A social accounting matrix for the agricultural sector of Pakistan.

Havinga, Ivo C. ; Sarmad, Khwaja ; Hussain, Fazal 等

1. INTRODUCTION

The purpose of this paper is to analyse the effect of alternative agricultural policies on production, consumption and income distribution within a social accounting framework. This is done by applying the social accounting multiplier analysis on the agricultural SAM for Pakistan for the year 1979-80. The paper focuses attention on the agricultural production sector, the related food producing industrial sectors and food consumption sectors, which are represented in the agriculture SAM by disaggregated accounts, while all the other production sectors in the economy have been aggregated into a single account.

The paper is organized as follows: The SAM for the agricultural sector of Pakistan is presented in Section 2, followed by a discussion of multiplier decomposition in Section 3. Section 4 presents the results of the multiplier analysis and Section 5 gives a summary of the main results.

2. A SAM FOR THE AGRICULTURAL SECTOR OF PAKISTAN FOR 1979-80

The SAM for Pakistan's agricultural sector consists of the following main accounts: Wants account; Factors accounts; Institutions accounts; Activities accounts and an exogenous account which contains the flows of sectoral exports minus competitive imports, investments, net income transfers from the rest of the world and a government account. In addition, there is an exogenous account representing savings, indirect and direct taxes. Schematically, this is shown in Table 1 where the entries in the table denote matrices and vectors.

The flows of the endogenous accounts of the agricultural SAM are presented in Table 2. Rows and columns [W.sub.1] to [W.sub.8] in Table 2 give the wants accounts, which denote the household consumption expenditure on various commodity items. The factors accounts (row and columns [F.sub.9] to [F.sub.19]) record the receipts of factor incomes and their disbursement over various spending institutions. The institutions accounts (rows and columns 120-130) highlight the divisions of the household sector into various household groups. The receipts and expenditures of the institutions accounts are recorded in row and column 20 to 30 respectively, while the activities accounts (row and columns [S.sub.31] to [S.sub.45]) record the input-output production flows, which have been obtained by aggregating the PIDE Input-Output Table for 1975-76.

The exogenous accounts consist of the government account, the capital account and the rest of the world account. These accounts include indirect taxes, subsidies, payments of pensions, savings, investment, exports and imports.

3. DECOMPOSITION OF SAM MULTIPLIERS

The SAM-multiplier model is developed along similar lines as the traditional input-output model with the difference that the SAM-multiplier model takes account of the structure of production as well as factor income and its distribution across household groups and other spending institutions.

Mathematically, the SAM-multiplier model can be represented by the following matrix equation:

y = Ay + X ... ... ... (1)

where

A is the matrix of endogenous accounts consisting of elements shown by the [A.sub.ij] matrices in Table 1, X is the vector of exogenous outgoings, and y is the vector of row totals.

Equation (1) can be rewritten as:

y = [M.sub.a]X ... ... ... ... (2)

where

[M.sub.a] is the matrix of aggregate multipliers.

Following Pyatt, G. and A. Roe (1977) we can rewrite Equation (1) as

y = [A.sup.*.sub.y] + [(I - [??]).sup.-1] X ... ... ... (3)

where

A = matrix of diagonal elements of the exogenous accounts in Table 1,

(I-[??])= the transfer multiplier, denoted by [M.sub.1'], which represents the total production effects arising from changes in final demand, and

[A.sup.*] = [(I-A).sup.-1] (A-[??]).

Substituting for (I-[??]) and solving Equation (3) we get

y = [(I-[A.sup.*].sup.-1] [M.sub.1]X ... ... ... (4)

We have shown elsewhere [I. Havinga, K. Sannad et al., (1987)] that the matrix [(I-[A.sup.*]).sup.-1] can be split into two commutative submatrices denoted by [M.sub.2] and [M.sub.3] such that if

[(I-[A.sup.*]).sup.-1] = (I+[A.sup.*] + [A.sup.*2] + [A.sup.*3])[(I-[A.sup.*4]).sup.-1] then

[(I-[A.sup.*]).sup.-1] = (I+[A.sup.*] + [A.sup.*2] + [A.sup.*3])(I+[A.sup.*4] + [A.sup.*8] + ... + [A.sup.*n]) = [M.sub.2][M.sub.3]

where

[M.sub.2] measures the open loop effect, and [M.sub.3] measures the closed loop effect. We have also shown that the commutative nature of [M.sub.2] and [M.sub.3] does not affect the aggregate multiplier matrix [M.sub.a], and that the actual path of the impact of exogenous changes in X on y remains the same.

4. RESULTS

Aggregate Multipliers

Table 3 reports the aggregate SAM multipliers (the matrix [M.sub.a]) Rows 1 to 8 show the total impact of an exogenous change in the demand in each of the eight agricultural sectors on consumption. The wheat sector has slightly higher impact multipliers as compared to the other agricultural sectors. In general, the impact multipliers show that the food sectors have greater potential for generating higher growth rates as compared to non-food sectors.

Rows 10 to 11 reflect the total impact of an exogenous change in demand in each of the eight agricultural sectors on the pattern of income distribution. Income changes have been normalized by the total change and reported in Table 4. The results reported in Table 4 show that an exogenous increase in demand in the agricultural sector causes a redistribution of income in favour of the medium and small-farm households, the landless and non-farm households, at the cost of the large farm and urban households and firms. The redistribution effects of an increase in demand of the agricultural goods processing industries are less progressive in the rural areas, as large-farm households tend to benefit more, but more progressive in the urban areas as the poorest households derive relatively higher benefits.

Disaggregate Multipliers

Transfer Effects: Table 5 presents the matrix [M.sub.1], which describes the technical impact multipliers of the Leontief inverse. The matrix shows that with the exception of the pulses sector the backward linkages between the various agricultural sectors are more or less the same, but generally lower than those observed for the agricultural processing sectors, as well as for the other manufacturing and services sectors.

Closed-Loop Effects: Table 6, which reports the matrix [M.sub.3] shows that the closed-loop effects are higher than the transfer effects, implying that private household consumption has a greater impact on the production structure as compared with the other components of aggregate demand. Changes in the pattern of household consumption influence the various sectors in different degrees e.g. the largest forward linkages of 12.9 and 12.5 are generated by the other manufacturing sector and the services sector respectively, while the edible oils and other food sectors generate the smallest linkages.

