Analysis of inter-industry relations in Pakistan: some further experiments with the 1975-76 data.
Syed, Aftab Ali
INTRODUCTION
Input-Output (I-O) tables of Pakistan's economy for the year
1975-76 were published by the Pakistan Institute of Development
Economics (PIDE) in 1983. They delineated the structure of production of
118 industries together with the disposition of their output by five
categories of final demand: consumption expenditures; gross fixed
capital formation; changes in stocks; exports; and re-exports. Imports
have been shown to be absorbed as intermediate inputs as well as
destined for final consumption. The present author presented an
analytical paper [3], based on the said data-base, in which despite the
useful industrial details captured, the pre-dominant agrarian nature of
Pakistan's economy was emphasized. Agricultural sector's
contribution to the total gross domestic product (GDP) at factor cost
amounted to 22.1 percent. Although the I-O tables identified some 81
manufacturing industries--both large-scale and small-scale--there were
only seven industries whose contribution to the total GDP was of any
significance. The manufacturing sector, as a whole, contributed only
about 11.7 percent of the total GDP. Service industries, construction
and the like still account for the rest of the GDP.
The present study, therefore, analyses the interdependence between
the agricultural sector and the rest of the economy. Agriculture has
been disaggregated into 8 subsectors whereas the rest of the economy has
been compressed into 6 sectors: non-crops; mining and quarrying;
large-scale manufacturing; small-scale manufacturing; construction; and
services. Table A 6 provides a concordance of industries used in this
study with those of PIDE's I-O classification of industries.
The plan of presentation is as follows. Section I describes the I-O
structure of production in terms of 14 sectoral disaggregation of
Pakistan's economy for 1975-76. Salient structural features of the
economy are highlighted. In Section II, an open output-determination
model of the Leontief type is formulated. It distinguishes between
domestic transactions and those arising from imports. Some empirical
applications of the formulated model are discussed in Section III.
Finally, in Section IV some concluding remarks and suggestions for
further research are presented.
I. SALIENT FEATURES OF PAKISTAN'S ECONOMY: 1975-76
The basic table of the Input-Output system is known as Transactions
Table in which are entered, in value terms, the various economic flows
within the economy during some particular base year. Such a table for
Pakistan's economy for the year 1975-76 appears in the Appendix as
Table A 1. The economy has been divided into 14 sectors. Output of each
sector is distributed along a row of the table while columns record the
inputs of the sectors in question.
The first row of Table A 1, for example, shows how the output of
the wheat sector was disposed of. The entry of 635,306 (in thousands of
rupees) in the first column relates mainly to the seeds sold off to
farms. The entries of 1,520,924 in Column (9), of 532,467 in Column
(11), and of 7,518,850 in Column (12) refer to the animals sold for
processing; wheat sold for milling, etc. In the columns of final demand
the output of wheat, for example, appears as being used by final
consumers directly, So, of the total wheat output of 12,396,121, some
82.3 percent goes for further processing and the rest ends up as being
used by final consumers.
If we look at the first column of Table A1, we see the various
items which were purchased by the wheat-growing sector in 1975-76. Apart
from the 635,306 mentioned above for Row (1), these were animal feeds,
fertilizers, agricultural machinery, services, etc., which were bought
as farm inputs.
The other entries in the wheat-growing Column (1) are: imports;
indirect taxes less subsidies; and value added. This sector imports
272,918 worth of agricultural machinery etc. as an input, pays no taxes,
and is not subsidized, whereas the expenditures on wages and salaries
amount to 6,972,335. The latter component is variously characterized as
value added or gross domestic product at factor cost representing the
remuneration paid to factors of production. The GDP is obtained by
deducting imports from total primary inputs (7,245,253 - 272,918 =
6,972,335). This result derives from the national accounting definitions
and so it can be seen that the input-output system is intimately
associated with the national accounts.
In an input-output table, total value of the output of each
productive sector, i.e. the row total, is always equal to its total
expenditure on inputs, i.e. the column total. For the wheat-growing
sector, this equality between the row total and column total can be
readily ascertained from the Transactions Table A1. No such equality,
however, is imposed on the Final Demand Sectors or on the Primary Input
Sectors. It is sufficient that all the final sectors taken together
should be equal to the total of the primary inputs. This would also be
apparent from Table A1--column total of final demand is equal to the row
total of primary inputs.
The equality of inputs and output in a Transactions Table is, of
course, an accounting identity. In preparing the accounts for each
sector, total output is first determined. Expenses, including imported
inputs, are deducted from this and the balance is defined as
"income arising" in the sector. This latter item can be taken
as being equivalent to wages, salaries, and profits. Hence, for each
production sector, wages, salaries, and profits plus other expenses are
equal to output.
