Abstract
Income and expenditure issues in Malaysia had been recently discussed by many researchers as these are the basis of every sustainable economy. Malaysians should understand their spending behaviour based on their revenue. The study is conducted to demonstrate the relationship between household income and expenditure as well as demographic characteristics in northern region, central region, southern region and east coast of Peninsular Malaysia by using appropriate statistical techniques. The dataset being employed was extracted from Household Expenditure Survey (HES) 2019 by the Department of Statistics Malaysia (DOSM). The study is focused on the households who lived in Kuala Lumpur, Selangor, Johor, Penang and Kelantan to represent each region in Peninsular Malaysia. The data analysis was conducted using Chi-square test, bivariate analysis, simple linear regression and multiple linear regression. The results showed that household expenditure is directly proportional to household income, and household revenue was significantly influenced by all demographic variables while household spending was affected by particular characteristics, such as gender, ethnicity, educational level and activity status. Kelantan households revealed the lowest average household income whereas Kuala Lumpur families possessed the highest household revenue. The findings of household income and expenditure distribution based on activity status and regions can contribute to all Malaysians especially fresh graduates, individuals who are going to settle down, NGOs and retirees. Future research can be conducted by utilising comprehensive data to study the distribution of household revenue and spending at the district areas in each state, along with data visualisation techniques.
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References
The Guardian, Household income crucial in children's life prospects, says LSE report. The Guardian. (2017). Retrieved from https://www.theguardian.com/inequality/2017/jul/12/household-income-crucial-role-children-life-prospects-lse-report?CMP=share_btn_tw
A. Ridzuan, M. Razak, Z. Ibrahim, A. Noor, E. Ahmed, Household consumption, domestic investment, government expenditure and economic growth: new evidence from Malaysia. J. Sci. Res. Rep. 3(17), 2373–2381 (2014)
R. Cárdenas-Retamal, J. Dresdner-Cid, A. Ceballos-Concha, Impact assessment of salmon farming on income distribution in remote coastal areas: the Chilean case. Food Policy 101, 102078 (2021)
C. GradÃn, Race and income distribution: evidence from the USA, Brazil and South Africa. Rev. Dev. Econ. 18(1), 73–92 (2014)
N. Jumadi, A.A. Bujang, H.A. Zarin, The relationship between demographic factors and housing affordability. Malays. J. Real Estate 5(1), 49–58 (2010)
H. Van Vu, The impact of education on household income in rural Vietnam. Int. J. Financ. Stud. 8(1) (2020)
S.A.A. Saadv, A. Adam, The relationship between household income and educational level. (south Darfur rural areas-Sudan) statistical study. Int. J. Adv. Stat. Probab. 4(1), 27 (2016)
F. Nusrat, Impact of household and demographic characteristics on poverty in Bangladesh: a logistic regression analysis. In: 2015 Awards for Excellence in Student Research and Creative Activity (2015)
B.N. Lazarus, A study of household income determinants and income inequality in the Tominian and Koutiala zones of Mali (2013)
T.Q. Tuyen, The impact of farmland loss on income distribution of households in Hanoi’s peri-urban areas Vietnam. Hitotsubashi J. Econ. 55(2), 189–206 (2014)
H.G.P. Jansen, J. Pender, A. Damon, W. Wielemaker, R. Schipper, Policies for sustainable development in the hillside areas of Honduras: a quantitative livelihoods approach. Agric. Econ. 34(2), 141–153 (2006)
S. Biwei, H. Almas, Analysis of the determinants of income and income gap between Urban and Rural China. China Econ. Policy Rev. 02(01), 1350002 (2013)
