Identification of key sectors in the Bangladesh

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Identification of key sectors in the Bangladesh economy: A linkage analysis approach Mohammad Alauddin

a

a

Visiting Fellow, Department of Economics, University of Newcastle, New South Wales, 2308, AustraliaCurrently on leave from Rajshahi University, Bangladesh. Available online: 28 Jul 2006

To cite this article: Mohammad Alauddin (1986): Identification of key sectors in the Bangladesh economy: A linkage analysis approach, Applied Economics, 18:4, 421-442 To link to this article: http://dx.doi.org/10.1080/00036848600000039

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Applied Economics, 1986, 18, 421-442

IdentiJication of key sectors in the Bangladesh economy: a linkage analysis approach MOHAMMAD ALAUDDIN

Downloaded by [UQ Library] at 04:53 20 June 2012

Visiting Fellow, Department of Economics, University of Newcastle, New South Wales 2308, Australia* This paper purports to identify key sectors in the Bangladesh economy employing the concepts of forward and backward linkages. An attempt is made to rank sectors according to their employment and output potentials. The paper draws a distinction between gross and net linkages defined respectively on the inverses of the Leontief Technology Matrix and the domestic matrix. Using data for Bangladesh, it is shown that the transition from gross to net linkages implies significant divergence in sectoral rankings. This appears to be true for ranking of sectors in terms of output and employment, suggesting a potential conflict between employment and output generation potentials particularly in the industrial sectors. When net linkages are considered, agricultural sectors appear to rank high on both counts.

I. I N T R O D U C T I O N In an effort to formulate his theory of economic development the concept of linkages was first explicitly introduced by Hirschman (1958). Linkages indicate the degree of structural interdependence in an economy and the extent to which the growth in one sector can provide stimulus to expansion in others. Since the pioneering study by Rasmussen (1956) a number of studies employing input-output technique have measured forward and backward linkages in order to identify 'key' sectors and assess relative employment and output generation potentials of different sectors within an economy.' The measurement of various linkages and identification of key sectors within an input-output model takes account of production interdependencies. A development strategy based on key sectors is likely to promote overall economic development (cf. Meller and Marfan, 1981, p. 266). Acharya and Hazari (1 971) employed concepts of 'gross'and 'net' linkages (the former defined on the basis of the inverse of the 'Leontief' matrix and the latter on the 'domestic' inverse matrix). Using data for India and Pakistan and some simple indices of linkages they provide *Currently on leave from Rajshahi university, Bangladesh. ' A few such studies are Diamond (1975), Hazari (1970), Hazari and Krishnamurty (1970), Jones (1976), Meller and Marfan (1 98 l), Schultz (1976) and Yotopoulos and Nugent (1 973, 1976). 0003-6846/86 $03.00 +.12

0 1986 Chapman and Hall Ltd.

42 1

M.Alauddin


422

empirical evidence that these two concepts imply very different ranking of sectors.' They argue that gross linkages may give a misleading picture of the potential for stimulating development. Further, in an import-dependent economy, it might be more logical to use net rather than gross linkages to assess the potentials for induced development. Higher priority to sectors ranking high on counts of net (output) linkages may thus be warranted, unless dictated otherwise by some special priorities like employment considerations (see Hewings, 1982, p. 95). A divergence between gross and net linkages has also been reported by Bulmer-Thomas (1978). The studies by Hazari (1970) and Hazari and Krishnamurty (1970) using Indian data and gross linkages have found evidence of a conflict between employment and output objectives in development planning. A study by Ahmed (1973) found similar evidence for Bangladesh. Apart from making use of only the inverse of the Leontief matrix, Ahmed's study suffers because he does not identify key sectors on the basis of the strengths of their linkages. Also Ahmed employed a highly aggregated 7-sector input-output framework, sacrificing a considerable amount of detail in the process. Given the limitations of using only gross linkages, the present study takes account of both gross and net linkage effects and follows Rasmussen (1956) in ranking sectors on their output and employment generation potentials. This is in order to see if there is any evidence of a likely conflict between interindustry employment and output potentials. i n view of a very high incidence of unemployment and underemployment in Bangladesh, as well as in other less developed countries (LDCs), considerations of employment assume critical i m p ~ r t a n c eThe .~ paper is organized as follows: Section I1 provides the analytical framework, while Section III discusses the data employed. Section IV presents empirical results and their interpretation. Finally, Section V concludes the paper. %I. A N A L Y T I C A L F R A M E W O R K Let A = n X n matrix of coefficients; h = n*X n diagonal matrix of imports; A = M X -'= n X n diagonal matrix of import coefficients; y = n X l final demand vector; X = n X l gross output vector.

,.

Define B = (1-A)-',

then the sum of the elements in the jth column of B

Acharya and Hazari define forward and backward linkages (gross and net) as merely the row and column sums of the appropriate inverse matrices. Many difficult definitions and measurement issues are involved in this regard. See, for example, Sen (1975). For a detailed analysis of the magnitude of employment problems in LDCs see Turnham (1971), Edwards (ed., 1974). For unemployment and underemployment rates as well as surplus labour in Bangladesh agriculture, which employsabout 80 % of the country's labour force, see Ahmed (1974).Ahmed (1978), Mujeri and Alauddin (1984), Muqtada (1975) and Saha (1982).