An evaluation of the Transactions Table A 1 would show that the
economy of Pakistan produced goods and services worth about Rs 243.3
billion in 1975-76. By far the largest producer was the services sector
that was followed by large-scale manufacturing, non-crops sector, other
crops sector, and wheat-growing sector. The economy earned a total of
about Rs 8.76 billion from its exports--mostly from the manufactured
goods (Rs 8.39 billion). Imports of goods, both for intermediate use and
for final consumption, amounted to Rs 41.5 billion. The total output of
Rs 243.3 billion resulted in the creation of Rs 116.8 billion of value
added.
We have calculated the direct value-added and import coefficients
as a proportion of the output of various industries. These are shown in
Table A 2. An examination of the value-added coefficients would reveal
quite a variation in income-creating effects of production industries.
Generalizing, one can say that, with the exception of large-scale
manufacturing, small-scale manufacturing, and pulses, all other sectors
of the economy have high income per rupee of final demand. That is to
say, a large proportion of the production costs in these industries is
in the form of direct payments to factors of production. The
tobacco-growing sector has, by far, the highest value added of about 74
paisas on a rupee of expenditure. This is followed by the sugar-cane-
growing sector with a coefficient of about 0.66. On the other hand, in
goods-producing industries (both large-scale and small-scale
manufacturing), in which the costs of purchased materials absorb a
greater fraction of total outlays, the direct income created is
relatively small--0.18 for large-scale manufacturing and about 0.17 for
small-scale manufacturing.
Looking at the direct import coefficients, it would be clear that
the large-scale manufacturing and construction sectors have a higher
proportion of imported inputs than are had by other industries. It
should be borne in mind that these directly imported intermediate inputs
utilized by the industries in question eventually lead to chain effects
within the overall productive system, requiring additional indirect
imports.
II. THE INPUT-OUTPUT MODEL
Input-Output tables for the economy of Pakistan in 1975-76
distinguish between the transactions that arise through imports and
those arising through domestic production. However, imports are not
given in the form of a matrix for industry-by-industry transactions.
They are given as a row as shown in Transactions Table A1.
The notation and model are outlined below.
[X.sup.d.sub.ij] = Domestic output of industry i as input in
industry j (i, j = 1, 2, ... n);
[X.sup.m.sub.jj] = Total imports of industry ], used as an input in
industry j (j = 1,2, ..., n given as a row);
[X.sup.m.sub.j] = Level of importing activity or value of imports
of industry j;
[X.sup.d.sub.j] = Level of domestic output of industry j;
[X.sub.j] = [X.sup.d.sub.j] + [X.sup.m.sub.j]: Total supply of
industry j;
[Y.sup.d.sub.i] = Final demand for industry i (consumption -
investment - stock changes - exports);
[Y.sup.m.sub.i] - Final import demand in inudstry i;
D = [d.sub.ij] = [X.sup.d.sub.ij]/[X.sup.d]: Domestic output
coefficient matrix (14 x 14); and
M = [M.sub.jj] = [X.sup.m.sub.jj]/[X.sup.d.sub.j]: Diagonal import
input coefficient matrix (14 x 14).
The balance equation is
[X.sup.d.sub.i] + [X.sup.m.sub.i] = [n.summation over (J = 1)]
[d.sub.ij][X.sup.d.sub.j] + [M.sub.ii][X.sup.d.sub.i] + [Y.sup.d.sub.i]
+ [Y.sup.m.sub.i] ... ... (1)
Equation (1) can be partitioned and written in matrix notation:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)
where (I - D) refers to (14 x 14) input-output domestic
coefficients matrix, M refers to a 14 x 14 imports coefficients diagonal
matrix, [X.sup.d] refers to a 14 x 1 gross domestic output vector,
[X.sup.m] is a 14 x 1 vector of total imported output in each industry,
and [Y.sup.d] and [Y.sup.m] are domestic and imported final demand
vectors or order 14 x 1.
In this model, the intermediate import requirements are determined
by the domestic output levels and domestic output structure is
determined by the domestic input coefficients. The total final demand is
decomposed into two components: domestic and imported.
If we rewrite Equation (2) in terms of [MATHEMATICAL EXPRESSION NOT
REPRODUCIBLE IN ASCII], we obtain
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)
The inverse of the partitioned matrix on the right-hand side of
Equation (3) is
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
[(I - D).sup.-1] can be interpreted as the total requirement of
domestic output per unit of final demand in each of the industries in
the economy.
The column sums of [(I - D).sup.-1] indicate the total domestic
output requirements of sector j per unit of final demand of that
industry, while the off-diagonal elements of [(I - D).sup.-1] are the
direct output requirements emerging from that industry's output to
meet the final demand originating in that industry.
