factors affecting child mortality in europeancountries from 2009 to 2018

Nguyễn Thúy QuỳnhFaculty: International EconomicsKeyword: child mortality, female literacy rate, GDP per capita, total fertility rate, EuropeanOur essay titled: “Factors affecting child

FOREIGN TRADE UNIVERSITY

FACULTY OF INTERNATIONAL ECONOMICS

-*** -ECONOMETRICS MID-TERM PAPER

Major: International Economics

Topic: Factors affecting child mortality in European

countries from 2009 to 2018

Group: 2 Class: KTEE218.1 Supervisor: Ms Nguyen Thuy Quynh

Hanoi, December 2022

TABLE OF CONTENTS

INDIVIDUAL ASSESSMENT 2

DECLARATION 6

ACKNOWLEDGEMENTS 7

SUMMARY 8

ABSTRACT 9

INTRODUCTION 10

SECTION 1 OVERVIEW OF THE TOPIC 11

1.2 Variables Definition and Economic Theories related 11

1.2.1 Child mortality 11

1.2.2 Gross Domestic Product per capita (GDP per capita) 11

1.2.3 Total fertility rate 12

1.2.4 Literacy rate 12

1.3 Variable Relationship 13

1.4 Related published researches 13

1.4.1 Factors affecting infant mortality rates: evidence from cross-sectional data (MOHAMMED ZAKIR and PHANINDRA V WUNNAVA, Department of Economics, Middlebury College, 1997) 13

1.4.2 National infant mortality rates in relation to gross national product and distribution of income (Simon Hales, Philippa Howden-Chapman, Clare Salmond, Alistair Woodward, Johan Mackenbach, Department of Public Health, Wellington School of Med, 1999) 14

1.4.3 Women's Schooling, the Selectivity of Fertility, and Child Mortality in Sub-Saharan Africa (Mark Pitt, 1995) 14

1.5 Hypothesis 15

2.1 Methodology 16

2.1.1 Method to derive a model 16

2.1.2 Method to collect and analyze data 16

2.2 Theoretical model specification 16

2.2.1 Proxy to measure 16

2.2.2 Specify the model 18

2.2.3 Theoretical relationship between dependent and independent variables 18 2.3 Data description 19

2.3.1 Sources of Data 19

2.3.2 Descriptive statistics and interpretation for each variable 19

2.3.3 Correlation matrix 21

SECTION 3 ESTIMATED MODEL AND STATISTICAL INFERENCE 22

3.1 Estimated model 22

3.2 Hypothesis testing 23

3.2.1 Testing research hypothesis 23

3.2.2 Testing the overall significance of the model 23

3.2.3 Testing individual coefficients’ significance 24

3.3 Recommendation 25

CONCLUSION 26

REFERENCES 27

APPENDIX 29

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LIST OF TABLES

Table 1 Sample data statistics 19Table 2 Correlation matrix 20Table 3 STATA results 21

The research “Factors affecting child mortality in European countries from

2009 to 2018” was carried out by Group 2 - class KTEE218.1, consisting of 5 members Vu Huu Binh, Pham An Hieu, Dang Nhat Minh, Nguyen Anh Duc and Nguyen Hoang Duong

We hereby declare that we have collected data and conducted the research ourselves This research has not been submitted, in whole or in part, for any other processional qualification and all used references are cited in the References of this Research

Hanoi, 12/7/2022

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Our group would love to send the dearest thank to M.S Nguyen Thuy Quynh for your extraordinary assistance to this research All the knowledge during the course of Econometrics 1 is our inspiration to conduct this research and we could not proceed without your valuable feedback and contribution For us, it is our precious honor and pleasure to have a lecturer like you

We have made all efforts to complete this research, using all the methods and theories we gained from the course There may be shortcomings in our research but

we are glad to receive any comments or suggestions from you so we can improve onour work for the next time

Once again, we want to express our deepest gratitude and we hope to have more chances to learn from you and receive your invaluable advices in the nearest future

Sincerely,

Group 2

Instructor: M.S Nguyễn Thúy Quỳnh

Faculty: International Economics

Keyword: child mortality, female literacy rate, GDP per capita, total fertility rate, European

Our essay titled: “Factors affecting child mortality rate in European countries from 2009 to 2018.” investigates the child mortality rate in 47 European countries during this period by using econometrics method We aim to measure the change in child mortality rate caused by 3 factors: Female literacy rate, GDP per capita and fertility rate Data is collected from credible sources such as: World Bank and countryeconomy and then analyzed using STATA 16 Using regression analysis and the OLS method, we were able to find out that female literacy rate and GDP per capita have adverse relationships with child mortality rate while high fertility rate will increase child mortality The results are aligned with theoretical predictions andfindings of previous research Our findings suggest that governments should create policies that directly impact the aforementioned factors in favorable directions in order to minimize child mortality rate

1.1.1.1.

