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Investigate The Changes Of Expenditure Pattern Economics Essay

This chapter presents the methodology employed to investigate the changes of expenditure pattern. This chapter consists of several sections. The first section focuses on the discussion of the framework of the study in 4.2. The pattern of energy consumption and household expenditure, the theory of input output, hybrid input output table, energy intensity and CO2 emission factor are discussed in sections 4.3 - 4.4, followed by the direct and indirect CO2 emission by household and structural change of the decomposition in section 4.5-4.6. The last section (4.7) presents the data used in this study in the form of terminal period from 1990 – 2005 and a discussion on Malaysia Input–Output Table.

4.2 Framework of the study

The framework of this study is presented in Figure 4.1. The diagram reflects the flow chart of the methodology. This diagram consist three divisions that is energy requirement, energy analysis and CO2 emission, and structural decomposition. In order to achieve objective one, the study starts with evaluation of the growth of energy consumption and expenditure by using the compounded annual growth rate (CAGR). Energy consumption have split up into two characterization i.e direct and indirect in term of household perspective.

Energy analysis

Input output analysis

Hybrid analysis

Impact to environment

Direct

Indirect

2. Energy analysis & CO2 emission

3. Structural decomposition analysis (SDA)

1. Energy requirements & expenditure

CO2 emission factor

Direct

(Simple energy emission model)

Indirect

(Integrated IO model)

Structural decomposition analysis (SDA)

Hybrid Input Output Table

(HIOT)

CO2

Emissions by category

Energy consumption and expenditure and export (CAGR)

Energy intensity

Input

Output

Figure 4.1: Framework of the study

The direct energy consumption by production sectors are considered as indirect energy consumption by household. Household does not only consume direct energy for electricity, natural gas and petroleum product, but also they consume indirect energy by purchasing goods and services.

Households sector is the main consumption factor in the economy. The main consumption sector is formed by the households. Households have many categories of expenditures in buying product such as food, transport, electrical appliances, etc and use services such as medical, education, hotel etc. Household expenditure survey is employ in this study to identify the list of household expenditure on consumer goods and services. The whole economy is based on this consumption of goods produced by production sector and services provided by service sector.

This study followed by the process of energy analysis which using the input output analysis and hybrid analysis in order to complete the objective 2. The result from this analysis is possible to answer for many questions in this study. This part will start with the introduction on input output and hybrid analysis in the next sub-topic, (4.3 to 4.4). By constructing Hybrid input output table (HIOT), which the combinations of monetary and physical units, it easy to identify the total energy inputs used by every sector. The total of energy inputs is very important element in order to estimate an energy intensity and CO2 emission factor as well as to estimate CO2 emission by household direct (electricity, natural gas and petroleum product) and indirect (sector, consumption and export).

The study use structural decomposition analysis (SDA) to decompose the changes in CO2 emission direct and indirect in order to answer objective 3. In this study, Structural Decomposition Analysis concentrates on CO2 emission from the production and consumption sector and exported countries. This is because beside responsible to domestic pollution, Malaysia also responsible for the global environment resulted from their consumption.

4.3 Pattern of energy consumption and expenditure

This study uses the simple statistic method; compounded average growth rate (CAGR) in order to analysis the pattern of energy consumption and household expenditure. The CAGR was used in this study because it is often used to describe the growth over the period of time of some element such as GDP growth, income growth and the pattern of energy consumption and expenditure. CAGR is widely used, particularly in growth industries or to compare the growth rate of two years.

The patterns of energy consumption have divided into two characterization; direct and indirect in term of household perspective. In Malaysia, energy consumption directly used by household is from coal, petroleum product and electricity. While indirect energy used by household come from production activities such as natural gas, crude oil, coal, petroleum product, electricity and etc. This study also observes the pattern of household expenditure. In line with this, household expenditure has divided into 19 groups based on MISC. the pattern or growth rate of expenditure were calculated by terminal year; 1982/83, 1994/95, 1998/99 and 2004/05.

4.4 Energy analysis and CO2 emission factor

The model applied is an extended input-output model based on Malaysian input output tables plus energy flow matrices or commonly known as Hybrid input output table (HIOT). These can be linked together due to the use of common classifications. This study has chosen the model of Munksgaard et al. (2000) because the model covers the energy production and consumption cycle, and is able to distinguish between direct and indirect emissions but for this study have extend to export without emphasize government and investment .