Key sectors in the Bangladesh economy

423

implies the total (direct and indirect) output requirement for a unit increase in the final demand for the output of sector j. Similarly, the sum of the elements in the ith row of B n

1 Bij = Bi. j= 1

indicates the increase in output of sector i needed to sustain a unit of final demand of all the sectors. Rasmussen (1956, pp. 133-4) interprets the column averages


'. . . as an estimate of the (direct and indirect) increase in output to be supplied by an industry chosen at random if the final demand of the products of industry number j ( j= 1,2, . . . n) increases by one unit'. He has given a similar interpretation of the set of averages However, in order to be able to make interindustry comparisons, the set of averages defined in Equations 3 and 4 above are normalized with the help of the overall mean defined as

and thus consider the indices

and Ui. =

C(1ln)Bi.l

(7)

Rasmussen terms U.j and Ui. respectively as 'index of the power of dispersion' and 'index of the sensitivity of dispersion'. U.j and Ui. can also be regarded as measures of backward and forward linkages as seen by Hirschman (1958, p. 98 Q. Keeping in view the interpretation of the averages in Equations 3 and 4 U.j 1 implies industry j draws heavily (i.e. compared to the industries in general) on the system of industries and vice versa if U.j < 1. Similarly Ui. > 1 would mean that industry i generally (i.e. relatively to the system ofindustries in general) will need to increase its output more than other industries for a proportionate increase in demand, i.e. an increase distributed according to the known distribution of final demand. The converse is true if Ui. < 1. It should be noted that the indices defined in Equations 6 and 7 are unweighted averages and as such are sensitive to the influence of some extreme values. Therefore, they may not alone serve as meaningful pointers to describe a prevailing structure with reference to the interindustry power and sensitivity of dispersion for the individual industries. Rasmussen (1956, pp. 137-8)

M . Alauddin

424

points out that a certain industry may have a high U.j and still most industries will be left unchanged if the final demand for the products of that industry is increased. This is the case where the structure of interindustry relations implies that the industry in question draws heavily on one or a few of the industries. A similar problem might obtain even though Ui. is fairly high. Thus the limitation of indices defined in Equations 6 and 7 calls for supplementary indices. These are the indices of variability defined as


and

A high V.j is interpreted as showing that a particular industry draws onesidedly on the system of industries and a relatively low V.j as an industry drawing evenly from the system of industries. Similar meanings can be attached to the Vi.s. Now a 'key' sector can be defined as one for which, (i) U.j and Ui. are greater than unity, and (ii) both V.j and V i. are relatively low. In Hirschman's definition, a 'key' sector is one that has high forward and backward linkages. An industry with U.j, U i . > 1 can be defined as a 'key' sector in the Hirschman sense. However, Hirschman does not mention any restrictions on V.j and V i. While the matrix B = (l - A ) - ' describes structure of intersectoral linkages in terms of output, where !t = n X 1 vector of labour output coefficients and Lij is an element of L, can describe structural interdependence in terms of employment creation. Thus Lij represents employment created in sector i per unit of final demand in sector j. Parallel to the indices defined in Equations 6 and 7 the backward and forward linkages in terms of employment are defined as

where L.j

Lij indicates the total (direct and indirect) labour input requirement per unit of

= i

final demand of any industry; and Li. =

Lij implies the increase in labour input required by i

sector i per unit increase in the final demand of all sectors within the system. If Ej > 1 for a sector then the system of industries as a whole will need a relatively large increment in employment to sustain a unit increase in final demand in sector j and vice versa for


425


Ej < 1. Similarly Ei > 1 would entail a greater increase in the use of labour inputs than other industries for a given increase in final demand and the opposite is true if Ei < 1. The indices Ej and Ei are likely to suffer from the same limitation of the indices defined in Equations 6 and 7. This calls for supplementary indices parallel to those defined in Equations 9 and 10, and are defined in this case as

Relatively higher or lower values of Fjs and Fis have similar significance to that of those defined in Equations (9) and (10). Thus a key employment sector may be defined as one in which (i) Ej and Ei are greater than unity, and (ii) Fj and Fi are relatively low. The indices of backward and forward linkages in terms of output and employment have been defined above using the total inverse B = (I -A)- ' and, therefore, they can be called as gross linkages. Now net linkage indices can be computed on the inverse net of imports defined as B' = (I - 2 ~ -) l . This derivation warrants a little elaboration. In the absence of any information regarding the intersectoral distribution of imports, the derivation of the domestic inverse assumes a stable relationship between imports and total supply? The balance equation of the input-output model using matrix notations mentioned at the beginning of this section can be written as X = Ax+y-m (15) Then

+ y]

X =~ [ A X

(16)

where the ith element of 2 is defined .as di = [xi/xi + mi]. Therefore, X

= [ l - a ~ ]-l2,

(17)

and (I - a ~ ) 1 is the domestic inverse. Using the domestic inverse, linkages similar to U.j and Ui. (with supplementary indices V.j and Vi. defined earlier for output) can be computed. For employment similar linkage indices can be derived using Let us designate the corresponding net output and employment linkages and their respective supplementary indices as U1.j, U'i., V1.j, V'i., E'j, E'i, F'j, and F'i. 111. T H E DATA We have used the latest available 47-sector input-output table (Bangladesh Planning Commission, 1980). The data contained therein relate to the year 1976-7. The input-output table also provided data on sectoral output and import vectors. 4Cf.Acharya and Hazari (1971, p. 109), Bangladesh Planning Commission (1980, p. 27), and Hazari (1967, pp. 159-60).


