Abstract The study uses a geometric approach to analyze and examine how the factors including PM2.5 air pollution, GNI per capita and life expectancy at birth affect the Human Development Index (HDI) in 48 Asian countries from 2010 to 2021. We employ HDI as the dependent variable while the three indicators PM, GNI, LE are explanatory variables. Statistical data was collected from mainstream websites of the World Bank, UNDP and helped show the index of HDI and its components in 48 Asian countries. Knowledge acquired through the econometrics course enabled our team to utilize the economic model and linear regression. In addition, we used the Ordinary Least Squares method to estimate the regression function. At first, we laid foundations and provided an overall view about the Human Development Index (HDI) and its indicators. Economic theories learnt in class helped us to make predictions of the effects of those three factors affecting HDI. Secondly, we sorted data from 48 developed countries from 2010 to 2021 on Microsoft Excel and processed fixedrandom effects models by using STATA software. After that, the estimated model was yielded, and hypothesis testing was conducted. We then used STATA to evaluate the impacts of those indicators and describe how they affect the variation of HDI. Lastly, we produced a complete research report, concluding that most of those factors, according to the study, contributed to the Human Development Index. Keywords: HDI, GNI, life expectancy at birth, PM2.5 exposure
https://tailieuluatkinhte.com/ FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -*** ECONOMETRICS II MIDTERM ASSIGNMENT FACTORS AFFECTING HUMAN DEVELOPMENT INDEX IN ASIA FROM 2010 TO 2021 Class: KTEE318 Instructor: PhD Đinh Thị Thanh Bình Group: Group Hanoi, June 2023 https://tailieuluatkinhte.com/ FACTORS AFFECTING HUMAN DEVELOPMENT INDEX IN ASIA FROM 2010 TO 2021 Faculty of International Economics, Foreign Trade University PhD Đinh Thị Thanh Bình Faculty of International Economics, Foreign Trade University Abstract The study uses a geometric approach to analyze and examine how the factors including PM2.5 air pollution, GNI per capita and life expectancy at birth affect the Human Development Index (HDI) in 48 Asian countries from 2010 to 2021 We employ HDI as the dependent variable while the three indicators PM, GNI, LE are explanatory variables Statistical data was collected from mainstream websites of the World Bank, UNDP and helped show the index of HDI and its components in 48 Asian countries Knowledge acquired through the econometrics course enabled our team to utilize the economic model and linear regression In addition, we used the Ordinary Least Squares method to estimate the regression function At first, we laid foundations and provided an overall view about the Human Development Index (HDI) and its indicators Economic theories learnt in class helped us to make predictions of the effects of those three factors affecting HDI Secondly, we sorted data from 48 developed countries from 2010 to 2021 on Microsoft Excel and processed fixed/random effects models by using STATA software After that, the estimated model was yielded, and hypothesis testing was conducted We then used STATA to evaluate the impacts of those indicators and describe how they affect the variation of HDI Lastly, we produced a complete research report, concluding that most of those factors, according to the study, contributed to the Human Development Index Keywords: HDI, GNI, life expectancy at birth, PM2.5 exposure INTRODUCTION The Human Development Index (HDI) has emerged as a valuable metric for evaluating a nation's progress beyond economic growth alone As countries in Asia witness remarkable changes in the global economy, there is a growing need to understand the factors that influence the Human Development Index in the region This research paper aims to examine the factors affecting the HDI in Asia from 2010 to 2021, shedding light on the multidimensional nature of development and its implications for policymaking and societal well-being Understanding the determinants of the Human Development Index in Asia is of paramount importance While GDP has traditionally been used as the primary indicator of progress, it fails to capture the broader aspects of development, such as education, health, and income distribution By analyzing the factors that influence HDI, policymakers, researchers, and stakeholders can gain valuable insights into the key drivers of socio-economic development This knowledge will enable more informed decision-making and the formulation of effective policies aimed at improving the wellbeing and quality of life for people in the region The main objective of this research is to identify and analyze the factors that contribute to variations in the Human Development Index across Asian countries from 2010 to 2021 By examining these factors, we aim to provide a comprehensive understanding