4.4.1 Input-output analysis

This study applies an input-output analysis in order to implement the objectives of the study. Input-output analysis is a means which fulfils this multi-sector approach. Input-output analysis is an empirical tool designed to analyse interdependencies of sectors in the economy (Miller and Blair, 1985). Thus, it is able to identify any particular and specific burdens or benefits related to different sectors. The input output analysis describes the flows of goods and services via an economy units for a given time period basically a year. The Figure 4.2 represents a simplified version of an input-output table, indicating the monetary flows of the Malaysian economy in the year 2000.

The rows of this table describes that the total output of an industry sector can either go to other sectors (i.e. to intermediate demand) or to final demand (e.g. to household consumption). Thus, we can see to what extent any particular sectors can sell their manufactured goods and services to other sectors and to the final demand while the columns describes which inputs a sector uses to produce its output. The columns refer to the production side, while the rows show the distribution of the manufactured goods and services. Input output model can derive from input output table by using some mathematical calculation. The schematic of input-output models is simply to produce goods for final demand (or consumption). Basically, the aim of basic input-output model is to measure how much additional output is needed for each sector in response to a unit increase in the final demand.

The structure of the input-output table has two main functions: firstly, as a descriptive framework which explains interrelationships between industries or between inputs and outputs, and secondly, as material which provides data for describing the effect of a change in an activity or sector of the economy. The structure of an input-output table comprises of four quadrants as shown in Figure 4.2.

Industry sectors

Sector A (Agriculture, Crude oil, petroleum or Services)

Final Demand

Total Output

Sector A (Agriculture, Crude oil, petroleum or Services)

Quadrant I

(A)

Quadrant II

(Y)

X

Primary Inputs

Quadrant III

(W)

Quadrant IV

(V)

U

Total Input

xT

tT

 

Figure 4.2: Structure of an Input-Output Table

In quadrant I (A), there are "inter-industry transactions", i.e. transactions of commodities which are used as inputs in sectors. Numbers in a single row represent outputs allocated to sectors as inputs, and it is termed as "interindustry demand". Numbers in a column show the uses of inputs of a sector in a column, and the inputs are called "intermediate inputs". In input–output analysis, this quadrant plays an important role, because the sectoral interdependencies occur in this quadrant. The determination of multiplier effects is based on figures in quadrant I. In quadrant II (Y), the column represents private consumption, government consumption (federal, state, local), changes in inventory, gross fixed capital formation, and export. In a single row this quadrant represents the composition of final demand from a sector and how the output is provided. Likewise, a column shows the distribution of each final demand component by sectors.

Quadrant III (W) is usually called the "primary input" quadrant or the value–added quadrant. It contains gross value–added or primary inputs. A single row represents the distribution of gross value added by sectors, while a single column shows the composition of gross value component of gross value–added. Unlike other quadrants, in which one can interconnect, quadrant IV (V) is basically used for determining the gross domestic. This quadrant takes the sum of the incomes in the last row, which is equal to the sum of the outlays in the last column. The figure denotes the GDP.

It shows the changes in consumption may affect the production of different sectors then describe the structure of the economy and its interaction with the environment. For example, changes in agricultural product sales will have immediate (direct) effects on the food and beverages industry, but cause minimal immediate (indirect) effects on the transportation industry, and any other industries which provide inputs to the food and beverages industry. In this respect, input-output models illustrate how the economic changes in one industry can influence other industries.

Thus, input-output models consider both direct and indirect effects of all economic activities. This approach is able to distinguish between the intermediate demand effect (or production demand) and the final demand effect (or consumption demand). The production demand can be further divided into direct and indirect production demands. For example, households purchase goods and services for direct use; this constitutes the direct consumption demand effect. But, if the final demand for the output of a particular industry increases, a corresponding increase in the inputs to that industry is also necessary (this is the direct production demand effect). In the same way, increases in inputs from other industries must lead to a corresponding increase in the outputs from these sectors, and so forth for an unending number of rounds (these correspond to the indirect production effect).

