwAR3D2iXLXZQIgmfIWMCtRuN4LST587ZZS7CdTMmqe2zk1DH9vr9s9WLu6I https://data.worldbank.org/indicator/SE.SEC.CMPT.LO.ZS?fbclid=IwAR2kOUXKgV _mWLFj-Ofy28mPVozSm_mVd4DdwdfQ_qteEQBrE_CsYsrELlo APPENDIX Table 1: Data from database: Health nutrition and population statistics Country Name Current health expenditure Lower Physician Alcohol secondary education per capita Life expectancy Afghanistan 162,7811582 0,284 0,2 50,68683 63,763 Albania 759,6669842 1,1998 7,5 91,1 78,194 Algeria 998,1537539 1,83 0,9 79,07359 76,298 Angola 185,8204006 0,2 6,4 20,9 59,925 Antigua and Barbuda 976,3886597 2,8 91,4 76,617 Argentina 1531,038361 9,8 88,42663 76,221 Armenia 876,8568566 2,9 5,5 87,55285 74,64 Australia 4529,887082 3,5874 10,6 91,87532 82,44878 Austria 5295,181772 5,1441 11,6 97,17982 81,64146 Azerbaijan 1193,05883 3,4 0,8 89,03829 72,493 Bahamas, The 1435,567513 1,9 4,4 96,7 73,329 Bahrain 1866,29732 1,9 97,74154 76,899 Bangladesh 90,59840433 0,4822 76,53319 71,785 Barbados 1322,985509 2,5 9,6 100,8 78,888 Belarus 1151,408849 4,1 11,2 106,7573 73,82683 Belgium 4667,882287 3,3234 12,1 94,40424 81,43902 Belize 541,4343274 1,1 6,8 70,51413 74,219 Benin 83,47636765 0,1572 45,8472 60,885 Bhutan 293,1100222 0,3748 0,6 79,01542 70,781 Bolivia 496,3061886 1,6111 4,8 87,49558 70,626 1123,425425 6,4 75,98123 76,998 Botswana 931,3047144 0,3688 8,4 94,1 68,178 Brazil 1777,470477 2,1 7,8 71,8 75,23 Brunei Darussalam 1812,413646 1,8 0,4 101,2918 75,45 Bulgaria 1577,942762 12,7 47,55045 74,8122 Burkina Faso 115,6043314 0,06 8,2 30,14426 60,354 Burundi 50,25423113 0,05 7,5 41,03252 60,528 Cabo Verde 347,6412499 0,8 5,7 71,92952 72,347 Cambodia 228,5708677 0,2 6,7 47,43258 68,977 Canada 4718,296818 2,5668 8,9 100,3278 82,14224 29,9077719 3,3 10,02517 51,593 Bosnia Herzegovina Central Republic 0,9 and African 0,1 Chad 94,95477954 0,0475 1,6 15,07751 53,438 Chile 2002,008384 1,08 9,3 92,43022 79,779 Colombia 829,8029221 2,0036 5,8 76,9861 76,732 Costa Rica 1248,547928 1,1 4,8 56,7513 79,738 Cote d'Ivoire 162,6449615 0,2 8,4 39,52378 56,567 Croatia 1705,207618 2,9962 8,9 91,59296 78,02195 Cyprus 2270,831744 1,9511 10,8 97,6 80,513 Czech Republic 2484,633529 4,314 14,4 96,94885 79,02683 Denmark 5092,980309 4,4567 10,4 99,45043 80,85366 Djibouti 122,0756057 0,2 0,5 39,99493 65,064 Dominican Republic 936,82159 6,9 84,59305 73,471 Ecuador 942,8866596 2,05 4,4 104,086 76,365 Egypt, Arab Rep 516,3431545 0,8107 0,4 83,5875 71,482 El Salvador 599,5487168 1,569 3,8 79,91723 72,644 Equatorial Guinea 838,744272 11,3 24 57,713 Estonia 1987,718156 3,4651 11,6 107,9625 77,64146 Eswatini 663,2525798 0,0796 9,9 55,07566 56,962 Ethiopia 69,52478888 0,1 2,9 29,6 65,482 Fiji 313,1713121 0,8 96,81344 67,175 Finland 4112,054234 3,808 10,7 99,84802 81,42927 France 4782,288549 3,2349 12,6 98,28128 82,52439 Gabon 555,6279022 0,3611 11,5 21,7 65,418 Gambia, The 74,31114618 0,1 3,8 63,2 61,166 Georgia 797,1759528 5,1 9,8 106,8863 73,207 Germany 5463,330652 4,2087 13,4 57,82493 80,99024 Ghana 189,3748859 0,1283 2,7 79,3 63,124 Greece 2261,15653 10,4 90,09265 81,3878 Grenada 745,1027805 1,4 9,3 89,56044 72,408 Guatemala 462,405855 2,5 62,63609 73,541 Guinea 107,7236555 0,0788 1,3 36,5 60,17 Honduras 400,3364097 0,6086 47,45225 84,22683 Hungary 1963,16263 11,4 93,44505 76,06341 India 241,4830553 0,7592 5,7 85,88366 68,897 1,1 0,4 4,592 0,4 3,2312 Indonesia 362,7219413 0,4 0,8 95,05864 71,035 Iran, Islamic Rep 1563,751678 1,1 