The import dependence of an industry is not fully reflected in the
imports it uses in the process of production. In so far as the industry
uses some domestically produced inputs and the domestic supplies have,
in turn, some import content, the total import content must incorporate
this indirect content also. An illustration will make the interpretation
of direct and indirect intermediate import requirements clear. The
textiles sector may be using some imported synthetic fibres, directly
and domestically produced chemicals, dyes, machinery and other inputs.
The domestic production of these inputs involves the use of imported
inputs and domestic inputs, which again have some import content. The
matrix M[(I - D).sup.-1] yields these direct and indirect import
requirements. The column sums of this matrix indicate total intermediate
import requirements per unit of final demand in industry j, while the
diagonal elements of this matrix yield direct import requirements in
that industry per unit of final demand.
III. SOME APPLICATIONS OF THE INPUT-OUTPUT MODEL OF PAKISTAN'S
ECONOMY
The output-determination model of Pakistan's economy, as
formulated in the preceding section, can be used for a variety of
simulation purposes: We have used it to compute sectoral output and
income multipliers. Additionally, we have utilized this model to measure
below the impact of increased exports on the domestic output levels of
Pakistan's economy.
The inverse matrix, variously called the 'impact' or
'multiplier' matrix, provides the total effects (both direct
and indirect) as a result of a unit change in the bill of final demand.
These computed total effects are shown in Table A 3. Let us examine this
table.
Column (2) lists, for each of the industries, the total domestic
requirements per unit of final demand in terms of gross domestic output.
These are, in fact, the column sums of the inverse matrix indicating the
results of the demands exerted on all industries for a unit increase in
the final demand for respective industries. Column (3) reflects the
total requirements supplied by the sector in question alone, whereas in
Column (4) are listed the requirements supplied by other industries
(indirectly). For example, a unit increase in the demand for wheat leads
to a total increase of 1.652 in the output. The total contribution of
the wheat sector itself is 1.069 and the remainder 0.583 is supplied by
all other industries. In other words, a unit (Rupee) increase in final
demand for wheat results in a total increase of 65 paisas. Wheat sector,
itself, contributes about 7 paisas worth of output, whereas the
remaining 58 paisas worth is supplied by other industries. A similar
interpretation is applicable to other industries listed in Table A 3.
It is evident that the domestic production by industries requires
imports. Columns (5) to (7) delineate these import requirements. These
have been obtained by adjusting the inverse matrix for imports - M[(I -
D).sup.-1] in Equation (4) of the model. As an example, for the
large-scale manufacturing sector, Column (5) would indicate that the
total import requirements to fulfil a unit increase in its final demand
required a total increase of about 50 paisas of imports. Almost half
this increase in imports was required by the sector itself and the
remaining half related to the other industries--Columns (6) and (7),
respectively.
A perusal of this table would clearly indicate that the largest
output increases, per unit of final demand change, are recorded for the
small-scale manufacturing sector. The total import requirements (of .69)
are rather small. This highest total increase is followed by the pulses
sector (2.226) and large-scale manufacturing sector (1.915). The import
content of the latter sector is, however, relatively high (0.498).
The largest indirect output requirements, per unit of final demand,
are recorded for the small-scale manufacturing sector (1.253), followed
by the pulses sector (1.151) and construction (0.777). The total import
requirements of these sectors are relatively low.
Sectoral Multipliers for Pakistan's Economy: 1975-76
The relationship between the initial expenditure and the total
effect triggered by this initial expenditure is known as the multiplier
effect. Multiplier analysis assists in appraising the accumulated impacts in all industrial sectors of the economy that follow from
exogenous changes in the final demands placed upon a given industry.
Numerical estimates of the multiplier (1) provide answers to "what
if" questions. For example, what happens to Pakistani incomes per 1
million rupees of expanded exports? Multipliers are, however, based on
quite simplified assumptions concerning the behavioural response-patterns of industries and consumers to changes in demand and
income. They should, therefore, be used with caution.
There are numerous multiplier concepts. (2) In this study, two
forms of multipliers have been computed for Pakistan's economy. The
output multiplier, for each industry, measures the direct and indirect
(i.e. total) output produced in all industries per unit of final demand
for the industry. The value-added (or income) multiplier shows the total
change in the gross domestic product (at factor cost) per Rupee change
in final demand. (3)
Sectoral multiplier values, estimated on the basis of the 1975-76
I-O study of Pakistan's economy, are presented in Table A 4. Since
imports enter the domestic production process, two sets of output
multipliers are presented--one with import leakages and the other based
on domestic outputs requiring no imports.
A glance at this table would show quite clearly that the
small-scale manufacturing sector is, by far, the largest producer of
output (with import) per unit of final demand change. It is followed by
the pulses and large-scale manufacturing sectors. If, however, imports
are not allowed to be used, the values of output multipliers show a
markedly different pattern. The small-scale manufacturing sector loses
its preponderance. It is replaced by the large-scale manufacturing
sector, which registers a high multiplier-value of about 2.67. This is a
striking result that suggests that output increases, as a consequence of
domestically processed inputs, have a significant potential. As an
industrial strategy, this potential should be tapped.
