Output , Income and Employment Multipliers in Malaysian Economy : Input-Output Approach

This study attempts to investigate the success or failure development policies for Malaysia economy through the multipliers indices over the period 1983-2000. We used four input-output tables had published so far by Department Statistics of Malaysia (DSOM) for the period under study. The study employed the Leontief inverse model that is open with respect to household for simple multipliers of the output, income and employment; type I multipliers of the income and employment. While it used Leontief inverse model that is closed with respect to household for total multipliers of the output, income and employment; type II multipliers of the income and employment. New evidence is found in this study: first, there is still a high dependency on the primary sectors, such us Oil palm, Rubber primary products and Wood sectors. Second, output and income multipliers for Agriculture sector are still very weak even where some success has resulted from planning policies. Third, the main result of the investment policy was to transform Malaysia from a country of surplus labour to one with a shortage. Fourth, there is no consideration of efficiency or comparative cost in the selection of ‘key’ sectors by reference to multiplier indices.


The Problem and Objectives:
During the past three decades, the Malaysian planners have implemented a series of planning horizon, ranging from short to long-term development plans.Subsequently, updated and adequate data would be required for monitoring the progress and performance towards achieving the planned targets.The planners aim for the period 1998-2010 sets strategic directions for economic development to the year 2010.This policy has been formulated to ensure that the structural change role in national development is sustained and enhanced in the light of new and emerging challenges facing economic development.The specific target of the planners was, however, to increase per capita income during the 1980-1990 and 1991-2000 periods, by an annual compound rate of growth of 3.6% and 13.3% respectively.This aim required the manipulation of wages, salaries and the promotion of services.The planners intended to undertake the construction of a number of services, such as education, hospital etc, and increase household income by increasing wages and salaries.This policy was designed to distinguish between income changes resulting from population growth and those which follow from rising per capita income.Therefore, the planners have aimed to maximize the output, income and employment level during the 1980-2000 periods.Also, it aimed to reduce the growth rate of unemployment, which was reduced from 6.8 in 19716.8 in -19806.8 in to 4.3 in 19716.8 in -20026.8 in (Ching, 2006)).The planners have shown the allocations and annual compound growth rate target at sector level for the period 1980-2000 by several Malaysian plans (see www.epu.jpm.my/).It would therefore be expected that the Transportation, Education, Industry, Health, Services and Agriculture sectors would have a high ranking in terms of output, income and employment multipliers.Towards this end, the planners will focus on new approaches to increase productivity and competitiveness, deepen linkages with other sectors, venture into new frontier areas as well as conserve and utilize natural resources on a sustainable basis.The policy aims to set in place the enabling and supportive measures as well as a conducive environment to promote growth in the economy.The policies and strategies formulated will continue to emphasise productivity and market driven growth (Ministry of Agriculture and Agro-Based Industry, 2006).An approach employed by policy makers to project, plan and make decision on national development programs is to use an input-output model.Input-Output analysis has become an increasingly popular means for analyzing economic structures and assisting local economic development decision making.Input-output models provide a variety of useful information.It is a descriptive tool which describes the existing structure of a economy; it provides information on individual economic sectors, the linkages between them and how they co-vary.It also shows the relative importance of individual sectors conditions.Input-Output analyses describe the economic transactions pertaining to the economic activity that occurred within specified reference periods.In Malaysia, as in most natural resources developing countries, the availability of foreign exchange generated by the rapidly growing export of oil and gas, rubber and Palm oil has been of great importance to the process of economic development.The aim of Malaysia development policy has been, primarily, to invest in the commodities sectors.The rational behind this policy was to build a solid base for the Malaysia economy, by using the natural resources revenues to support the establishment of large scale enterprises, which could produce intermediate products at competitive prices for the other industries in the economy; this would thus aid the integration of the national economy.Secondary aims were to assist in income redistribution, import substitution, export growth and agricultural modernization.Unfortunately, such a policy of inter-sectoral imbalance between economic sectors has lead to a poorly integrated economy in the short-run, causing a heavy dependence on imports.The presently existing weak forward and backward linkages between sectors are cited among the problems existing in the Malaysian economy (BEKHET, 2009;and SHUJA and et al., 2007).In addition, the planners' policy towards the industrial sector regarding the adoption of advanced technology resulted in production below its potential maximum in the short-run.This is because a number of structural "bottlenecks" developed, such as an insufficiently trained labour force and a lack of managerial and technical skills, as well as a heavily bureaucratic and hierarchical structure of organization.This paper aims to assess the success or failure of Malaysian economic policy with input-output analysis.A static input-output model is used.Unfortunately, dynamic input-output models must be ignored, as the necessary capital matrix is not available for the Malaysian economy.The period of study is 1983 to 2000, during which time four input-output tables were established.
It would be expected that in resources-rich developing economy, such that of Malaysia, substantial structural change will take place over time.In particular, one might expect marked changes in the technologies employed, especially the nature of inter-industry trading.Also, change in the level and mix of final demand for produced goods would be expected to occur.One would anticipate that the role of state economic planning would be to facilitate and direct such developments.Input-output analysis is well suited to the analysis of the nature of economic development through changing demand and changing technology.Thus this paper uses input-output methods to explore the success of economic planning in Malaysia.A variety of input-output techniques and concepts are employed.All lead towards the conclusion that economic structural has occurred in Malaysia during the period of study.Also, there is evidence of increasing efficiency in the Malaysian economy through changing the ranking of the income, output and employment multipliers for the sectors.

