Manpower Requirements of Malaysian Manufacturing Sector under the Third Industrial Master Plan

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1 Malaysian Manpower Journal Requirements of Economic of Malaysian Studies 49 Manufacturing (1): 1-19, 2012 Sector under te Tird Industrial ISSN Master Plan Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Bee-Tin Poo a Universiti Kebangsaan Malaysia Zakaria Abdul Rasid b Malaysian Institute of Economic Researc Mod Kairul Hisyam Hassan c Universiti Malaysia Sarawak Abstract: Malaysia s competitive position is being callenged by emerging economies suc as te People s Republic of Cina, India, Central European countries and Latin America. To enance its competitiveness, te nation needs to increase its availability of skilled and knowledge workers in major categories. However, te present mismatc between te supply and demand for skilled workforce will need to be resolved. Hence, several aspects of manpower must be given priority in development planning to ensure tat te manufacturing sector continues to contribute towards maintaining Malaysia s overall global competitive position. Tis paper attempts to forecast future manpower requirements in by different occupational categories under te Tird Industrial Master Plan(IMP3). For tis purpose, unpublised data from te manufacturing survey and Malaysia inputoutput table will be utilised. Te metod of forecasting is based on te manpower requirements approac (MRA). Te results of our analysis sow tat te amount of labour required to produce te same unit of output over a period as decreased and output growt is faster tan employment growt, implying an increase in labour productivity in te manufacturing sector and oter sectors, especially in te ig skilled categories. Keywords: Forecasting, Industrial Master Plans, manpower, manufacturing, occupation JEL classification: J21, J24, J Introduction Te manufacturing sector in Malaysia as experienced rapid structural cange in its production process and te process is expected to continue as we move towards a ig value-added economy. From tecniques of production tat were labour intensive, we ave gradually sifted to more capital intensive production metods tat require upgrading in te skills composition of its labour force. Consequently, te structure of labour demand in te economy as also canged, favouring more professional and skilled labour (Rama and Idris 2001; Rama and Idris 2002a; 2006). It is terefore important to give some focus a b c Faculty of Economics and Management, Universiti Kebangsaan Malaysia,43600 UKM, Selangor, Malaysia. pbt@ukm.my (correspondeing autor). All errors or omissions rest solely wit te autors. Malaysia Institute of Economic Researc, Level 2, Podium City Point, Kompleks Dayabumi, Jalan Sultan Hisamuddin, Kuala Lumpur, Malaysia. zakaria@mier.po.my Department of Economics, Faculty of Economics and Business, Universiti Malaysia Sarawak, Kota Samaraan, Sarawak, Malaysia. mkisyam@feb.unimas.my 1

2 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan on aspects of manpower planning in line wit te priority given to it in te development planning of te country if we are to continue ensuring te manufacturing sector maintains its overall global competitiveness. In te Tird Outline Perspective Plan (OPP3, ), Nint Malaysia Plan (RMK 9), (Malaysia 2006) and te Tird Industrial Master Plan (IMP3), (MITI 2006), labour in te economy is projected based on average annual growt of labour (istorical data on labour) and output targets. Wile projection of labour for 2010 in IMP3 is presented by sector only and projection of manpower for 2010 in OPP3 is presented by occupation only for te wole economy, te present study will add to te above plans by projecting manpower requirements by sub-sector and occupation categories. Projecting manpower requirement is normally based on te past trends of labour and manpower productivity. Terefore, te present study will first estimate future manpower productivity, taking into account direct and indirect tecnical cange and ten determine ow canges in te final demand structure influence future manpower requirements. Tis paper is organised as follows. Section 2 provides a review of literature, wile Section 3 begins wit a definition of manpower planning and employment classification. Section 4 presents te uman resource requirements in IMP3. Te MRA metod togeter wit its analytic framework and source of data will be discussed in Section 5. Section 6 will present te empirical results and projected manpower requirements by sub-industries and occupational categories in te manufacturing sector. Te concluding remarks will be presented in Section Literature Review 2.1 Manpower Projection For a number of decades, economists ave disagreed over te need for forecasts of labour by skill and occupational group. Economists of neo-classical inclinations believe tat labour markets are flexible, tat skill substitution is relatively easy and tat wage differentials adjust spontaneously to any imbalances tat arise (Papps 2001). In contrast, tose wo are described as structuralists (Huges 1991) mention tat te labour market is relatively inflexible. Hence, tey believe tat forecasts of imbalances of demand and supply in some labour markets are pivotal to te development of programmes to ensure tat labour is obtainable in te required quality and quantity in eac occupation in te future. Occupational forecasts now ave two main roles namely, an information role and a policy role (Huges 1994). Teir policy task is to provide information on labour trends for broadly defined occupational groups for labour market decision makers. Teir information task is to supply data on labour trends for a large number of occupational sub-groups wic will make te labour market more transparent for scool leavers, employers, career guidance counselors and oters. Tese users are interested in aving occupational forecasts for educational planning purposes so tat training programmes can be regulated to ensure tat excess supply or demand do not appear for particular occupations and te intake of students into different levels of education is balanced. 2.2 Manpower Requirement Approac According to Papps (2001), te major objectives of labour forecasts now are to (i) provide information on te current state of labour markets and expected canges; (ii) evaluate te 2