of the dynamics and determinants of development in the region Additionally, we seek to offer insights into the potential policy implications for enhancing human development outcomes This study focuses on the Asian region, comprising diverse countries with varying levels of economic development, social structures, and cultural contexts By examining a wide range of nations, including both advanced and emerging economies, we aim to capture the heterogeneity of factors influencing HDI in Asia The study encompasses a period of eleven years, from 2010 to 2021, allowing for an in-depth analysis of long-term trends and capturing potential changes over time This research paper is structured as follows to address the research objectives and questions: Chapter 1: Introduction Chapter 2: Literature Review Chapter 3: Methodology Chapter 4: Data Analysis and Results Chapter 5: Discussion and Implications Chapter 6: Conclusion By addressing these aspects, this research paper aims to contribute to the existing literature on the factors influencing the Human Development Index in Asia and provide valuable insights for policymakers, researchers, and stakeholders in the region LITERATURE REVIEW The Human Development Report which is published annually focuses on human as a central topic, which throughout the years has been modified to better reflect it Researchers have been in a constant search for more accurate reflection of the problem, with the final three official dimensions being health, education, and standard of living These three dimensions have been annually analyzed and reported in from 1990 onwards, with respective indicators being life expectancy at birth, years of schooling, and gross national income per capita Initial studies about HDI can be exemplified by the case in 1994 of “Human Development Index: Methodology and measurement” by Amatyr K Sen and Sudhir Anand It focused differently on the same mentioned factors with much more complex calculations, with topics of interest including human development in general, aggregate indicators and intrapopulation, income distribution and poverty, life expectancy, and level of education, … The formulas the calculate HDI back then were very much different and complicated, using the minimum and maximum value of each indicator, together with a number of complex assumptions and rules for each Throughout the years, a more simplified approach has been acquired to carry out the research Many other research also focus on these factors that further support the foundation laid by Human Development Report, and at the same time, many more shed lights on other new indicators in the hope of discovering the influence of others factors on HDI, finding more and newer indicators, and testing its reliability Several examples of related research are listed below: An article published in 2018 named “Analysis indicator of factor affecting Human Development Index (IPM)” by Windya Wahyu Lestari and Victoria Efrida Sanar indicates that life expectancy index, education index and income index all have considerable impacts on Human Development Index with estimated result showing 14.788% of the variation of each observation is the same Mehran Alijanzadeh, Saeed Asefzadeh and Seyed Ali Moosaniaye Zare’s paper: ‘Correlation Between Human Development Index and Infant Mortality Rate Worldwide’ posted in 2016, Biotech Health Sci find the correlation between human development index and infant mortality rate The paper discovered the relationship between human development index with infant mortality rate It had the scope of 135 nations analysed and derived from SPSS software The conclusion is the report was that socio-economic factors or human dimensions are correlated with mortality rate The per capita income, life expectancy, and education with r being -0,625, -0,925, and -0,843 It indicated that these indicators are negatively correlated with the mortality rate (P< 0.01) In 2017, the study "Quality of Life among General Populations of Different Countries in the Past 10 Years, with a Focus on Human Development Index: A Systematic Review and Meta-analysis" was published, which mainly use mainly uses relevant factors to determine HDI relating to physical, psychological, social and environmental aspects to calculate the Quality of Life index in countries around the world Conclusion was the extremely high HDI subgroup had the greatest overall QOL mean at 74.26 (CI=72.40-76.12) while the lowest mean score was observed in the psychological domain (M=67.37; CI=66.23–68.52) Therefore, the former had the highest means of various QOL domains "The dynamic association between healthcare spending, CO2 emissions, and human development index in OECD countries" published in 2020 and "Environmental Sustainability and Human Development: A Greening of Human Development Index" published in 2014 as this study will show, also very clearly explores the connections between Health and