Open-Loop Effects: Table 7, which reports the open-loop effects shows that an exogenous increase in the demand of the agricultural production sectors would redistribute income in favour of rural households. While a similar result is obtained for the agricultural processing sectors, there is in addition, a favourable redistribution of income in favour of poor households in the urban areas. These results are in sharp contrast to the regressive redistribution of income that would be caused by an exogenous increase in demand of the services sector.

Interdependence

A comparison of the impact multipliers in Tables 3 and 5 shows that the backward linkages reported in Table 3 (aggregate SAM Multipliers) are higher as compared to those in Table 5 (Leontief multipliers). This suggests a stronger interdependence between production sectors within the SAM framework as compared to the interdependence of production sectors within a Leontief framework. Table 8 gives a comparison of the degree of interdependence for the two frameworks.

Table 8 shows that only 8 percent of the Leontief multipliers exceed the value of 0.75 as compared with 21 percent of the aggregate SAM multipliers.

5. CONCLUSIONS

In this paper a SAM for the agricultural sector of Pakistan for the year 1979-80 has been presented. The SAM multiplier analysis yielded an aggregate SAM multiplier matrix, which was decomposed into different matrices representing the transfer, closed-loop and open-loop effects.

The results showed that when there is an exogenous increase in demand the food production sectors cause a much greater impact on household consumption as compared to the non-food production sectors. Within the agricultural sector the wheat producing sector produces the largest linkages. The results show that an exogenous increase in demand in the agricultural sector would also generate progressive income redistributional effects in the rural areas. A comparison of the Leontief multipliers with the aggregate SAM multipliers shows that the latter have stronger sectoral interdependence and a more heterogenous production structure. This suggests that when simulating the effect of various policy measures the SAM-multiplier model yields better results as compared with the input-output model.

Comments on "A Social Accounting Matrix for the Agricultural Sector of Pakistan"

One appreciates to see in this paper the application of one of the latest modelling techniques, namely, the Social Accounting Matrix (SAM) to the analysis of the agricultural sector in Pakistan. The authors have rightly claimed the superiority of this technique over the input-output model which helps in explaining the production account of the economy only. In the case of Pakistan, where not much is yet known about the macro relationships, treatment of agricultural production consumption, investment and income distribution within an overall economic setting provides a useful framework to understand the problems of this sector.

However, the following comments are offered to sharpen its analytical content.

First, a relatively minor point is that the authors in an attempt to be compact and precise in their writing have become somewhat abstract and unclear. I believe that while introducing a new technique such as SAM and new terminologies such as

[M.sub.1] = Transfer effect of X;

[M.sub.2] = 'Open-loop' effect;

[M.sub.3] = 'Closed-loop' effect of all endogenous account;

and 'Agricultural Satellite SAM', it would have helped the reader if those concepts were elaborated more clearly and systematically. At present the readers feel lost when the authors present something in Table 1, and even in Table 2, but with little explanation Of the entries in those tables.

Second, the authors do not disclose the sources of the data used and the quality of those data. Obviously, no matter how sound a particular analytical technique is, the usefulness of empirical results depends on the accuracy of data used in its estimation. The authors do state that identifying data gaps is one of the objectives of their paper. But neither such gaps nor the problems of data actually used have been mentioned anywhere in the paper.

Third, one of the common problems which I have observed in the analytical part of the paper is that the interpretation of the results is very mechanical. The authors do not try to highlight the significance of the results which otherwise are quite interesting. For example, while elaborating the consumption effect of various exogenous changes it is stated that the 'wheat sector' has a slightly higher effect than the rest of the agricultural sector. It is not clear why so? Similarly, it is not clear why there was a relatively more increase in consumption of pulses and livestock at the same time in response to exogenous changes. How comparable are their findings, with consumption behaviour observed in other studies is an important question which has also not been dealt with in the paper.

Fourth, the most intriguing part of the results relates to the effect of growth on income distribution. The authors find this effect in agriculture to be positive, particularly for small farmers and landless labourers. This might be a valid finding but unless the authors explain how actually this happened one cannot accept it as there is a great deal of empirical evidence against it, for example, see K. Griffin, (1972); M. H. Khan (1979); and Faiz Mohammad (1986).

Moreover, it is not clear why the authors left out 'tenants' as one of the 'institutional groups' in the agricultural sector of Pakistan in their analysis.

Fifth, I feel that the authors need to qualify their statement about the intersectoral production relationships and their effect on income distribution. Strong forward or backward linkages of agricultural production with other sectors does not necessarily mean better income distribution in a sector. Expansion in agricultural production must be accompanied by increased demand for labour, better terms of trade, and improved ownership distribution to have a favourable effect on income distribution.

Finally, there was a need to point out somewhere in the paper the weakness of the SAM model as applied to the agricultural sector in Pakistan. Besides being static in nature, its omission of prices, agrarian structure, and particularly interfarm transfers of land and other assets does not allow an unquestioned use of this model. Similarly, from the point of a developing country where the behaviour of production, consumption and investment over time of a sector is of crucial importance, a static model has limited relevance. However, this problem is common to studies based on SAM and should not undermine the worth of the present paper.

Faiz Mohammad

International Institute Islamic Economics, Islamabad

REFERENCES

Griffin, Keith (1972). The Political Economy of Agrarian Change. Cambridge, Mass.: Harvard University Press.

Khan, M. H. (1979). The Economics of Green Revolution. New York, Washington and London: Praeger Publishers.

Mohammad, Faiz (1986). "Wealth Effects of the Green Revolution in Pakistan". Pakistan Development Review. Vol. XXV, No. 4.

REFERENCES

Cohen, S. I. (1986). "Social Accounting and Multiplier Analysis for Pakistan". Paper presented at Technical Workshop on Social-economic Accounting, Modelling and Surveying, held at Islamabad on April 9-10, 1986.

Havinga, I., et al. (1987) "An Agricultural Satellite SAM: With an Application to Pakistan". Paper presented at the Fourth Annual General Meeting of the Pakistan Society of Development Economists, held at Islamabad on August 1-3, 1987.

