Introduction
The state by state assessment of levels of poverty provides a rather realistic assessment of poverty rates as compared to a national outlook. A state by state approach enhances the review of poverty at a closer level to the individuals as compared to the national level. In the state of Ohio, the variations in poverty can be explained by a number of demographic variables or characteristics. Of these variables, the education level of the individuals, the number of children in the household and the household incomes are considered essential factors in studying this level of relationship. In this study, the above three variables will be examined on their impact on poverty levels in the Ohio state. The below research hypothesis that the research seeks to test:
Null hypothesis: Education levels, number of children in the households and the household incomes have no statistically significant relationship with the poverty levels of the populations.
Alternative hypothesis: Education levels, number of children in the households and the household incomes have a statistically significant relationship with the poverty levels of the populations.
Background or Literature
A review of studies examining poverty and the demographic factors take into consideration a variety of demographic factors. Under the Center for Global Development (n.d.), it is revealed that one of the factors influencing poverty are the fertility choices of the households. The research conducted by this institution indicates that fertility is essential as it determines the number of children that a household has further examining the amount of pressure exerted on the income generated by the household. In this study, the number of children representing a demographic factor in a household contributes to the level of affordability that the household has which in turn affects their ability to live under poverty. Center for Global Development (n.d.) further asserts this claim by indicating that those households with the least number of children have more disposable income compared to those that have more number of children. In addition to the above, Adams et al. (2014), it is affirmed that the number of children in a household contributes towards the level of poverty that the household has and the ability to meet their daily finance needs. The authors affirm that the higher the number of children the higher the level of dependence of the household. Factors such as health, feeding, and accommodation as part of the basic needs become challenging to meet with a higher number of dependents in the household as compared to lower numbers. Using regression analysis, Chaudhry, Malik, and Hassan (2009) affirms to the existence of a statistically significant relationship between poverty levels and the attributes of a household including the size which includes the number of children, dependency levels and the education codes of the households. In another study conducted by Siwar, Ahmed and Idris (2013) introduce the level of education of households as another factor contributing towards the levels of poverty experienced with the results indicating that households led by poorly educated people have higher poverty margins compared to those with educated leaders. The results indicate that a higher level of education enables the leader of the household to obtain meaningful employment that in turn influences their ability to live above the poverty line.
Methodology
In making the research possible, the researcher seeks to conduct a multiple regression including the dependent variable poverty line and the independent variables that include the level of education of the participants, the number of children in a single household and the household incomes. In examining the above variables, the regression model below is employed:
PR=a+βEL+βCHH+βHI+er
In the above regression model, the PR indicates the poverty rate of the households that is the dependent variable. The EL indicates the education levels of the individuals in the households while the CHH covers the number of children in the household that is used to determine the level of dependence. Also, the a in the regression equation indicates the intercept of the study while β indicates the slope of the line of best fit in the regression equation. HI, on the other hand, represents the independent variable household incomes that is an essential measure of their ability to meet the other independent variables. On the other hand, the er represents the level of error considered in the regression equation above. The above regression equation is used in conducting an assessment of the relationship between these variables with the expectation of a statistically significant relationship between the independent and dependent variables. One of the problems expected with the above variables is the correlation between the independent variable. A high correlation would affect their inclusion in a single regression equation.
Data Collected
The data used in this study covered the three main variables that included poverty levels of the populations of Ohio, the household income levels and the number of people in the household. The data for the study is obtained from various sources with the data covering from 2000 to 2017. The summary statistics below including the number of observations, the means and standard deviations presented below provide a summary of the study data. Also presented are data on the correlation that is contributive in studying the subject of study and assessing the relationship between the two independent variables and the single dependent variable.
Dependent Variable: Poverty Levels
For the study revealed, the coefficients were essential as they reflected the nature of relationship existing between the variables. The coefficients reveal a positive value for household incomes and poverty levels indicating that an increase in the former would lead to an increased ability to deal with poverty. On the other hand, a decline in the household incomes would yield to a higher poverty rate given the affected affordability of the households. On the contrary, the people in the household have an inverse relationship with the poverty levels. An increase in the number of people in a household would yield to a decline in income availability and hence lead to more poverty. A decrease in the number of people in a household, on the other hand, would provide more funds for expenditure.
Conclusion
The results presented in the study above indicates that the poverty rates are affected by the income levels, total incomes in a household which also indicates the number of children in a household. The study is a further affirmation that poverty is significantly influenced by the number of children in a household, the incomes levels and the level of education that also determines the ability to gain employment based on the literature review.
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References
Adams, M., Augustyns, N., Janssens, H., Vriesacker, B., & Van Hal, G. (2014). What socio-demographic factors influence poverty and financial health care access among disabled people in Flanders: a cross-sectional study. Archives of Public Health, 72(1). doi:10.1186/2049-3258-72-5
Center for Global Development. (n.d.). Demographics and Poverty. Retrieved from https://www.cgdev.org/page/demographics-and-poverty
Chaudhry, I. S., Malik, S., & Hassan, A. (2009). The Impact of Socioeconomic and Demographic Variables on Poverty: A Village Study. The Lahore Journal of Economics, 14(1), 39-68.
Siwar, C., Ahmed, F., & Idris, N. D. (2013). Relationship between Poverty and Socio-demographic Characteristics of Poor Households: A Case Study in Kelantan, Malaysia. Proceedings of the 2013 International Conference on Advances in Social Science, Humanities, and Management. doi:10.2991/asshm-13.2013.127