An input-output model is useful in analysing the economic relationship of linkages among major sectors of an economy. An input-output model is an equilibrium model in that it assumes no surplus of production or consumption. This implies the model as a static model. Economists regularly use the input-output model to examine the economic impact of the sectoral output, employment and income on the economy due to changes in exogenous variables. Central to the use of input-output models is the assumption that demand is a fixed proportion of total output. Thus, any increase in total output will lead to a specific increase in each input category that is used in the production of that output which can be represented by the technical coefficient (aij) of the particular sector,

aij = xij / Xj (1)

where, xij is output from sector i used as an input in sector j and Xj represents total output of sector j.

The input-output table shows the inter-industry transactions, the final demand and the primary input sections. Taking a flow of intermediate goods from sector i to sector j as aij, production in sector i as Xi, the price of output in sector i as Pi, and final demand for output from sector i as Fi, then the value of output produced by sector i is; PiXi = j Pi xij + PiFi (2)

Then, substituting Equation (1) into Equation (2) gives

Xi = j aij Xi + Fi (3)

Equation (3) indicates that total output is the sum of products for intermediate use and output consumed in final demand market. It is the ith row of the matrix equation X = AX + F (4)

where, A (n x n) represents the technical coefficients matrix, X (n x m) represents column vector of sectoral gross output and F (n x m) represents column vector of final demands which comprise private consumption, public expenditure, investment and exports.

Equation (4) can be solved for X giving

F = (I – A) X

(I – A)-1 (I – A) X = (I – A)-1 F

IX = (I – A)-1 F

X = (I – A)-1 F (5)

Where

I is the identity matrix and

(I – A) -1 is the Leontief inverse matrix (n x n)or usually called the multiplier matrix.

Each of the multiplier matrixes or coefficients shows total requirements (both the direct and indirect effects) of increasing final demand for any sector. Each cell in the "total" row of the total requirements table gives the analyst a multiple by each dollar of increased final demand that will impact the overall output of the economy. It measures how much total production of goods and services is required throughout the economy for every one dollar of additional final demand for the goods produced by the industry named at the top of the column.

4.4.2 Hybrid Input Output analysis

This study use the hybrid input output table in order to trace energy flows in the economy in Ktoe and non-energy flows in value term such as ringgit Malaysia (RM). Table 4.3 shows the relationship between energy use and other sector in the economy within the extended input output framework.

Generally, energy input output determines the total of energy required to deliver a product to final demand, (Miller and Blair,2009). Energy sector divided into 3 main sectors as follows:

Crude oil, natural gas and coal

Petroleum product and coal

Electricity

Industry sector

Energy sector

Other sector

Intermediate demand

Final demand

Total output

Consumption

Government

Gross capital formation

Export

Energy sector

ENERGY CONSUMPTION (KTOE)

Other sector

INTERMEDIATE CONSUMPTION (RM)

FINAL DEMAND (RM)

(RM)

Primary input

Import

(KTOE)

(RM)

(RM)

 

Value added

GROSS VALUE ADDED (RM)

 

Total input

(KTOE)

(RM)

 

 

 

 

 

Figure 4.3: Schematic of Hybrid input output table

while non energy sector and services have divided into 37 sectors including agriculture, manufacturing, construction and services. In order to construct Hybrid input output table, the minor modification were applied in the interindustry transactions in the basic input output framework of figure 4.2. In the hybrid input output an analogous set matrices to Z, A, and L, that is energy transactions or flow of energy matrix which measured in physical unit of Ktoe, where A is direct energy requirements matrix and L is the total energy requirements matrix. From the traditional input output accounting identity, Zi + f = x where Z is the matrix of interindustry transaction, f is vector of total final demands (private consumption, government, investment and export) and x is the vector of total output. All these items are measured in Ringgit Malaysia (RM), but in this case, this study were measured energy flow in physical unit of Ktoe, hence assume that an analogous identity given by Ei + q = g, where E is the matrix of energy flows from energy producing sector to all sector as consumers of energy, q is the vector of energy deliveries to final demand and g is the vector of total energy consumption. This study aggregated 40 sectors which 3 is energy sectors, then Z will be 40 x 40, but E will be of dimension 3 x 40. It is the same to f and x are of dimension 40 x 1; q and g will be of dimension 3 x 1. In previously A is the matrix of technical coefficients then Z =Aû and it follows that L = (I - A)-1, the familiar Leontief inverse, so that total requirements can be expressed as x = Lf, then L is the total energy requirements in the equation g = αf where α is 3 x 40.