3 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan effects different policies migt ave on te level; and (iii) identify te implications of existing occupational trends and structure of labour in te future. Bootby et al. (1995) also believe tat te aim of occupational forecasting sould be to project ex ante imbalances between labour demand and supply across occupations and terefore contribute to increasing te average rate of return to education by securing a better matc between skills tat are supplied and demanded. As noted by Psacaropoulos et al. (1983), a wide range of planning tecniques are available to manpower planners. However, one tecnique above all oters as become synonymous wit manpower planning: te Manpower Requirement Approac(MRA) or Manpower Requirement Forecasting. MRA was developed for one of te first manpower planning projects in te Mediterranean Regional Project initiated by te OECD in te early 1960s. In tose days, te idea was to use forecasts for planning purposes. Given economic targets suc as te growt pat of te economy, labour requirements in terms of various qualifications and occupations were derived. Compared wit rater simplistic projections of te supply side of te economy, tis approac was to assist policymakers in te determination of training and education policies necessary to acieve te targets for economic growt (Neugart and Scomann 2002). Bootby et al. (1995) observed tat te manpower requirement approac considers te level and composition of economic activity to be te main determinants of occupational requirements, assuming a relatively fixed production tecnology. However, MRA as been widely criticised especially on its assumption of a fixed relationsip between te quantity of goods and labour (Adams et al. 1992). Te fixed relationsip between labour and te quantity of goods produced is not borne out in practice. Furtermore, goods and services can be produced wit more or less labour of different kinds as dictated by economic conditions and te relative prices of capital and labour. Manpower requirement ratios do cange in response to economic circumstances. Te second essential assumption in MRA is tat te elasticity of substitution between different kinds of labour is equal to (or near) zero (Hopkins 2002). According to Scultz (1988), altoug models of manpower requirement ave lost favour among economists, tis perspective preserves considerable followers among policy makers and oter practitioners. Manpower forecasts are still utilised in many parts of te world especially for setting long-term quantitative targets for educational systems. Models of manpower requirement are useful in providing an objective description of te economic scarcity of te specific skills tat te educational system contributes to produce. MRA also offers information were priorities can be set wit te goal of maximising returns from resources and distributing tese returns to individuals equitably. According to Zakaria and Siti (1997), manpower forecasts can be used as an aid to educational planning. Te forecasts feed into educational decision-making directed towards te formulation of immediate employment policy. Tey used MRA to forecast manpower requirements in Malaysia for year 2000 by using unpublised data on te number of persons engaged in te manufacturing industries. Teir study concluded tat by te year 2000 tere may be a substantial deficit of skilled tecnical and professional expertise needed to support. Tey also claimed tat too muc money is being spent in Malaysia on educational administration and not enoug on tecnical and vocational education. A variety of 3

