AN EMPIRICAL ANALYSIS OF ENGEL CURVE ON ENERGY · PDF fileThe study was focused in forming an...

Proceedings of the Australian Academy of Business and Social Sciences Conference 2014

(in partnership with The Journal of Developing Areas)

ISBN 978-0-9925622-0-5

AN EMPIRICAL ANALYSIS OF ENGEL CURVE ON ENERGY FOR HOUSEHOLDS

IN SABAH AND SARAWAK BASED ON LOCATION AND INCOME GROUP.

Vivin Vincent Chandran

Caroline Geetha

Kwang Jing Yii

Universiti Malaysia Sabah, Malaysia

Amran Ahmed

Universiti Malaysia Perlis, Malaysia

ABSTRACT

The study was focused in forming an empirical model of Engel curve on energy for households in Sabah and Sarawak. Open-

ended questionnaire was used as an instrument of study involving 1,002 respondents in Sabah and Sarawak. The dependent

variable was budget share of energy expenditure meanwhile the independent variables were total household expenditure, age,

household size, educational level, gender and regional variables. All the independent variables were converted to logarithm form

except for gender and all regional variables as the dummy variables. The Ordinary Least Square estimation was carried out on the

cross sectional data. The coefficients were used to estimate the Engel curve expenditure elasticities. The findings revealed that

total household expenditure (income) and household size were the important determinant in explaining the energy expenditure.

Meanwhile the estimation of Engel curve expenditure elasticities showed that energy was a necessity good for all income groups

in both urban and rural areas. Low income group was found to be more sensitive on energy expenditure to the changes in

household income.

JEL Classifications: C13, D12, Q49, R22.

Keywords: Engel Curve, Energy, Expenditure Elasticity, Households, Location, Income Group.

Corresponding Author’s Email Address: [email protected], [email protected], [email protected],

[email protected].

INTRODUCTION

Malaysia is a country that has a total area of 329,847km2 with an estimated population of 29 million in 2012 (CIA,

2011). Malaysia is rich with natural resources in areas like minerals, agriculture and forestry. In the mineral area, tin

used to be the main contributor to Malaysia’s economy in 1980s. After the collapse of tin market, petroleum and

natural gas replaced tin as the most important pillar for Malaysia’s economy. However, by tracking on the current

production rates, the government estimates that the country will be able to produce oil for another 18 years and

natural gas up to 35 years only (Chua and Oh, 2010). Unfortunately, this is due to the oil resources depleting around

2030 if there is no new oil field found and eventually affect the energy sectors such as industrial, transport and

residential and commercial.

In Malaysia, energy was consumed by industrial sector, transport sector, residential and commercial sector,

non-energy sector, and agriculture and forestry sector. According to Ninth Malaysia Plan, the largest energy

consumer in Malaysia was the transport sector which occupied 41.1 percent of the total energy demand in 2010. This

was followed by industrial sector with 38.8 percent. Besides, residential and commercial sector appeared as the third

largest sector for energy demand which was amounted to 12.8 percent. For non-energy together with agriculture and

forestry were only amounted to 6.5 percent and 0.8 percent of total energy demand.

However, this study concentrated towards the residential sector because of various reasons. Firstly, based on

the classical energy ladder model hypothesis and the multiple fuel model hypothesis, changes in consumer behavior

towards the consumption of energy can take place due to changes in household income. This enables the consumers

to switch to different sources of energy and the effect of income can be easily measured. Secondly, the energy

demand on the residential users is mainly influenced by its welfare factors. The welfare factors can be measured

based on age, gender and education level of the head of household, household size, income status and location (urban

and rural). Thirdly, the study concentrates on residents because it is in line with the aim of the government to make

Malaysia a high income nation. Therefore, measures need to be taken to increase the purchasing power of consumers

especially the residents because they are the main contributors of the GDP reflected by the component of consumer

expenditure used in calculating GDP with expenditure approach.

mailto:[email protected]






ISBN 978-0-9925622-0-5

On the other hand, since Malaysia consists of a nation with two major geographical locations, Peninsular

Malaysia and East Malaysia., this study focused only on East Malaysia which consists of Sabah and Sarawak. Sabah

and Sarawak are located in the island of Borneo. Peninsular Malaysia is different from Sabah and Sarawak not only

in terms of its geographical location but also in terms of its economic activities, affordability (purchasing power),

demographic structure and infrastructure.

No doubt, energy expenditure aimed to provide positive impact to the economy but many researchers found

that expenditure on energy as one of the principal cause of unsustainable development in Malaysia. Malaysian

government had a great deal of leeway in giving subsidy for the consumption of energy. However, Malaysia still

experienced difficulties in balancing its budget due to subsidy given for energy expenditure. The budget deficit was

mostly managed from substantial oil revenue. But petroleum was a depleting resource and was highly volatile.

Besides, the extensive subsidies system incurred excess consumption and shortages. Since the energy consumption

was closely related to subsidy, a discipline fiscal management in controlling energy expenditure was essential

towards deciding the amount of energy expenditure made by household. Therefore, the consumers’ behavior need to

be accessed through their expenditure. This can be created by forming an empirical model of the Engel curve for

energy expenditure.

In Malaysia, researchers like Tey et al. (2008a, 2008b, 2009) used Engel curve to investigate the demand

for food like rice, meat and vegetable but yet to be done for energy demand. Therefore, this study examined the

energy expenditure using Engle curve. The objectives of this study were specified as follow:

i. To identify the relationship between budget share of energy expenditure with total household

expenditure (income) and demographic variables in Sabah and Sarawak based on location and income

group.

ii. To estimate the expenditure elasticity of energy in Sabah and Sarawak based on location and income

group.

LITERATURE REVIEW

Gundimeda and Kohlin (2008) used Engel curve to form a linear relationship between the budget share of energy and

the logarithm of total expenditure at the first stage of the study. Demographic variables were added in the model

since the parameters were not constant across all households. Statistical Analysis Software (SAS) was used to

estimate the model. The cross sectional data that consists of 10,000 samples from National Sample Survey

Organisation (NSSO) were used. The findings claimed that energy consumption was not only influenced by the

growth of population and income, but also other factors such as geographical area, forest cover, and occupation.