4.4.3 Energy intensity (Total energy requirement)

Input-output energy analysis is a specific application of economic input-output analysis. The first work on input output energy analysis have done by Wright (1974), and Bullard and Herendeen (1975) and recent review by Peet (1993). The objective of input-output energy analysis is the calculation of energy intensities or total energy requirement. The energy intensity of an economic sector gives the total amount of energy, both direct and indirect, that is needed for one financial unit of production of that sector. The direct energy use of an economic sector comprises the energy directly used in the production process of that sector. The indirect energy use of an economic sector comprises all the energy that is needed for the production and delivery of the goods and services that are used in the production process. These goods and services include both the goods and services from domestic and foreign origins and the capital goods. In this study, input-output energy analysis is used for the determination of the total primary energy needed for the production of final demand.

The primary energy requirements of final demand are also called the cumulative energy requirements, total energy requirements, or the embodied energy of final demand. The total amount of primary energy that is required for producing final demand is allocated to this final demand. In principle, primary energy is used in a restricted number of energy sectors and distributed, in the form of goods and services, over all final deliveries (Miller and Blair, 1985). For this study, to determine the total energy requirements of household is by combining energy intensity with expenditure by household as done by Park (2007) for Korean households energy requirement.

The input output system in monetary units can be formulated in equation 1 and equation 2.

t1j + f1j – m1j = X1 (6)

ej1 + tj1 + V1 = X1 (7)

where X1 is the production of sector 1, e.g. petroleum product, t1j are the intermediate outputs of sector 1 to be used for the production of goods of sectors 1 to 40, tj1 are the intermediate inputs from sectors 1 to 40 for the production of goods of sector 1. f is the final demand which includes consumption (private and government), investments and exports. m is the imports and V is the value added inputs. The first summation of Equation 2 means the inputs of 3 energy sectors. The second summation of Equation 2 means the inputs of 37 non-energy sectors.

This study converted the monetary unit input–output tables into energy input–output tables with the help of energy prices (Miller and Blair, 1985). First, average energy prices are calculated using information on energy use and expenditure by fuel of the input–output tables. Average energy prices are calculated as ratios of energy use (inputs) to the total output (intermediate plus final demand) by fuel, expressed in Ktoe/RM, same as energy intensities as shown in Equation 3. The reciprocal numbers of the energy intensities are more commonly used prices expressed in RM/Ktoe. Thus, higher Ktoe/RM values or higher energy intensities mean lower energy prices.

Pi = ei/Xi-mi (Ktoe/RM) (8)

where ei is energy use. P1, the price of energy sector 1, e.g. price of petroleum product, is used to quantify 40 intermediate inputs of petroleum product to produce goods of 40 sectors. Industries (40 sectors) will pay much lower prices than households (final expenditure) for the same fuel. The price differential exists within the intermediate demand for fuels. For more discussions see Lenzen (1998)

t1,j x P1 = te1,j (9)

Once intermediate energy inputs (energy input–output tables) are computed as in Equation 4, it is easy to estimate direct energy intensities of individual sectors. Direct energy intensities are calculated as ratios of direct energy expenditure converted in energy terms to total inputs (intermediate inputs and value added inputs), also expressed in toe/RM in

d1 = ei, 1/Xi (toe/RM) (10)

where d1 (direct) is the direct energy intensity of sector 1. Total or cumulative energy intensities can be then computed by multiplying them with the Leontief inverse (1-A)-1 of the corresponding input–output table as expressed in

di,j x (1-A)-1 = Ti,j (11)

The indirect energy intensities are the differences between total Equation 6 and direct energy intensities Equation 5 equal to Equation 7.

Tij –dij =Indij (12)

Sectoral total or cumulative energy consumption can be computed by multiplying total energy intensity with sectoral household expenditure. Indirect household energy consumption is then the sum of sectoral cumulative energy consumptions of 37. Direct use of petroleum products, coal and electricity in primary energy terms by households is considered as direct household energy consumption. Total household energy consumption is the sum of direct and indirect energy requirement.