4 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan government programmes are designed to redress te skilled manpower imbalance, but tere will always be manpower disequilibrium in a dynamic economy. In anoter major study, Rama and Idris (2002a) forecast future manpower requirements in Malaysian agriculture-based industries for by using MRA. Tey found tat for te period 1997 to 2001, te types of industries tat demand ig manpower are manufacturing firms tat deal wit wood, cork and rubber. However, skilled labour suc as engineers and tecnicians are less required in agriculture-based industries compared to te non-agriculture based industries. 3. Manpower Planning and Employment Classification Manpower planning is basically concerned wit securing te rigt number of people wit te rigt qualifications for te rigt jobs at te rigt time (Ritcer 1984). Te most popular approac begins wit a conditional projection of manpower needs given sectoral output forecasts. According to Amjad (1985), manpower planning as two objectives. Te first is to make an assessment of te skilled uman resource needs of te economy during a specific time period (say a five-year plan). Te second is to provide an analytical framework for undertaking uman resource planning wic will elp identify te skills requirements for educational planning and te making of appropriate investments in education, training and manpower development. As skills is a multi-dimensional concept, direct measurement is difficult. In empirical work, proxies for skills are often used. Two metods are frequently used to separate aggregate labour into different components. First, one uses job or occupation classifications to create proxies for skilled and unskilled labour, and te oter employs educational caracteristics to measure skills (Poo 2006). In order to make te data comparable wit te Malaysia Standard Classification of Occupations in te Labour Force Survey Report publised by te Department of Statistics, Malaysia (DOS), te present paper classifies te labour occupations according to te Dictionary of Occupational Classification (DOC) (see Table 1). Te DOC is fundamentally aligned to International Standard Classification of Occupation publised by te International Labour Organisation (Poo 2006). Table 1. Employment classification Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Professional Tecnical and Related Workers Administrative and Managerial Workers Clerical and Related Workers Sales Workers Service Workers Agriculture, Animal Husbandary and Forestry Worker, Fisermen and Hunters Production and Related Workers, Transport Equipment, Operator and Labourers Source: Poo (2006) 4

5 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan 4. Human Resource Requirements in te Tird Industrial Master Plan (IMP3) During te first five years of te Plan period, overall employment in te economy is expected to increase by an average annual growt of 1.9 per cent, from 10.9 million in 2005 to 12 million in Te services sector will continue to be te largest source of employment, accounting for 52.2 per cent of te total employment by 2010, wile te manufacturing sector accounts for 30 per cent (Table 2). For te period , total employment is expected to register iger growt. Tis is in tandem wit te anticipated expansion in te economy, particularly te manufacturing, services and construction sectors wic are expected to contribute more tan 95 per cent of te GDP in Employment sare in te agriculture sector is estimated at 11.1 per cent in Tere will be greater need for a skilled workforce as te sector is targeted to become knowledgeintensive and commercially driven. Among te categories of skilled workforce required are agricultural and soil scientists, botanists, erbalists and aquaculture and organic farming specialists. Te application of ig tecnology planting metods and mecanisation will enance te productivity of te sector and reduce dependency on unskilled labour (MITI 2006). To facilitate acievement of te macro-target of te uman resource requirement in IMP3, a strategy of developing innovative and creative uman capital as been set. Te availability of te required talents and expertise by bot manufacturing and services sectors will become important as industries and services move towards a more knowledge-based operating environment. Strategies to meet te required talents and expertise include te following: 1. Matcing te supply of talents and expertise wit market requirements. 2. Increasing te supply of tecnically-skilled, knowledge-intensive and ICT-trained workforce. Table 2. Employment by sector ( ) Sector Average Sare of total Sare of total ( 000 person) ( 000 person) annual employment employment growt 2005 (%) 2010 (%) (%) Total Employment 10, , Manufacturing 3, , Services 5, , Agriculture, 1, , forestry and fisery Construction Mining and quarrying Source: Tird Industrial Master Plan ( ) 5

