The Problem of Infant Mortality - Research Proposal Example

Statistical Concepts for Research and number submitted Contents Introduction 3 ment of the Problem 3 Literature Review 4 Hypothesis 5 Data 5 Results 7 Synthesis 7 Conclusion 8 References 9 Appendix 10 Introduction The purpose of this paper is to discuss the impacts of economic and social factors that influence the rate of infant mortality in countries. Infant mortality is one of the parameters that vary widely among nations. It has been observed that the level of infant mortality is higher among developing countries compared to developed countries. Proponents of health economics state that, health is one of the most important factors that determine the level of productivity of workforce that can sustain long-term economic growth of the nation. Mortality and morbidity rates have long been used by researchers as a measure to study the health status of a nation. The idea is to understand which social and economic parameters have major impact on the infant mortality rates so that government can invest in these parameters and improve the health and productivity of the economy. The paper limits itself to five variables namely GDP per capita, female literacy, health expenditure of state, access to clean water and sanitation facilities s as determinants of infant mortality. The researcher has used Linear Regression Model for econometric modeling to answer the research question. Statement of the Problem The problem of infant mortality is considerably high in the developing countries compared to the developed countries. Works of researchers like Firebaugh and Beck (1994) had shown that difference in the level of economic development between nations is one of the strongest factors that cause differences in the level of mortality in a country. Majority of the studies that have been conducted in the context of infant mortality have focused on modernization theory to determine the impact on infant mortality. It has often been found that; infant mortality rate of developing countries is much higher compared to that of developed countries. The research conducted by Liu, et al. (1991) has confirmed that, socioeconomic development of a country is closely related to the status of mortality including that of infant mortality in a country. Based on these research works it can be argued that infant mortality of developing countries is closely related to the aspect of socio-economic development. This research is relevant because it helps to explore the factors that contribute positively to the health status of developing countries. The research can have important implications for policy makers. Literature Review There is a wide variety of literature that has focused on the socio-economic indicators and their impact on the infant mortality of a country. There are five main theories that have come to the forefront in the works of researchers which have the power to explain the variation of infant mortality rates between countries. These theories are modernization theory, gender stratification theory, developmental state theory, dependency theory and economic disarticulation theory (Flegg, 1982). Researchers supporting the modernization theory states that, increase in the level of economic output and industrialization of a country have the capability to improve housing conditions, healthcare services and educational attainment of a nation thereby, reducing the level of infant mortality (Frey & Field, 2000). Gender stratification theorists state that improvement in health and education of women automatically reduces the level of infant mortality. Proponents of developmental theory argues as the development of the state progresses the policies adopted by it changes and greater attention is provided to the redistribution of resources in favor of promoting the health conditions (Williamson & Boehmer, 1997). Such efforts are automatically correlated with the reduction in infant mortality rate. Researchers of dependent theory states that if dependent relations exist between countries then human-well being is hampered. Finally, economic disarticulation theorists claims that if the multiple-sectors of the economy are independent of one another, then this in turn leads to uneven economic development (Frey & Field, 2000). Few studies conducted by researchers have tried to club the different theories and conduct comprehensive studies to find the impact on infant mortality of countries. For instance, the study conducted by Shen and Williamson (2001) had combined all the theoretical perspectives and studied infant mortality in 82 countries. The results from their study had confirmed that all of the five theoretical backgrounds affect the level of infant mortality in countries. Economic growth, distributive efforts by the state and women’s health have been found to be significant factors impacting mortality of children. For instance, the research conducted by H. Arik and M. Arik (2010) had studied the impact of economic growth and socio-economic indicators on the infant mortality of 66 countries. The research had applied both linear and non-linear regression models to formulate the results. The research had confirmed that GDP per capita is an important determinant