Data and Mathematical Techniques:
Basically, the present study uses secondary data based on the four input-output tables compiled for the Malaysia economy so far.These tables were produced by the Department of Statistics.For analytical and comparable purposes, the original input-output tables consisting of different number of sectors are aggregated into 39 sectors based on International Standard Industrial Classification (ISIC).These sectors are shown in (Table 1).Input-output multipliers are used related to output, income, and employment, as defined earlier in this paper.They are now well established as indicators of the importance of particular sectors and the interdependence of the industrial of the importance of particular sectors and the interdependence of the industrial structure.The following notation is used throughout this paper: h is the household input coefficient vector.h ˆ is a diagonalised (n*n) matrix of the household input coefficients .A is a square matrix of order (n+1)*(n+1).it has an added household row and column (i.e. the household is endogenous).


 is the reduced augmented Leontief inverse matrix, of order (n*n) order.In this matrix, r refers to the matrix being reduced, by having eliminated the household row and column.e is the number of workers employed by the household sector.It is defined as the employment vector.w is the employment output ratio vector (numbers of jobs per RM million of output).I will show later how define this ratio (subsection 3.3).
x ˆ is a diagonalised matrix of the total outputs.w ˆ is a diagonalised (n*n) matrix of the employment output ratio.

Output Multiplies
An output multiplier for sector j is defined as the total value of production in all sectors of the economy that is necessary in order to satisfy a RM's (Malaysian Currency, Ringgit (RM)).worth of final demand for sector j's output [VIETH.1976;P.16].However, in this section I shall describe several kinds of output multipliers.

Simple Output Multiplier
For the simple output multiplier, the total production is the direct and indirect output effect, obtained from a model in which households are exogenous.The initial output effect on the economy is defined to be simply the initial RM's worth of sector j output needed to satisfy the additional final demand.Then, formally, the output multiplier is the ratio of the direct and indirect effect to the initial effect alone.These output multipliers are different from those for the Keynesian system because we can generate a multiplier for each sector rather based solely on the effects of interindustry trading without household spending being involved.I shall be using Δf and Δx to represent changes in the final demand and gross outputs, respectively.Here Δf indicates an additional RM's worth of final demand for the output of any sector of the Malaysian economy.The implications for all sectors in the economy of an additional RM's worth of final demand for any sector output are given by: Δx = (I-A) -1 Δf (1) The output multiplier for any sector (for example agriculture) is defined as the sum of elements in the agriculture column divided by one RM.The one RM in the denominator is the initial effect on the agriculture sector output of the new RM's worth of final demand for the agriculture sector's product.Mathematically, the vector of the simple output multiplier m is given by: The results for the Malaysian economy are shown in Table 2.It will be noted that the results are very identical to the linkages, where they are discussed as linkages analysis.However, these figures may also be interpreted as multiplier, as will be discussed in section 4.