6 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan 3. Encouraging greater collaboration between training institutes and to optimise te utilisation of available resources and facilities. 4. Empasising a iger level of creativity, innovation and oter enabling skills in te educational, and tecnical and vocational training systems. 5. Creating a critical mass of local experts in scientific and engineering fields to meet R&D requirements. 6. Rationalising laws and regulations to provide greater flexibility and mobility in employment. 5. Metodology and Data Sources 5.1 Input-Output Model In te input-output approac, te balance equation can be written as X=AX+F (1) were F is te vector of final demand X is te vector of sectoral output A is te tecnical coefficient matrix Solving te balance equation for X, we obtain X=(I-A) -1 F Let R=(I-A) -1 were R=(r ij ) is Leontief inverse matrix. We may write equation (1) as X=RF. (2) 5.2 Input-Output Industrial Labour Model Industrial labour can be tougt of as being distributed in certain proportions trougout all industries. Using equation (2), we can estimate te impact of any cange in final demand on te level of total industrial labour in te economy. By deriving a row vector of n labour coefficients, l i (eac element of wic depicts te number of workers required to produce a unit of i s output, were i = 1 n), te labour coefficient is terefore, calculated as follows for eac : l i =L i /X i were L i = level of labour in i X i = total output of i l i = row vector of labour coefficient (i= 1, 2, 3..n). Ten l i = [l 1 l 2 l 3... l n ] 6

7 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Te level of labour in eac is uniquely related to te amount of total output produced by tat. Tus, to find te amount of labour employed in i, we merely multiply te corresponding labour coefficient, l i by te total output X i of tat sector. By summing te of labour coefficients and total outputs of all industries trougout te economy, we can derive te following expression for total industrial employment: LT = n l i X i (3) i= 1 were L T represents total industrial employment in te economy. From equation (3), in any given year, te following identity as to old as well: L = lx (4) By combining equations (2) and (4) te following expression is arrived as L = lrf Tus te labour requirement equation of an I-O production system of n sector is L = l(i - A) -1 F (5) Teoretically and empirically, te most serious supposition in te I-O labour model is te assumption of a single type of labour per sector (labour is omogenous). By ironing out all differences between types of employed labour, tis assumption directly violates te basic idea of I-O economics, tat is, structural differentiation (Holub and Tappeiner 1989). Te most important of tese structural differentiations is certainly based on te different categories of labour. Te model of manpower structural decomposition analysis begins wit te labour requirement equation of an input-output production system wit n sectors and m occupations or manpower. Labour row vector coefficient l i ave to be extended to an m x n matrix or manpower coefficient matrix (H). Tus, te replacement of labour vector coefficient (l) wit manpower coefficient matrix (H) yields te equation sown below: L = H(I - A) -1 F (6) were H = M m1 M m2 M m3 L L L O 1n 2n 3n M mn were L is a total manpower requirement column vector by occupations (m x 1), measured in workers; H is a manpower coefficient matrix by occupation and by sector (m x n) wit te coefficients measured in terms of workers required per unit output; F is a final demand vector (n x 1) measured in value terms; A is a tecnical coefficient matrix (n x n), wic measures te input requirements per unit output in value terms; and I is an identity matrix (n x n). 5.3 Te Inter- Manpower Requirement Model Te tecnique wic will be used in te present study is te input-output inter- manpower forecast model introduced by Psacaroupoulos (1973). Wit respect to te 7

8 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan modifications of te manpower requirement approac, te main feature of te model developed below links te skill structure of te labour force or manpower to te economy as a wole as sown in equation (6). Tus, te manpower requirement for n sectors can be expressed as: L = H(I - A) -1 (F) Λ (7) ^ denotes te diagonal matrix of te F vector in te parenteses Te manpower coefficient matrix H of te base year will not be te same as tat of te target year of te projection. In order to take into account te cange in manpower productivity, we sould ideally adjust every element of te H matrix. In te present researc, manpower productivity is measured by compounded annual growt rate of labour (π). Te adjustments factor reflects productivity growt of a particular occupation of labour or manpower in tat sector. Tus equation (7) becomes Λ L T were 1 Λ ( I A ) ( F = H ) adj H adj = bπ Λ LT b π t T = forecast of manpower for n sectors (number of workers) = matrix of manpower coefficient in te base year (were b = manpower coefficient matrix, H) = elements of labour productivity adjustment by sector and category of occupation. = Leontief inverse matrix in te base year and 1 j I A t 1 Λ ( F T ) = forecast of diagonal matrix of final demand Equation (8) indicates tat labour by occupation estimates for a future period is determined by growt rate of manpower productivity and expected output level. Meanwile compounded growt rate of labour by occupation (π) will measure adjustments of manpower productivity growt. Forecast of manpower is carried out under te general equilibrium framework, wic allows interactive influences among sectoral manpower coefficients, sectoral annual growt rate of manpower productivity, direct and indirect inter- transaction, and sectoral final demand. 5.4 Compounded Annual Growt Rate of Labour (π) Compounded annual growt rate of labour was used to obtain te labour productivity adjustment. Te function took te simple form of = W t jm W W ( ) t jm 0 jm 0 n W (1 + π ) jm 1 n = 1+ π (8) 8