The largest income increases are registered for the non-crops
sector of the economy--a value of 2.87. This is followed by the
large-scale manufacturing sector, which shows an income multiplier of
2.66. The income multiplier values in the agricultural subsectors either
show lower values than their corresponding output multipliers (with
import leakages) or show increases almost similar to those registered
for outputs when imports are not taken into account.
The disaggregated summary measures of output and income estimated
for Pakistan's economy are analytically quite useful in that they
provide an analyst with a choice for policy-making purposes. Should one
opt for an output-creation objective of an income-generation objective
of an anticipated expenditure programme within an overall planning
framework?
Impact of Changes in Exports on the Domestic Output Levels
The object of an economic activity is satisfaction of final demand.
This fact has to be exploited by using the 'open' I-O model
specified. That is, exports, gross fixed capital formation, consumption
expenditure, changes in stocks and re-exports can be assumed to be
related to other sectors of production. These various components of
final demand are, however, autonomously determined by factors outside
the system. As an illustrative exercise, we have assumed that exports of
tobacco, oilseeds other than cotton, other crops, mining and quarrying,
and large-scale manufacturing increase by 10 percent each. The impacts
of these increases on the domestic output are measured. Results of this
simulation exercise are presented in Table A 5.
The large-scale manufacturing sector shows, by far, the largest
total increase in outputs. Although a 10-percent increase in the exports
of this sector leads directly to a marked stimulation of this sector (of
49.3 percent), the spin-off effects are shared evenly by other sectors
of the economy. Sectors like construction, small-scale manufacturing,
pulses, etc., are cases in point. The impact of increased exports of
tobacco, oilseeds other than cotton, non-crops, and mining and quarrying
is, however, felt basically by these sectors' increased production.
Other related industries do not show any significant increases in the
production levels. The impact of exports of the 'other crops'
sector appears rather uniform on the production level of other
industries. The largest total increase in production is, of course,
reflected in the sector in question.
The above simulation exercise is indicative of the fact that the
I-O model can serve as an important analytical tool for consistency
planning. It can assist the economic planners in formulating alternative
objectives for the planned expenditure programmes.
IV. CONCLUDING REMARKS AND SOME SUGGESTIONS FOR FURTHER RESEARCH
Input-Output tables of Pakistan's economy for the year 1975-76
became available in 1983. The present author analysed these tables, and
the results obtained [3] demonstrated that, although the industrial
details captured by the tables were quite commendable--118 industries
and five categories of final demand--the predominantly agrarian nature
of the economy was manifest. For the purposes of this study, the said
I-O tables have been aggregated into 14 broad sectors encompassing the
total economy. (4) The agrarian characteristics of the economy have been
preserved by highlighting 8 agricultural subsectors. Manufacturing
industries have been aggregated to form two broad sectors--large-scale
and small-scale. A close scrutiny of Table A 1 would show that of the
total output of the agricultural sector (of Rs 44.5 billion),
approximately 66 percent (i.e. about Rs 29.4 billion) is slated for
processing (inter-industry use). The output of the large-scale
manufacturing sector is split roughly half and half between the
intermediate use and final demand use. On the other hand, a higher
proportion of the services sector's output goes to final use (about
60 percent) than for intermediate use (40 percent).
The treatment of imports also deserves mention. In the earlier
study [3], imports were embedded in the domestic production and the
possibility of having all the input requirements met domestically was
distinctly recognized. Such a distinct recognition has been made in this
paper, and two separate sets of output multipliers--one with import
leakages and the other without them--have been estimated. An interesting
comparison is given in Table A 4. For example, if imports are not taken
into account in the small-scale manufacturing sector, its output
multiplier drops from 2.34 to 1.19. The situation is, however, reversed
for the large-scale manufacturing sector, where the output multiplier
value is higher (2.66) with no imports, as compared with the output
multiplier with import leakages (1.91).
One can also find the income multipliers in Table A 4. It should be
pointed out in this vein, however, that these multipliers refer to the
total income (value added) originating in the sectors under study. They
are deficient in that they do not refer to labour income or to the
profitability of an industry. Analytically what needs to be done is the
disaggregation of the value-added vector in terms of its various
components: the labour's share, profit, net income of
unincorporated business, etc.
The treatment of the public sector is quite inadequate. A clear
distinction between the goods-producing activities and general
administration must be maintained. The former entails splitting the
production of large-scale manufacturing sector into public and private
enterprises. The latter implies that the general administration of the
government producing only wages and salaries should be ascribed to the
final demand side of the I-O tables.