From the coefficient of expenditure with the negative sign indicated that the domestic energy was a necessity good

where the share of energy expenditure decreased when income increased. It was only insignificant among low

income group in urban area. Besides, household size was also found to influence the energy demand with positive

relation. The regional dummy variables were found to be significant except for high income group in urban area. The

Engel expenditure elasticities for energy among all income groups were estimated between 0 to 1 which supported

that energy was necessary type.

Besides, Chambwera and Folmer (2007) analyzed urban energy demand particularly firewood in energy

mix context among 500 households in Harare in 2003. At the first stage of the study, an Engel function that

represented the share of energy expenditure in total household expenditure in logarithm form was estimated. The

function was extended to include other household characteristics such as household size, number of rooms used by

household, assets, education level of household head and occupancy. The findings revealed that the share of energy

decreased when total expenditure increased. This indicated that energy was a necessity good for both electrified and

non-electrified households. The coefficients for both groups were statistically significant but the electrified

households were found to be more sensitive to changes in income. This was due to the basic energy needs for non-

electrified households may hardly to be identified. Besides, household size had a positive impact on the energy

consumption for both groups but only electrified households was found to be significant. Meanwhile the educational

level was found to be not significant for both households which indicated that psychogenic needs did not exist at the

first stage of budgeting process.

Olivia and Gibson (2006) adapted 1999 SUSENAS survey on 28,964 households in Java, Indonesia to

examine their monthly expenditure for around 300 different products. The quantity purchased of food, fuels and

electricity were requested in order to obtain the unit values where the actual market prices was not being collected.

Based on Deaton (1990), the unit values helped to correct biases and acquire the price responses more precisely than



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the actual market prices. The study used the cluster sampling which select sixteen households within districts and

regions. The findings in the first stage estimation indicated that kerosene and lubricant oil occupied 47 percent and

27 percent in budget shares which were the highest and lowest percentage respectively. Lubricant oil, LPG and

gasoline had the high expenditure elasticity of quantity which account to 2.80, 2.74 and 2.69 respectively. For the

unit value equation, only lubricant oil significantly responded to the household expenditures which the quality

elasticity was 0.07.

In addition, Filippini and Pachauri (2004) discussed the price elasticities and income elasticities of

electricity demand in urban India households. The study used the disaggregated level survey data from around

30,000 households. The model established by the electricity demand was a function of total household expenditure,

monetary expenditure on electricity and physical quantity of electricity consumed, average price of electricity, and

geographic and socio-economic variables. Due to the different weather in India, monthly data was used to estimate

the three different seasons which were monsoon, summer and winter. The findings revealed that the estimates of

income, own and cross price elasticities of electricity demand in urban India was fairly stable over the three seasons.

The income elasticities of electricity demand was found to be elastic while the price elasticities was inelastic. The

electricity demand during the summer months was more price inelastic than others seasons of the year due to the

higher temperature and the usage of air conditioners increased. The model revealed that income was the most

important economic variable.

Reddy (1995) examined the relationship between energy consumption with household income, household

size and energy prices in Bangalore, India by using multiple regression models. The total of 1000 households’

sample was used in the survey. The findings indicated that income was found to be significant in influencing the

energy consumption. When household income increased, energy consumption increased as well. The own price

elasticities of energy was found to have the expected negative signs and significant at the 5 percent level. However,

household size was found to have positive relationship with energy consumptions. This did not support most studies

where household size had a negative impact on per capita fuel consumption especially for modern fuels. This was

due to the large households who used energy more efficiently compared to the smaller households.

Furthermore, Hughes (1985) used a cross sectional survey to examine the relationship between energy

consumption and income on urban household in Nairobi, Kenya. The study explained the energy consumption

patterns in the Nairobi household sector. The survey consists of four types of data which are social and basic

necessities, household income, fuel consumption, price and end use, and appliance ownership and usage. The single

regression model examined the relationship between energy consumption as dependent variables and income as

independent variables. Meanwhile the multiple regression model was established by the logarithms of energy

consumption as dependent variable while the independent variables were logarithms of household income, household

size, energy prices and number of energy appliances. The findings indicated that energy consumption had a positive

relation with income and household size. Meanwhile price was not used as a determinant of energy consumption in

the study. It was also seen that energy consumption was highly consumed by high income group compared to low

income group.

METHODOLOGY

The research instrument used was a questionnaire with open ended questions. The questionnaire enquires the

demographic information of the respondents. This includes gender, level of education, household size, household

income and the location (rural or urban) to determine the welfare effect or consequences of the subsidy given to the

residents in Sabah and Sarawak. Then, it looks into the monthly expenditure of the household for energy (petrol,

diesel, electricity, LPG and kerosene) and non-energy use (medical, education, loan installment, food, utility,

entertainment, investment, clothing and public transport).

In this study, the two-stage cluster sampling method was used to choose the respondents. The state of Sabah

was divided into 5 clusters which represented by Kota Kinabalu, Tawau, Sandakan, Kudat and Beufort. Meanwhile

Sarawak was represented by Kuching, Sibu, Sarikei, Mukah and Miri. The respondents were further distinguished

into urban and rural areas. Then, the respondents were also categorized into high, middle and low income groups

respectively based on total monthly household income. Referring to the formula developed by Cochran (1963), the

total sample size of 1,002 households were chosen from Sabah and Sarawak. A structured face to face interview was

done individually which completed within 10 to 15 minutes per session.

Model Formation of Engel Curve



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Williams (1977) defined that Engel curves are the diagrammatic representation of how expenditure on a commodity

(or quantity consumed) varies with income or total expenditure. Total expenditure is used as a better proxy than

income as a measurement of households’ resources when estimating Engel curves. It is also found to be more stable

than income in interpreting as encompassing aspects of permanent income. Besides, the estimates of income in

household budget studies often suffer significant measurement bias because households don not reveal their actual

income earned. The dependent variable in an Engel curve can be expressed in either quantity or expenditure terms.

However, the income elasticity of demand for a commodity may itself vary with income where Engel curve will

exhibit different geometric properties at different income levels.