Total Output Multipliers
If we consider the input coefficient matrix, A, closed with respect to households (i.e.households are endogenous), then we capture in the model the additional induced effects of household income generation through payments for labour services and associated consumer expenditures on goods produced by the various sector.This is akin to the Keynesian multiplier, discussed above.We call this coefficient matrix the augmented coefficient matrix A , which was defined earlier in this section.Also, I defined the augmented Leontief inverse matrix as Clearly, the elements in  also relate final demand changes to sectoral outputs, only now these are in a model with households endogenous, and hence the effects tend to be larger.We assess the impact of a new RM's worth of final demand for any sector's output with: In the general, the total output multiplier vector, m , is given by: However, if we are interested in the total output multipliers from the original n sectors, by ignoring the household row and column we can calculate the reduced total output multipliers.This can be done by using the matrix, which was defined earlier.In general, the reduced total output multiplier vector, m r , is given by summing the reduced augmented Leontief inverse matrix I have applied equations (4) to the four Malaysian input-output tables between 1983 and 2000.The results are shown in Table 2.Not only do industries make purchases from other sectors, they also make purchases from the labour force.The next task is to calculate the income multipliers associated with these purchases.

Income Multiplier
As the name implies, income multipliers attempt to translate, in one way or another, the impacts of final demand spending changes, into changes income received by household (labour supply).There are basically two ways in which this can be done.One straightforward approach is simple to convert each element in a particular column of ) A I ( 1   , which measures the value of direct plus indirect output effects, into RM's worth of household income, via household input coefficients [MILLER and BLAIR, 1985;P.105].These are the coefficients that make up the (n+1)th sector (household) row, '  h .This is used in closing the model with respect to household, and indicates household income received per RM's worth of sectoral output.Thus the direct plus indirect effects for sector j would be in terms of (one) RM's worth of new household income.The initial effect is in terms of (one) RM's worth of final demand, and hence output for sector.Unlike output multipliers, then, they do not blow up or multiply one (initial) estimate of output to another (larger) estimate of output.Rather, they translate an initial output estimate (which comes from an initial final demand change) into an expanded (direct plus indirect) estimate of the value of resulting employment (household income).

Simple Household Income Multiplier
In general, we will be using n for the simple household income multiplier for sector j.The "simple" refers to the fact that these multipliers are found using elements in the (I-A) -1 matrix with the households exogenous.We can represent this mathematically, as: Continuing with the tables for Malaysian economy, we have the results shown in Table 3.These figures illustrate the effect of an additional RM of final demand for the output of any sector, when all of direct and indirect effects are converted into RM estimate of income.This would generate the total effect by that amount of new household income, this total, which would be earned by employees in that sector.

Total Household Income Multiplier
If the augmented matrix is used rather then (I-A) -1 , total (direct, indirect and induced) income effects, or total household income, multipliers are obtained.As before, using the overbar to denote the multiplier derived from A , a similar equation to ( 6) is obtained, namely: The results of the Malaysian economy are shown in table 3. We recall the interpretation of any element in  as measuring the total effect on sector i output of one RM's worth of new demand for sector j output.Thus, the household input coefficient is the total effect on the output of the household sector, which is the total value of labour services needed when there is one RM's worth of new final demand for goods of sector j.This is precisely what we mean by the total household income multiplier.
If we are only interested in household income generating effects originating in the n original sectors, we would calculate a reduced total household income multiplier, n r , by ignoring the last row and column in equation ( 7).