Pyatt, G., and A. Roe (1977). Social Accounting for Development Planning with Special Reference to Sri Lanka. Cambridge : Cambridge University Press.

IVO C. HAVINGA, KHWAJA SARMAD, FAZAL HUSSAIN and GHULAM BADAR, The authors are Senior Lecturer at the Institute of Social Studies, The Hague, Holland, Senior Research Economist and Staff Economists, respectively at the Pakistan Institute of Development Economics, Islamabad.

Table 1
Schematic Presentation of the SAM

 1. Wants 2. Factors 3. Institu-
Receipts Account Account tions Account

Endogenous 1. Wants [A.sub.13]
 2. Factors
 3. Institutions [A.sub.32] [A.sub.33]
 4. Activities [A.sub.41]

Exogenous Others Residual Balance

Totals [Y'.sub.1] [Y'.sub.2] [Y'.sub.3]

 4. Activities Exogenous Total
 Account Account
Receipts
 Government, Capital
 & Rest of the World

Endogenous 1. Wants [X.sub.1] [Y.sub.1]
 2. Factors [A.sub.24] [X.sub.2] [Y.sub.2]
 3. Institutions [X.sub.3] [Y.sub.3]
 4. Activities [A.sub.44] [X.sub.4] [Y.sub.4]

Exogenous Others

Totals [Y'.sub.4]

Table 2
Agriculture SAM for Pakistan 1979-80

 I 20 I 21 I 22 I 23 I 24

W 1 Wheat and Flour 861. 1111. 9851. 103. 131.
W 2 Rice and Flour 303. 290. 1436. 55. 550.
W 3 Pulses 190. 365. 915. 58. 421.
W 4 Sugar 1075. 3175. 1086. 134. 870.
W 5 Live Stock 2022. 3771. 16819. 38. 692.
W 6 Edible Oils 433. 897. 1090. 107. 596.
W 7 Miscellaneous 3866. 4257. 4952. 36. 1607.
 Food
W 8 Other Commodities 14876. 13116. 3266. 372. 3909.

 Total 23625. 26982. 68810. 904. 8777.

 I 25 I 26 I 27 I 28 I 29

W 1 Wheat and Flour 20. 225. 831. 974. 2105.
W 2 Rice and Flour 8. 84. 264. 290. 672.
W 3 Pulses 5. 58. 210. 244. 532.
W 4 Sugar 13. 142. 467. 525. 1186.
W 5 Live Stock 61. 651. 1938. 2080. 4923.
W 6 Edible Oils 15. 166. 572. 653. 1451.
W 7 Miscellaneous Food 66. 693. 2057. 2214. 5232.
W 8 Other Commodities 299. 2985. 7494. 7756. 19352.

 Total 487. 5005. 13833. 14737. 35453.

 S 31 S 32 S 33 S 34 S 35

F 9 Large Holdings 920. 198. 138. 34. 1204.
F 10 Medium Holdings 1759. 761. 265. 66. 2303.
F 11 Small Holdings 7431. 3214. 1118. 278. 9727.
F 12 Landless 152. 66. 23. 6. 199.
F 13 Non-farm 1086. 469. 163. 41. 1422.
F 14 Employer 5. 2. 1. 0. 7.
F 15 Professional 2. 1. 0. 0. 3.
F 16 Non-manual 3. 1. 0. 0. 4.
F 17 Manual 149. 64. 22. 6. 195.
F 18 Self-employed 634. 274. 95. 24. 831.
F 19 Firms 628. 271. 94. 24. 827.

 Total 12769. 5521. 1919. 479. 16722.

 S 36 S 37 S 38 S 39 S 40

F 9 Large Holdings 625. 101. 1076. 270. 130.
F 10 Medium Holdings 1195. 193. 2058. 232. 112.
F 11 Small Holdings 5047. 816. 8695. 366. 177.
F 12 Landless 103. 17. 178. 0. 0.
F 13 Non-farm 737. 119. 1270. 41. 18.
F 14 Employer 4. 1. 6. 7. 3.
F 15 Professional 1. 0. 2. 28. 12.
F 16 Non-manual 2. 0. 4. 81. 36.
F 17 Manual 101. 16. 174. 290. 128.
F 18 Self-employed 431. 70. 742. 331. 146.
F 19 Firms 426. 68. 735. 256. 77.

 Total 8672. 1401. 14940. 1902. 839.

 S 41 S 42 S 43 S 44 S 45

F 9 Large Holdings 218. 179. 586. 5352. 14460.
F 10 Medium Holdings 187. 154. 504. 4605. 12442.
F 11 Small Holdings 295. 243. 795. 7257. 19608.
F 12 Landless 0. 0. 0. 0. 15.
F 13 Non-farm 30. 25. 81. 741. 1989.
F 14 Employer 5. 4. 15. 133. 374.
F 15 Professional 20. 17. 55. 502. 4665.
F 16 Non-manual 60. 49. 161. 1468. 12044.
F 17 Manual 214. 176. 576. 5256. 7202.
F 18 Self-employed 244. 201. 657. 5998. 25280.
F 19 Firms 128. 105. 345. 3147. 7670.

 Total 1401. 1153. 3775. 34459. 105749.

 F 9 F 10 F 11 F 12

I 20 Large Holdings 27400. 0. 0. 0.
I 21 Medium Holdings 0. 28620. 0. 0.
I 22 Small Holdings 0. 0. 69390. 0.
I 23 Landless 0. 0. 0. 810.
I 24 Non-farm 0. 0. 0. 0.
I 25 Employer 0. 0. 0. 0.
I 26 Professional 0. 0. 0. 0.
I 27 Non-manual 0. 0. 0. 0.
I 28 Manual 0. 0. 0. 0.
I 29 Self-employed 0. 0. 0. 0.
I 30 Firms 0. 0. 0. 0.

 Total 27400. 28620. 69390. 810.

 F 13 F 14 F 15 F 16

I 20 Large Holdings 0. 0. 0. 0.
I 21 Medium Holdings 0. 0. 0. 0.
I 22 Small Holdings 0. 0. 0. 0.
I 23 Landless 0. 0. 0. 0.
I 24 Non-farm 8780. 0. 0. 0.
I 25 Employer 0. 640. 0. 0.
I 26 Professional 0. 0. 5980. 0.
I 27 Non-manual 0. 0. 0. 15670.
I 28 Manual 0. 0. 0. 0.
I 29 Self-employed 0. 0. 0. 0.
I 30 Firms 0. 0. 0. 0.