The preferred shape of Engel curves was influenced by the formal introduction of income into demand

theory by Hicks and Allen. Allen and Bowley (1935) assumed that marginal utilities were linear in commodities to

derive and estimate linear Engel curves (constant marginal propensities to consume) from British household

expenditure surveys. Meanwhile linear curves may be valid over some income ranges, they have the undesirable

property that all income elasticities converge to unity as income increases. Prais and Houthakker (1955) used a range

of functional forms in order to find the best fit of the model including the double logarithmic form where the

coefficient on income provides a direct measure of the income elasticity of demand.

However, using broad commodity classes in the study would exhaust total expenditure. This requires Engel

curve estimates to satisfy a number of global properties such as predicted budget shares lying between zero and one,

and summing to one (adding-up property). The double logarithmic form does not satisfy the adding-up property

unless all income elasticities are unity. The alternative to solve this problem was using semi-logarithmic equation

where budget share as the dependent variable (Working, 1943).

Therefore, the linear relationship in Engel curve in this study is established between the budget share of

energy expenditure ( ) and the logarithm of total household expenditure ( ).

(1)

where = total energy expenditure / total household expenditure.

Since the preference parameters are unlikely to be constant across all households, demographic variables are

allowed in the model. Thus, the following Engel form is estimated as

∑ (2)

where ∑ , and is the demographic variables like the age, educational level and gender of

household head, household size and regional dummy variables. The parameters , , and are the

characteristics of the household preference and estimated by weighted least squares. Finally, the completed Engel

equation for each income group in both urban and rural areas for Sabah is formed as

(3)

For Sarawak, it is established as

(4)

where is age of household head, is household size, is educational level in terms of schooling years of

household head, is dummy variable where male equal to 1 and otherwise zero, the regional dummy

variable refers to the selected region equal to 1 and otherwise zero and so on.

The expenditure elasticity of the energy demand, for an average household is calculated using formula

as below:-

(5)



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If is greater than 0, the commodity is a luxury since the budget share increases with income. Meanwhile

if is less than 0, the commodity is a necessity due to the budget share falls as income increases. When is found

to be negative sign and is less than in absolute value, the commodity is claimed as an inferior type. These

coefficients allow the impact of household characteristics to be in detail based on budget share.

FINDINGS

Engel Curve Estimation

Low Income Households in Rural Sabah

Table 1 showed the estimation of Engel curve for low income households in rural area in Sabah. The ratio of

monthly total energy expenditure over total household expenditure was regressed against the total household

expenditure, the age of the household head, size of household, level of education for the household head, gender of

the household head and regions in Sabah such as Tawau, Sandakan, Kudat and Beufort. Kota Kinabalu was excluded

because it was used as the reference category due to its large sample size compared to other regions. The

independent variables of total household expenditure (sig.=0.0118), age (sig.=0.0153), household size (sig.=0.0004)

and the region of Tawau (sig.=0.0000) were found to be significant at 5 percent significance level. All other variables

like educational level (sig.=0.8068) and gender (sig.=0.9452) of the household head as well as the regions like

Sandakan (sig.=0.1664), Kudat (sig.=0.5618) and Beufort (sig.=0.6944) were found to be insignificant at 5 percent

significance level. The value of R-squared showed that 39.62 percent changes in the budget share of total energy

expenditure over total household expenditure could be explained by total household expenditure and the

demographic variables such as the head of household’s age, educational level, gender, household size and regions.

Meanwhile around 60.38 percent changes in the budget share of energy expenditure were explained by other factors.

The negative sign of the coefficient for total household expenditure (-0.050248) indicated that energy was a

necessity commodity for low income group in rural area in Sabah. It also showed that one unit increase in total

household expenditure would reduce the budget share of energy expenditure by 5.03 percent. Besides, one unit

increase in the age of household head would increase the budget share of energy expenditure by 9 percent.

Meanwhile household size was found to influence the budget share of energy expenditure by 6.82 percent when the

number of the household members was increased by one unit. The only significant Tawau region dummy variable

had positive coefficient which indicated that low income households in rural area in Tawau experienced the growth

in budget share of energy expenditure compared to Kota Kinabalu which was used as the reference category.

TABLE 1: ESTIMATION OF ENGEL CURVE FOR LOW INCOME HOUSEHOLDS IN RURAL AREA IN

SABAH

Variable Coefficient Std. Error t-Statistic Prob.

C 0.088719 0.194133 0.457004 0.6486 LOG(TEXP) -0.050248 0.019623 -2.560654 0.0118

LOG(AGE) 0.090096 0.036559 2.464377 0.0153

LOG(HS) 0.068236 0.018545 3.679547 0.0004 LOG(EDU) -0.002984 0.012171 -0.245174 0.8068

GENDER 0.001232 0.017875 0.068906 0.9452

TWU 0.095494 0.018297 5.219143 0.0000 SDKN 0.024119 0.017312 1.393172 0.1664

KUDAT -0.017929 0.030813 -0.581878 0.5618

BEUF 0.012041 0.030572 0.393849 0.6944 R-squared 0.396195

Middle Income Households in Rural Sabah

Table 2 showed the estimation of Engel curve for middle income households in rural area in Sabah. The budget share

of monthly total energy expenditure was regressed against the total household expenditure, the age of the household

head, size of household, level of education for the household head, gender of the household head and regions in

Sabah such as Kota Kinabalu, Sandakan, Kudat and Beufort. Now, Tawau was excluded and used as the reference

category because it was the region with the largest sample size among the middle income group in rural area in

Sabah.

The independent variables, total household expenditure (sig.=0.0007) and household size (sig.=0.0034)

were found to be significant in explaining the changes in budget share of energy expenditure at 5 percent



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significance level. In contrast, other variables like age (sig.=0.3471), educational level (sig.=0.0764) and gender

(sig.=0.1039) of the household head as well as all the regions like Kota Kinabalu (sig.=0.2227), Sandakan

(sig.=0.4216), Kudat (sig.=0.0846) and Beufort (sig.=0.1029) were found to be insignificant at 5 percent significance

level. However, the household head’s educational level and region variable of Kudat were found to be significant at

10 percent significance level. This indicated that these two variables also influenced the budget share of energy

expenditure but with less significant effect compared to total household expenditure and household size. The value of

R-squared indicated that 29.54 percent changes in the budget share of energy expenditure could be explained by total

household expenditure, the head of household’s age, educational level, gender, household size and regions. The

remaining value of R-squared ascertained that another 70.46 percent changes in the budget share of energy

expenditure were explained by other factors.