Type I Income Multiplier
There is a second kind of simple income multiplier, the type I income multiplier, for any sector j.This has the simple household income multiplier as in equation ( 6), as a numerator, and uses as a denominator not the initial RM's worth of output, but rather its initial labour income effect, h.We can use y to represent this type of income multiplier for sector j.Then, following BRADLEY and JAMES [1969;p.310]we can write: For our input-output tables for the Malaysian economy, the results are shown in table 4 for 1983, 1987, 1991 and 2000 respectively.These multipliers represent the ratio of the direct plus indirect income effects to the direct income effect.

Type II Income Multiplier
This multiplier has the total household income multiplier as in equation ( 7), as a numerator, and uses as a denominator the initial labour income effect, h [MILLER and BLAIR 1985;P.108].As usual, using the overbar to denote a measure that is calculated from The parallel between this measure and the type I effect in equation ( 8) is the same as that between the total n and simple n household income multiplier is equations ( 7) and ( 6) respectively.The numerator for y is n from equation ( 6), and the numerator for y is n from equation ( 7).The results of this multiplier, for the Malaysian economy, for the 1983, 1987, 19918 and 2000 tables are shown in Table 4.These multipliers show by how much the initial income effects (household input coefficients) are blown up, or multiplied.This occurs when direct, indirect and induced effects (due to household spending because of increased household income) are taken into account, in which household are an endogenous sector.

Relationships between Income Multipliers
To the extent that the results of an input-output analysis in which households remain exogenous tend to underestimate total effects, type II multipliers may be more useful than simple, or type I, multipliers in estimating potential impacts.However, if one is primarily interested in ranking or ordering the sectors, for example, which sector has the largest multiplier, which has the next largest, and so on, then simple or type I multipliers are just as useful as total or type II income multipliers.This is because the ratio of total to simple household multipliers or type II to type I income multipliers can be shown to be a constant across all sectors [MILLER and BLAIR, 1985;P.105].
The results for Malaysian economy for this ratio are 1.065, 1.068, 1.066 and 1.153 for the 1983, 1987, 1991 and 2000 tables respectively.Moreover, the constant ratio can be easily found without any need for This represents a computational advantage [MILLER and BLAIR, 1985;P.109].The above is a brief discussion of the relationship between income multipliers.For more detailed discussions see especially SANDOVAL [1967], BRADLEY [1969], KATZ [1980], andMILLER andBLAIR [1985].

Employment Multiplier
If we assume that the levels of employment in an industry are closely related to output, such that the employment/output ratio can be defined for all levels of output, then the entries in the input-output system can be converted to employment terms to yield employment multipliers [GEOFFREY, 1985;P.36].This means, if it is possible to estimate relationships between the value of the output of a sector and employment in that sector (in physical, not monetary, terms), then one can calculate employment multipliers, rather than income multipliers for each sector.So, her we are used the employment output ratio (numbers of jobs per RM million of output), w.Then, mathematically, w is: (11) w represents the RM value of labour inputs to each of the n sector per RM's worth of sectoral output.It represents the payments per employee.That is, using the physical input coefficients, in w makes explicit the differing wage rates in different sectors.We will only calculate the employment multipliers for 1991 and 2000 because the employees for that years unavailable.