The employment figures used to derive sectoral labour coefficients were estimated from a number of sources. Without going into the controversies surrounding the conceptual and measurement issues, labour employment here is defined to include only those persons who were actually engaged in various sectors of the economy. Labour requirements for the agricultural crop sectors were estimated by using per acre labour requirement data for various crops from Bangladesh Planning Commission (1980a). This involved consideration of distribution of acreage by variety of crops and use of irrigation by techniques. The data of these variables were taken from Bangladesh Bureau of Statistics (1982). The estimation of labour requirements for livestock, forestry and fisheries sectors posed special problems. In the absence of any similar coefficients, employment figures in each of these sectors for 1975-6 were taken from Clay and Khan (1977, p. 21) and then adapting their respective growth rates from FAO (1974), the projected 1976-7 figures were estimated. The derivation of employment figures for the sectors within the nonagricultural complex involved approximation and arbitrariness to a certain degree. This was unavoidable because employment data according to the sector classification scheme used in the input-output table were not directly available from any sources. Various sources (such as Bangladesh Planning Commission 1980b, Table 6.2, Bangladesh Bureau of Statistics 1977, p. 443) provide employment data on the basis of broad categories of economic activity e.g. industry (large and medium; small and cottage), construction, services, transport, finance and banking, etc. Industrial employment was estimated to be in the vicinity of l .2 million man-years (Bangladesh Planning Commission 1980b; Weza 1978, p. 10). It consists of employment in large and medium firms (about 0.4 million), in handloom industries (0.2 million) and in small and cottage industries (about 0.6 million). The Census of Manufacturing Industries employment figures (for large and medium) available from Bangladesh Bureau of Statistics (1982, pp. 169 and 324 ff.) were used as they broadly conformed to the sector classification of the input-output table. The small and cottage industry figures were allocated to different industries according to the proportion of their value added except for those industries where small and cottage industry category was known to be nonexistent. These included sectors such as fertilizer, petroleum products, cement, basic metals. For mill-made cloth, jute textiles, cotton yam, no small and cottage component was added as it was included in the handloom sector. For the other nonagricultural sectors, construction (0.4 million), trade (0.99 million), finance and banking (0.07 million), electricity and gas (0.01 million), transport (0.4 million), services (2.61 million), employment figures were allocated for different component sectors according to the proportion of their value added in the broad category of economic activity to which they belonged. Data on sector classification, code used, output, import and employment are presented in Appendix E. IV. E M P I R I C A L R E S U L T S Tables 1 and 2 record identification of key sectors on the basis of both gross and net linkages in terms of output as well as employment potentials. From Table 1 it can be seen that on output potentials, 17 sectors emerge as key sectors in terms of gross backward linkage (petroleum, Bangladesh Planning Commission (1980, pp. 35-6).

Table 1. Key sector analysis: output potentials, Bangladesh 1976-7 Gross linkageb

Net linkage


back PETRLEUM ELCTRCTY PAPER CONSTRAN NONRESBL URBHOUSE MILLCLTH CONSELGS MISCINDS JUTETXTL RURHOUSE HANDCLTH CEMENT COTTNY RN TRANSERV BSCIMETL PHRMACEU

rnk

Sector

forw

rnk

Sector

PETRLEUM TR ADSERV BSICMETL MISCINDS TRANSERV OTHRCHEM COTTON OTHRCROP LIVSTOCK METLPROD

11.780 3.934 2.158 2.003 1.461 1.341 1.193 1.126 1.106 1.033

1 2 3 4 5 6 7 8 9 10

LEATHER URBHOUSE JUTETXTL NONRESBL SUGAR RURHOUSE CONSELGS CONSTRAN HANDCLTH ELCTRCTY WOOD TOBACCO FERTILZR HEALTH OTHRCONS BSICMETL JUTE TEA PUBLICAD FISHRIES HOUSSERV OTHRCROP RICE LIVSTOCK SALT

'See Appendix E for definition of codes. bback = backward linkage; forw = forward linkage; rnk = rank (in descending order).

back

rnk

Sector TRADSERV BSICMETL MISCINDS TRANSERV OTHRCROP FORESTRY LIVSTOCK PETRLEUM JUTE OTHRSERV ELCTRCTY COTTNYRN BANKINSR RICE WOOD

forw

rnk


428

M. A lauddin

electricity, paper, construction, transport, rural and urban housebuilding rank high), while there are 10 key sectors in terms of gross forward linkage (petroleum, trade service, basic metal, miscellaneous industries and transport service being top ranking). Only four (petroleum, miscellaneous industries, transport service and basic metals) are key sectors on both linkages. It is worth noting that none of the key sectors on backward linkage is agricultural while only three agricultural sectors (cotton, other crop and livestock) are key sectors on gross forward linkage, and then again they rank quite low. On the basis of net linkage, 25 are key sectors on backward linkage, while on forward linkage 15 are key sectors. Ranking high on net backward linkage are leather, urban housebuilding, jute textiles, nonresidential building and sugar. On net forward linkage high ranking sectors are trade service, basic metals, miscellaneous industries, transport service and other crops. Only 7 are key sectors when both forward and backward net linkages are considered. They are jute, rice, other crops, livestock, electricity, wood and basic metal. Thus in terms of gross linkage key sectors include those from the manufacturing industries and other sectors within the services and construction groups of economic activity. But in terms of net linkages most key sectors are nonindustrial and some agricultural sectors tend to emerge as key sectors, although not very high up in rank. Table 2 provides information which suggests that on gross employment potentials there are 16 key sectors (5 agricultural, 7 industrial and 4 others) on backward linkage and 13 key sectors (6 agricultural, 1 industrial and 6 others) on forward linkage. On both counts 9 sectors (5 agricultural, none industrial, and 4 others) can be considered key sectors. Notable among the key sectors in terms of employment are jute, rice, cotton, trade service,jute textile, livestcck and other crops. In terms of net employment potential, there are 18 key sectors (5 agricultural, 5 industrial and 8 others) on backward linkage, 13 key sectors (5 agricultural, none industrial, 8 others) on forward linkage and 1 1 key sectors (4 agricultural, none industrial, and 7 others) on both counts. The important sectors in this respect are jute, rice, livestock, jute textiles, trade service, and other construction. The information in Tables 1 and 2 when considered together indicates that on gross linkage, there are 4 key sectors (cotton yarn, cloth: mill-made, cloth: handloom and jute textile) in both output and employment terms on backward linkage criterion. On the forward linkage effect, there are 6 key sectors (3 agricultural, 1 industrial and 2 others). They are cotton, other crops, livestock, miscellaneous industries, trade service and transport service. On net linkages there are 18 key sectors in both output and employment on backward linkage criteria, important among them being jute, rice, jute textiles, other construction, livestock and cotton textiles. Using forward linkage there are 8 key sectors among which jute, rice, other crops, and construction deserve special mention. To sum up, we find that gross and net linkages imply very different rankings. Wankings on output and employment criteria make a significant difference. Nonagricultural sectors (industrial and nonindustrial) rank high on output terms while agricultural and other nonindustrial sectors rank high on employment. Agricultural output linkages are weak because of two reasons: first, the bulk of agricultural products goes directly to the consumers, and secondly, traditional agriculture is composed basically of primary activities and primitive industries, usually requiring a small proportion of inputs from other sectors. Strong employment linkages result in the main from a large proportion of value added such as labour being required in agriculture. The position of industrial sectors tends to change significantly