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Child mortality is an indicator of health as well as overall national

development In this research, we aim to explore the impacts of female literacy, GDP per capita, and total fertility rate on the number of child deaths in Europe and Central Asia Literacy not only shows parents’ knowledge about childcare, but also allows them to have meaningful employment to provide for the young Total fertility rate indicates the healthcare level, as well as the responsibility level of the parents in using contraceptive and family planning The GDP per capita of a region reveals the economic growth and average income per capita in the area Through econometrics methods using the regression model, the research results reveal that child mortality has an inverse relationship with female literacy level and GDP per capita The study also finds a positive correlation between child mortality and total fertility rate

Long-term efforts to eliminate child mortality have become a top priority for many governments throughout the world As one of the primary problems that need addressing for countries to achieve sustainable development goals set by the global community, child mortality is a challenge that requires intensive research and analysis to overcome While numerous developed countries have greatly reduced child mortality rates by investing in medical and educational programs, improving welfare systems, and eliminating different types of diseases,… We still have a long way to go to eliminate this problem for good, especially in underdeveloped countries

As with many problems concerning human welfare and long-term

development, child mortality is widely considered to be a complex issue caused by

a variety of factors, including, but not limited to economic development, education system, and general population health To combat this problem, it is best that we research deeply into its root to figure out all the factors that caused it and

understand the direction to modify these factors in our favor In order to achieve this, we have conducted a research named: “Factors affecting child mortality rate”.Our objective of the research is to describe the factors impacting child mortality rate in various countries, showing the relationships and the magnitude of the relationships between the factors and child mortality rate We have decided on 3 research objects, that is: GDP per capita, female literacy rate and fertility rate.This research consists of 3 main sections In section 1, we present 4 parts: the definition of all objects mentioned in the research, the economic theories related to the research, other related research and our research hypotheses After that, we cover the methodology to derive the model and analyze the data collected, the theoretical model specification and describe the data In the last section, we show the estimation of the model, the hypothesis testing and recommendations

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SECTION 1 OVERVIEW OF THE TOPIC

1.2 Variables Definition and Economic Theories related

1.2.1 Child mortality

Child mortality is the mortality of children under the age of five The child mortality rate, also under-five mortality rate, refers to the probability of dying between birth and exactly five years of age expressed per 1,000 live births

Child Mortality calculation:

per 1000 per day

1.2.2 Gross Domestic Product per capita (GDP per capita)

GDP per capita is the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output, divided by mid-year population This calculation reflects a nation's standard

of living

GDP per capita = Gross domestic product (GDP) is the total monetary or market value of all the finished goods and services produced within a country’s borders in a specific time period As a broad measure of overall domestic production, it functions as a comprehensive scorecard of a given country’s economic health

1.2.3 Total fertility rate

The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age-specific fertility rates It is calculated by totalling the age-specific fertility rates as defined over five-year intervals (Age-specific fertility rate is the number of live-births born to females of a specific age group, out of every thousand females in the same age group.)

Together with mortality and migration, fertility is an element of population growth, reflecting both the causes and effects of economic and social developments.This indicator is measured in children per woman

Total fertility rate formula:

TFR = 5 Where TFR is total fertility rate per woman in a specific year and ASFR is age-specific fertility rate per 1000 women in a 5-year increment age group

1.2.4 Literacy rate

The literacy rate is defined by the percentage of the population of a given age group that can read and write The adult literacy rate corresponds to ages 15 and above, the youth literacy rate to ages 15 to 24, and the elderly to ages 65 and above

It is typically measured according to the ability to comprehend a short simple statement on everyday life Generally, literacy also encompasses numeracy, and measurement may incorporate a simple assessment of arithmetic ability The literacy rate and number of literates should be distinguished from functional literacy, a more comprehensive measure of literacy assessed on a continuum in which multiple proficiency levels can be determined

Calculation method:

A high literacy rate (or low illiteracy rate) suggests the existence of an effective primary education system and/or literacy programs that have enabled a