9 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan W W t jm 0 jm 1 n 1 = π 1 t n W jm π = 0 W jm were W t = labour coefficient in sector j by category of occupation m for terminal year jm 0 W = labour coefficient in sector j by category of occupation m for initial year jm N = difference between te terminal year and initial year (9) W W t 1 n jm 0 jm Data Sources Tis study utilised two kinds of data. Te first set of data is unpublised data on number of persons engaged in te manufacturing industries classified by Malaysia Industrial Classification (MIC) (DOS 1972) and te Malaysia Standard Industrial Classification (MSIC) (DOS 2000) at 5 digits collected from te DOS. Tese data were for te years 1978 and Te unpublised data for final demand in year 2010 were collected from Economic Planning Unit (EPU). As mentioned earlier, we classified te labour occupations according to te DOC, in order to make te data comparable wit te Malaysia Standard Classification of Occupations in te Labour Force Survey Report (Ministry of Labour 1972) Te second set of data used Malaysia s Input Output tables for 1978 and 2000 publised by te DOS. Te input-output data ave been aggregated and reduced to 32 x 32 dimensions, covering all 31 manufacturing industries/commodities and single sectors wic represent oter sectors tat include te services, agriculture, mining, construction, and te rest of public sectors (Poo 2006). 6. Results and Discussion Te input-output model enables us to evaluate te performance of te economy in terms of te amount of primary factors required, particularly labour, to deliver a given bill of final demand (Zakaria 1991; Zakaria and Can 1995; Zakaria and Can 1997; Zakaria and Siti Kairon 1997). Hence tis paper attempts to estimate future manpower productivity by taking into account direct and indirect tecnical cange and canges in final demand structure tat influence future manpower requirements. Te final result in manpower forecasting will be te number of workers employed by various categories of occupation in te future. Based on Table 3, te manpower projection under IMP3 by using MRA can be seen from te estimated results tat summarise manpower requirement for te year 2010 and is projected to increase by 88.4 per cent compared to year Comparing tese results wit IMP3 publised by Ministry of International Trade and Industry (MITI 2006) and under te projection of te Nint Malaysia Plan ( ) (Malaysia 2006), tere are differences in te data for total manpower requirements in te economy, and total manpower requirements in te manufacturing sector, but te differences are not too wide as sown in Table 4. Te estimated results, as reported in Table 3, indicate tat total manpower requirement projection 9

10 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan Table 3. Projected manpower requirements 2010 (number of persons) Sector Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Total Meat diary Veg fruit (Preserved food) Oils and fats Grain mill Bakery, confect. Oter foods Animal feed Beverages Tobacco Textile Wearing apparel Wooden Furniture & fixtures Paper & printing Industrial cemicals Paints and lacquers Oter cemical Petroleum, coal Processed rubber Rubber Plastic

11 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Table 3. Continued Sector Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Total Cina, glass & clay product Cement, lime plaster Oter non-met mineral Basic metal Oter metal Non-electrical macinery Electrical macinery Motor veicles Oter transport equipment Oter manufacturing Oter sectors Total Source: Estimated from equation (8) Table 4. Comparing projected manpower requirements in 2010 under MRA wit IMP3 and te Nint Malaysia Plan Sector IMP3 ( ) Manpower Requirements and te Nint Malaysia Plan Approac (MRA) ( ) ( 000) % ( 000) % Manufacturing 3, , Oter sectors 8, , Total 11, , Source: IMP3 ( ), Nint Malaysia Plan ( ) and Table 3 11

