Testing the Permanent Income Hypothesis: Micro Evidence from the East Coast Region of Malaysia

Based on the Milton Freidman views, permanent income has an impact on the total household consumption. The life cycle hypothesis stated that individual consumption is based on the changes in income. Both views emphasised on the relation between income and consumption. Based on PIH studied by Freidman in 1957, people opt to make a less saving when the expected future income to rise and it indicates the negative relationship between those two factors (Ireland. P.N, 1995). Meanwhile Robert Hall (1978) derived the Permanent Income Hypothesis from mathematical theory using the joint behavior of consumption, income and saving. In other related study by David Hage (1994), these three variables (consumption, income and saving) have been adopted to forecast the US economy in 1994. The purpose of this study is to identify the impact of income on household consumption using PIH. A total of 645 household samples have been collected from the East Coast region of Malaysia. The estimation model utilized the cross-sectional regression with household income as a proxy to test the Permanent Income Hypothesis. The basic regression model take into account the basic variables for Permanent Income Hypothesis; income, saving and loan and socio-economic and demographic factors represented by age, educational level, job sector and household member. There were several important results based on this study; i) as household income increases by RM1.00, consumption rises by RM0.07 ii) as household saving increases by RM 1.00, household consumption goes up by RM0.45 and iii) as household loan increases by RM1.00, the household consumption increases by RM0.94. Apart from these results, there were also interesting findings revealed on the socio-economic and demographic factors on the household consumption patterns. From the regression estimation, the results indicated a positive significant relationship between household consumption as dependent variable with household income, loan, saving, education level, type of employees and family size.