Food Expenditure of the B40 Households: Developing a Decision-Support System for Food Price Determination in Malaysia (S/O14168)

• Main Authors: Jan, Soon Jan, Applanaidu, Shri Dewi, Abdul Adzis, Azira, Zainal Abidin, Norhaslinda
• Format: Monograph
• Language: English
• Published: UUM 2021
• Subjects: HN Social history and conditions. Social problems. Social reform
• Online Access: https://repo.uum.edu.my/id/eprint/31568/1/14168.pdf; https://repo.uum.edu.my/id/eprint/31568/

In Malaysia, certain income groups still remain vulnerable to economic shocks, particularly the B40 households. The increase in the average monthly income of B40 households is very much less than the increase in the Consumer Price Index (CPI) of food and non-alcoholic beverages. The B40 group spends almost 80% of income on routine essential expenses, with the highest proportion spent on food and non-alcoholic beverages. Hence, any spikes in food prices will impact this income group the most. Indeed, the following fundamental questions remain, what is the spending pattern of B40 households specifically on food items; does the rise in food prices affect severely the expenditure of B40 households. Therefore, this study aims to determine the overall pattern of food expenditure of the poor. The study is based on the Malaysian Household Expenditure Survey (HES) on household consumption expenditure focusing on food item expenditure by B40 households. Descriptive analysis indicates, average expenditure on food consumption by B40 households is RM563.13, while average monthly income is RM 2,540.81. While, for M40 and T20 average monthly food expenditure among households is estimated at RM766.59 and RM948.60 respectively. The average monthly income is estimated at RM 5,723.34 and RM14,159.87 for M40 and T20 respectively. The B40 income group spends 29% of their income on food expenditure. Fresh fish, fresh meat, fresh vegetables, rice, and bread are the top five food expenditures respectively. The regression analysis indicates that, apart from semi-skilled occupation, all other factors in the linear model significantly affects the food expenditure. Estimated coefficients from the econometric models are then used as inputs for the food price determination system, which will give a signal to policy-makers whether to increase or decrease particular food prices. Food prices will have serious repercussions on the food expenditure of B40 households, and therefore need to be regulated carefully. Consequently, the food price determination decision-support system we are proposing, is a part of the Industrial Revolution 4.0 component which utilises data for improved decision-making. Policy-makers can use this system to simulate changes in food prices to see how such changes affect B40 household expenditure on food items