12 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan in te economy for year 2010 was recorded as million workers, wile in te IMP3 (MITI 2006) and Nint Malaysia Plan (Malaysia 2006) projections, it was about million workers. Te lower employment forecasts in te present study may be due to labour productivity improvement provided for in MRA. Matematically expressed as H adj = bπ in equation (8), te smaller value of π will yield a smaller value of bπ. Terefore, pre-multiplying bπ wit te output targets will also yield a lower projected employment. Projected manpower requirements using equation (7) wic is based on a matrix of manpower requirements in te base year only (assume tat occupation matrix H of te base year is te same as tat of te target year of projection) will yield iger employment forecasts compared to equation (8) because H adj = bπ <H, terefore L Λ T < L. On te oter and, te manufacturing accounted for about 2.29 million (20.40%) of total workers in te economy, wile in IMP3 and te Nint Malaysia Plan, te total was 3.13 million (26.15%) (see Table 4). In tat respect, electrical macinery (14%), wooden (12%), and basic metal (10%) industries are te sub-sectors in manufacturing industries wic contributed igly to te economy. It migt be tat tese industries are labour intensive. For te category of workers, group 7 is te major group of workers in te manufacturing industries sector wit 1.7 million wit te major contribution coming from electrical macinery, wooden, and basic metal, wic accounted for 0.24 million, 0.21 million, and 0.20 million, respectively. It is followed by group 1 and group 3 were te workforce is also engaged in te same industries wit group 7. Table 5 sows tat during te period , output increased by 6.76 per cent and employment by 1.90 per cent indicating an increase in labour productivity in te Malaysian economy. Witin te same period, manufacturing output increased by 7.0 per cent and employment by 4.0 per cent. Te iger growt in groups 1, 2 and 7 (professional, tecnical and related workers; administrative and managerial workers; production and related workers and transport equipment, operator and labourers) indicates a iger demand for skilled workers (groups 1 and 2) as industries sift towards iger valued-added and knowledgeintensive activities. However, demand for group 6 namely agriculture, animal usbandary and forestry worker, fisermen and unters will see a decline in 2010 compared to oter categories of occupation. A comparison by sub-industries in Table 5 sows tat oter cemical, nonelectrical macinery, and electrical macinery ad a negative growt in employment. Tis implies tat an increase in output required less amounts of labour employed in Wit rapid developments in new and innovative, te requires qualified and experienced scientists in various areas. In contrast, tree sub-sectors sowed no labour productivity improvement (increase in employment iger tan te increase in output) namely processed rubber, basic metal, and meat dairy industries. It migt be due to te labour-intensive nature of tese industries. In te long run, tese industries must attempt to reduce te labour component and improve productivity by developing and adopting automated production processes. Meanwile, industries suc as bakery, confectionery, beverages, and oter manufacturing sow labour productivity improvement. Te move towards more capital-intensive operations and expansion into iger value-added production as seen a greater number of skilled workers being employed to andle more sopisticated macinery in tese industries. 12

13 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Table 5. Annual rate of growt of output and manpower requirements ( ) Sector Output Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Total Meat diary Veg fruit (Preserved food) Oils and fats Grain mill Bakery, confect. Oter foods Animal feed Beverages Tobacco Textile Wearing apparel Wooden Furniture & fixtures Paper & printing Industrial cemicals Paints and lacquers Oter cemical Petroleum, coal Processed rubber 13

14 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan Table 5. Continued Sector Output Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Total Rubber Plastic Cina, glass & clay Cement, lime plaster Oter non-metal mineral Basic metal Oter metal Non electrical macinery Electrical macinery Motor veicles Oter transport equipment Oter manufacturing Oter sectors Total Source: Calculated from Industry Surveys and Annual Survey of Manufacturing Industries (unpublised data) and Table 3 14

