An Econometric Analysis of Income, Education and Residential Status on Family Education Expenditures
DOI:
https://doi.org/10.59075/ijss.v3i3.1919Keywords:
Education expenditure, PSLM, OLS Method, Linear regression, family head, residential status of the household, income level.Abstract
This study assesses family spending on higher education in Pakistan. It researches the components and variables completing the families spending on schooling utilizing information from PSLM data 2018-19. The results derived from estimation depict that change in the level of degrees, income and change in residency concerning across country sets the expenses of family on higher education. Additionally. This analysis considers residency status of the household that too incorporates the family spending on education. This study strictly empathizes residency into account and drawing statistical inferences. Such consequences drawn definitely help and support in policy formation and recommendations. This analysis has definitely established right direction to promote higher education in the country. It has observed all the responsible factors that how family heads react to promote education. Residential status of the households have shared its contribution that how this affects the behavior of the households when they live in the different nature of accommodations with respect to their expenses. It has examined this effect through statistical data. However, this exploration ends that all factor have positive influence in policy recommendations for education. Further, all revelations can have inferential scope of issues concerning educational implications in Pakistan. These all factors have specific role in the determination of the allocation of budget on education from government side. The OLS (ordinary Least Square) Method and Regression analysis technique used to execute the regression. This method and technique signifies to situation when a model has dependent variable as quantitative. Estimates and results will implement the policy and provide a solution for all of the issues that the variables have explained.
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