Table 2. Key sector analysis: employment potentials, Bangladesh 1976-7. (Abbreviations as in Table 1). Gross linkage

Net linkage

Sector

back

rnk

Sector

forw

rnk

Sector

back

rnk

Sector

forw

rnk

COTTON COTTNYRN JUTE RICE JUTETXTL HANDCLTH MILLCLTH LIVSTOCK OTHRCONS OTHRSERV EDUCATN LEATHER WHEAT HOUSSERV PUBLICAD HEALTH

3.190 2.524 2.249 2.007 1.888 1.565 1.535 1.412 1.383 1.143 1.134 1.107 1.100 1.096 1.064 1.050

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

TRADSERV COTTON JUTE LIVSTOCK RICE OTHRSERV OTHRCROP TRANSERV MISCINDS EDUCATN OTHRCONS FORESTRY PUBLICAD

8.071 6.500 3.333 2.835 2.363 2.195 1.732 1.723 1.276 1.090 1.077 1.037 1.035

1 2 3 4 5 6 7 8 9 10 11 12 13

JUTE RICE JUTETXTL LIVSTOCK OTHRCONS OTHRSERV EDUCATN HOUSSERV LEATHER PUBLICAD SALT TRADSERV HEALTH OTHRCROP SUGAR . FISHRIES WOOD HANDCLTH

3.525 3.076 2.841 2.130 1.895 1.800 1.764 1.690 1.594 1.519 1.432 1.415 1.409 1.275 1.271 1.206 1.164 1.038

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

TRADSERV JUTE RICE LIVSTOCK OTHRSERV OTHRCROP EDUCATN TRANSERV OTHRCONS HOUSSERV PUBLICAD FORESTRY SALT HEALTH MISCINDS

6.463 5.080 3.419 3.125 2.499 2.133 1.728 1.713 1.709 1.578 1.555 1.554 1.208 1.127 1.022

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15


M.A lauddin when net linkages and gross linkages are taken into account. 'This appears to support the hypothesis that sectors with high import content are likely to rank low when linkages are computed net of imports. One example is petroleum which has a very high import content and ranks high on gross linkage criteria but has a very low rank only on net forward linkage. Cotton, another example of high import content, ranks very high on gross employment linkage but fails to be among the key sectors in terms of net linkages. These aspects come into clearer focus when rankings of all the sectors are considered on the basis of strengths of gross and net linkages (forward and backward) and on output and employment potentials. This information is provided in Appendix A to D. To obtain a more definite picture of the difference in sectoral ranking by the two types of linkages as well as two types of objectives in development planning, rank correlation coefficients have been computed. These results are presented in Table 3. From part A of Table 3 we can see that the coeffiicents of rank correlation between gross and net linkages of sectors are quite low on output terms. For employment, the rank correlation between gross and net linkages of sectors does not appear to be low and in fact, for forward linkages, the coefficients appear to be quite high. From part B of Table 3, it can be seen that on gross linkage rank, difference between employment and output appears to be very high, suggesting a potential conflict between employment and output objectives. This difference, though still high, tends to narrow down when rank correlation coefficients of employment and output potentials are computed on the basis of net linkages. Table 3. Rank correlation between gross A.

Linkage

and net linkages

Rank correlation between gross and net linkages Output

Employment

Forward Backward

0.4 105 0.1958

0.8 106 0.5666

B. Linkage

Rank correlation between employment and output potentials Gross

Forward Backward

0.1766 -0.1671

Net 0.5468 0.5208

V. C O N C L U D I N G R E M A R K S

The transition from gross to net linkages leads to a significant divergence in sectoral rankings in terms of both output and employment in the case of a highly import-dependent economy like Bangladesh. There also appears to be a difference in ranks when employment and output linkages are considered. This clearly underlines the importance of drawing a distinction between gross and net linkages and consider trade-offs between output and employment. The net linkages are likely to provide a more realistic indicator of structural interdependencies among



43 1

productive sectors of the economy (cf. Lin and Yotopoulos, 1975, p. 4). When net linkages are considered, agricultural sectors which are less import-dependent appear to rank high on both counts. Thus a strategy of development based on the policy of developing nonagricultural sectors is likely to be less satisfactory in terms of employment generation. The linkage indices can be used as indicators for determining intersectoral allocation of resources. In terms of policy, our analysis indicates the sectors that might be given preference in Bangladesh if compatibility between the objectives of output growth and employment generation is to be ensured. It seems as though there is a case for expansion of agricultural sectors. Conceptual difficulties and statistical pitfalls surrounding the derivation and use of various linkage measures are inherent in input-output analysis, and warrant caution in interpreting the result^.^ In addition, there are a number of inadequacies specific to our analysis which need to be kept in mind. In the first place, our analysis is addressed to output and employment linkages, and considerations of consumption, fiscal, or income generation linkages were not accommodated. Secondly, existence of underemployment in agriculture might have introduced bias in our estimation of linkage indices. Although estimation of agricultural employment has taken account of only those actually employed, some bias may still be introduced inadvertently if the original data happened to contain some underemployment. Thirdly, our analysis does not consider the institutional framework of technology generation and the institutional framework of agro-rural development which are admittedly important variables underlying the process of output and employment growth. These limitations notwithstanding, it is still possible to obtain significant pointers from the linkage approach. The results of our analysis provide possible guidelines for incremental resource allocation in the planning process. The findings at this stage are, however, essentially tentative. Only further research with a broader scope can establish confidence in these results.

6 F ~limitations r of linkages and problems associated with the identification of key sectors see Bharadwaj (1966) and McGilvray (1977).


APPENDIX A.