15 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Twelve industries in te manufacturing sector ave been targeted for greater development and promotion under IMP3. Table 6 sows projected manpower requirements in te resource-based, non-resource based, oter manufacturing and oter. Te resource-based registered about 1.07 million employed compared to te non-resource based of 1.02 million. Te wood-based contributed te most to te resource-based wit 0.40 million, followed by te petrocemicals at 0.20 million, and food processing at 0.19 million. In te non-resource based, te major contributors to job creation were te metal wit 0.33 million, followed by electrical and electronics wit 0.32 million. Employment creation in te non-resource based is attributed to expansion in te basic metal and metal, as well as electrical and electronics. For te oter industries group, te increase comes mainly from te services sector, for example, business services and financial services, recording about 8.96 million workers. By category of occupation, Groups 1 and 7 are te major group of workers in te resource-based and non-resource based. Te total number of igly skilled workers (Group 1 and Group 2), in te non-resource based exceeds tose of te resource based. Tis is reflected in iger speed factory automation or mecanisation wic as seen increasing demand for tese categories of workers in te as against te resource-based. 7. Concluding Remarks Tis paper attempts to estimate future manpower productivity, taking into account direct and indirect tecnical cange and ow canges in final demand structure influence future manpower requirements. Te results of our analysis sow tat te amount of labour required to produce te same unit of output over a period as decreased and growt of output is faster tan growt in employment, implying an increase in labour productivity in te manufacturing and oter sectors. Projection of manpower requirements clearly sow tat tere will be eavy demand for professional, tecnical and related workers and administrative and managerial workers. Tis finding is supported by te study of Rama and Idris (2002a) wo state tat te types of industries were te demand for manpower is ig are te wood and cork and rubber. However, skilled labour suc as engineers and tecnicians are less required in te agriculture-based compared to te nonagriculture-based industries. In order to meet tis demand, more ig skilled workers (administrative and managerial workers, professional, tecnical and related workers) ave to be supplied from eiter te local universities or from abroad. If we compare our results wit te IMP3 and Nint Malaysia Plan targets, tey do not vary significantly. Our analysis is more detailed because projected manpower requirements are done by sub-industries and occupational categories. Furtermore, projected manpower is not only based on targets output but also on labour productivity improvement. In making forecasts of manpower requirement, we ave constructed te labour utilisation matrix. Because of lack of data and time constraints, our study used two points in time (1978 and 2000) to adjust te labour productivity growt. In fact, wen calculating te manpower requirements based on targets output, te alternative is using time-series data. Furtermore, 15

16 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan Table 6. Projected manpower requirements (2010) in resource-based and non-resource based industries Sector Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group7 Total Resource- 109,806 23,752 57,916 6,888 29, ,109 1,069,994 Based Industry Petro- 32,006 7,084 11, , , ,303 cemicals Parma- 2, , ,475 13,818 ceutical Wood- 25,563 7,806 18,900 1,506 7, , ,032 based Rubber 11,325 1,789 5, , , ,675 Oil palm- 22,154 1,601 6, ,561-95, ,384 based Food , ,782 processing Non- 131,179 26,715 40,452 11,830 22, ,908 1,017,036 Resource- Based Industry Electrical 48,685 8,688 10, , , ,765 and electronics Medical devices Textiles 12,810 1,913 6,925 5,937 9, , ,558 and apparel Macinery 15,803 1,398 3, ,622 89,983 & equipment 16

17 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Table 6. Continued Sector Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group7 Total Metal 42,942 9,832 16,854 5,326 8, , ,178 Transport 10,940 4,884 3, ,142-81, ,552 equipment Oter 27,657 4,578 11,757 2,394 7, , ,901 manufacturing Industry Oter 926, ,928 1,070,076 1,068,0021,292,560 1,117,288 2,940,346 8,956,274 Total 1,194, ,973 1,180,201 1,089,1141,352,834 1,117,288 4,721,081 11,252,206 Economy Source: Derived From Table 3 tere as been a cange in code from MIC 1972 to MSIC 2000 since 2000 for te data in manufacturing sector at 5 digits resulting in difficulties in matcing te classification. Tis could affect te quality of data. Given more time and resources, future researc can consider te labour productivity improvement adjustment factor by estimating elasticities of labour wit respect to output for various sectors and employment categories. References Adams, A.V., J. Middleton and A. Ziderman Manpower planning in a market economy wit labour market signals. International Labour Review 13(30): Amjad, R Te application of standard tecniques of manpower planning in developing countries: a ARTEP approac. In: Manpower Planning in ASEAN Countries, ed. K. Kalirajan and P. Arudsoty. Singapore: Regional Institute of Higer Educational and Development. Amjad, R Human Resource Planning: Te Asian Experience. ARTEP. ILO Asian Employment Program, New Deli: International Labour Office. Blaug, M Approaces to educational planning. Te Economic Journal 76: Bootby, D., W. Rot and R. Roy Te Canadian Occupational Projection System: A Metodological Enancement. Applied Researc Branc Researc Paper No R-95-). Ottawa: Human Resource Development Canada. Department of Statistics Malaysia Industrial Classification. Kuala Lumpur: Percetakan Nasional Berad. Department of Statistics Malaysia Standard Industrial Classification. Kuala Lumpur: Percetakan Nasional Berad. Department of Statistics (various issues). Input-Output Tables for Malaysia. Kuala Lumpur: Percetakan Nasional Berad. Holub, H.W. and G. Tappeiner An extenssion of input-output employment models. Economy System Researc 1(3):