Energy was also found to be a necessity commodity for middle income among rural households in Sabah

due to the negative sign of coefficient for total household expenditure (-0.062429). The coefficient also ascertained

that one unit increased in total household expenditure would reduce the budget share of energy expenditure by 6.24

percent. In addition, one unit increased in household size would significantly raise the budget share of energy

expenditure by 4.06 percent. On the other hand, educational level would increase the budget share of energy

expenditure by 2.85 percent when one unit increases in schooling year of household head was used. For the regional

dummy variable, Kudat was found to have less budget share of energy expenditure by 3.74 percent compared to

Tawau which was used as the reference category.

TABLE 2: ESTIMATION OF ENGEL CURVE FOR MIDDLE INCOME HOUSEHOLDS IN RURAL

AREA IN SABAH


C 0.402062 0.167272 2.403639 0.0185 LOG(TEXP) -0.062429 0.017783 -3.510566 0.0007

LOG(AGE) 0.032582 0.034449 0.945815 0.3471

LOG(HS) 0.040569 0.013450 3.016307 0.0034 LOG(EDU) 0.028529 0.015894 1.794898 0.0764

GENDER 0.023284 0.014158 1.644586 0.1039

KK -0.014756 0.012008 -1.228880 0.2227 SDKN -0.011269 0.013950 -0.807801 0.4216

KUDAT -0.037447 0.021443 -1.746295 0.0846

BEUF -0.041585 0.025206 -1.649813 0.1029

R-squared 0.295426

High Income Households in Rural Sabah

Table 3 showed the estimation of Engel curve for high income households in rural area in Sabah. The budget share of

monthly total energy expenditure was regressed against the total household expenditure, the age of the household


Sabah such as Kota Kinabalu, Sandakan, Kudat and Beufort. Tawau was excluded because it was used as the

reference category due to its large sample size. All the independent variables were found to be insignificant in

explaining the changes in budget share of energy expenditure at 5 percent significance level. The value of R-squared

indicated that 23.34 percent changes in the budget share of energy expenditure could be explained by total household

expenditure, the head of household’s age, educational level, gender, household size and regions. The remaining R-

squared showed that 76.66 percent changes in the budget share of energy expenditure were explained by other

factors. Energy was also a necessity commodity for high income households in rural area in Sabah due to the

negative sign of coefficient for total household expenditure.

TABLE 3: ESTIMATION OF ENGEL CURVE FOR HIGH INCOME HOUSEHOLDS IN RURAL AREA

IN SABAH


C 1.020528 0.685738 1.488218 0.1605

LOG(TEXP) -0.093811 0.077745 -1.206651 0.2491

LOG(AGE) -0.034833 0.102059 -0.341300 0.7383 LOG(HS) 0.072753 0.058156 1.250981 0.2330



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LOG(EDU) -0.028623 0.088415 -0.323731 0.7513

GENDER -0.000934 0.041448 -0.022528 0.9824 KK 0.015008 0.042712 0.351379 0.7309

SDKN -0.014161 0.041781 -0.338934 0.7401

KUDAT -0.014148 0.054564 -0.259298 0.7995 BEUF -0.012052 0.085854 -0.140377 0.8905

R-squared 0.233432

Low Income Households in Urban Sabah

Table 4 indicated the estimation of Engel curve for low income households in urban area in Sabah. The ratio of



the household head and regions in Sabah such as Tawau, Sandakan, Kudat and Beufort. Kota Kinabalu was excluded

because it was used as the reference category due to its large sample size.

The independent variables such as total household expenditure (sig.=0.0106) and age (sig.=0.0264) were

found to be significant in explaining the changes in the budget share of energy expenditure at 5 percent significance

level. All other variables like household size (sig.=0.3182), educational level (sig.=0.0658) and gender (sig.=0.5794)

of the household head as well as all the regions like Tawau (sig.=0.9688), Sandakan (sig.=0.9958), Kudat

(sig.=0.8418) and Beufort (sig.=0.6404) were found to be insignificant at 5 percent significance level. However,

educational level was found to be significant at 10 percent significance level which had less effect on the budget

share of energy expenditure. The value of R-squared ascertained that 21.33 percent changes in the budget share of

energy expenditure could be explained by total household expenditure, the head of household’s age, educational

level, gender, household size and regions. Another 78.67 percent changes in the energy expenditure budget share

were explained by other factors.

The negative sign of coefficient for total household expenditure (-0.049219) showed that energy was a

necessity commodity for low income among urban households in Sabah. The coefficient also explained that there

was 4.92 percent decreased in the budget share of energy expenditure when the total household expenditure was

increased by one unit. Besides, the age of household head was found to raise the budget share of energy expenditure

by 6.82 percent when one unit increased in it. Meanwhile one unit of schooling year increase in educational level

would slightly increase the energy expenditure budget share by 2.65 percent.

TABLE 4: ESTIMATION OF ENGEL CURVE FOR LOW INCOME HOUSEHOLDS IN URBAN AREA IN

SABAH


C 0.205144 0.139780 1.467613 0.1470

LOG(TEXP) -0.049219 0.018713 -2.630267 0.0106

LOG(AGE) 0.068272 0.030050 2.271973 0.0264 LOG(HS) 0.016104 0.016010 1.005870 0.3182

LOG(EDU) 0.026518 0.014176 1.870671 0.0658

GENDER 0.007832 0.014059 0.557057 0.5794 TWU 0.000740 0.018849 0.039259 0.9688

SDKN 9.50E-05 0.017916 0.005301 0.9958

KUDAT 0.005573 0.027817 0.200352 0.8418 BEUF -0.016840 0.035887 -0.469267 0.6404

R-squared 0.213339

Middle Income Households in Urban Sabah

Table 5 showed the estimation of Engel curve for middle income households in urban area in Sabah. The budget

share of monthly total energy expenditure was regressed against the total household expenditure, the age of the

household head, size of household, level of education for the household head, gender of the household head and

regions in Sabah such as Tawau, Sandakan, Kudat and Beufort. Kota Kinabalu was excluded and used as the

reference category because it was the region with the largest sample size.

