Relationship between B40 Household Income and Demographic Factors in Malaysia
Humaida Banu Samsudin1, Amirul Aqil Nadzrulizam2

1Humaida Banu Samsudin*, Actuarial Science Programme, Faculty of Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
2Amirul Aqil Nadzrulizam, Actuarial Science Programme, Faculty of Science and Technology, University Kebangsaan Malaysia,  Bangi, Selangor, Malaysia. 

Manuscript received on November 13, 2020. | Revised Manuscript received on November 22, 2020. | Manuscript published on December 10, 2021. | PP: 113-117 | Volume-10 Issue-2, December 2020 | Retrieval Number: 100.1/ijitee.B82861210220| DOI: 10.35940/ijitee.B8286.1210220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Income inequality has become a major economic growth problem faced by most countries in the world. The income gap that exists between the rich and the poor grows wider every year. The Malaysian government have set up multiple economic policies and provided various aids that focuses on improving the B40’s economic situation and reduce the income gap that exist amongst them. Data for this study are obtained from the Household Income Survey (HIS). This study makes the comparison on the range and average of income amongst the B40 household income of each state in Malaysia. This comparison analyses the income gap that exist amongst the local households. Income inequalities amongst B40 households are prominent in Selangor, which recorded a huge income gap amongst the households. Kelantan has the lowest maximum and average income value amongst B40 from all states. The demographic factors that have significant impacts on the distribution of income amongst the B40 population in Malaysia was analysed using regression models. Residential area, levels of academic studies and working status of the head of household are the factors that effects B40 populations in Malaysia. 
Keywords: B40 household, Demographic factors, Income, Multiple linear regressions.
Scope of the Article: Rock Mechanics and Mining Sciences