The I-O model has been used further m this study to measure the
impact of exogenous changes--increased exports, in our case--on the
domestic output levels of industries. It has been demonstrated that a
10-percent increase in the exports of the large-scale manufacturing
sector stimulates the domestic production quite significantly--not only
in this sector but also across the board. A similar increase in the
other agrarian exports results in a stimulation of the domestic
production of the sectors concerned. The spill-over effects for other
sectors are, however, quite restricted. This exercise demonstrates the
usefulness of an I-O model for varied policy-simulation purposes. It can
be effectively used as a tool for preparing consistent economic plans
for the country.
Comments on "Analysis of Inter-industry Relations in Pakistan:
Some Further Experiments with these 1975-76 Data"
The Study explores interdependence of agricultural and
non-agricultural activities in Pakistan. Although quite useful, the
study suffers from various shortcomings associated with sector
classification and data. My comments are grouped into the following four
main heads:
(i) Adequacy of the sectoral classification.
(ii) Data employed in the study.
(iii) Errors in the results reported.
(iv) Interpretation of the results.
I. SECTORAL CLASSIFICATION
The Input-Output table for 1975-76 (118 sectors)has been aggregated
into fourteen sectors--eight relating to agriculture and six to
non-agricultural activities. It is true that in order to focus on the
agricultural sector, aggregation of non-agricultural activities is
essential. However, the basic principle of sector classification is that
the differences in classifications of economic activities should not
affect the results in a very significant way. It is in this regard that
the Sector Classification Scheme adopted in the study is inadequate at
least on three counts:
(i) Since the demand of agriculture for manufacturing inputs, in
general, relates to chemicals, it would have been more meaningful to
analyse the inter-dependence if "Chemicals Sector" was
separated from other manufacturing activities.
(ii) Similarly, separation of water availability from other
services would have given more insights.
(iii) Agricultural processing has been included in manufacturing.
For purposes of this study, however, it would have been more useful if
either the agricultural processing was taken separately or was
integrated with Agriculture. It may be noted that it is because of this
sector classification that the study has reached the disturbing
conclusion that almost all the exports of Pakistan are of manufactured
goods.
II. DATA PROBLEMS
Input-Output tables and National Accounts are expected to give
similar results. However, if significant differences do exist, they need
to be explained, and it need be, should be corrected. Some of the
discrepancies/errors are as follows:
(i) The study shows no subsidies to agriculture sector in 1975-76,
while they amounted to Rupees 607 million on fertilizer, Rupees 381
million on pesticide and Rupees 24 million on tubewells.
(ii) As against Pakistan's actual exports of Rupees 11.25
billion, the study gives a very low figure of Rupees 8.70 billion. On
the other hand, imports of Rupees 41.5 billion taken in the study are
more than double the actual imports of Rupees 20.47 billion.
(iii) Indirect taxes minus subsidies given in the study are Rupees
3.75 billion, while National Accounts provide a figure of Rupees 10.63
billion.
(iv) Value-added is stated to be Rupees 141.5 billion on page 5,
while in the appendix it is Rupees 116.8 billion.
Results
The study presents rather odd results. For example:
(i) When import leakages are plugged, the multipliers are expected
to be higher, but except for large-scale manufacturing and the services
sectors, the multipliers reported in the study are smaller when imports
are substituted by local inputs.
(ii) In Table A 3, entries of imports requirements, specially
relating to services sector, are incorrect. These errors are also
carried into Table A4.
(iii) Results relating to income multipliers seem to be suspect and
need to be checked.
Interpretation of the Results
The results have been presented without drawing any implications.
The section needs to be strengthened. For example:
(i) Value added to output ratios have been presented for various
sectors. This information is innocuous unless these ratios are related
to capital and labour used in the sector.
(ii) Income multipliers show the changes in total demand when final
demand changes. The response of supply also needs to be analysed.
(iii) Export earnings have been analysed with a view to determine
the effect on total demand. The analysis could have been extended to the
net foreign exchange earnings if exports of different economic
activities had change by one unit.
In sum, the paper is on an interesting theme. If data problems are
resolved and sector classification is made more appropriate, it would
yield very useful insights, despite the limitation of Input-Output
Analysis such as constant returns and zero substitution between inputs.
