2020
DOI: 10.3390/economies8040083
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Decomposing Inequality in Household Consumption Expenditure in Malaysia

Abstract: This study aims to examine the sources and determinants of consumption expenditure inequality in Malaysia as well as to quantify their proportional contributions to the total explained inequality using the Household Expenditure Survey (HES) data for the year 2014 collected from the Malaysian Department of Statistics (DOSM). The study applies Field’s regression-based decomposition method to the log-linear regression model of per capita monthly consumption expenditure. It is found that the model explains about 5… Show more

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Cited by 14 publications
(26 citation statements)
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References 33 publications
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“…Mean-while, the years of schooling have a negative and significant effect in determining the grain expenditure share. This is in line with (Kirk et al, 2018;Ayyash & Sek, 2020), which stated that the education of heads of households has a positive effect on animal-sourced food expenditure share (beef and pork). Consumers with higher levels of education will have better access to information than consumers with low levels of education.…”
Section: Resultssupporting
confidence: 86%
“…Mean-while, the years of schooling have a negative and significant effect in determining the grain expenditure share. This is in line with (Kirk et al, 2018;Ayyash & Sek, 2020), which stated that the education of heads of households has a positive effect on animal-sourced food expenditure share (beef and pork). Consumers with higher levels of education will have better access to information than consumers with low levels of education.…”
Section: Resultssupporting
confidence: 86%
“…Approximately 82.4% had a monthly household income below RM 3,000 (USD 675), which is the median income for the bottom 40% of the income household group according to the Household Income and Basic Amenities Survey conducted in 2016 by the Department of Statistics. 19 …”
Section: Resultsmentioning
confidence: 99%
“…The study found age and household size to be negatively influencing expenditure and household income contributing to widen income inequality. In Malaysia, Ayyash and Sek (2020) found sex and age of household heads to be contributing negatively to inequality and had inequality decreasing effects, with negative impact on inequality. Elsewhere, in South Korea, Shin (2020) analysed data linking survey data with administrative data shows that wealth, employment status, family size, and education were significant contributors of income inequality.…”
Section: Results Of Step By Step Multiple Linear Regression Analysismentioning
confidence: 99%