The independent variables such as total household expenditure (sig.=0.0312) and household size

(sig.=0.0007) were found to be significant in explaining the changes in budget share of energy expenditure at 5



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percent significance level. On the contrary, other variables like age (sig.=0.7272), educational level (sig.=0.0606)

and gender (sig.=0.3061) of the household head as well as all the regions like Tawau (sig.=0.6217), Sandakan

(sig.=0.0536), Kudat (sig.=0.3849) and Beufort (sig.=0.6246) were found to be insignificant at 5 percent significance

level. Nevertheless, it could be seen that educational level and region variable of Sandakan influences the budget

share at 10 percent significance level. The value of R-squared indicated that 23.73 percent changes in the budget

share of energy expenditure could be explained by total household expenditure, the age, educational level and gender

of household head, household size and regions. The remaining of 76.27 percent changes in the budget share were

explained by other factors.

Energy was also found to be a necessity commodity for middle income among urban households in Sabah

due to the negative sign of coefficient for total household expenditure (-0.03411). The coefficient also explained that

one unit increase in total household expenditure would reduce the budget share of energy expenditure by 3.41

percent. Moreover, one unit increase in household size would significantly raise the budget share of energy

expenditure by 3.61 percent. On the other hand, educational level influenced the budget share by reducing it with

3.14 percent when there was one unit increase in schooling year. Meanwhile households in Sandakan were

significantly found to have less energy expenditure with 1.84 percent of budget share compared to Kota Kinabalu.

TABLE 5: ESTIMATION OF ENGEL CURVE FOR MIDDLE INCOME HOUSEHOLDS IN URBAN

AREA IN SABAH


C 0.429872 0.132521 3.243806 0.0015

LOG(TEXP) -0.034110 0.015638 -2.181212 0.0312

LOG(AGE) 0.007408 0.021188 0.349663 0.7272 LOG(HS) 0.036134 0.010346 3.492566 0.0007

LOG(EDU) -0.031449 0.016600 -1.894589 0.0606

GENDER -0.008676 0.008440 -1.027981 0.3061 TWU 0.004447 0.008987 0.494808 0.6217

SDKN -0.018370 0.009423 -1.949430 0.0536

KUDAT -0.012550 0.014390 -0.872162 0.3849 BEUF 0.011778 0.024009 0.490580 0.6246

R-squared 0.237287

High Income Households in Urban Sabah

Table 6 showed the estimation of Engel curve for high income among the urban households in Sabah. The ratio of



the household head and regions in Sabah such as Kota Kinabalu, Sandakan, Kudat and Beufort. Tawau was excluded

because it was used as the reference category due to its large sample size.

The only independent variable that influenced the budget share of energy expenditure significantly at 5

percent significance level was total household expenditure (sig.=0.0008). All other variables like the age

(sig.=0.3850), educational level (sig.=0.1365) and gender (sig.=0.4845) of the household head and household size

(sig.=0.1295) as well as all the regions variables like Kota Kinabalu (sig.=0.7256), Sandakan (sig.=0.5872), Kudat

(sig.=0.4854) and Beufort (sig.=0.1178) were found to be insignificant at 5 percent significance level. The value of

R-squared indicated that 34.35 percent changes in the budget share of total energy expenditure over total household

expenditure could be explained by total household expenditure and the demographic variables such as the age,

educational level and gender of household head, household size and regions. The remaining of 65.65 percent changes

in the energy expenditure budget share were explained by other factors.

The negative sign of coefficient for total household expenditure (-0.070223) indicated that energy was also

a necessity commodity for high income group in urban area in Sabah. The coefficient also explained that one unit

increased in total household expenditure would reduce the budget share of energy expenditure by 7.02 percent.

TABLE 6: ESTIMATION OF ENGEL CURVE FOR HIGH INCOME HOUSEHOLDS IN URBAN AREA

IN SABAH


C 0.699550 0.182654 3.829926 0.0003



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LOG(TEXP) -0.070223 0.019768 -3.552272 0.0008

LOG(AGE) 0.025493 0.029100 0.876061 0.3850 LOG(HS) 0.028318 0.018388 1.540091 0.1295

LOG(EDU) -0.026841 0.017754 -1.511795 0.1365

GENDER -0.009643 0.013698 -0.703959 0.4845 KK -0.005323 0.015083 -0.352894 0.7256

SDKN -0.007652 0.014011 -0.546180 0.5872

KUDAT -0.021103 0.030036 -0.702595 0.4854 BEUF -0.027504 0.017297 -1.590053 0.1178

R-squared 0.343526

Low Income Households in Rural Sarawak

Table 7 showed the estimation of Engel curve for low income households in rural area in Sarawak. The ratio of



the household head and regions in Sarawak such as Sibu, Sarikei, Mukah and Miri. Kuching was excluded and used

as the reference category due to it was the region with the largest sample size.

The independent variables of total household expenditure (sig.=0.0000) and the region of Mukah

(sig.=0.0017) were found to be significant in explaining the changes in the budget share of energy expenditure at 5

percent significance level. All other variables like age (sig.=0.4996), educational level (sig.=0.4069) and gender

(sig.=0.9761) of the household head and household size (sig.=0.0955) as well as the regions like Sibu (sig.=0.1108),

Sarikei (sig.=0.4163) and Miri (sig.=0.7266) were found to be insignificant at 5 percent significance level.

Nonetheless, household size was claimed to be significant at 10 percent significance level which might influence the

budget share with less effect compared to total household expenditure and region variable of Mukah. The value of R-

squared showed that 32.35 percent changes in the budget share of total energy expenditure over total household

expenditure could be explained by total household expenditure and the demographic variables such as the household

head’s age, educational level and gender, household size and regions. The remaining of 67.65 percent changes in the

budget share were explained by other factors.

Energy was claimed as a necessity commodity for low income group in rural area in Sarawak due to the

negative sign of coefficient for total household expenditure (-0.059325). The coefficient also ascertained that 5.93

percent decreased in the budget share of energy expenditure when one unit increased in total household expenditure.