4.4.4 Carbon dioxide (CO2) emission factor

The study will estimate the CO2 emission by production sector generally produced by energy activities using the six steps of calculation of CO2 emission provided by IPCC (Intergovernmental Panel on Climate Change) Guidelines which gives instructions for estimating the emissions of CO2. This study use the Tier 1 methods, concentrate on estimating the emissions from the carbon content of fuels supplied to the country as a whole. The first step starts with enter the energy data or information in original unit i.e. Ktoe into the workbook provided by IPCC. Then the second step is converting the energy consumption unit from Ktoe into Terrajoule (TJ) for each fuel by multiply the energy consumption in unit Ktoe to the relevant conversion factor or scaling factor so that energy consumption in terrajoule (TJ). For the third step, enter the carbon emission factor to convert energy consumption into carbon content by multiply the energy consumption in TJ by the carbon emission factor to give the carbon content in Tonnes of C. Then divide carbon content in tones C by 103 to give gigagrams of carbon. This study have skipped step four because additional information is not available or considered credible, so carbon stored not necessary to calculate. In the fifth step, this study used fraction of carbon oxidized provided by IPCC in order to correct the carbon unoxidized. The last step or step six is converting the CO2 emission by multiply actual carbon emission by 44/12 to final total carbon dioxide emitted from energy consumption. Once, the CO2 emission calculated, it is easy to determine the CO2 emission factor by using following formula.

EFi = Ci/ ei (13)

where EFi is the CO2 emission factor of energy type 1 i.e. petroleum product. Ci is the CO2 emission from energy type 1 and ei is the energy consumption by sector type 1.

4.5 Carbon dioxide (CO2) emission estimation by category

The direct CO2 emissions are emissions related to the consumption of energy commodities in the households such as electricity, gas and petroleum product. The indirect CO2 emissions by household are emissions related to the production of all other commodities for the households including tangible and intangible goods and services.

This study is carried out in three steps:

1. Direct CO2 emissions from household energy use are analyzed using a simple energy-emission model.

2. Indirect CO2 emissions are analyzed using an integrated input output model that also incorporates energy and emissions matrices.

3. The variables used in this study will be confirmed with the econometric analysis.

4.5.1 Direct CO2 emissions by household

Model (16) below estimates direct CO2 emissions from household energy use as the product total energy consumption and the composition of energy types in the household and energy supply sector as given in Munksgaard et al. (2000) [1] 

Ed=qd md fd (14)

where Eh denotes a scalar of total direct CO2 emissions from the household; qh is a 1 x 4 vector including the consumption of four types of energy in the household, such as electricity, natural gas, LPG and kerosene in units of toe; mh is a 4 x 11 matrix of fuel mix in the household sector such as the demand for 11 energy types per unit of total energy demand for four energy consumption categories. f is a 11 x 1 vector of CO2 emission factors in units of T-CO2/toe for 11 energy types.

4.5.2 Indirect CO2 emissions by household (Final demand)

Model (15) estimates the indirect CO2 emissions from household consumption by using the extended input-output model introduced by Leontief and Ford (1972).

Ei = fi (mi # ri) (I-A)-1 FDS#FDL (15)

Where # denotes element by element multiplication, Ei denotes a scalar of total indirect CO2 emissions in the production sectors as a consequence of production of goods for household consumption; fi is an 11x1 vector of CO2 emissions per unit of consumption of each of the 11 energy types; mi is a 11x40 matrix of fuel mix in the production sectors, i.e. demand for 11 energy types per unit of total demand for energy for all production sectors; ri is a 1x40 vector of energy intensities, i.e. total energy consumption per unit of production in all 40 sectors; (I-A)-1 is the 40 x 40 Leontief inverse matrix, Cec is a 40 x 30 matrix of the composition of household expenditure class aggregates, i.e. 30 private consumption household expenditure class aggregates apportioned by production sectors; cg is 30 x 1 vector of aggregate household expenditure class by region and stratum in private consumption, i.e. demand for 30 expenditure class per unit of total consumption; C denotes a scalar of total private consumption. Equation (15a) is for CO2 emission by exported countries where F is multiplication of environmental matrix, (I-A)-1 is the 40 x 40 Leontief inverse matrix and €€p,g,r is 40 x 30 selected exported country.