Environmental concerns and the Human Development Index (HDI) More specifically, research in 2014 shows that the close relationship between the development index of environmental sustainability and the HDI constitutes a U-shaped relationship between the HDI and the EPI In addition, this study also considers and calculates a new index, which is EHDI, between both environmental factors and witnessing a huge change in order, which is said to be objective and ensure the development of the environment more sustainable And the 2020 study shows that: all three key variables, health care costs, CO2 emissions and HDI all show a cause-andeffect relationship; A two-way causal relationship exists between health care costs and CO2 emissions, which suggests that CO2 emissions significantly increase health care costs in OECD countries, similarly, head investment in health care also increases emissions by using more energy; positive relationship of investment in health facilities with HDI and finally, CO2 reduction has a positive effect on HDI THEORETICAL BACKGROUND 3.1 HDI 3.1.1 Definition Human Development is defined as the process of enlarging people's freedom allowing them to lead a healthy life, having a decent standard of improved living and guaranteed human rights Therefore, according to the World Health Organization (WHO), the Human Development Index is a composite summary measure of a country's average achievements in three fundamental dimensions of human development: health, knowledge, and standard of living The implications of HDI are: - Highlighting for policymakers, the media, and non-government organizations that the development of a country must be assessed by humans and their capabilities, not economic indicators - Questions the policymakers about their choices; analyze countries with the same level of income but different human development outcomes - Highlight differences within countries, between provinces or states, and across genders, ethnicities and other socioeconomic groupings 3.1.2 Measurement HDI a measure of a country's average achievements in three dimensions of human development: - A long and healthy life – determined by life expectancy - Education acquisition – determined by the median number of years spent in school for persons aged 25 and older and by the predicted years of schooling for youngsters starting school - A reasonable standard of living – determined by Gross National Income per capita Therefore, based on these assumptions, the formula for calculating HDI is: HDI = √3 LEI × EI × II LEI: Life Expectancy Index EI: Education Index II: Income Index 3.1.3 Components LEI: Life Expectancy Index The mean number of years a newborn is expected to live if exposed to the sex- and age-specific death rates in effect at the time of his or her birth, for a specific year, in a given country, territory, or geographic area This indicator is calculated as: LEI = ¿−20 85−20 LE: Life Expectancy at birth EI: Education Index Since 2010, the expected years of schooling for pupils under the age of 25 and the average number of years spent in school by adults have been combined equally (50%– 50%) to calculate the education index In the years before 2010, the education index was measured by the adult literacy rate (with a two-thirds weighting) and the combined primary, secondary, and tertiary gross enrollment ratio (with a one-third weighting) The largest updated formula of EI: EI = MYSI+ EYSI MYSI: Mean Years of Schooling Index (MYSI = MYS represent for maximum 15 years of schooling) 15 EYSI: Expected Years of Schooling Index (EYSI = EYS represent for maximum 18 years of schooling) 18 II: Income Index The income index here differs from that used in HDI in that it incorporates a sufficiency threshold below the HDI’s maximum value of $75,000 (2017$ PPP) This is because to achieve an income of $75,000 per capita is empirically incompatible with planetary boundaries Nations with income over $60,000 have an average material footprint of 35t per capita (more than five times over the planetary boundary) and CO2 emissions of 19t per capita (eleven times over the planetary boundary) These levels of ecological impact are highly destabilizing and cannot be universalized In this sense, the HDI income index effectively precludes nations from achieving very high HDI while at the same time remaining ecologically sustainable II = ln (GNIpc)−ln(100) ln(75,000)−ln (100) GNIpc: Gross National Income at purchasing power parity per capita As analyzed, the components of the HDI include income, education and life expectancy Combined with the literature review ahead, this study will focus primarily on the income and health dimensions, ignoring the education dimension Therefore, to study HDI, we use 03 independent variables: GNI per capita, PM 2.5 exposure and life expectancy at birth 3.2 GNI per capita 3.2.1 Definition Gross National Income (GNI) is the sum of all the money that a country's citizens