O U T P U T POTENTIALS: GROSS A N D NET LINKAGES Backward linkage

Forward linkage

Grossb abs RICE WHEAT JUTE COTTON TEA OTHRCROP LIVSTOCK FISHRIES FORESTRY SUGAR EDIBLOIL SALT TOBACCO OTMRFOOD CQSTTNYRN MILLCLTN HANDCLTH JUTETXTL PAPER LEATHER FERTILZR

Net rnk

cov

rnk

abs

Gross

rnk

cov

rnk

Net

abs

rnk

cov

rnk

0.55 0.51 0.70 1.19 0.41 1.13 1.07 0.41 0.87 0.45 0.49 0.44 0.41 0.41 0.77 0.52 0.42 0.53 0.63 0.49 0.53

20 28 16 7 43 8 9 44 13 33 29 36 45 42 15 25 38 24 18 30 22

5.31 5.89 4.54 3.69 6.85 3.26 2.87 6.83 3.56 6.25 5.66 6.35 6.86 6.84 4.08 5.58 6.62 5.34 4.89 6.66 5.22

21 29 15 13 44 9 7 41 12 31 27 34 47 42 14 26 37 22 19 38 20

abs

rnk

cov

rnk

14 44 9 47 32 5 7 31 6 23 39 29 35 38 12 41 25 19 37 18 27

5.70 6.15 4.73 4.14 6.85 3.63 3.96 6.83 3.72 6.45 6.36 6.59 6.86 6.84 4.61 5.90 6.64 5.89 5.48 6.76 5.92

21 28 15 12 44 8 10 41 9 33 32 36 47 42 13 26 37 25 20 40 27

(Cont.)


A P P E N D I X A. (Cont.) PHRMACEU 1.05 OTHRCHEM 0.97 CEMENT 1.13 BSICMETL 1.06 METLPROD 0.94 MACHINRY 0.99 TRANSEQP 0.87 WOOD 0.73 MISCINDS 1.23 URBHOUSE 1.32 RURHOUSE 1.13 NONRESBL 1.35 CONSELGS 1.27 CONSTRAN 1.54 OTHRCONS 0.90 PETRLEUM 4.17 ELCTRCTY 2.49 GAS 0.55 TRANSERV 1.09 TRADSERV 0.52 HOUSSERV 0.56 HEALTH 0.96 EDUCATN 0.48 PUBLICAD 0.73 BANKINSR 0.59 OTHRSERV 0.43

17 20 13 16 22 18 27 33 9 6 11 5 8 4 26 1 2 42 15 44 40 21 46 32 38 47

3.17 3.56 4.04 4.57 3.59 3.34 3.71 4.17 3.28 2.54 2.81 2.53 2.84 2.85 3.43 6.21 4.66 5.10 4.43 5.48 4.95 3.39 5.84 3.96 4.80 6.52

9 17 27 33 19 13 22 28 12 2 5 1 6 7 16 46 34 39 29 43 37 15 45 26 36 47

0.67 0.45 0.73 1.17 0.27 0.22 0.20 1.31 0.89 1.62 1.49 1.61 1.46 1.44 1.17 0.62 1.38 0.92 1.00 0.92 1.04 1.18 0.88 1.08 0.99 0.85

40 42 38 16 44 45 46 11 33 2 6 4 7 8 15 41 10 32 26 31 21 14 34 19 28 35

4.31 4.30 4.74 5.64 4.53 4.43 4.62 4.53 4.74 3.67 4.03 3.70 4.21 4.10 5.09 6.29 4.63 6.21 5.92 6.20 5.51 4.85 6.45 5.35 5.75 6.74

15 0.47 14 1.34 24 0.95 37 2.16 19 1.03 16 0.92 20 0.54 18 0.53 23 2.00 1 0.43 4 0.44 2 0.45 10 0.44 6 0.42 27 0.42 45 11.78 21 0.67 43 0.52 40 1.46 42 3.94 35 0.41 25 0.42 46 0.41 31 0.52 39 0.60 47 0.80

31 6 11 3 10 12 21 23 4 37 35 32 34 40 39 1 17 26 5 2 47 41 46 27 19 14

6.47 2.48 4.63 2.47 3.06 3.32 5.70 5.35 1.94 6.57 6.31 6.22 6.29 6.66 6.85 2.34 4.57 5.40 1.97 0.80 6.86 6.72 6.86 5.48 4.63 3.49

35 6 18 5 8 10 28 23 2 36 33 30 32 39 43 4 16 24 3 1 45 40 46 25 17 11

0.44 0.55 0.73 2.12 0.36 0.23 0.16 1.02 2.06 0.87 0.91 0.90 0.90 0.85 0.86 1.43 1.14 0.99 1.87 4.05 0.83 0.85 0.83 1.00 1.05 1.17

42 40 36 2 43 45 46 15 3 24 20 22 21 28 26 8 11 17 4 1 33 30 34 16 13 10

6.49 3.42 4.69 3.35 3.47 4.10 5.88 5.45 2.33 6.57 6.31 6.36 6.35 6.73 6.85 2.93 5.41 5.77 3.10 1.43 6.86 6.74 6.86 5.80 5.42 4.87

34 6 14 5 7 11 24 19 2 35 29 31 30 38 43 3 17 22 4 1 45 39 46 23 18 16

"See Appendix E for definitions of sectors. babs = absolute value; cov = coefficient of variation; rnk = rank (in ascending order for coefficient of variation, in descending order for absolute value).