 Total 8780. 640. 5980. 15670.

 F 17 F 18 F 19

I 20 Large Holdings 0. 0. 0.
I 21 Medium Holdings 0. 0. 0.
I 22 Small Holdings 0. 0. 0.
I 23 Landless 0. 0. 0.
I 24 Non-farm 0. 0. 0.
I 25 Employer 0. 0. 0.
I 26 Professional 0. 0. 0.
I 27 Non-manual 0. 0. 0.
I 28 Manual 16410. 0. 0.
I 29 Self-employed 0. 40500. 0.
I 30 Firms 0. 0. 15800.

 Total 16410. 40500. 15800.

 W 1 W 2 W 3 W 4 W 5

S 31 Wheat 4477. 0. 0. 0. 0.
S 32 Rice 0. 564. 0. 0. 0.
S 33 Sugar 0. 0. 0. 2016. 0.
S 34 Pulses 0. 0. 1215. 0. 0.
S 35 Live Stock. 0. 0. 0. 0. 31968.
S 36 Raw Cotton 0. 0. 0. 0. 0.
S 37 Oil Seeds 0. 0. 0. 0. 0.
S 38 Other + Tobacco 0. 0. 0. 0. 0.
S 39 Grain Milling 11736. 0. 0. 0. 0.
S 40 Rice Milling 0. 33RR 0. 0. 0.
S 41 Sugar 0. 0. 0. 6320. 0.
S 42 Edible Oils 0. 0. 0. 0. 0.
S 43 Other Food + 0. 0. 1782. 338. 1028.
 Cigarts
S 44 Other 0. 0. 0. 0. 0.
 Manufactures
S 45 Services 0. 0. 0. 0. 0.

 Total 16213. 3952. 2997. 8674. 32996.

 W 6 W 7 W 8 S 31 S 32

S 31 Wheat 0. 0. 0. 977. 0.
S 32 Rice 0. 0. 0. 0. 425.
S 33 Sugar 0. 0. 0. 0. 0.
S 34 Pulses 0. 0. 0. 0. 0.
S 35 Live Stock. 0. 0. 0. 750. 208.
S 36 Raw Cotton 0. 0. 0. 0. 0.
S 37 Oil Seeds 199. 0. 0. 0. 0.
S 38 Other + Tobacco 0. 15149. 0. 0. 0.
S 39 Grain Milling 0. 1008. 0. 0. 0.
S 40 Rice Milling 0. 76. 0. 0. 0.
S 41 Sugar 0. 0. 0. 0. 0.
S 42 Edible Oils 5781. 541. 0. 0. 0.
S 43 Other Food + 0. 6185. 0. 0. 0.
 Cigarts
S 44 Other 0. 2020. 44032. 2565. 891.
 Manufactures
S 45 Services 0. 0. 58790. 4239. 2742.

 Total 5980. 24980. 102822. 8531. 4268.

 S 33 S 34 S 35 S 36 S 37

S 31 Wheat 0. 0. 2554. 0. 0.
S 32 Rice 0. 0. 939. 0. 0.
S 33 Sugar 32. 0. 233. 0. 0.
S 34 Pulses 0. 471. 717. 0. 0.
S 35 Live Stock. 38. 264. 0. 285. 116.
S 36 Raw Cotton 0. 0. 0. 1135. 0.
S 37 Oil Seeds 0. 0. 0. 0. 515.
S 38 Other + Tobacco 0. 0. 9129. 0. 0.
S 39 Grain Milling 0. 0. 0. 0. 0.
S 40 Rice Milling 0. 0. 0. 0. 0.
S 41 Sugar 0. 0. 0. 0. 0.
S 42 Edible Oils 0. 0. 0. 0. 0.
S 43 Other Food + 0. 0. 0. 0. 0.
 Cigarts
S 44 Other 320. 491. 485. 2242. 156.
 Manufactures
S 45 Services 1120. 693. 3963. 4893. 493.

 Total 1510. 1919. 18020. 8655. 1280.

 S 38 S 39 S 40 S 41 S 42

S 31 Wheat 0. 11923. 0. 0. 0.
S 32 Rice 0. 0. 3707. 0. 0.
S 33 Sugar 0. 0. 0. 1147. 0.
S 34 Pulses 0. 0. 0. 0. 0.
S 35 Live Stock. 800. 0. 0. 0. 0.
S 36 Raw Cotton 0. 0. 0. 0. 0.
S 37 Oil Seeds 0. 0. 0. 0. 2071.
S 38 Other + Tobacco 1494. 298. 0. 117. 0.
S 39 Grain Milling 0. 0. 0. 0. 0.
S 40 Rice Milling 0. 0. 0. 0. 0.
S 41 Sugar 0. 0. 0. 658. 0.
S 42 Edible Oils 0. 0. 0. 0. 3550.
S 43 Other Food + 0. 0. 0. 0. 85.
 Cigarts
S 44 Other 1858. 642. 107. 497. 629.
 Manufactures
S 45 Services 6622. 1529. 744. 1539. 235.

 Total 10774. 14392. 4558. 3958. 6570.

 S 43 S 44 S 45

S 31 Wheat 0. 0. 0.
S 32 Rice 0. 0. 0.
S 33 Sugar 0. 0. 0.
S 34 Pulses 0. 0. 0.
S 35 Live Stock. 0. 144. 0.
S 36 Raw Cotton 0. 12734. 0.
S 37 Oil Seeds 0. 0. 0.
S 38 Other + Tobacco 2. 249. 1321.
S 39 Grain Milling 1332. 2232. 0.
S 40 Rice Milling 724. 1231. 0.
S 41 Sugar 6. 64. 0.
S 42 Edible Oils 1. 1870. 0.
S 43 Other Food + 3096. 2453. 0.
 Cigarts
S 44 Other 2. 31057. 41316.
 Manufactures
S 45 Services 6. 8336. 24608.

 Total 5169. 60370. 67245.