of infant mortality rate but this does not have a linear relationship with infant mortality. Additionally, the level of literacy rate of women and high fertility rates had emerged as important factors that affect infant mortality (Andes, 1989). Majority of the researchers have confirmed that education and income inequality plays an important role in determining the status of infant mortality in developing countries. Per capita GDP, which is often considered as a proxy of standard of living has been found to be an important factor that can help in the prevention of certain diseases like diarrhea and nutrition related problems. The research conducted by Jeuland, et al. (2013) had found out that the lack of proper sanitation; hygiene and access to clean drinking water are factors that have adversely affected the mortality rates in the developing countries. The findings from their research had suggested that, it is important to take accelerated efforts to improve health and sanitation of South Asia and Sub-Saharan Africa. Other developing countries like Latin America and Asia and Pacific regions have shown considerable improvements over time. Many researchers have found that maternal education is an extremely important factor that can help in the reduction of infant mortality in a country. This happens because, women who are educated have a tendency to less fatalistic about the ill health of their children. Educated women have also been found to be altering the traditional relationships in a society by providing great attention for the care of the child (Caldwell, 1979). Hypothesis Based on the above discussion the hypothesis can be framed as: H0: Infant Mortality of developing nations does not depend on socio-economic factors. H1: Infant Mortality of developing nations depends on socio-economic factors. Data The data for this research has been collected from thirty developing countries namely India, China, Brazil, Russia, South Africa, Afghanistan, Albania, Argentina, Bangladesh, Bhutan, Bolivia, Malawi, Turkey, Sudan, Uganda, Pakistan, Paraguay, Peru, Romania, Jordan, Iran, Iraq, Indonesia, Angola, Zimbabwe, Zambia, Yemen, Vietnam and Benin. The secondary data has been collected from government publications and international organizations like World Bank and UNDP. The method of sampling can be classified as purposive because, the researcher had previously determined the variables that influence infant mortality and collected data specifically on these variables. Econometric Model The hypothesis of the research can be stated by the following econometric model: (IMR)ij = α + β1(Female Literacy)ij + β2(public expenditure on health)ij + β3(GDP per capita)ij + β4(Safe drinking water)ij + β5(Good sanitation facility)ij + €ij The above equation shows that the researcher have assumed that, there is a linear relationship between the dependent and independent variables. IMR: IMR represents the infant mortality rate of a country and it represents the number of children dying before the age of one year per 1000 live births. This is the independent variable under study. Female Literacy: Female Literacy rate has been defined as the percentage of women above the age of seven years who can read as well as right with proper understanding. GDP per capita: GDP per capita is defined as the total value of goods and services produced in a country divided by the total number of population in the country. It is a rough representation of the overall standard of living of country. Health Expenditure: The health expenditure of a country can be considered as the total expenditure incurred on health care as a proportion of the total GDP. Access to safe drinking water: It is a measure of the percentage of population in a country that have an access to clean and safe drinking water. Sanitation facilities: It is a measure of the percentage of population that has access to acceptable sanitation standards in a country. Female Literacy rate, GDP per capita, health expenditure, safe drinking water and sanitation facility are considered as independent variables in the equation as they have been pointed out to be significant variables that impacts infant mortality rate of a country. Thus, research is a cross-country study that infant mortality rate considers thirty developing countries by collecting data on the each of the six five variables. The data that is collected for the research can be classified as pooled data. This is because the data contains components of both time-series data (data collected for last 13 years) and cross-sectional data (data collected for 30 countries). In order to make the analysis simple, it has been assumed that the time series data is stationary. According to the researchers it has been confirmed that, if the time series data is stationary then this implies that mean and variance of the data does not exhibit any trend over time. Results The results obtained from the regression have been shown in the appendix. It has been found that the value of R2 is 0.844 (Shown in Table 1 of Appendix) which implies that the independent variables explain 84% of the variation in the dependent variable. The overall model is significant as the p value of F value is 0.00 which is definitely less than 