APPENDIX B . EMPLOYMENT A N D O U T P U T RANKINGS: GROSS LINKAGES" Output potentials

Employment potentials

Backward linkage

Forward linkage

Backward linkage

Forward linkage

Sector

abs

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

rnk

RICE WHEAT JUTE COTTON TEA OTHRCROP LIVSTOCK FISHRIES FORESTRY SUGAR EDIBLOIL SALT TOBACCO OTHRFOOD COTTWYRN MILLCLTH HANDCLTH JUTETXTL PAPER LEATHER

0.58 0.68 0.64 0.80 0.85 0.59 0.55 0.60 0.49 0.86 0.93 0.55 0.76 0.93 1.13 1.28 1.13 1.13 1.58 0.99

39 34 35 30 29 37 43 36 45 28 25 41 31 24 14 7 12 10 3 19

5.12 4.45 4.52 4.45 3.84 5.04 5.19 4.71 5.77 3.70 3.60 5.12 3.82 3.22 3.34 2.76 2.78 3.16 3.78 3.59

41 31 32 30 25 38 42 35 44 21 20 40 24 10 14 3 4 8 23 18

0.55 0.51 0.70 1.19 0.41 1.13 1.07 0.41 0.87 0.45 0.49 0.44 0.41 0.41 0.77 0.52 0.42 0.53 0.63 0.49

20 28 16 7 43 8 9 44 13 33 29 36 45 42 15 25 38 24 18 30

5.31 5.89 4.54 3.69 6.85 3.26 2.87 6.83 3.56 6.25 5.66 6.35 6.86 6.84 4.08 5.58 6.62 5.34 4.89 6.66

21 29 15 13 44 9 7 41 12 31 27 34 47 42 14 26 37 22 19 38

2.01 1.10 2.25 3.19 0.57 0.88 1.41 0.80 0.58 0.86 0.84 0.94 0.44 0.96 2.52 1.53 1.56 1.89 0.64 1.1 1

4 13 3 1 38 21 8 28 37 22 25 18 45 17 2 7 6 5 35 12

6.24 5.32 6.01 6.05 4.12 5.23 5.40 5.09 5.78 3.50 3.74 5.55 3.22 3.09 5.35 3.86 3.40 4.24 3.21 3.50

44 32 41 42 25 31 36 30 40 18 19 39 10 7 35 20 15 26 9 17

2.36 1.00 3.33 6.50 0.32 1.73 2.84 0.58 1.04 0.29 0.20 0.81 0.07 0.35 0.46 0.25 0.37 0.67 0.20 0.21

5 14 3 2 30 7 4 20 12 32 39 16 45 28 24 35 26 18 40 38

5.31 5.89 4.54 3.69 6.85 3.26 2.87 6.83 3.56 6.25 5.66 6.35 6.86 6.84 4.08 5.58 6.62 5.34 4.89 6.66

21 29 15 13 44 9 7 41 12 31 27 34 47 42 14 26 37 22 19 38

(Cont.)


APPENDIX B. (Cont.) FERTILZR PHRMACEU OTHRCHEM CEMENT BSICMETL METLPROD MACHINRY TRANSEQP WOOD MISCINDS URBHOUSE RURHOUSE NONRESBL CONSELGS CONSTRAN OTHRCONS PETRLEUM ELCTRCTY GAS TRANSERV TRADSERV HOUSSERV HEALTH EDUCATN PUBLICAD BANKINSR OTHRSERV

0.94 1.05 0.97 1.13 1.06 0.94 0.99 0.87 0.73 1.23 1.32 1.13 1.35 1.27 1.54 0.90 4.17 2.49 0.55 1.09 0.52 0.56 0.96 0.48 0.73 0.59 0.43

23 17 20 13 16 22 18 27 33 9 6 11 5 8 4 26 1 2 42 15 44 40 21 46 32 38 47

3.25 3.17 3.56 4.04 4.57 3.59 3.34 3.71 4.17 3.28 2.54 2.81 2.53 2.84 2.85 3.43 6.21 4.66 5.10 4.43 5.48 4.95 3.39 5.84 3.96 4.80 6.52

aAbbreviationsand codes as in Appendix A.

11 0.53 9 0.47 17 1.34 27 0.95 33 2.16 19 1.03 13 0.92 22 0.54 28 0.53 12 2.00 2 0.43 5 0.44 1 0.45 6 0.44 7 0.42 16 0.42 46 11.78 34 0.67 39 0.52 29 1.46 43 3.94 37 0.41 15 0.42 45 0.41 26 0.52 36 0.60 47 0.80

22 31 6 11 3 10 12 21 23 4 37 35 32 34 40 39 1 17 26 5 2 47 41 46 27 19 14

5.22 6.47 2.48 4.63 2.47 3.06 3.32 5.70 5.35 1.94 6.57 6.31 6.22 6.29 6.66 6.85 2.34 4.57 5.40 1.97 0.80 6.86 6.72 6.86 5.48 4.63 3.49

20 35 6 18 5 8 I0 28 23 2 36 33 30 32 39 43 4 16 24 3 1 45 40 46 25 17 11

0.57 0.72 0.84 0.65 0.33 0.55 0.55 0.52 0.79 0.86 0.83 0.74 0.83 0.73 0.91 1.38 0.65 0.54 0.34 0.64 0.91 1.10 1.05 1.13 1.06 0.53 1.14

39 32 24 34 47 41 40 44 29 23 27 30 26 31 20 9 33 42 46 36 19 14 16 11 15 43 10

3.07 2.90 2.90 4.02 3.98 3.95 3.17 3.38 4.08 3.25 2.72 2.83 2.75 3.44 3.25 5.34 4.79 3.22 5.43 5.53 6.37 6.21 4.57 6.58 5.34 4.88 6.76

6 5 4 23 22 21 8 14 24 12 1 3 2 16 13 34 28 11 37 38 45 43 27 46 33 29 47

0.06 0.13 0.55 0.10 0.16 0.63 0.30 0.21 0.53 1.28 0.26 0.24 0.27 0.36 0.39 1.08 0.05 0.12 0.34 1.72 8.07 0.99 0.71 1.09 1.04 0.55 2.19

46 42 22 44 41 19 31 37 23 9 34 36 33 27 25 11 47 43 29 8 1

15 17 10 13 21 6

5.22 6.47 2.48 4.63 2.47 3.06 3.32 5.70 5.35 1.94 6.57 6.31 6.22 6.29 6.66 6.85 2.34 4.57 5.40 1.97 0.80 6.86 6.72 6.86 5.48 4.63 3.49