Note: Table gives non-zero endogenous elements of SAM.

Table 3
Aggregate Multiplier Matrix [M.sub.a]

 S31 S32 S33 S34 S35
 Wheat Rice Sugar Pulses Live
 Stock

W 1 Wheat and Flour 0.3373 0.2961 0.2933 0.2685 0.3049
W 2 Rice and Flour 0.0796 0.0700 0.0640 0.0640 0.0719
W 3 Pulses 0.0599 0.0527 0.0523 0.0483 0.0540
W 4 Sugar 0.1690 0.1492 0.1482 0.1386 0.1520
W 5 Live Stock 0.6695 0.5887 0.5839 0.5381 0.6042
W 6 Edible Oils 0.1123 0.0993 0.0968 0.0929 0.1008
W 7 Miscellaneous Food 0.4671 0.4135 0.4116 0.3884 0.4191
W 8 Other Commodities 1.9739 1.7452 1.7352 1.6241 1.7766

 Total 3.8706 3.4147 3.3928 3.1630 3.4836

120 Large Holdings 0.4982 0.4432 0.4426 0.4273 0.4440
121 Medium Holdings 0.5761 0.5078 0.5045 0.4704 0.5183
122 Small Holdings 1.6180 1.4088 1.3891 1.2343 1.4724
123 Landless 0.0234 0.0201 0.0196 0.0165 0.0216
124 Non-farm 0.2149 0.1864 0.1833 0.1607 0.1963
125 Employer 0.0099 0.0089 0.0090 0.0089 0.0087
126 Professional 0.0809 0.0736 0.0745 0.0746 0.0717
127 Non-manual 0.2134 0.1946 0.1965 0.1970 0.1891
128 Manual 0.2755 0.2458 0.2463 0.2487 0.2418
129 Self-employed 0.6272 0.5640 0.5661 0.5570 0.5573
130 Firms 0.2965 0.2629 0.2621 0.2517 0.2649

 Total 4.4341 3.9162 3.8938 3.6471 3.9861

S31 Wheat 1.4732 0.3669 0.3611 0.3494 0.4517
S32 Rice 0.1136 1.1448 0.0985 0.0975 0.1289
S33 Sugar 0.0685 0.0603 1.0693 0.0368 0.0682
S34 Pulses 0.0493 0.0430 0.0424 1.2866 0.0695
S35 Live Stock 0.7444 0.6401 0.6239 0.7054 1.6479
S36 Raw Cotton 0.3127 0.2744 0.2744 0.2927 0.2668
S37 Oil Seeds 0.0744 0.0657 0.0654 0.0636 0.0660
S38 Other +Tobacco 0.5413 0.4745 0.4691 0.4765 0.7574
S39 Grain Milling 0.3417 0.3002 0.2980 0.2813 0.3057
S40 Rice Milling 0.1128 0.0992 0.0987 0.0952 0.1002
S41 Sugar 0.1383 0.1720 0.1213 0.1135 0.1243
S42 Edible Oils 0.2589 0.2285 0.2277 0.2218 0.2294
S43 Other Food +
 Cigarts 0.3010 0.2655 0.2643 0.2559 0.2673
S44 Other Manufactures 2.5438 2.2328 2.2325 2.3813 2.1706
S45 Services 2.4685 2.2721 2.3020 2.2850 2.2028

 Total 9.5424 8.5901 8.5505 8.9627 8.8566

 S36 S37 S38 S39 S40
 Raw Oil Other Grain Rice
 Cotton Seed Milling

W 1 Wheat and Flour 0.2820 0.2937 0.2806 0.3133 0.2830
W 2 Rice and Flour 0.0668 0.0693 0.0663 0.0743 0.0674
W 3 Pulses 0.0503 0.0521 0.0499 0.0560 0.0508
W 4 Sugar 0.1427 0.1469 0.1409 0.1594 0.1456
W 5 Live Stock 0.5615 0.5826 0.5574 0.6248 0.5663
W 6 Edible Oils 0.0951 0.0975 0.0937 0.1064 0.0975
W 7 Miscellaneous Food 0.3964 0.4057 0.3901 0.4438 0.4074
W 8 Other Commodities 1.6701 1.7174 1.6484 1.6857 1.7055

 Total 3.2648 3.3653 3.2272 3.6437 3.3237

120 Large Holdings 0.4271 0.4315 0.4167 0.4821 0.4485
121 Medium Holdings 0.4856 0.5006 0.4799 0.5426 0.4954
122 Small Holdings 1.3336 1.4120 1.3407 1.4702 1.3076
123 Landless 0.0187 0.0207 0.0193 0.0203 0.0174
124 Non-farm 0.1759 0.1877 0.1778 0.1934 0.1703
125 Employer 0.0087 0.0087 0.0083 0.0099 0.0093
126 Professional 0.0716 0.0702 0.0689 0.0797 0.0758
127 Non-manual 0.1890 0.1852 0.1816 0.2107 0.2007
128 Manual 0.2393 0.2364 0.2297 0.2799 0.2641
129 Self-employed 0.5455 0.3438 0.5284 0.6147 0.5771
130 Firms 0.2530 0.2564 0.2476 0.2915 0.2645

 Total 3.7481 3.8531 3.6988 4.1949 3.8307

S31 Wheat 0.3512 0.3646 0.3476 1.1606 0.3522
S32 Rice 0.0957 0.0986 0.0941 0.1064 0.8110
S33 Sugar 0.0577 0.0596 0.0571 0.0645 0.0588
S34 Pulses 0.0411 0.0433 0.0409 0.0459 0.0413
S35 Live Stock 0.6129 0.6632 0.6158 0.6873 0.6101
S36 Raw Cotton 1.3394 0.2629 0.2550 0.2991 0.2688
S37 Oil Seeds 0.0634 1.2941 0.0617 0.0707 0.0644
S38 Other +Tobacco 0.4550 0.4747 1.5085 0.5283 0.4620
S39 Grain Milling 0.2879 0.2937 0.2834 1.3197 0.2890
S40 Rice Milling 0.0957 0.0973 0.0934 0.1026 1.0962
S41 Sugar 0.1168 0.1201 0.1153 0.1304 0.1191
S42 Edible Oils 0.2208 0.2230 0.2148 0.2460 0.2742
S43 Other Food +
 Cigarts 0.2561 0.2595 0.2498 0.2853 0.2598
S44 Other Manufactures 2.2073 2.1388 2.0750 2.4335 2.1871
S45 Services 2.1998 2.1577 2.1205 2.3859 2.2756