Besides, one unit change in the region of Mukah would raise the budget share of energy expenditure by 11.36

percent. For household size, one unit increase in the number of household member would lead to 1.94 percent

increase in the budget share.

TABLE 7: ESTIMATION OF ENGEL CURVE FOR LOW INCOME HOUSEHOLDS IN RURAL AREA IN

SARAWAK


C 0.546191 0.095265 5.733392 0.0000

LOG(TEXP) -0.059325 0.010614 -5.589319 0.0000 LOG(AGE) 0.012655 0.018699 0.676745 0.4996

LOG(HS) 0.019386 0.011555 1.677677 0.0955

LOG(EDU) 0.005693 0.006844 0.831810 0.4069 GENDER 0.000275 0.009171 0.030002 0.9761

SIBU -0.017630 0.010990 -1.604219 0.1108

SARIKEI -0.015048 0.018460 -0.815158 0.4163 MUKAH 0.113635 0.035544 3.197029 0.0017

MIRI -0.003921 0.011195 -0.350276 0.7266

R-squared 0.323487

Middle Income Households in Rural Sarawak

Table 8 showed the estimation of Engel curve for middle income households in rural area in Sarawak. The budget





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regions in Sarawak such as Sibu, Sarikei, Mukah and Miri. Kuching was excluded because it was used as the

reference category due to its large sample size.

The independent variables such as total household expenditure (sig.=0.0058) and household size

(sig.=0.0008) were found to be significant in explaining the changes in budget share of energy expenditure at 5

percent significance level. In contrast, other variables like age (sig.=0.6226), educational level (sig.=0.6504) and

gender (sig.=0.2071) of the household head as well as all the regions like Sibu (sig.=0.3555), Sarikei (sig.=0.5714),

Mukah (sig.=0.9503) and Miri (sig.=0.0597) were found to be insignificant at 5 percent significance level. However,

it could be seen that the region of Miri was significant at 10 percent significance level. The value of R-squared

indicated that 28.89 percent changes in the budget share of energy expenditure could be explained by total household

expenditure, the age, educational level and gender of household head, household size and regions. Another 71.11

percent changes in the budget share were explained by other factors.

The negative sign of coefficient for total household expenditure (-0.063972) indicated that energy was a

necessity commodity for middle income among rural households in Sarawak. The coefficient also explained that one

unit increased in total household expenditure would reduce the budget share of energy expenditure by 6.40 percent.

In addition, one unit increase in household size would significantly raise the budget share of energy expenditure by

8.75 percent. For the regional dummy variable, middle income households in rural areas in Miri were found to

experience the reduction in budget share of energy expenditure compared to Kuching which was the reference

category.

TABLE 8: ESTIMATION OF ENGEL CURVE FOR MIDDLE INCOME HOUSEHOLDS IN RURAL

AREA IN SARAWAK


C 0.466235 0.194966 2.391364 0.0196

LOG(TEXP) -0.063972 0.022439 -2.850855 0.0058 LOG(AGE) 0.014241 0.028801 0.494447 0.6226

LOG(HS) 0.087517 0.024937 3.509562 0.0008

LOG(EDU) 0.006769 0.014868 0.455277 0.6504 GENDER 0.016231 0.012742 1.273884 0.2071

SIBU 0.016367 0.017591 0.930405 0.3555

SARIKEI -0.019080 0.033548 -0.568751 0.5714 MUKAH -0.001538 0.024581 -0.062569 0.9503

MIRI -0.029170 0.015228 -1.915523 0.0597

R-squared 0.288915

High Income Households in Rural Sarawak

Table 9 showed the estimation of Engel curve for high income households in rural area in Sarawak. The budget share

of monthly total energy expenditure was regressed against the total household expenditure, the age of the household


Sarawak such as Sibu and Miri. Sarikei and Mukah were not included due to zero sample size found in the study.

Meanwhile Kuching was also excluded because it was used as reference category due to its largest sample size.

The only independent variable that significantly influence the budget share of energy expenditure was

household size (sig.=0.0266). All other variables like total household expenditure (sig.=0.8867), the age

(sig.=0.1571), educational level (sig.=0.7884) and gender (sig.=0.2093) of household head as well as the regions like

Sibu (sig.=0.4176) and Miri (sig.=0.0761) were found to be insignificant at 5 percent significance level.

Nevertheless, it could be seen that the region of Miri was significant at 10 percent significance level. The value of R-

squared indicated that 87.68 percent changes in the budget share of energy expenditure could be explained by total

household expenditure, the household head’s age, educational level, gender, household size and regions. The

remaining of 12.32 percent changes in the budget share were explained by other factors.

Energy was also claimed as a necessity commodity for high income households in rural area in Sarawak due

to the sign of total household expenditure coefficient (-0.022989) was negative. On the other hand, the coefficient of

household size (0.098369) explained that one unit increase in household size would raise the budget share of energy

expenditure by 9.84 percent. Moreover, households in Miri were found to reduce the budget share of energy

expenditure by 6.21 percent compared to Kuching households.



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TABLE 9: ESTIMATION OF ENGEL CURVE FOR HIGH INCOME HOUSEHOLDS IN RURAL AREA

IN SARAWAK


C 0.649481 1.356456 0.478807 0.6523

LOG(TEXP) -0.022989 0.153349 -0.149912 0.8867

LOG(AGE) -0.124012 0.074550 -1.663458 0.1571 LOG(HS) 0.098369 0.031635 3.109504 0.0266

LOG(EDU) -0.013053 0.046096 -0.283172 0.7884

GENDER 0.066041 0.045842 1.440607 0.2093 SIBU -0.037343 0.042285 -0.883120 0.4176

MIRI -0.062129 0.027858 -2.230225 0.0761

R-squared 0.876754

Low Income Households in Urban Sarawak

Table 10 showed the estimation of Engel curve for low income among the urban households in Sarawak. The ratio of



the household head and regions in Sarawak such as Sibu, Sarikei, Mukah and Miri. Kuching was excluded and used

as the reference category due to it was the region with the largest sample size.