A. R. Kemal
Ministry of Finance, Islamabad
APPENDIX
LIST OF TABLES
A 1. Transactions Table: 1975-76
A 2. Direct Value-added and Import Coefficients: 1975-76
A 3. Total (Direct plus Indirect) Output Requirements per Unit of
Final Demand: 1975-76
A 4. Sectoral Multipliers: 1975-76
A 5. Impact of a 10-percent Increase in Export on the Domestic
Output Levels of Industries: 1975-76
A 6. Concordance of Industries used in this Study with those of
PIDE's Classification
Table A1 Transactions Table: 1975-76
(Figures in Thousands)
Wheat Rice Cotton
Growing Growing Growing
Sectors (1) (2) (3)
l. Wheat 635,306 -- --
2. Rice -- 114,688 --
3. Cotton -- -- 120,107
4. Sugar-cane -- -- --
5. Tobacco -- -- --
6. Oilseeds other
than Cotton
Seeds -- -- --
7. Pulses -- -- --
8. Other Crops 84 10 24
9. Non-crops 2,220,263 638,343 704,945
10. Mining & Quarrying 35 26 118
11. Large-scale
Manufacturing 536,850 195,822 279,996
12. Small-scale
Manufacturing -- -- --
13. Construction -- -- --
14. Services 1,688,340 1,096,464 1,167,746
Total Inter-
industry 5,150,878 2,045 2,272,936
Primary Inputs
Imports 272,918 71,676 136,490
Indirect Taxes
less Subsidies -- -- --
Value Added 6,972,335 1,886,140 3,271,084
Total Primary 7,245,253 1,957,816 3,407,574
TOTAL INPUT 12,396,131 4,003,169 5,680,510
Oilseeds
Sugar- other than
cane Cotton
Sectors Growing Tobacco Seeds
(4) (5) (6)
l. Wheat -- -- --
2. Rice -- -- --
3. Cotton -- -- --
4. Sugar-cane 163,794 -- --
5. Tobacco -- 20,900 --
6. Oilseeds other
than Cotton
Seeds -- -- 11,334
7. Pulses -- -- --
8. Other Crops 13 2 --
9. Non-crops 278,435 17,367 203,447
10. Mining & Quarrying 29 4 1
11. Large-scale
Manufacturing 167,483 15,405 20,078
12. Small-scale
Manufacturing -- -- --
13. Construction -- -- --
14. Services 1,056,651 60,616 113,441
Total Inter-
industry 1,666,405 114,294 348,301
Primary Inputs
Imports 63,119 8,851 5,148
Indirect Taxes
less Subsidies -- -- --
Value Added 3,382,081 348,811 532,865
Total Primary 3,445,200 357,662 538,013
TOTAL INPUT 5,111,605 471,956 886,314
Other
Sectors Pulses Crops Non-crops
(7) (8) (9)
l. Wheat 1,520,924
2. Rice 231,000
3. Cotton --
4. Sugar-cane 451,000
5. Tobacco --
6. Oilseeds other
than Cotton
Seeds 81,170 --
7. Pulses -- 165,000
8. Other Crops 551,791 885,700 5,646,800
9. Non-crops 2,144,485 --
10. Mining & Quarrying -- 27 100,000
11. Large-scale
Manufacturing 74,709 338,081 69,130
12. Small-scale
Manufacturing -- -- --
13. Construction -- -- --
14. Services 196,993 2,025,647 1,662,347
Total Inter-
industry 903,993 5,393,940 9,846,201
Primary Inputs
Imports 25,410 142,115 --
Indirect Taxes
less Subsidies -- -- --
Value Added 286,572 9,139,933 13,908,199
Total Primary 311,982 9,282,048 13,908,199
TOTAL INPUT 1,215,975 14,675,988 23,754,400
Large.
Mining & scale
Sectors Quarrying Mfg. Mfg.
(10) (11) (12)
l. Wheat -- 532,467 7,518,850
2. Rice -- 83,266 2,463,187
3. Cotton -- 4,906,840 --
4. Sugar-cane -- 991,374 854,713
5. Tobacco -- 305,321 11,586
6. Oilseeds other
than Cotton
Seeds -- 77,394 609,084
7. Pulses -- -- --
8. Other Crops -- 206,027 288,951
9. Non-crops -- 1,275,320 200,797
10. Mining & Quarrying -- 339,544 154,195
11. Large-scale
Manufacturing 78,552 10,548,307 4,353,902
12. Small-scale
Manufacturing -- 38,022 2,258,904
13. Construction -- -- --
14. Services 444,855 7,981,012 3,442,346
Total Inter-
industry 523,407 27,284,894 22,156,515
Primary Inputs
Imports 102,450 9,158,279 1,654,145
Indirect Taxes
less Subsidies 18,873 3,375,673 --
Value Added 1,135,302 9,056,307 4,755,627
Total Primary 1,256,625 21,590,259 6,409,627
TOTAL INPUT 1,780,032 48,875,153 28,566,142
Total
Inter-
Sectors Construction Services industry