 Total 8.4008 8.5532 8.1328 9.8697 9.1195

 S41 S43 S44 S45
 Sugar Other Other Service

W 1 Wheat and Flour 0.2044 0.1904 0.1421 0.2118 0.2522
W 2 Rice and Flour 0.0691 0.0454 0.0341 0.0509 0.0612
W 3 Pulses 0.0372 0.0343 0.0259 0.0386 0.0465
W 4 Sugar 0.1084 0.0987 0.0755 0.1127 0.1362
W 5 Live Stock 0.4132 0.3818 0.2871 0.4282 0.5141
W 6 Edible Oils 0.0731 0.0661 0.0507 0.0759 0.0930
W 7 Miscellaneous Food 0.3071 0.2766 0.2134 0.3191 0.3913
W 8 Other Commodities 1.2715 1.1548 0.8829 1.3195 1.6086

 Total 2.4640 2.2480 1.7117 2.5566 3.1032

120 Large Holdings 0.3499 0.3090 0.2463 0.3678 0.4465
121 Medium Holdings 0.3681 0.3367 0.2580 0.3844 0.4575
122 Small Holdings 0.9032 0.8718 0.6286 0.9332 1.0739
123 Landless 0.0107 0.0113 0.0073 0.0108 0.0118
124 Non-farm 0.1148 0.1129 0.0797 0.1182 0.1343
125 Employer 0.0076 0.0065 0.0034 0.0080 0.0100
126 Professional 0.0608 0.0499 0.0385 0.0597 0.0917
127 Non-manual 0.1616 0.1326 0.1032 0.1594 0.2408
128 Manual 0.2199 0.1912 0.1653 0.2428 0.2631
129 Self-employed 0.4579 0.3919 0.3108 0.4700 0.6249
130 Firms 0.2045 0.1823 0.1457 0.2161 0.2567

 Total 2.8589 2.5959 1.9889 2.9704 3.6111

S31 Wheat 0.2571 0.2404 0.2651 0.2880 0.3200
S32 Rice 0.0710 0.0663 0.0928 0.0845 0.0893
S33 Sugar 0.2345 0.0399 0.0305 0.0455 0.0548
S34 Pulses 0.0300 0.0281 0.0209 0.0312 0.0373
S35 Live Stock 0.4373 0.4197 0.3057 0.4568 0.5416
S36 Raw Cotton 0.2104 0.1901 0.1285 0.3672 0.2726
S37 Oil Seeds 0.0489 0.4757 0.0329 0.0595 0.0625
S38 Other +Tobacco 0.3630 0.3144 0.2388 0.3583 0.4375
S39 Grain Milling 0.2127 0.1980 0.2598 0.2481 0.2658
S40 Rice Milling 0.0718 0.0667 0.1107 0.0896 0.0907
S41 Sugar 1.1972 0.0808 0.0623 0.0930 0.1115
S42 Edible Oils 0.1702 1.7552 0.1144 0.2094 0.2177
S43 Other Food +
 Cigarts 0.1962 0.1961 1.4000 0.2381 0.2497
S44 Other Manufactures 1.7120 1.5467 1.0458 2.9875 2.2182
S45 Services 1.7827 1.4225 1.0200 1.6350 2.9514

 Total 6.9950 7.0405 5.1281 7.1917 7.9206

Table 4
Percentage Distribution of Multiplier over

Institutions Wheat Rice Sugar Pulses Live Raw
 Stock Cotton

Large holding 11.24 11.32 11.37 11.72 11.14 11.40
Medium holding 12.99 12.97 12.96 12.90 13.00 12.95
Small holding 36.49 35.97 35.84 33.84 36.94 35.58
Landless 0.53 0.51 0.50 0.45 0.54 0.50
Non-farm 4.85 4.76 4.71 4.41 4.92 4.69
Employer 0.22 0.23 0.23 0.24 0.22 0.23
Professional 1.82 1.89 1.91 2.05 1.80 1.91
Non-manual 4.81 4.97 5.05 5.40 4.74 5.04
Manual 6.21 6.28 6.33 6.82 6.07 6.39
Self-employed 14.15 14.40 14.54 15.27 13.98 14.56
Firms 6.69 6.71 6.73 6.90 6.64 6.75

Institutions Oil Other Grain Rice Sugar Edible
 Seeds Milling cane Oil

Large holding 11.20 11.27 11.49 11.71 12.24 13.90
Medium holding 12.99 12.97 12.93 12.93 12.88 12.97
Small holding 36.64 36.25 35.05 34.14 31.59 33.58
Landless 0.54 0.52 0.48 0.45 0.37 0.44
Non-farm 4.87 4.81 4.61 4.45 4.01 4.35
Employer 0.23 0.22 0.24 0.24 0.26 0.25
Professional 1.82 1.86 1.90 1.98 2.13 1.92
Non-manual 4.81 4.91 5.02 3.24 5.65 5.11
Manual 6.13 6.21 6.67 6.89 7.69 7.37
Self-employed 14.11 14.29 14.65 15.06 16.02 15.10
Firms 6.66 6.69 6.95 6.91 7.15 7.02

Institutions Other Other Service Original
 Distr.