18 Bee-Tin Poo, Zakaria Abdul Rasid and Mod Kairul Hisyam Hassan Hopkins, M Labour Market Planning Revisited. New York: Palgrave Macmillan. Huges, G Manpower Forecasting: A Review of Metods and Practice in Some OECD Countries. Dublin: Te Economic and Social Researc Institute and FAS- Te Training and Employment Autority. Huges, G An overview of occupational forecasting in OECD countries. International Contributions to Labour Studies 4: Malaysia Eigt Malaysia Plan. Kuala Lumpur: Percetakan Nasional Berad. Malaysia Nint Malaysia Plan. Kuala Lumpur: Percetakan Nasional Berad. Ministry of International Trade and Industry (MITI) Second Industrial Master Plan, : Executive Summary. Kuala Lumpur: Percetakan Zainon Kassim (M) Sdn Bd. Ministry of International Trade and Industry (MITI) Tird Industrial Master Plan. 2006, : Malaysia-Towards Global Competitiveness. Kuala Lumpur: Percetakan Nasional Bd. Ministry of Labour Dictionary of Occupational Classifiction (DOC)/Kamus Pengkelasan Pekerjaan. Kuala Lumpur: Percetakan Nasional Berad. Neugart, M. and K. Scomann Employment Outlooks : Wy Forecast te Labour Market and for Wom? Discussion paper FS ) Berlin: Labour Marker Policy and Employment Unit. Poo, B.T Structural Cange and Manpower Requirement in Malaysian Manufacturing Sector. PD proposal. Serdang: Universiti Putra Malaysia. Papps, K.L Occupational and Skill Forecasting: A Survey of Oversea Approaces wit Application for New Zealand. Occasional Paper 2001/1. Wellington: New Zealand Department of Labour. Psacaropoulos, G An Input-Output Model for te assessment of labour skill requirements. Higer Education 2: Psacaropoulos, G., H. Keit, D. Cristoper and H. Robinson Manpower Issue in Educational Investment: A Consideration of Planning Processes and Tecniques. Staff Working Papers No 624, Wasington, DC: World Bank. Psacaropoulos, G. and M. Woodall Education for Development: Analysis of Investment Coices. New York: Oxford University Press. Rama, I. and J. Idris Tecnological expansion and input elasticity of substitution in te Malaysian manufacturing sector. Malaysian Journal of Economic Studies 39(1&2): Rama, I. and J. Idris. 2002a. Impact of output level and input price on demand for labour and manpower requirement in te agriculture based manufacturing sector. Jurnal Ekonomi dan Manajeman 7 (1) : Rama, I. and J. Idris Elasticity of substation between foreign and local workers in te malaysian manufacturing sector. Pertanika Journal of Social Science and Humanities 14(1): Ritcer, L Manpower Planning in developing countries: canging approaces and empases International Labour Review 123: Scultz, T. P Education investments and returns. In: Handbook of Development Economics, ed. C. Hollis and T.N. Srinivasan, 1 st ed., vol. 1, pp Zakaria, A.R Costs of production and labour productivity: 1978 and 1983 Malaysian vintage tecnology. Jurnal Ekonomi Malaysia 23: Zakaria, A.R. and K.Y. Can Trade performance of Malaysian manufacturing product composition and factor intensities. Asian Economies 24:

19 Manpower Requirements of Malaysian Manufacturing Sector under te Tird Industrial Master Plan Zakaria, A.R. and K.Y. Can Measuring labour productivity troug labour requirement approac: te Malaysian experience. Pertanika Journal of Social Science & Humanities 5: Zakaria, A.R. and Siti Kairon, S Manpower requirements and supply in te Malaysian manufacturing sector: te case of an emerging industrial economy. In: Case Studies in Education Researc and Policy, Asian Development Bank, pp