(13) (14)
l. Wheat -- -- 10,207,547
2. Rice -- -- 2,892,141
3. Cotton -- -- 5,026,947
4. Sugar-cane -- -- 2,460,881
5. Tobacco -- -- 337,807
6. Oilseeds other
than Cotton
Seeds -- -- 697,812
7. Pulses -- -- 246,170
8. Other Crops -- 622,437 7,650,048
9. Non-crops 534,848 52,800 8,892,841
10. Mining & Quarrying 811,178 195,107 1,600,264
11. Large-scale
Manufacturing 2,664,483 4,792,473 24,135,271
12. Small-scale
Manufacturing 1,310,084 - 3,607,010
13. Construction - 475,125 475,125
14. Services 1,134,870 11,576,397 33,647,055
Total Inter-
industry 6,455,463 17,714,339 101,876,919
Primary Inputs
Imports 2,070,890 7,181,867 20,893,358
Indirect Taxes
less Subsidies -- 359,073 3,753,619
Value Added 6,518,727 55,622,255 116,816,093
Total Primary 8,589,617 63,163,195 141,463,070
TOTAL INPUT 15 D45.080 80,877,534 243,339,989
Final Demand
Other Total
Final Final
Sectors Exports Demand Demand
l. Wheat -- 2,188,574 2,188,574
2. Rice -- 1,111,028 1,111,028
3. Cotton -- 653,563 653,563
4. Sugar-cane -- 2,650,724 2,650,724
5. Tobacco 99,556 34,565 134,121
6. Oilseeds other
than Cotton
Seeds 54,825 133,677 188,502
7. Pulses -- 969,805 969,805
8. Other Crops 121,757 6,904,363 7,026,120
9. Non-crops 1,450 14,860,109 14,861,559
10. Mining & Quarrying 85,542 94,226 179,768
11. Large-scale
Manufacturing 8,392,389 16,226,614 24,619,003
12. Small-scale
Manufacturing -- 24,959,132 24,959,132
13. Construction -- 14,569,951 14,569,951
14. Services -- 47,230,509 47,230,509
Total Inter-
industry 8,755,519 132,586,840 141,342,359
Primary Inputs
Imports -- -- 20,654,874
Indirect Taxes
less Subsidies -- -- --
Value Added -- -- --
Total Primary -- -- --
TOTAL INPUT -- -- --
Total
Sectors Output
l. Wheat 12,396,121
2. Rice 4,003,169
3. Cotton 5,680,510
4. Sugar-cane 5,111,605
5. Tobacco 471,928
6. Oilseeds other
than Cotton
Seeds 886,314
7. Pulses 1,215,975
8. Other Crops 14,676,168
9. Non-crops 23,754,400
10. Mining & Quarrying 1,780,032
11. Large-scale
Manufacturing 48,754,274
12. Small-scale
Manufacturing 28,566,142
13. Construction 15,045,076
14. Services 80,877,564
Total Inter-
industry 243,219,278
Primary Inputs
Imports 41,548,232
Indirect Taxes
less Subsidies --
Value Added --
Total Primary --
TOTAL INPUT --
Table A2 Direct Value-added and Import
Coefficients, 1975-76
Value
Sectors Added Import
Wheat 0.562 0.022
Rice 0.471 0.018
Cotton 0.576 0.024
Sugar-cane 0.662 0.012
Tobacco 0.739 0.019
Oilseeds other than Cotton 0.601 0.006
Pulses 0.236 0.021
Other Crops 0.623 0.010
Non-crops 0.585 --
Mining & Quarrying 0.638 0.058
Large-scale Manufacturing 0.185 0.187
Small-scale Manufacturing 0.166 0.058
Constructior 0.433 0.138
Services 0.688 0.009
Total Economy 0.480 0.086
Table A 3 Total (Direct Plus Indirect) Output Requirements
per Unit of Final Demand: 1975-76
(1) (2) (3) (4) (5) (6) (7)
Wheat 1.652 1.069 0.583 0.035 0.023 0.012
Rice 1.771 1.031 0.740 0.021 0.018 0.003
Cotton 1.606 1.031 0.575 0.031 0.025 0.006
Sugar-cane 1.474 1.036 0.438 0.015 0.013 0.002
Tobacco 1.354 1.047 0.307 0.020 0.019 0.001
Oilseeds other than
Cotton 1.611 1.013 0.598 0.006 0.005 0.001
Pulses 2.226 1.075 1.151 0.023 0.022 0.001
Other crops 1.562 1.108 0.454 0.018 0.011 0.007
Non-crops 1.642 1.060 0.582 -- -- --
Mining and Quarrying 1.417 1.001 0.461 0.063 0.058 0.005
Large-scale
Manufacturing 1.915 1.312 0.603 0.498 0.246 0.252
Small-scale
Manufacturing 2.339 1.086 1.253 0.069 0.063 0.003
Construction 1.778 1.001 0.777 0.141 0.138 0.003
Services 1.331 1.192 0.139 0.402 0.106 0.296
Column (2) Total direct and indirect domestic requirements per unit
of final demand in terms of gross outputs: [(I - D).sup.-1].