Simple and Total Employment Multipliers
These measures of employment effects (or household employment multipliers) are parallel to the income effect and household income multipliers described in the previous section.The major difference is that the physical labour input coefficient vector, w, is used instead of the monetary labour input coefficient, h.That is, the elements in w are used in place of the elements in h.Using l for the simple employment effect or simple household employment multiplier for sector j, the measure analogous to n in equation ( 6) is: I have applied this equation to the Malaysian economy for the 1983, 1987, 1991 and 2000 tables.These results are shown in table 5.These multipliers would represent the number of new jobs created expressed as total employment for every new employee to meet increased final demand of new output.If the augmented Leontief inverse matrix, 1   then we would have total employment effects or total household employment multiplier.This is analogous to n in equation ( 7) with: The total employment multipliers for the Malaysian economy are shown in table 5.If we are interested only in the total employment effect on the original n sectors, not including the household sector, we would calculate a reduced total employment effect l r multiplier.This means, we are omitting that last element in the jth column of 3.3.2Type I and type II Employment Multiplier Type I and type II employment multipliers follow from the same argument as was presented for type I and income type II income multipliers, [RICHARDSON, 1972;P.35].One may wish to relate the simple or total employment effect to an initial change in employment, not final demand (and output) in monetary terms.The type I employment multiplier uses l as a numerator and w (not RM1) as the denomination.Mathematically, the vector of the employment multiplier t is given by; The results for the Malaysian economy are shown in table 6.The meaning of these is that for each new job created in any sector, for example Oils and Fats product, there is a total of 12.646 and 16.245 jobs created in all sectors throughout the economy in 1991 and 2000 respectively.When using allows us to measure the type II employment multiplier.Using t for the vector of this multiplier which is parallel to the type II income multipliers, [MILLER and BLAIR 1985;PP.112-113].Then, we have: The results obtained by this equation for the Malaysian economy are shown in Table 6.The high values of sectors Oils & Fats product, Processed Rubber & Rubber product, Animal Feeds product, Industrial Chemicals and Forestry & Logging product is a result of pre-1990 planning policy.These sectors were the only real area of growth of employment opportunity.The other sectors were characterised by high unemployment.

Relationships between Employment Multipliers
The purpose of this section is to consider the relationship between type I and II employment multipliers.It is not possible to establish a constant relationship between type II and type I employment multipliers, as was the case for income multipliers, as was explained in the previous section.This is derived in MILLER and BLAIR [1985, P.145].For more details on employment multipliers see BRADLEY and GANDER [1969], KATZ [1980], MILLER and BLAIR [1985] AND SANDOVAL [1967].

Interpretation of the Empirical Results:
If we assume that planners try to determine in which sector of the economy to spend one additional unit, a comparison of output multipliers would show where this spending would have the greatest impact on output or employment generated throughout the economy.Note that when maximum total output effects are the exclusive goal of planner's spending, it would always be rational to spend all the money in the sector whose output, income and employment multiplier is the largest.Tables 2-6 show the ranking of the sectors of the Malaysian economy in terms of the ranking of each sector's multipliers.Therefore, a sector with several elements in the high ranking would be said to be a key sector, in terms of the definition in the first paragraph of this section.

Output Multipliers
For Malaysian Economy, the largest simple and total output multipliers for 1983 and1987 are associated with Oils and fats product, Foods Production other, Livestock breeding, Furniture & Fixtures, Processed Rubber &Rubber product, and Hotel & Restaurants sectors.For 1991 and 2000 Tables are associated with Oils and Fats product, Livestock breeding, Petroleum and Coal product, Foods production, Wooden products, and Industrial Chemicals (see Table 2).Therefore, planners of the Malaysian economy should theoretically have spent all funds available for investment in these sectors at that time, because this spending would have had the largest impact on the total RM value of output generated throughout the economy.Of course, there would be other reasons for using some of the expenditure on the output of the other sectors.These reasons could be taking into account strategic factors, equity, capacity constraints for production, and so on.Note also that multipliers of this sort may overstate the effect on the economy in the above illustration.If some sectors are operating at or near full capacity, then some of needed new inputs would have to be imported into the economy, or outputs from some sectors would be shifted from exports and kept in the economy for use as inputs.