A. Nasir, N.H. Nik Mustapha, N.F. Kamil, Analysis of income and expenditure of households in the east coast of peninsular Malaysia. J. Glob. Bus. Econ. 2(1), 59–72 (2011)
NTA, Lower-income countries and the demographic dividend. NTA Bull. 5, 1–8 (2012)
T.Q. Tuyen, Socio-economic determinants of household income among ethnic minorities in the North-West Mountains Vietnam. Croatian Econ. Surv. 17(1), 139–159 (2015)
F. Shamim, E. Ahmad, Understanding household consumption patterns in Pakistan. J. Retail. Consum. Serv. 14(2), 150–164 (2007)
M. Ayyash, S.K. Sek, Decomposing inequality in household consumption expenditure in Malaysia. Economies 8(4), (2020)
G. Thangiah, M.A. Said, H.A. Majid, D. Reidpath, T.T. Su, Income inequality in quality of life among rural communities in Malaysia: a case for immediate policy consideration. Int. J. Environ. Res. Public Health 17(23), 1–19 (2020)
L.D. Schroeder, D.L. Sjoquist, P.E. Stephan, Linear regression. In: Understanding regression analysis: an introductory guide, pp. 1–20. SAGE Publications Inc (2017)
D. Taluker, Assessing determinants of income of rural households in Bangladesh: a regression analysis. J. Appl. Econ. Bus. Res. 4(2), 80–106 (2014)
A. Strothmann, A. Marsh, S. Brown, Impact of household income on poverty levels
W. Lens, M. Lacante, M. Vansteenkiste, D. Herrera, Study persistence and academic achievement as a function of the type of competing tendencies. Eur. J. Psychol. Educ. 20(3), 275–287 (2005)
J. Frost, Choosing the correct type of regression analysis. Statistics By Jim (2017)
J. Frost, Ordinary least squares. Statistics By Jim (2020)
R. Bevans, An introduction to simple linear regression. Scribbr (2020)
W. Kenton, Multiple linear regression (MLR) definition. Investopedia (2021)
M.N.B.M. Arshad, Return to education by ethnicity: a case of Malaysia. Int. J. Econ. Manage. 10(1), 141–154 (2016)
P. Cuadrado, O. Fulmore, E. Phillips, The influence of education levels on income inequality (2019)
Q. Talley, T. Wang, G. Zaski, Effect of education on wage earning (2018)
N.F.N. Najdi, N.F. Khairul Adlee, A.A. Adnan, N.I. Mustafa Khalid, I. Suzilah, Exploratory data analysis on household expenditure survey 1998 and 2014. J. Hum. Capital Dev. (JHCD) 12(1), 25–48 (2019)
N. Valenzuela-Levi, The rich and mobility: a new look into the impacts of income inequality on household transport expenditures. Transp. Policy 100, 161–171 (2021)
H.L.S. Heng, A.T.K. Guan, Examining Malaysian household expenditure patterns on food-away-from-home. Asian J. Agricult. Dev., pp. 11–24 (2007)
A. Fatima, Z. Ahmad, Estimation of household expenditures on the basis of household characteristics by gender. Pak. J. Soc. Issues 4, 1–15 (2013)
G. Yan, Y. Peng, Y. Hao, M. Irfan, H. Wu, Household head’s educational level and household education expenditure in China: the mediating effect of social class identification. Int. J. Educ. Dev. 83, 102400 (2021)
A.A. Molla, C. Chi, A.L.N. Mondaca, Predictors of high out-of-pocket healthcare expenditure: an analysis using Bangladesh household income and expenditure survey, 2010. BMC Health Serv. Res. 17(1), 1–8 (2017)
Pew research center: household expenditures and income. In: The Pew Charitable Trusts (2016)
Acknowledgements
The research work is supported by Ministry of Higher Education, Malaysia. Fundamental Research Grant Scheme (FRGS) grant (Vot K297), reference number FRGS/1/2020/STG06/UTHM/02/4.
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May, T.K., Saharan, S., Rusiman, M.S. (2023). Analysis of Income and Expenditure of Households in Peninsular Malaysia. In: Mustapha, A., Ibrahim, N., Basri, H., Rusiman, M.S., Zuhaib Haider Rizvi, S. (eds) Proceedings of the 8th International Conference on the Applications of Science and Mathematics. EduTA 2022. Springer Proceedings in Physics, vol 294. Springer, Singapore. https://doi.org/10.1007/978-981-99-2850-7_17
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