According to model (15) and (15a), indirect CO2 emissions change as a consequence of changes in seven factors plus export: f, mi, ri, (I-A-)-1, Cec, cg, C., €. Whereas C and c are factors of consumer behavior, i.e. demand for consumption by expenditure class, f, mi, ri, and (I-A)-1 are factors of behavior of the firm, i.e. demand for inputs in the energy supply sector and other production sectors and € represented the export activities.

4.6 Decomposition of CO2 emissions using Structural Decomposition Analysis (SDA)

The first important feature is it includes the households’ direct demand for energy and secondly, it handles the changes in expenditure class for private consumption at an aggregated level, encompassing 30 expenditure class by region and strata according to MISC [2] . In addition, the data cover 40 production sectors and 11 types of energy. The analysis covers the period from 1991 to 2005.

Thus all changes may be weighted using either base-year values [3] for the other two factors or current-year values. Both approaches cause considerable bias, however. Nevertheless, this method of decomposition is inconsistent with recent developments in economic theory.

According to model (16) direct CO2 emissions are dependent on the changes in the factors qh, mh and f. The decomposition analysis is carried out by changing the factors one by one in order to quantify the contribution of each factor to the total change in emissions. The contribution of each factor, e.g. qh, is estimated as the change in the factor (∆qh). This is subsequently multiplied by the other factors (mh and f). The other factors may figure at base level or at current-year level, however. This method is adopted from Munkgaard et al. (2000)

Each element in the decomposition formula has the same general form.

Thus, the total change in emissions from time t - 1 until time t is

∆E= (∆qd md fd) + (qd ∆md fd) + (qd md ∆fd) (16)

Where ∆qd is the effect of changes in household energy consumption level; ∆md is the effect of changes in the composition of energy types in household energy consumption; ∆f is the effect of changing emission factors, i.e the effect of fuel mix changes in energy production.

While the decomposition indirect CO2 emission in model (17), the total change in emissions from time t - 1 until time t is ∆Ei

∆Ei = ∆fi (mi # ri) (I-A)-1 CeccgC +

fi (∆mi # ri) (I-A)-1 CeccgC +

fi (mi # ∆ri) (I-A)-1 CeccgC +

fi (mi # ri) ∆ (I-A)-1 CeccgC +

fi (mi # ri) (I-A)-1 ∆CeccgC +

fi (mi # ri) (I-A)-1 Cec∆cgC +

fi (mi # ri) (I-A)-1 Ceccg∆C (17)

∆Ei = ∆F(I-A)-1 €€p,g,r + F∆(I-A)-1 €€p,g,r (17a)

+ F(I-A)-1 ∆€€p,g,r

Where ∆f is the emission factor effect (or effect of fuel mix changes in energy production); ∆mi is the effect of fuel mix changes in the production sectors; ∆ri is the effect of changes in energy intensities; (I-A)-1 is the input mix effect; ∆ Cec is the effect of changes in mix within household expenditure class aggregates; ∆ cg is the effect of changes in mix between household expenditure class aggregates in private consumption; and ∆C is the effect of change in total consumption level. Same to decomposition on export where ∆F is changes in factor environment pollution, and ∆€€p,g,r is the effect changes in mix within exported country. Again, each element in the decomposition formula has the same general form.

4.7 Data sources

The data used for this analysis were:

The Malaysian input-output tables aggregated on a consistent 40 production sector basis for 1991 and 2000 where all the values are expressed at the constant prices of 2000 published by the Department of Statistic (DOS). These tables encompass 92 production sectors and five categories of final demand. One of the latter is private consumption, which is divided into 16 components.

Regarding energy and pollutant emissions, CO2 data of household activities from the Department of Environmental (DOE) and Malaysia Energy Commissioner (PTM).

The consumer surveys from the Department of Statistics of Malaysia (HES 19980/1982 to HES 2004/2005 and some data such as Malaysia GDP and GDP per capita and population from Earth Trends Country Profiles, World Bank, International Monetary Fund and Centre Intelligences Agencies.

The figures of total registered transport provided by the Department of Road Transportation (JPJ), Transportation and Communication and Population by DOS.

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