Household Income Multipliers
With household income multipliers, one has some choice regarding what should logically be termed the initial effect of new final demand.With output multipliers, it was fairly clear that the initial effect of RM's worth of final demand for sector j output is that sector j production must increase by one RM (and eventually, of course by more than one RM).With income effects, the same RM's worth of new demand for sector j becomes, initially the same RM's worth of new output by sector j.This is what we considered to be the initial effect in developing the household income multipliers, above.However, the initial RM's worth of new output from sector j means an initial additional income payment of hi to workers in sectors i (see Section Three for definition of h).Hence h could be viewed as the initial income effect of the new demand for sector j output.From the input-output table for the Malaysian economy in 1983, 1987, and 1991 using the simple and total household income multipliers, it emerges that expenditures had the greatest effect in generating new household income when they were spent on the output of the Education, Health, Other Services, Banks and Financial & Insurance, Rubber primary products, Wholesale & Retail Trade, and Forestry & Logging products sectors.However, in 2000 the greatest effect in generating new household income came when spending was on the same sectors above with Building & Construction, and Wooden Products instead of Rubber primary products, and Forestry & Logging products sectors.If we examine the type I and type II income multipliers for 1983, 1987, and 1991, it emerges that expenditures had the greatest effect in generating new household income when spent on the Oils & Fats products, Petroleum & Coal product, Animal Feeds product, Processed Rubber & Rubber Product, Foods Production other, Wooden products, and Real estate & ownership dwellings.However, in 2000 the greatest effect in generating new household income came when expenditures were applied to the same sectors as in 1983, plus Livestock breeding and Industrial Chemicals instead of Animals Feeds product and Processed Rubber & Rubber product sectors.

Employment Multipliers
The simple and total household employment multipliers for the Malaysian economy appear to be very small.But that is simple because they represent jobs created per RM of new sectoral output (which, as usual, arise because of an additional RM's worth of final demand for the sector).The result would be substantially higher in the Rubber primary products, Agriculture products, Rubber primary products, Furniture & Fixtures, oil Palm primary products, Hotel & Restaurant, Education and Processed Rubber & Rubber products sectors, being for the 1983, 1987, 1991and 2000 tables respectively (see Table 5).The meaning of the results of the type I and type II employment multipliers, as shown in Table 6, is that for each new job created in any sector, for example Oils and Fats, there was a total of 13.419 jobs created in all sectors throughout the economy in 1991, and 17.897 jobs in 2000 respectively (Table 6).If we examine the type I and II employment multipliers, then the sectors that would have generated the highest job multipliers in all sectors throughout the economy in the 1980-2000 period were Oils & Fats, Animal Feeds, Processed Rubber, Industrial Chemicals, Motor Vehicle manufacturing and Food Production.But if we examine the Simple and Total employment multipliers, then these sectors were However, the question is what the policy implications of these results are.This could be discussed in the next section.