The independent variables like the household head’s gender (sig.=0.0404) and the region of Miri

(sig.=0.0005) were found to be significant in explaining the changes in the budget share of energy expenditure at 5

percent significance level. All other variables like total household expenditure (sig.=0.0760), age (sig.=4196) and

educational level (sig.=0.8468) of the household head and household size (sig.=0.6401) as well as all the included

regions like Sibu (sig.=0.3303), Sarikei (sig.=0.7964) and Mukah (sig.=0.0909) were found to be insignificant at 5

percent significance level. However, total household expenditure and region variable of Mukah were claimed to

significant at 10 percent significance level. The value of R-squared showed that 30.10 percent changes in the budget

share of total energy expenditure over total household expenditure could be explained by total household expenditure

and the demographic variables such as the household head’s age, educational level and gender, household size and

regions. Another 69.90 percent changes in the budget share were explained by other factors.

Energy was known as a necessity commodity for low income group in urban area in Sarawak due to the

negative sign of coefficient for total household expenditure (-0.030284). It also ascertained that there was 3.03

percent decrease in budget share when one unit increase in total household expenditure. The coefficient of gender

indicated that the male household head would raise the budget share of energy expenditure compared to female

household head. Besides, the low income households in urban Miri would have less budget share of energy

expenditure by 5.20 percent compared to Kuching which was the reference category. On the other hand, households

in Mukah would experience the increase in budget share by 8.77 percent compared to Kuching.

TABLE 10: ESTIMATION OF ENGEL CURVE FOR LOW INCOME HOUSEHOLDS IN URBAN AREA

IN SARAWAK


C 0.329020 0.138006 2.384100 0.0201 LOG(TEXP) -0.030284 0.016791 -1.803628 0.0760

LOG(AGE) 0.017182 0.021152 0.812302 0.4196

LOG(HS) 0.006074 0.012928 0.469841 0.6401 LOG(EDU) 0.002200 0.011336 0.194048 0.8468

GENDER 0.029219 0.013963 2.092572 0.0404

SIBU -0.030466 0.031060 -0.980876 0.3303

SARIKEI 0.009455 0.036488 0.259136 0.7964

MUKAH 0.087669 0.051074 1.716492 0.0909

MIRI -0.052046 0.014297 -3.640339 0.0005 R-squared 0.300954

Middle Income Households in Urban Sarawak



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Table 11 showed the estimation of Engel curve for middle income households in urban area in Sarawak. The budget



regions in Sarawak such as Sibu, Sarikei, Mukah and Miri. Kuching was excluded because it was used as the

reference category due to its large sample size.

The independent variables like the total household expenditure (sig.=0.0000), household size (sig.=0.0000)

and the region of Miri (sig.=0.0006) were found to be significant in explaining the changes in budget share of energy

expenditure at 5 percent significance level. On the contrary, other variables like age (sig.=0.4681), educational level

(sig.=0.7346) and gender (sig.=0.8178) of the household head as well as the regions like Sibu (sig.=0.6040), Sarikei

(sig.=0.5891) and Mukah (sig.=0.8222) were found to be insignificant at 5 percent significance level. The value of

R-squared indicated that 35.32 percent changes in the budget share of energy expenditure could be explained by total

household expenditure, the age, educational level and gender of household head, household size and regions.

Another 64.68 percent changes in the budget share were explained by other factors.

The negative sign of the coefficient for total household expenditure (-0.096374) indicated that energy was a

necessity commodity for middle income among urban households in Sarawak. The coefficient also explained that

one unit increased in total household expenditure would reduce the budget share of energy expenditure by 9.64

percent. Besides, one unit increased in household size would significantly raise the budget share of energy

expenditure by 5.41 percent. Moreover, the middle income households in urban Miri possessed the fall in the budget

share of energy expenditure with 4.25 percent compared to Kuching which was the reference category.

TABLE 11: ESTIMATION OF ENGEL CURVE FOR MIDDLE INCOME HOUSEHOLDS IN URBAN

AREA IN SARAWAK


C 0.816439 0.161263 5.062781 0.0000 LOG(TEXP) -0.096374 0.021086 -4.570525 0.0000

LOG(AGE) 0.016656 0.022885 0.727797 0.4681

LOG(HS) 0.054132 0.012209 4.433815 0.0000 LOG(EDU) -0.004767 0.014032 -0.339728 0.7346

GENDER -0.002111 0.009148 -0.230813 0.8178

SIBU -0.005629 0.010827 -0.519923 0.6040 SARIKEI -0.009893 0.018267 -0.541555 0.5891

MUKAH -0.004516 0.020049 -0.225233 0.8222

MIRI -0.042524 0.012152 -3.499343 0.0006

R-squared 0.353158

High Income Households in Urban Sarawak

Table 12 showed the estimation of Engel curve for high income households in urban area in Sarawak. The budget



regions in Sarawak such as Sibu, Sarikei and Miri. Kuching was excluded and used as the reference category due to

it was the region with the largest sample size. Meanwhile Mukah was also excluded due to zero sample size found in

the study.

All the independent variables were found to be insignificant in explaining the changes in the budget share of

energy expenditure at 5 percent significance level. However, the variable of age (sig.=0.0913) was found to be

significant at 10 percent significance level. The value of R-squared indicated that 27.28 percent changes in the

budget share of energy expenditure could be explained by total household expenditure, the household head’s age,

educational level, gender, household size and regions. The remaining of 72.72 percent in the budget share were

explained by other factors. Energy was claimed as a necessity commodity for high income households in urban area

in Sarawak due to the sign of coefficient for total household expenditure (-0.041519) was negative. Moreover, one

unit increase in the age of household head, there was 13.02 percent decrease in the budget share of energy

expenditure.

TABLE 12: ESTIMATION OF ENGEL CURVE FOR HIGH INCOME HOUSEHOLDS IN URBAN AREA

IN SARAWAK



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C 1.017325 0.521887 1.949320 0.0595 LOG(TEXP) -0.041519 0.055095 -0.753582 0.4563

LOG(AGE) -0.130209 0.074919 -1.738006 0.0913

LOG(HS) 0.077516 0.052410 1.479049 0.1483 LOG(EDU) -0.055288 0.045310 -1.220214 0.2308

GENDER 0.006435 0.028740 0.223904 0.8242

SIBU -0.004775 0.033671 -0.141817 0.8881 SARIKEI 0.050866 0.083806 0.606949 0.5479

MIRI -0.042543 0.028792 -1.477594 0.1487

R-squared 0.272773

Expenditure Elasticity

Table 13 showed the estimation of expenditure elasticity of Engel curve based on location and income group in

Sabah. It could be seen that all the value of expenditure elasticity for energy were in positive sign and less than one.