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large proportion of the population to acquire the ability of using the written word (and making simple arithmetic calculations) in daily life and to continue learning It

is common practice to present and analyse literacy rates together with the absolute number of adult illiterates as improvements in literacy rates may sometimes be accompanied by increases in the illiterate population due to a changing

demographic structure

1.3 Variable Relationship

Female literacy plays a critical role in the overall growth and development of children It has been proved from research that children who are taken care of by literate mothers get all round development in every aspect of their life There is an inverse relationship between female literacy rate and infant mortality and children mortality rate

There is a very strong relationship between child mortality and economic development: higher GDP means a lower child mortality

Lower (or higher) mortality might induce lower (or higher) fertility, but it is well established that higher birth rates lead to higher infant and child mortality

1.4 Related published researches

1.4.1 Factors affecting infant mortality rates: evidence from sectional data (MOHAMMED ZAKIR and PHANINDRA V WUNNAVA, Department of Economics, Middlebury College, 1997)

cross-The research’s methodology is a quantitative research This communication studied the impacts of fertility rates, female participation in the labour force, per capita GNP, female literacy rates, and government expenditure on health as a percentage of GNP on infant mortality rates Results, based on 117 countries for the year 1993, and after adjusting for heteroscedasticity, indicate that with the exception

of expenditure on health programmes, all other factors significantly affect infant mortality rates However, the findings contradict Chowdhury’s (1988) theory that there is a dual causality between infant mortality rates and fertility rates, but demonstrate that fertility rates do have an effect on infant mortality rates

Furthermore, of all the independent variables, fertility rates and female literacy rates

have the strongest impact on infant mortality rates Hence, these factors should be given prime importance when developing programmes to curb infant mortality.

1.4.2 National infant mortality rates in relation to gross national product and distribution of income (Simon Hales, Philippa Howden- Chapman, Clare Salmond, Alistair Woodward, Johan Mackenbach, Department of Public Health, Wellington School of Med, 1999)

This research uses quantitative method The research examines the relation between infant mortality rates, gross national product, and income distribution usingthe World Bank database (38 countries in 1970 and 26 countries in 1990 Its findingssupport the hypothesis that average measures of population health are influenced bythe distribution of income within societies From the results, it can be seen that infant mortality rate was negatively associated with GNP per head, and positively associated with income inequality, both of the relations are highly significant (p < 0,001) When they used 1990 data on the GNP per head and the Gini coefficient to validate the model, predictions for infant mortality rates in 1990 were in close agreement with the true values (r=0.89 with the Gini coefficient data for 26 countries; and r=0.91 with the Gini coefficient data for 94 countries) The findings suggest that in poor countries (GNP per head < US$1000) a substantial reduction in infant mortality rate may be possible by decreasing income inequality or increasing GNP per head In rich countries, reduction of income inequality is likely to be more effective in lowering infant mortality rates than further increases in GNP per head would be

1.4.3 Women's Schooling, the Selectivity of Fertility, and Child Mortality

in Sub-Saharan Africa (Mark Pitt, 1995)

This paper estimates the determinants of child mortality in the fourteen Saharan countries for which Demographic and Health Surveys (DHS) data are available It differs radically from the usual approach of estimating reduced-form equations of child mortality from samples of children by allowing for the possibilitythat such samples are choice-based, reflecting prior selective fertility decisions

Sub-In 5 of the 14 countries, the estimated selectivity parameter, p, is statistically significant at the 0.05 level or less In three of these five countries the correlation

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coefficients are positive, indicating negative birth selection, and two of them are positive Negative birth selection means that unmeasured factors associated with higher child mortality are associated with higher fertility - mothers of children morelikely to die before the age of 24 months (conditional on the exogenous variables) are more likely to experience a birth in any time period Overall, 9 out of 14 correlation coefficients are positive Among the estimates uncorrected for the selectivity of fertility, mother's schooling reduces the probability of child mortality before age two in every case, and is statistically significant at communion levels of significance for all countries except Tanzania (t= -1.07) Among the selection-corrected estimates, women's schooling is also negatively associated with mortality

in every case, and also statistically significant in every case (for Tanzania the statistic becomes -4.42)

t-1.5 Hypothesis

Based on existing research and knowledge, all three factors: GDP per capita, female literacy and fertility rate are all known to have an impact on child mortality More specifically, GDP per capita and female literacy are hypothesized to be negatively related to child mortality while high fertility rate will generally increase child mortality rate