Logistic regression analysis of household income and expenditure patterns in Ghana
No Thumbnail Available
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University of Cape Coast
Abstract
Description
x, 116p. : ill.
Studies into income, expenditure and standard of living of individuals and households are well documented in literature. Many of these studies cover different forms of poverty indicators and variables. The methods used in this analysis were mainly econometric models. The study is concerned with determining the indicators and variables that possibly influence income, expenditure and living standard of households. The objective here is to model the determinants of living standards or poverty status of households. To this end, secondary data were obtained from the Ghana Statistical Service. Some sections of GLSS 3 and GLSS 4 were used to develop the model. Nine variables were recorded and about 4500 respondents were used for each of the surveys, that is GLSS 3 and GLSS 4. Exploratory data analysis was employed in preliminary stages of the analysis. Logistic regression was used because this modeling technique is considered as the appropriate technique for modeling income and expenditure, since the outcome or response variable is dichotomous. It was found out that poverty was more prevalent and severe in the rural areas than the urban areas. In determining the poverty status of a household head, that is, whether he or she is poor or not poor; household size, locality, age of head, education and occupation played a significant role. The poverty status model developed was made up of the variables mentioned above. A household status could be determined by substituting the values of the variables in the model. The outcome (response) may be close to one or zero.
Studies into income, expenditure and standard of living of individuals and households are well documented in literature. Many of these studies cover different forms of poverty indicators and variables. The methods used in this analysis were mainly econometric models. The study is concerned with determining the indicators and variables that possibly influence income, expenditure and living standard of households. The objective here is to model the determinants of living standards or poverty status of households. To this end, secondary data were obtained from the Ghana Statistical Service. Some sections of GLSS 3 and GLSS 4 were used to develop the model. Nine variables were recorded and about 4500 respondents were used for each of the surveys, that is GLSS 3 and GLSS 4. Exploratory data analysis was employed in preliminary stages of the analysis. Logistic regression was used because this modeling technique is considered as the appropriate technique for modeling income and expenditure, since the outcome or response variable is dichotomous. It was found out that poverty was more prevalent and severe in the rural areas than the urban areas. In determining the poverty status of a household head, that is, whether he or she is poor or not poor; household size, locality, age of head, education and occupation played a significant role. The poverty status model developed was made up of the variables mentioned above. A household status could be determined by substituting the values of the variables in the model. The outcome (response) may be close to one or zero.
Keywords
Poverty, household surveys, cost and standard of living