APPENDIX C. EMPLOYMENT POTENTIALS: GROSS AND NET LINKAGESa Gross

Net

Backward linkage

Forward linkage

Backward linkage

Forward linkage

Sector

abs

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

RICE WHEAT JUTE COTTON TEA OTHRCROP LIVSTOCK FISHRIES FORESTRY SUGAR EDIBLOIL SALT TOBACCO OTHRFOOD COTTPdYR N MILLCLTH HANDCLTH JUTETXTL PAPER LEATHER

2.01 1.10 2.25 3.19 0.57 0.88 1.41 0.80 0.58 0.86 0.84 0.94 0.44 0.96 2.52 1.53 1.56 1.89 0.64

4 13 3 1 38 21 8 28 37 22 25 18 45 17 2 7 6 5 35 12

6.24 5.32 6.01 6.05 4.12 5.23 5.40 5.09 5.78 3.50 3.74 5.55 3.22 3.09 5.35 3.86 3.40 4.24 3.21 3.50

44 32 41 42 25 31 36 30 40 18 19 39 10 7 35 20 15 26 9 17

2.36 1.00 3.33 6.50 0.32 1.73 2.84 0.58 1.04 0.29 0.20 0.81 0.07 0.35 0.46 0.25 0.37 0.67 0.20 0.21

5 14 3 2 30 7 4 20 12 32 39 16 45 28 24 35 26 18 40 38

5.31 5.89 4.54 3.69 6.85 3.26 2.87 6.83 3.56 6.25 5.66 6.35 6.86 6.84 4.08 5.58 6.62 5.34 4.89 6.66

21 29 15 13 44 9 7 41 12 31 27 34 47 42 14 26 37 22 19 38

3.08 0.49 3.52 0.01 0.79 1.27 2.13 1.21 0.90 1.27 0.75 1.43 0.58 0.81 0.36 0.35 1.04 2.84 0.36 1.59

2 33 1 47 26 14 4 16 20 15 28 11 32 25 36 39 18 3 38 9

6.32 5.53 6.08 6.14 4.55 5.32 5.45 5.34 5.85 3.58 3.81 5.62 3.39 3.60 6.12 3.51 3.99 4.46 3.35 3.64

42 33 37 40 24 28 32 30 35 11 16 34 6 14 38 10 17 23 5 15

3.42 0.44 5.08 0.01 0.51 2.13 3.13 0.93 1.56 0.44 0.17 1.21 0.12 0.38 0.51 0.17 0.58 0.97 0.15 0.33

3 27 2 46 24 6 4 17 12 26 35 13 40 30 23 34 21 16 38 32

5.70 6.15 4.73 4.14 6.85 3.63 3.96 6.83 3.72 6.45 6.36 6.59 6.86 6.84 4.61 5.90 6.64 5.89 5.48 6.76

1.11

rnk 21 28 15 12 44 8 10 41 9 33 32 36 47 42 13 26 37 25 20 40 (Cont.)


APPENDIX C. (Cont.) FERTILZR PHRMACEU OTHRCHEM CEMENT BSICMETL METLPROD MACHINRY TRANSEQP WOOD MISCINDS URBHOUSE RURHOUSE NONRESBL CONSELGS CONSTRAN OTHRCONS PETRLEUM ELCTRCTY GAS TRANSERV TRADSERV HOUSSERV HEALTH EDUCATN PUBLICAD BANKINSR OTHRSERV

0.57 0.72 0.84 0.65 0.33 0.55 0.55 0.52 0.79 0.86 0.83 0.74 0.83 0.73 0.91 1.38 0.65 0.54 0.34 0.64 0.91 1.10 1.05 1.13 1.06 0.53 1.14

39 32 24 34 47 41 40 44 29 23 27 30 26 31 20 9 33 42 46 36 19 14 16 11 15 43 10

3.07 2.90 2.90 4.02 3.98 3.95 3.17 3.38 4.08 3.25 2.72 2.83 2.75 3.44 3.25 5.34 4.79 3.22 5.43 5.53 6.37 6.21 4.57 6.58 5.34 4.88 6.76

"Abbreviationsand codes as in Appendix A.

6 5 4 23 22 21 8 14 24 12 1 3 2 16 13 34 28 11

37 38 45 43 27 46 33 29 47

0.06 0.1 3 0.55 0.10 0.16 0.63 0.30 0.21 0.53 1.28 0.26 0.24 0.27 0.36 0.39 1.08 0.05 0.12 0.34 1.72 8.07 0.99 0.71 1.09 1.04 0.55 2.19

46 42 22 44 41 19 31 37 23 9 34 36 33 27 25 11 47 43 29 8 l

15 17 10 13 21 6

5.22 6.47 2.48 4.63 2.47 3.06 3.32 5.70 5.35 1.94 6.57 6.31 6.22 6.29 6.66 6.85 2.34 4.57 5.40 1.97 0.80 6.86 6.72 6.86 5.48 4.63 3.49

20 35 6 18 5 8 10 28 23 2 36 33 30 32 39 43 4 16 24 3 1

45 40 46 25 17 11

0.62 0.39 0.34 0.36 0.29 0.14 0.10 0.1 1 1.16 0.60 0.86 0.83 0.83 0.75 0.90 1.89 0.07 0.29 0.48 0.84 1.42 1.69 1.41 1.76 1.52 0.77 1.80

30 35 40 37 42 43 45 44 17 31 21 23 24 29 19 5 46 41 34 22 12 8 13 7 10 27 6

3.24 3.17 3.01 4.12 4.25 4.31 3.50 3.59 4.16 4.00 3.41 3.60 3.50 4.84 4.60 6.17 5.01 3.22 6.12 6.44 6.46 6.40 5.38 6.72 5.93 5.33 6.81


APPENDIX D. EMPLOYMENT A N D O U T P U T RANKINGS: N E T LINKAGESa Output potentials