92,63842 76,047 Ireland 5299,653967 2,9536 13 99,40218 81,70488 Israel 2843,044007 3,2176 3,8 101,4142 82,40732 Italy 3427,306466 4,0323 7,5 99,82848 83,2439 Jamaica 535,6645833 0,4588 4,2 85,6 74,175 Japan 4592,428208 2,4118 102,5113 83,98488 Jordan 494,7536463 1,4099 0,7 60,8 74,184 Kazakhstan 858,76985 3,3 7,7 115,854 72,3 Kenya 143,5442376 0,2 3,4 81,07376 65,393 Kiribati 249,8413143 0,2 0,4 93,00531 67,577 Korea, Rep 2711,738257 2,3124 10,2 101,4697 82,27561 Kuwait 2899,260238 2,6 89,65478 75,224 Kyrgyz Republic 240,2266108 1,9 6,2 93,02118 70,95122 Lao PDR 154,6294593 0,5 10,4 66,77488 66,924 Latvia 1589,692045 3,1946 12,9 96,21353 74,58049 Lebanon 1147,374774 2,2485 1,5 51,40735 78,8 Lithuania 1978,269356 4,337 15 101,3228 74,67073 Luxembourg 6374,203539 2,9234 13 98,72927 82,68537 Madagascar 90,42908953 0,2 1,9 36,02995 65,931 Malawi 115,156902 0,0157 3,7 30,2 62,681 Malaysia 1052,54758 1,5 0,9 84,47251 75,649 Maldives 1628,542879 1,0379 2,7 103,6456 78,013 Mali 81,18253226 0,1393 1,3 30,57335 57,987 Malta 3511,136456 3,8 8,1 99,80421 82,45366 Mauritania 163,9174489 0,2 28,42434 64,208 Mauritius 1206,739779 3,6 88,48086 74,39488 Mexico 971,8231599 2,2478 6,5 91,62148 74,917 Moldova 480,3830005 3,2 15,2 83,07987 71,617 Mongolia 466,6912181 2,8866 7,4 136,6 69,321 Montenegro 1333,9299 97,10362 76,568 Morocco 465,6996018 0,7 0,6 67,83518 75,974 Mozambique 61,64512077 0,1 2,4 22,5 58,309 Myanmar 291,0885467 0,6214 4,8 54,65364 66,205 Nepal 155,9695883 0,7 86,20061 69,848 Niger 61,43025084 0,1 0,5 16,85617 61,137 Nigeria 213,7372371 0,4 13,4 60 53,541 Norway 6203,454703 4,4948 7,5 101,0668 82,40732 Pakistan 144,1238241 0,1 0,3 53,96524 66,77 Panama 1750,298851 1,5699 7,9 84,2 77,964 Paraguay 767,7671156 1,4 7,2 83,9 73,836 Peru 680,9994927 1,27 6,3 86,14601 76,044 Poland 1784,396984 2,3998 11,6 95,42526 77,85122 Portugal 2778,415587 3,3356 12,3 55,9 81,12439 Qatar 3926,121037 2,7831 89,31027 79,868 Romania 1152,175449 2,2586 12,7 86,39524 75,30976 Russian Federation 1329,29242 4,0139 11,7 98,91831 71,65122 Rwanda 130,380629 0,14 34,62466 67,93 Samoa 352,799723 0,3409 2,5 99,14866 72,895 196,8968792 0,3 6,8 74,2 69,67 Saudi Arabia 3117,233527 2,39 0,2 105,1 74,761 Senegal 141,6948615 0,0692 0,7 36,94113 67,078 Serbia 1322,563548 3,125 11,1 95,14309 75,6878 Seychelles 1122,563754 0,9458 12 125,2212 74,30976 Singapore 4083,751681 2,3063 107,3664 82,84634 Slovak Republic 2172,16039 2,4643 11,5 96,1 77,16585 Slovenia 2772,229776 2,9953 12,6 96,13171 81,17561 Sao Tome Principe 2,3 and Solomon Islands 117,7578748 0,1999 1,4 70,6 72,424 South Africa 1071,347104 0,8024 9,3 75,42397 63,153 Spain 3259,802775 4,0691 10 91,87004 83,32927 Sri Lanka 491,4933648 1,0578 4,3 95,09033 76,482 Sweden 5386,734023 5,3996 9,2 108,2457 82,30732 Switzerland 7867,394505 4,2363 11,5 98,13683 83,60244 Thailand 635,021796 0,4457 8,3 79,82983 76,403 Tunisia 806,3436155 1,2722 1,9 70,8 76,115 2546,187603 2,3944 3,8 81,9 77,47 United Kingdom 4177,815131 2,7959 11,5 147,9423 81,1561 United States 9869,742382 2,5948 9,8 156,9345 78,53902 Uruguay 1958,900218 3,9329 10,8 74,1 77,498 Vanuatu 116,0924795 0,1706 52,9 70,021 Vietnam 356,2796547 0,8199 8,4 87,55834 75,172 Zambia 175,1783521 0,0913 4,8 53,4 62,464 United Emirates Arab ... 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. .. 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. .. rate 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