Large holding 12.38 12.38 12.37 11.91
Medium holding 12.97 19.94 12.67 12.44
Small holding 31.61 31.42 29.74 30.17
Landless 0.37 0.36 0.33 0.35
Non-farm 4.01 3.98 3.72 3.82
Employer 0.27 0.27 0.28 0.28
Professional 1.94 2.01 2.54 2.60
Non-manual 5.17 5.37 6.67 6.81
Manual 8.11 8.17 7.29 7.13
Self-employed 15.63 15.82 17.30 17.61
Firms 7.33 7.27 7.11 6.87

Table 5
Transfer Multiplier Matrix [M.sub.1]

 S31 S32 S33 S34 S35
 Wheat Rice Sugar Pulses Live
 Stock

S31 Wheat 1.0633 0.0066 0.0059 0.0208 0.0816
S32 Rice 0.0041 1.0484 0.0029 0.0090 0.0302
S33 Sugar 0.0003 0.0002 1.0095 0.0010 0.0069
S34 Pulses 0.0011 0.0006 0.0003 1.2470 0.0261
S35 Live Stock 0.0440 0.0240 0.0129 0.1420 1.0159
S36 Raw Cotton 0.0394 0.0312 0.0346 0.0686 0.0210
S37 Oil Seeds 0.0023 0.0020 0.0021 0.0041 0.0012
S38 Other + Tobacco 0.0158 0.0105 0.0028 0.0453 0.2847
S39 Grain Milling 0.0073 0.0062 0.0064 0.0127 0.0039
S40 Rice Milling 0.0040 0.0034 0.0015 0.0070 0.0021
S41 Sugar 0.0002 0.0002 0.0002 0.0004 0.0001
S42 Edible Oils 0.0087 0.0073 0.0076 0.0151 0.0046
S43 Other
 Food + Cigarts 0.0091 0.0077 0.0080 0.0159 0.0049
S44 Other
 Manufactures 0.3208 0.2703 0.2818 0.5583 0.1711
S45 Services 0.3317 0.3861 0.4276 0.5348 0.2804

 Total 1.8523 1.8068 1.8113 2.6828 1.9347

 S36 S37 S38 S39 S40
 Raw Oil Other Grain Rice
 Cotton Seed Milling

S31 Wheat 0.0077 0.0078 0.0964 0.7785 0.0061
S32 Rice 0.0037 0.0034 0.0029 0.0040 0.7179
S33 Sugar 0.0002 0.0004 0.0002 0.0003 0.0001
S34 Pulses 0.0006 0.0014 0.0008 0.0009 0.0004
S35 Live Stock 0.0253 0.0537 0.0326 0.0377 0.0170
S36 Raw Cotton 1.1086 0.0254 0.0272 0.0414 0.0335
S37 Oil Seeds 0.0024 1.2315 0.0016 0.0029 0.0020
S38 Other + Tobacco 0.0111 0.0379 1.0701 0.0125 0.0090
S39 Grain Milling 0.0075 0.0047 0.0050 1.0011 0.0062
S40 Rice Milling 0.0041 0.0026 0.0028 0.0042 1.0034
S41 Sugar 0.0002 0.0001 0.0001 0.0002 0.0002
S42 Edible Oils 0.0089 0.0056 0.0060 0.0091 0.0074
S43 Other
 Food + Cigarts 0.0094 0.0059 0.0063 0.0096 0.0077
S44 Other
 Manufactures 0.3300 0.2064 0.2210 0.3370 0.2723
S45 Services 0.3960 0.3000 0.3384 0.3721 0.4369

 Total 1.9159 1.8668 1.7215 2.6331 2.5200

 S41 S42 S43 S44 S45
 Sugar Edible Other Other Service
 Oils

S31 Wheat 0.0054 0.0072 0.0901 0.0271 0.0075
S32 Rice 0.0027 0.0035 0.0454 0.0137 0.0038
S33 Sugar 0.1909 0.0002 0.0001 0.0002 0.0001
S34 Pulses 0.0001 0.0005 0.0001 0.0002 0.0001
S35 Live Stock 0.0044 0.0199 0.0049 0.0081 0.0025
S36 Raw Cotton 0.0353 0.0308 0.0070 0.1855 0.0516
S37 Oil Seeds 0.0021 0.4334 0.0004 0.0110 0.0001
S38 Other + Tobacco 0.0258 0.0072 0.0045 0.0083 0.0118
S39 Grain Milling 0.0065 0.0074 0.1165 0.0343 0.0095
S40 Rice Milling 0.0036 0.0040 0.0633 0.0189 0.0051
S41 Sugar 1.1086 0.0002 0.0006 0.0010 0.0003
S42 Edible Oils 0.0078 1.6083 0.0017 0.0409 0.0114
S43 Other
 Food + Cigarts 0.0082 0.0254 1.2694 0.0429 0.0119
S44 Other
 Manufactures 6.2876 0.2508 0.0566 1.5094 0.4195
S45 Services 0.4166 0.1784 0.0712 0.2124 1.2279

 Total 2.1057 2.5776 1.7318 2.1189 1.7661

Table 6
Closed-Loop Multiplier Matrix [M.sub.3]

 S31 S32 S33 S34 S35
 Wheat Rice Sugar Pulses Live
 Stock

S31 Wheat 1.2692 0.2756 0.2216 0.0990 0.1923
S32 Rice 0.0713 1.0000 0.0539 0.0211 0.0509
S33 Sugar 0.0439 0.0307 1.0365 0.0330 0.0314
S34 Pulses 0.0315 0.0264 0.0261 1.0093 0.0225
S35 Live Stock 0.4584 0.3841 0.3808 0.1359 1.3275
S36 Raw Cotton 0.1756 0.1411 0.1458 0.0521 0.1254
S37 Oil Seeds 0.0459 0.0315 0.0382 0.0136 0.0328
S38 Other + Tobacco 0.3375 0.2878 0.2803 0.1001 0.2411
S39 Grain Milling 0.2192 0.1817 0.1821 0.0650 0.1566
S40 Rice Milling 0.0707 0.0393 0.0587 0.0210 0.0505
S41 Sugar 0.0888 0.0744 0.0737 0.0263 0.0634
S42 Edible Oil 0.1596 0.1317 0.1326 0.0474 0.1141
S43 Other
 Food + Cigarts 0.1870 0.1567 0.1553 0.0555 0.3336
S44 Other
 Manufactures 1.4283 1.1968 1.1864 0.4235 1.0206
S45 Services 1.3746 1.1518 1.1419 0.4076 0.9822

