Examining the Dynamics of Infant Mortality Rates: A Time Series Analysis

Abstract

This paper examines the relationship between infant mortality rates and different independent variables. The Augmented Dickey-Fuller test and unit root tests are common statistical techniques used to assess the stationarity of time series data. Stationarity is a key concept in time series analysis, as it implies that the statistical properties of a series, such as its mean and variance, do not change over time. The Augmented Dickey-Fuller test is a hypothesis test used to determine whether a time series is stationary or non-stationary. It evaluates whether the data exhibits a unit root, which suggests non-stationarity. If the test statistic is less than the critical value at a certain significance level, the null hypothesis of a unit root is rejected, indicating that the series is stationary. The study utilized Autoregressive Distributed Lag modeling to investigate the relationship between infant mortality rates and several key independent variables over the period 1975-2014. The results revealed significant negative associations between infant mortality rates and various factors. Higher levels of health expenditure were found to be strongly correlated with lower infant mortality rates, suggesting the importance of investing in healthcare infrastructure. Additionally, increased female enrollment in education was linked to reduced infant mortality rates, indicating the role of education in promoting maternal and child health. Lower unemployment rates were also associated with lower infant mortality rates, reflecting the positive impact of socioeconomic stability on infant health outcomes. Surprisingly, inflation showed a negative relationship with infant mortality rates, warranting further investigation into its potential effects on healthcare accessibility and quality. Furthermore, the presence of lady health visitors and rural health centers was found to significantly reduce infant mortality rates, highlighting the importance of accessible healthcare services in mitigating infant mortality. The findings underscore the multifaceted nature of factors influencing infant mortality rates and emphasize the importance of comprehensive healthcare, education, and socioeconomic policies in improving infant health outcomes over time.