Column (3) Total direct domestic requirements per unit of final
demand: diagonal elements of [(I - D).sup.-1].
Column (4) Column (2) minus column (3): Total indirect domestic
requirements per unit of final demand.
Column (5) Total direct and indirect import requirements per unit
of final demand: M[(I - D).sup.-1].
Column (6) Total direct import requirements per unit of final
demand: diagonal elements of M[(I - D).sup.-1].
Column (7) Column (5) minus column (6): total indirect import
requirements per unit of final demand.
Table A4 Sectoral Multipliers: 1975-76
Sectors Output Multipliers
With Without
Import Import Income
Leakages Leakages Multipliers
Wheat 1.652 1.591 1.607
Rice 1.771 1.167 1.168
Cotton 1.606 1.292 1.294
Sugar-cane 1.474 1.250 1.182
Tobacco 1354 1.053 1.064
Oilseeds other than Cotton 1.611 1.000 1.043
Pulses 2.226 1.095 1.093
Other Crops 1.562 1.800 1.852
Non-crops 1.642 -- 2.870
Mining and Quarrying 1.417 1.086 1.103
Large-scale Manufacturing 1.915 2.663 2.659
Small-scale Manufacturing 2339 1.190 1.185
Construction 1.778 1.022 1.034
Services 1.331 44.667 4.531
Table A 5
Impact of 10 percent Increase in Exports on the
Domestic Output Levels of Industries: 1975-76
(In Thousands of Rupees)
Oilseeds
other
than Other Non-
Sectors Tobacco Cotton Crops crops
Wheat 57 8 7,413 335
Rice 70 10 6,544 286
Cotton 64 9 5,079 222
Sugar-cane 47 7 2,484 101
Tobacco 114,628 6 1,716 70
Oilseeds other
than Cotton 35 61,094 8,681 397
Pulses 84 12 18,055 831
Other Crops 36 5 148,467 267
Non-crops 22 3 36,127 1,692
Mining and
Quarrying 58 8 542 7
Large-scale
Manufacturing 939 129 3,207 98
Small-scale
Manufacturing 241 1,441 5,664 169
Construction 196 150 2,495 93
Services 67 10 1,601 11
Total 116,545 62,890 248,076 4,578
Mining & Large-scale
Sectors Quarrying Manufacturing
Wheat 191 731,896
Rice 233 899,459
Cotton 189 826,815
Sugar-cane 139 609,887
Tobacco 102 540,334
Oilseeds other
than Cotton 182 455,726
Pulses 361 1,084,692
Other Crops 153 467,662
Non-crops 481 284,554
Mining and
Quarrying 94,231 749,676
Large-scale
Manufacturing 962 12,111,693
Small-scale
Manufacturing 850 2,452,889
Construction 5,370 2,474,058
Services 370 861,066
Total 103,816 24,550,406
Table A 6 Concordance of Industries used in this
Study with those of PIDE's Classification
PIDE's
Industrial
Classification
Industries Numbers
1. Wheat 001-002
2. Rice 003-004
3. Cotton 005-006
4. Sugar-cane 007-008
5. Tobacco 009
6. Oilseeds other than Cotton 010
7. Pulses 011
8. Other Crops 012
9. Non-crops 013-015
10. Mining and Quarrying 016
11. Large-scale Manufacturing 017-067
12. Small-scale Manufacturing 068-097
13. Construction 098-104
14. Services 105-118
Note: For PIDE's classification, see [2] .
REFERENCES
[1.] Hirsch, W. Z. "Inter-industry Relations of Metropolitan
Area". Review of Economics and Statistics. Vol. 5.1959. pp. 79-94.
[2.] Saleem, M., et al. "Revised PIDE Input-Output Table of
Pakistan's Economy: 1975-76". Islamabad: Pakistan Institute of
Development Economics. 1983. (Research Reports Series, No. 139)
[3.] Syed, A. A. "Analysis of Inter-industry Relations in
Pakistan for 1975-76". Pakistan Development Review. Vol. XXIV, Nos.
3 & 4. Autumn-Winter 1985.
(1) These are obtained by dividing the value of total effect by
their corresponding direct value.
(2) Since the inverse matrix of Pakistan's economy utilized in
this study refers to the 'open' output-determination model,
the calculated multipliers shown are technically known as Type-I
multiplier coefficients. When the 'closed' version of the
model is used, the resulting multipliers are called Type-II multipliers.
For a detailed explanation of these various multipliers, see [1, pp.
79-94].
(3) For exact formulation of output and income multipliers used in
this study, see [3].
(4) The concordance between this 14-sector classification and the
original 118 industries is given in Table A 6.
AFTAB ALI SYED, The author is Senior Research Economist at
Statistics Canada, Ottawa (Canada). The views expressed in the paper are
wholly of the author and do not in any way reflect the views of
Statistics Canada.