 Total 5.9614 5.1574 5.1214 2.4711 4.3451

 S36 S37 S38 S39 S40
 Raw Oil Other Grain Rice
 Cotton Seed Milling

S31 Wheat 0.1949 0.2038 0.2184 0.0369 0.0516
S32 Rice 0.0516 0.0540 0.0578 0.0101 0.0141
S33 Sugar 0.0318 0.0332 0.0356 0.0065 0.0091
S34 Pulses 0.0228 0.0238 0.0255 0.0044 0.0061
S35 Live Stock 0.3319 0.3470 0.3720 0.0638 0.0889
S36 Raw Cotton 1.1271 0.1329 0.1425 0.0261 0.0364
S37 Oil Seeds 0.0333 1.0348 0.0373 0.0070 0.0098
S38 Other + Tobacco 0.2444 0.2554 1.2738 0.0503 0.0703
S39 Grain Milling 0.1587 0.1659 0.1779 1.0303 0.0423
S40 Rice Milling 0.0512 0.0335 0.0574 0.0101 1.0142
S41 Sugar 0.0643 0.0672 0.0720 0.0112 0.0185
S42 Edible Oil 0.1156 0.1208 0.1295 0.0244 0.0139
S43 Other
 Food + Cigarts 0.1354 0.1416 0.1518 0.0281 0.0192
S44 Other
 Manufactures 1.0342 1.0811 1.1590 0.2123 0.2965
S45 Services 0.9953 1.0405 1.1154 0.2035 0.2842

 Total 4.5924 4.7554 3.0260 1.7268 2.0151

 S41 S42 S43 S44 S45
 Sugar Edible Other Other Service
 Oil

S31 Wheat 0.0695 0.0407 0.0659 0.1029 0.2037
S32 Rice 0.0189 0.0111 0.0234 0.0283 0.0558
S33 Sugar 0.0123 0.0072 0.0152 0.0183 0.0150
S34 Pulses 0.0083 0.0048 0.0102 0.0124 0.0243
S35 Live Stock 0.1197 0.0701 0.1480 0.1790 0.3516
S36 Raw Cotton 0.0491 0.0287 0.0606 0.0733 0.1449
S37 Oil Seeds 0.0132 0.0077 0.0163 0.0197 0.0390
S38 Other + Tobacco 0.0946 0.0554 0.5269 0.1414 0.2791
S39 Grain Milling 0.0570 0.0334 0.0704 0.0852 0.1671
S40 Rice Milling 0.0189 0.0111 0.0234 0.0283 0.0559
S41 Sugar 1.0249 0.0146 0.0508 0.0373 0.0728
S42 Edible Oil 0.0457 1.0268 0.0365 0.0683 0.1355
S43 Other
 Food + Cigarts 0.0528 0.0309 1.0653 0.0790 0.1560
S44 Other
 Manufactures 0.3992 0.2338 0.4934 1.5967 1.1792
S45 Services 0.3826 0.2241 0.4729 0.5719 2.1295

 Total 2.3666 1.8005 2.6892 3.0428 5.0306

Table 7
Open-Loop Multiplier Matrix [M.sup.2]

 S31 S32 S33 S34 S35
 Wheat Rice Sugar Pulses Live
 Stock

120 Large Holdings 0.0423 0.0406 0.0402 0.0142 0.0346
121 Medium Holdings 0.0926 0.0777 0.0771 0.0275 0.0662
122 Small Holdings 0.3914 0.3280 0.3254 0.1158 0.2796
123 Landless 0.0080 0.0067 0.0067 0.0025 0.0057
124 Non-farm 0.0572 0.0479 0.0474 0.0171 0.0409
125 Employer 0.0003 0.0002 0.0003 0.0000 0.0002
126 Professional 0.0001 0.0001 0.0000 0.0000 0.0001
127 Non-manual 0.0002 0.0001 0.0000 0.0000 0.0001
128 Manual 0.0078 0.0065 0.0064 0.0025 0.0056
129 Self-employed 0.0334 0.0200 0.0276 0.0100 0.0239
130 Firms 0.0331 0.0277 0.0274 0.0100 0.0238

 Total 0.6725 0.3615 0.5585 0.1996 0.4807

 S36 S37 S38 S39 S40
 Raw Oil Other Grain Rice
 Cotton Seed Milling

120 Large Holdings 0.0351 0.0367 0.0393 0.0165 0.0240
121 Medium Holdings 0.0667 0.0701 0.0732 0.0142 0.0207
122 Small Holdings 0.2834 0.2963 0.3176 0.0224 0.0327
123 Landless 0.0058 0.0062 0.0065 0.0000 0.0000
124 Non-farm 0.0414 0.0432 0.0464 0.0025 0.0033
125 Employer 0.0002 0.0004 0.0002 0.0004 0.0006
126 Professional 0.0001 0.0000 0.0001 0.0017 0.0022
127 Non-manual 0.0001 0.0000 0.0001 0.0030 0.0066
128 Manual 0.0051 0.0058 0.0064 0.0178 0.0236
129 Self-employed 0.0242 0.0254 0.0271 0.0203 0.0269
130 Firms 0.0239 0.0247 0.0258 0.0157 0.0142

 Total 0.4869 0.5087 0.5458 0.1165 0.1548

 S41 S42 S43 S44 S45
 Sugar Edible Other Other Service
 Oil

120 Large Holdings 0.0324 0.0189 0.0400 0.0484 0.0031
121 Medium Holdings 0.0278 0.0163 0.0344 0.0416 0.0715
122 Small Holdings 0.0439 0.0257 0.0542 0.0656 0.1127
123 Landless 0.0000 0.0000 0.0000 0.0000 0.0001
124 Non-farm 0.0045 0.0026 0.0055 0.0067 0.0114
125 Employer 0.0007 0.0004 0.0010 0.0012 0.0021
126 Professional 0.0030 0.0018 0.0038 0.0045 0.0260
127 Non-manual 0.0089 0.0052 0.0110 0.0133 0.0692
128 Manual 0.0318 0.0186 0.0393 0.0475 0.4140
129 Self-employed 0.0363 0.0213 0.0448 0.0542 0.1453
130 Firms 0.1900 0.0111 0.0235 0.0284 0.0441

 Total 0.2083 0.1220 0.2575 0.3114 0.6078

Table 8
Degree of Interdependence

Multipliers [M.sub.a] [M.sub.1]
(Value) (Percent) (Percent)

 0-0.25 47 82
0.26-0.50 27 9
0.51-0.75 5 1
0.75-1.00 1 1
 >1.00 20 7

Source: Tables 3 and 5.