This indicated that energy was a necessity commodity for all income groups in both urban and rural area in Sabah. In

the urban area, middle income group possessed the highest expenditure elasticity which was amounted to 0.770. This

was followed by low income group with 0.724 and high income group with 0.536 in the estimation of expenditure

elasticity for energy. In contrast, the situation in rural area showed a difference where low income group occupied

the highest ranking of expenditure elasticity with 0.764. This was followed by middle income group with

expenditure elasticity of 0.624. High income group was still found to have lowest responsiveness of demand for

energy towards the changes in income with only 0.351 expenditure elasticity.

TABLE 13: EXPENDITURE ELASTICITY OF ENGEL CURVE BASED ON LOCATION AND INCOME

GROUP IN SABAH

Income Group

Sabah

Urban Rural

High 0.536 0.351

Middle 0.770 0.624

Low 0.724 0.764

Table 14 showed the estimation of expenditure elasticity of Engel curve based on location and income

group in Sarawak. Similar to Sabah, all the value of expenditure elasticity for energy were in positive sign and less

than one. This indicated that energy was a necessity commodity for all income groups in both urban and rural area in

Sarawak. In urban area, low income group was found to have the highest responsiveness of demand for energy

towards the changes in income. The expenditure elasticity was estimated as high as 0.840 for the urban low income

group. The expenditure elasticity of energy demand among high income group in urban Sarawak was estimated as

0.725 which was larger than middle income group with only 0.382. On the other hand, high income group in rural

area responded significantly on energy demand towards the changes in income compared to low and middle income

groups where the expenditure elasticity were estimated as 0.862, 0.730 and 0.661 respectively.

TABLE 14: EXPENDITURE ELASTICITY OF ENGEL CURVE BASED ON LOCATION AND INCOME

GROUP IN SARAWAK

Income Group

Sarawak

Urban Rural

High 0.725 0.862

Middle 0.382 0.661

Low 0.840 0.730

DISCUSSION AND CONCLUSION

From the estimation of Engel curve, it could be seen that the variable of total household expenditure was significant

in influencing the budget share of energy expenditure in both urban and rural areas in Sabah and Sarawak. It was

only applicable for low and middle income groups. This meant that income was a very important factor for

households to make decision in consuming energy. However, the energy expenditure among high income groups was



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not affected by their income except for urban households in Sabah. All the coefficients of total household

expenditure were in negative sign which indicated that energy was a necessity commodity to households in Sabah

and Sarawak. This was in line with the study conducted by Gundimeda and Kohlin (2008) and Chambwera and

Folmer (2007).

Another important factor in influencing the energy expenditure was household size. In Sabah, the variable

was found to be significant among middle income groups in both urban and rural areas as well as low income group

in rural area. All the income groups in rural area in Sarawak were influenced by household size in consuming energy

meanwhile it was only for middle income group in urban area. The respective positive sign for the coefficient of

household size indicated that the budget share of energy expenditure raised as the number of household member

increased. This was in line with the findings by Deaton and Muellbauer (1980) who claimed that the larger

households spent a larger budget share on necessities goods compared to smaller households for the same level of

total expenditure. Reddy (1995) argued that this might be due to inefficient consuming had occurred when energy

expenditure raised as household size increased. Meanwhile Chambwera and Folmer (2007) asserted that the

economies of scale found was inverted U-type pattern where initially positive impact on budget share with household

size but it turned to negative impact when the household size increased.

The variable of educational level of household head only influenced the energy expenditure among

households in Sabah but with less significant effect. This indicated that psychogenic needs existed in the budgeting

process. Low income group in urban area and middle income group in rural area comprise of positive relationship

which indicated that higher schooling years obtained by household head raised the energy expenditure. In contrast,

middle income group in urban Sabah possessed negative relationship between educational level and energy

expenditure. The findings were in contrast with the study by Chambwera and Folmer (2007) who found the

educational level to be insignificant in explaining the energy expenditure.

The age of household head was found to be positively influenced the budget share of energy expenditure

among low income group in both urban and rural areas in Sabah. However, the situation was different in Sarawak

where the households head’s age only affected the energy expenditure among high income group with negative and

smaller effect. Moreover, the variable of gender of household head only significantly influenced the energy

expenditure among low income group in urban area in Sarawak. It showed that the male household head led to the

increase in budget share of demand for energy compared to the female. This may due to female household head had

higher consciousness on saving.

As for regional dummy variable in Sabah, low income household in rural area in Tawau was found to have

higher budget share of energy expenditure compared to Kota Kinabalu. For middle income group in Sabah, the urban

household in Sandakan and rural household in Kudat were claimed to consume less energy compared to Kota

Kinabalu and Tawau respectively but with less significant effect. In Sarawak, it was found that Miri households

experienced reduction in budget share of energy demand compared to Kuching among low and middle income

groups. On the contrary, low income households in Mukah possessed higher energy expenditure compared to

Kuching in both urban and rural areas.

Finally, all the Engel expenditure elasticities for energy were estimated in the value between 0 to 1. This

supported that energy was a necessity good to all the income groups in both urban and rural areas in Sabah and

Sarawak. But low income group was found to be more sensitive on budget share of energy expenditure to the

changes in household income. The findings were in line with the study of Gundimeda and Kohlin (2008). However,

it was different to the study conducted by Olivia and Gibson (2006) and Filippini and Pachauri (2004) who estimated

the expenditure or income elasticities as greater than 1 that indicated that energy was luxury good.

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359-371.

Tey, Y.S., Fatimah, M.A., Mad Nasir, S., Zainalabidin, M. Alias, R., “Demand for Meat Quantity and

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Tey, Y.S., Mad Nasir, S., Zainalabidin, M., Amin, M. A., and Alias, R., “Demand Analyses of Rice in

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https://www.cia.gov/library/publications/the-world-factbook/goes/my.html

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