The effects of monthly family income distribution on negative social and economic changes in Baghdad Governorate During the period (2005-2024(

Abstract

The size of household income and the ways it is allocated across different uses have clear effects on various aspects of life, household income is an influential variable in the lives of family members, especially in the present time when life pressures have intensified, while social norms have weakened, this has contributed to the emergence of numerous negative social changes that have begun to impose themselves and increase the challenges  face families, such as rising divorce rates, youth reluctance to marry, student dropout from schools, and behavioral deviations that are continually increasing , the issue of household income size and its distribution is a common problem,  those with low incomes may face negative social changes, and those with financial abundance are also not immune from the negative effects of money. As is evident, a lack of money causes many negative social phenomena, while excessive wealth is also not free from such phenomena, as observed among many affluent families and societies,  The problem from which this research originates is tracking the most prominent effects of these phenomena in Baghdad Governorate, as it is the capital of Iraq and hosts many key political and economic centers, The research examines variables during a time period filled with events related to the methods of distributing public money, which had severe impacts on household income for the majority of citizens, leading to or contributing to the emergence of negative social and economic effects, From the findings of the research, it can be concluded that household income distribution and price levels were influential factors in the negative changes. However, the results of the statistical analysis were not highly supportive, as the independent variable (monthly household income) did not show a clear, significant effect. The analysis also indicated stability in the studied phenomena. Therefore, the research recommends including additional mediating variables to enhance the explanatory power of the statistical model, expanding the sample size to include broader areas and social categories, and using more complex analytical models such as regression or path analysis to better understand causal relationships in this field.