Employment potentials

Backward linkage Sector RICE WHEAT JUTE COTTON TEA OTHRCROP LIVSTOCK FISHRIES FORESTRY SUGAR EDIBLOIL SALT TOBACCO OTHRFOOD COTFNYRN MILLCLTH HANDCLTN J UTETXTL PAPER LEATHER FERTILZR

abs

Backward linkage

Forward linkage

Forward linkage

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

rnk

abs

rnk

cov

rnk

23 43 17 47 18 22 24 20 30 5 27 25 12 29 37 39 9 3 36 1 13

5.72 5.34 5.14 5.15 5.07 5.47 5.45 5.44 6.10 4.17 4.09 5.57 4.67 4.21 6.27 4.26 4.28 3.99 4.48 4.19 4.23

38 30 28 29 26 34 33 32 41 7 5 36 22 9

1.03 0.29 1.38 0.00 0.84 1.78 1.51 0.84 1.68 0.88 0.55 0.85 0.81 0.57 1.10 0.46 0.86 0.97 0.62 0.98 0.85

14 44 9 47 32 5 7 31 6 23 39 29 35 38 12 41 25 19 37 18 27

5.70 6.15 4.73 4.14 6.85 3.63 3.96 6.83 3.72 6.45 6.36 6.59 6.86 6.84 4.61 5.90 6.64 5.89 5.48 6.76 5.92

21 28 15 12

3.08 0.49 3.52 0.01 0.79 1.27 2.13 1.21 0.90 1.27 0.75 1.43 0.58 0.81 0.36 0.35 1.04 2.84 0.36 1.59 0.62

2 33 1 47 26 14 4 16 20 15 28 11 32 25 36 39 18 3 38 9 30

6.32 5.53 6.08 6.14 4.55 5.32 5.45 5.34 5.85 3.58 3.81 5.62 3.39 3.60 6.12 3.51 3.99 4.46 3.35 3.64 3.24

42 33 37 40 24 28 32 30 35 11 16 34 6 14 38 10 17 23 5 15 4

3.42 0.44 5.08 0.01 0.51 2.13 3.13 0.93 1.56 0.44 0.17 1.21 0.12 0.38 0.51 0.17 0.58 0.97 0.15 0.33 0.08

3 27 2 46 24 6 4 17 12 26 35 13 40 30 23 34 21 16 38 32 42

5.70 6.15 4.73 4.14 6.85 3.63 3.96 6.83 3.72 6.45 6.36 6.59 6.86 6.84 4.61 5.90 6.64 5.89 5.48 6.76 5.92

21 28 15 12 44 8 10 41 9 33 32 36 47 42 13 26 37 25 20 40 27 (Cont.)

4 12 13 3 17 8 11

44 8 10 41 9 33 32 36 47 42 13 26 37 25 20 40 27


APPENDIX D. (Cont.) PHRMACEU OTHRCHEM CEMENT BSICMETL METLPROD MACHINRY TRANSEQP WOOD MISCINDS URBHOUSE RURHOUSE NONRESBL CONSELGS CONSTRAN OTHRCONS PETRLEUM ELCTRCTY GAS TRANSERV TRADSERV HOUSSERV HEALTH EDUCATN PUBLICAD BANKINSR OTHRSERV

0.67 0.45 0.73 1.17 0.27 0.22 0.20 1.31 0.89 1.62 1.49 1.61 1.46 1.44 1.17 0.62 1.38 0.92 1.00 0.92 1.04 1.18 0.88 1.08 0.99 0.85

40 42 38 16 44 45 46 11 33 2 6 4 7 8 15 41 10 32 26 31 21 14 34 19 28 35

4.31 4.30 4.74 5.64 4.53 4.43 4.62 4.53 4.74 3.67 4.03 3.70 4.21 4.10 5.09 6.29 4.63 6.21 5.92 6.20 5.51 4.85 6.45 5.35 5.75 6.74

aAbbreviationsand codes as in Appendix A.


APPENDIX E. SECTORS, CODES, O U T P U T , IMPORT A N D EMPLOYMENT

Sector classification

Code

01. Rice 02. Wheat 03. Jute 04. Cotton 05. Tea 06. Other crops 07. Livestock 08. Fisheries 09. Forestry 10. Sugar 11. Edible oil 12. Salt 13. Tobacco products 14. Other food 15. Cotton yarn 16. Cloth: Mill-made 17. Cloth: Handloom 18. Jute textile 19. Paper 20. Leather 21. Fertilizer 22. Pharmaceuticals 23. Other chemicals 24. Cement 25. Basic metals 26. Metal products 27. Machinery 28. Transport equipment 29. Wood 30. Miscellaneous industries 31. Urban housebuilding 32. Rural housebuilding 33. Nonresidential building 34. Constrn: Electrcty & Gas 35. Construction: transport 36. Other construction 37. Petroleum products 38. Electricity 39. Gas 40. Transport service 41. Trade service 42. Housing service 43. Health 44. Education 45. Public administration 46. Banking and insurance 47. Other service

RICE WHEAT JUTE COTTON TEA OTHRCROP LIVSTOCK FISHRIES FORESTRY SUGAR EDIBLOIL SALT TOBACCO OTHRFOOD COTTNY RN MILLCLTH HANDCLTH JUTETXTL PAPER LEATHER FERTILZR PHRMACEU OTHRCHEM CEMENT BSICMETL METLPROD MACHINRY TRANSEQUP WOOD MISCINDS URBHOUSE RURHOUSE NONRESBL CONSELGS CONSTRAN OTHRCONS PETRLEUM ELCTRCTY GAS TRANSERV TRADSERV HOUSSERV HEALTH EDUCATN PUBLICAD BANKINSR OTHRSERV

Source: As described in the text (Section 111).

Output Imports (million Taka)

Employment ('000man-yrs)

K e y sectors in the Bangladesh economy

ACKNOWLEDGMENTS The author is indebted to Professor C. A. Tisdell and Dr. C. W. Stahl for critical discussion at various stages of this paper. Acknowledgement of helpful suggestions is also due to an anonymous referee.


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