Policy Implications
The theoretical basis and objectives of Malaysian planning since 1970 have been discussed in (Section 2) and more details in (CHING, 2006).This policy emphasised the provision of work opportunities and the raising of the standard of living, through increasing real national income and per capita income.The results have shown in Tables 2-6 and discussed in the previous section show how far this policy has been achieved.The results show that although some progress has been made, it falls far short of what the planners desired.The output and income multipliers for the commodities sectors still remain weak.The employment multipliers are still high ranking for the Rubber primary products, Agriculture products, Furniture & Fixtures, Processed Rubber, Hotel & Restaurant, and Education sectors, which is a reflection that these were considered as key sectors for the planner's policy to maximize the employment level during the period under study.But if we examine the type I and II employment multipliers, then these sectors were Oils & Fats, Processed Rubber, Animal Feeds, Industrial Chemical and Food Production But in general the impact of spending on the Rubber product, Furniture & Fixtures, Hotel & Restaurant, and Education sectors was higher than that of spending on the rest of the economy.These results give us the same evidence, as found in the linkages analysis (SHUJA, et al., 2007, andBEKHET, 2010).That is, there is still a high dependency on the primary sectors.Also, output and income multipliers for the Agriculture sector are still very weak, even where some success has resulted from planning policies.But the main result of the investment policy was to transform Malaysia from a country of surplus labour to one with a shortage.Malaysia attracted an immigrant labour force which is estimated the ratio of foreign workers to labour force worsened from 1:10 in 1995 to 1:8 in 1997 and improved to 1:13 in 2000 [Eight Malaysia Plan, 2003].In addition, the declining rate of growth in agriculture and an increasing rate in the Construction, Services, Wholesale and Retail Trade, and Transportation and Communication sectors was the most profound factor in increasing the emigration of the labour force from the Agricultural sector to these other sectors.This is because wages in these sectors were higher than in the Agriculture sector.Finally, there is no consideration of efficiency or comparative cost in the selection of 'key' sectors by reference to multiplier indices.Although it is not a simple matter to determine where Malaysia comparative advantage lies, international trade theory can be used to suggest that LDC', in particular Malaysia, have a comparative advantage relative to DCs in labour-intensive manufactured exports.If we define 'labour-intensive' to mean the direct and indirect labour requirements per unit of output, such an activity will substitute labour for capital not only directly, but also indirectly by making little use of intermediate inputs, or importing rather than purchasing them locally; such a sector will therefore have low output multipliers and yet it is a suitable candidate for promotion [RIEDEL, 1975;1976].Agriculture is of course the prime example of such sector in Malaysia.The absence of consideration of efficiency is particularly serious when we consider that much of the potential stimulus provided by expansion of a 'key' sector is translated into growth trough import substitution.Multiplier analysis does not permit one to distinguish between the cases where the stimulus is sufficient or insufficient to justify the establishment of a supplying industry.In the first case, the policy should ensure that the stimulus is translated into growth, while in the second it should only do so if the protection/subsidy needed to make the activity competitive is justified in terms of some other criteria (e.g.infant industry arguments).Multiplier analysis measures whish the inducement which is offered to a sector or a group of sectors if final demand changes at the margin; it can therefore be used to see if policy is consistent with the ranking of sectors; to isolate 'enclave' sector and to help promote policies for the integration of the enclave with the national economy; or to establish a changes in sectoral interdependence over time.Furthermore, because the planners aimed to maximize the output, income and standards of living level, then they should take the sectors with high output and income multipliers.Also, they should take the sectors with high employment multipliers.These sectors are discussed in the previous section and listed in tables 2-6, where they are identified as having high ranking multipliers.However, I feel this sort of analysis needs to consider a more fundamental set of objective than multipliers analysis.Industrialisation is not usually considered as an objective in itself, but as indication for the rise in the final demand, especially exports, which is supposed to accompany it.If, however, we consider final demand as our objective, then each investment needs to be evaluated in terms of its sectoral impact.This can be achieved by reference to triangularisation techniques, using input-output methods would be introduced in next paper.

Conclusions
As previously discussed, output, income and employment multipliers were calculated using simple and total multipliers.These results are presented in table 2, 3, and 5. Also, type I and type II multipliers for income and employment were calculated, and these results are shown in tables 4 and 6.The difference between simple and total multipliers is that the simple multiplier is calculated with households exogenous, while the total multiplier uses households as endogenous.The immense amount of information provided by detailed output, income and employment multipliers is valuable for those national planners who need to know in which industries output, income and employment changes will occur.The usefulness of these detailed multipliers for policy analysis and planning is evident.Knowledge of the industry in which the output changes will occur can also be used, by transportation and communication planners, to determine changes in transportation network equipment required to meet the shifts in industries production; by investment planners to designate industries where capital replacement or expansion is needed; by energy planners to determine the impact that production, transportation and investment changes will have on energy demand, and by various others types of planners.If some other kind of multiplier relationship were desired, such as an energy or investment multiplier, the same basic type of adjustment would be required.In the case of the investment relationship, the well known accelerator principle become more significant than of output, income and employment specified here.Sectors Names: as shown in Table 1.

Table 2 .
Simple and Total Output Multipliers.

Table 3 .
Simple and Total Household Multipliers.

Table 4 .
Type I and 2 Income Multipliers.

Table 5 .
Simple and Total Employment Multipliers.

Table 6 .
Type I and 2 Employment Multipliers.