0.05. This is because; the chosen level of significance is 5% which implies that only 5 out of 100 times the constructed interval will not contain the value of true population parameter (Anderson, et al., 2013). From the coefficients of variables shown in Table 2 of appendix it can be seen that, all the coefficients are negatively correlated to the dependent variable. Except for GDP per capita all the other economic variables has turned out to be statistically significant. This is determined from the t-value of the coefficients. Larger the t value from 1 greater is its explanatory power. Researchers have established that if the p-value is lesser than the chosen level of significance then the independent variable as well as its corresponding coefficient turns out to be statistically significant (Wooldridge, 2012). From the F-value in the above discussion it can be stated that the null hypothesis will be rejected and the alternative hypothesis will be accepted. This implies that, the infant mortality of a country depends on the socio-economic variables of the country. Synthesis The findings from this research have similarities with the findings from literature. It has been found that GDP per capita have a statistically insignificant relationship with the level of infant mortality of a country. This however, does not imply that GDP per capita does not influence infant mortality. Findings from the research of H. Arik and M. Arik (2010) had confirmed that GDP per capita have a non-linear relationship with infant mortality. This provides a plausible explanation for the deviation of the result in this research. Linear econometric modeling may have created this problem. Other factors like literacy of women, health expenditure of state and access to clean drinking water have all been found to be important factors which are also supported in the works of other researchers. Conclusion Infant mortality is heavily influenced by the social and economic variables of a country. This research has found out that, social and economic variables of a country have a big influence on infant mortality. The hypothesis of the research, that infant mortality is influenced by socio-economic indicators has been accepted based on linear econometric modeling. Factors such as the level of educational attainment of women, role of state in promoting the health services of the country, access to safe drinking water and sanitation services has all been found to be statistically significant. The deviations that have been observed in the research findings have occurred mainly because of the style of econometric modeling. It is important for governments in developing countries to reduce infant mortality in to lowest minimum so that it does not hamper the long-term economic growth of a nation. Adaptation of social policies like enhancing the access to safe drinking water and increasing the level of women literacy can significantly reduce infant mortality of countries. References Anderson, D., Sweeney, D., Williams, T., Camm, J. & Cochran, J. (2013). Statistics for Business & Economics. Connecticut: Cengage Learning. Andes, N. 1989. Socioeconomic, Medical Care, and Public Health Contexts Affecting Infant Mortality: A Study of Community-Level Differentials in Peru. Journal of Health and Social Behavior, 30, 386-397. Arik, H. & Arik, M. (2009). Is it economic growth or socioeconomic development? a cross- sectional analysis of the determinants of infant mortality. The Journal of Developing Areas, 42(2), 31-55. Caldwell, J.C. (1979). Education as a factor in mortality decline: An examination of Nigerian data. Population Studies, 33, 395–413. Firebaugh, G. & Beck, F. D. (1994). Does economic growth benefit the masses? Growth, dependence, and welfare in the third world. American Sociological Review, 631-653. Flegg, A. T. (1982). Inequality of income, illiteracy and medical care as determinants of infant mortality in underdeveloped countries. Population studies, 36(3), 441-458. Frey, R. S. & Field, C. (2000). The determinants of infant mortality in the less developed countries: a cross-national test of five theories. Social Indicators Research, 52(3), 215-234. Jeuland, M. A., Fuente, D. E., Ozdemir, S., Allaire, M. C., & Whittington, D. (2013). The long-term dynamics of mortality benefits from improved water and sanitation in less developed countries. PloS one, 8(10), 17-45. Liu, K., Moon, M., Sulvetta, M. & Chawla, J. (1991). International infant mortality rankings: a look behind the numbers. Health care financing review, 13(4), 105-118. Shen, C. E. & Williamson, J. B. (2001). Accounting for cross-national differences in infant mortality decline (1965–1991) among less developed countries: effects of women’s status, economic dependency, and state strength. Social Indicators Research, 53, 257–288. Williamson, J. B. & Boehmer, U. (1997). Female life expectancy, gender stratification, health status, and level of economic development: A cross-national study of less developed countries. Social Science & Medicine, 45(2), 305-317. Wooldridge, J. (2012). Introductory econometrics: A modern approach. Connecticut: Cengage Learning. Appendix Figure 1: Model Summary Figure 2: ANOVA Table showing F value Figure 3: Coefficients Table Read More