and enterprises have made It is used to gauge and chart a country's wealth through time The sum of the country's gross domestic product (GDP) and its foreign-source revenue is the figure An estimate of the entire value of all products and services generated inside a country for a specific time period, typically a year, is known as GDP, which is more commonly used Gross national income (GNI), a substitute for the gross domestic product (GDP), is regarded by certain countries as being a more reliable estimate of a country's wealth In fact, GNI may now be the most accurate reflection of national wealth given today's mobile population and global commerce 3.2.2 Measurement As mentioned above, GNI and GDP are highly correlated, so to calculate GNI we have the following equation: GNI = GDP + (EXfs - IMfs) GDP: Gross Domestic Product EXfs: Money flowing from foreign countries IMFS = Money flowing from foreign countries 3.2.3 Components GNI consists of 02 main parts: GDP and (EXfs - IMfs) Explanation of these components: GDP: Gross Domestic Product A country's Gross Domestic Product, or GDP, is the total monetary or market value of all the goods and services produced within that country's borders during a specified period of time Which have been known as an extremely fundamental indicator to measure the economic development of a country Firstly, the basic formula: GDP = C + I + G + (X - M) C: Personal Consumption I: Investment in Business G: Government Spending NX: Exports-Imports Secondly, the income approach way: GDP=Total National Income + Sales Taxes + Depreciation + Net Foreign Factor Income Total National Income: Sum of all wages, rent, interest, and profits Sales Taxes: Consumer taxes imposed by the government on the sales of goods and services Depreciation: Cost allocated to a tangible asset over its useful life Net Foreign Factor Income: Difference between the total income that a country’s citizens and companies generate in foreign countries, versus the total income foreign citizens and companies generate in the domestic country EXfs - IMfs EXfs: Money flowing from foreign countries IMFS: Money flowing from foreign countries These indicators will be compiled annually by the General Statistics Office of Vietnam 3.3 Life Expectancy at birth 3.3.1 Definition The life expectancy at birth reflects the population's overall mortality rate It provides an overview of the mortality pattern that affects people of all ages, including children, adolescents, adults, and the elderly The average number of years a newborn should expect to live if they were subjected to the sex- and age-specific mortality rates that were in effect at the time of their birth for a particular year in a particular nation, territory, or geographic location 3.3.2 Measurement: Life expectancies are calculated using (abridged) life tables presenting age specific mortality rates Life expectancy tables are calculated based on death probabilities according to Farr's death rate method: qx= Mx Mx Bx+ Mx = the number of deaths at the age of x to under x+1 years in the reported period Bx = average population aged x to under x+1 in the base period qx = death probability from age x to x+1 Farr's method of calculation of abridged lifetables assumes that there is a constant mortality within the age intervals and thus the years of life lived by a person dying in the interval is (on average) half of the length of the interval 3.4 PM 2.5 exposure 3.4.1 Definition The term fine particles, or particulate matter 2.5 (PM2.5), refers to tiny particles or droplets in the air that are two and one half microns or less in width Like inches, meters and miles, a micron is a unit of measurement for distance There are about 25,000 microns in an inch The widths of the larger particles in the PM2.5 size range would be about thirty times smaller than that of a human hair The smaller particles are so small that several thousand of them could fit on the period at the end of this sentence According to UNDARK: “the bottom scale shows the U.S Environmental Protection Agency's current benchmarks specifically for PM2.5, which is measured in micrograms per cubic meter of air - sometimes rendered as µg/m³ The higher the mass of fine particulates in the air, the more dangerous it is to breathe” This is an indicator that greatly affects the life expectancy aspect of the HDI's lifespan Therefore, this index is included in the study to further analyze the level of influence, especially for developing countries in Asia 3.4.2 Measurement There are different ways to calculate PM 2.5, especially the “Direct Measurement Method” The BAM 1020 Beta Attenuation Mass Monitor is US-EPA designated for continuous PM2.5 monitoring and is used extensively in air quality monitoring networks worldwide In its standard configuration, the BAM 1020 will measure and then report PM levels with high accuracy on an hourly basis RESULTS 5.1 Data description 5.1.1 Data source