4.3 Agricultural Sector and Agro-Industry’s Multiplier Effects—SAM and Input-Output
4.3.2 The Input-Output Multiplier Analysis
4.3.2.1 Simulation Results from Input-Output Multiplier Analysis
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This chapter focuses on the potential of the Thai agricultural sector and food industry (agro-industry) in economic development of Thailand. Section 4.1 first discusses all the major points of potential, which include the potential in terms of the world food demand issues and the ability of Thailand to export agricultural and food produce, the ability of Thailand to improve technology related to agricultural and agro-industrial sectors, and the potential from the strong intersectoral linkage and multiplier effects of agricultural and agro-industrial sectors. Analyses of intersectoral linkage effects and multiplier effects are the main objectives of this chapter, which are elaborated in Section 4.2 and 4.3, respectively. The linkage effect analysis is done using an input-output analysis in order to find out the key sectors for the Thai economy which have strong backward and forward linkages. The multiplier effect analysis is done to find out which sector gives the highest output multiplier effects using an input-output analysis, with a reference to previous study using a social accounting matrix (SAM) analysis.
4.1 Potential of Thai Agricultural Sector and Agro-Industry 4.1.1 Food Demand Issues and Ability to Export
Mellor (1983) stated that in the developing world, demand for food would clearly continue to shift more rapidly than supply. Therefore, the price of food would shift upwards over the next two decades. This statement seems to be true in the present world at least in the case of Thailand. The producer prices of the majority of agricultural produce in Thailand have been on the increasing trend over the past decade as shown in Table 4.1. In developing countries, food import grew more rapidly than food exports despite different records of growth in per capita food production (Mellor and Johnston 1984). This leaves a large opportunity and markets for Thailand to export its agricultural and food produce to developing countries in many decades to come. Moreover, rising income in developing countries causes food demand to shift to highly
income elastic food, such as livestock, fruits and vegetables, and preferred cereals. This restrains the decline in the overall income elasticity for basic food staples. Therefore, Engel’s Law may not hold in an opened economy case, or at least not when there is a lot of food demand from developing countries and when world population is rising.
Moreover, high value-added agricultural products from Thailand are unique and have become globally well-known, such as the jasmine rice, packaged Thai cuisines and Thai sweets, tropical fruits, and Thai herbs. The Thai government is currently promoting Thai brand names to increase the products’ value-added.
In terms of the size effect, agricultural and agro-industrial exports ranked among the top five major exports of Thailand as can be seen in Table 4.2 (year 2001-2004).35 The share of agricultural export was still as large as 10.7 percent in 2004, which was after only electronics and electrical appliance exports. The performance of agro-industrial export in total export is also considered very high as its share was 6.6 percent in 2004. Moreover, the food industry (agro-industry) did contribute the most to GDP among all manufacturing sectors in the 1980s and was still among the top-performance sectors in the 1990s as shown in Figure 4.1 and 4.2.
Table 4.1—Producer Prices of Selected Agricultural Produce in Thailand, 1991-2002
Unit: Baht per Metric Ton
Year 1991 1993 1995 1997 1999 2001 2002
Rice, Paddy 4,089 3,215 4,132 5,472 5,579 4,484 4,425
Table 4.2—Thai Exports, 2001-2004 (percent of total export)
Year 2001 2002 2003 2004
Source: Author, using data from the Ministry of Commerce
Figure 4.1—GDP Originating from Manufacturing Sectors, 1970-1990
Source: NESDB
Figure 4.2—GDP Originating from Manufacturing Sectors, 1980-1996
Source: NESDB
GDP originating from manufacturing (M baht): 1972 price
0
4.1.2 Technological Issues
Johnston and Mellor (1961) stated that a healthy agricultural sector can be created by raising productivity by new technology, which would reduce the input usage and production costs and increase farm receipts. The agricultural sector itself requires only moderate capital outlays, so it can make net contribution to the capital requirements for infrastructure and industrial expansion. Therefore, return to investment in agricultural sector is very high, especially in terms of technological development. A healthy agricultural sector can be a good source of capital accumulation for industries and infrastructure for a country’s overall economic growth, which helps in structural transformation process.
In the case of Thailand, the agricultural sector has higher TFP growth than manufacturing industrial sectors, and higher than most nontradable sectors, except public administration, as shown in Section 2.2.1 in Chapter II (calculated by Tinakorn and Sussangkarn (1996); and Bhuvapanich (2002)). This is partly related to increased complexity of the input-output coefficient of the agricultural sector, but a lot is related to the investment in infrastructure development, the knowledge accumulation of farmers and agricultural scientists over the long years, and the effective systems for developing and disseminating innovations in agriculture, even though individual farmers may have little incentive to undertake research. Therefore, when giving more attention to the agricultural sector, the government needs not fear economic stagnation as a consequence. In fact, having a strong agricultural sector may provide an advantage as long as the diffusion of technology is encouraged. More sophisticated technological development in agricultural-related sectors should be easy for Thailand to improve if promoted more seriously exploiting the experiences of stakeholders. Moreover, since Thailand is lagging behind in technological improvement in manufacturing industrial sectors and the world competition is getting fiercer, it may be wise to invest more effort and budget in
technological improvement in areas where the country has more comparative advantage, such as agricultural and food sectors.
Impacts of the technological and productivity improvement on the real wage of farmers and household incomes will be tested in the computable general equilibrium (CGE) analysis in Chapter V.
4.1.3 Linkage Effects and Multiplier Effects
Linkage and multiplier effects will be analyzed in detail in Section 4.2 and 4.3, respectively, which are the main analyses of this chapter. The objective of the linkage effect analysis is to find out the key sectors for the Thai economy which have strong backward and forward linkages, using an input-output analysis. The objective of the multiplier effect analysis is to find out which sector gives the highest output multiplier effects using an input-output analysis. In conducting these two analyses we hope to find results that can support our hypothesis, that Thai agricultural-related sectors should be promoted since they have better linkage and multiplier effects than the non-food manufacturing industrial sectors, and they can also generate a better income distribution in the Thai economy.
4.2 The Intersectoral Linkages and the Key Sector Analysis—An Input-Output Analysis This intersectoral linkage and key sector analysis is the first main analysis of this chapter.
It aims to examine which sectors have strong backward and forward linkages in terms of both size and evenness. Those sectors then should be selected as the key sectors to be promoted under government’s policy. Before getting into the key sector analysis in Section 4.2.2, the theoretical backgrounds of the input-output analysis and the intersectoral backward and forward linkage analysis are explained in detail in Section 4.2.1. In conducting this key sector analysis, we hope
to find a positive result in both linkage size and evenness from the agricultural and agro-industrial sectors to support our hypothesis.
4.2.1 The Theoretical Background of Input-Output Analysis 4.2.1.1 Input-Output Framework
The input-output analysis was developed by Professor Wassily Leotief in the 1930s as a theoretical framework and an applied economic tool in a market economy. It displays sales and purchases relationship between different producers and consumers in an economy. It focuses on the interrelationships between sectors or industries in an economy with respect to the production and uses of their products and the products imported from abroad. The input-output analysis assumes that (1) the inputs used in producing a product are related to the industry output by a linear and fixed coefficient production function, at least in the short run, so each industry uses a fixed input ratio for the production of its output; (2) each industry produces only one homogenous commodity and there is no substitution among the different inputs; (3) production in every industry is subject to constant returns to scale; (4) there is excess in production capacity in all sectors, and increasing demand can always be met by higher output with no price increase.
In other words, sectoral production is completely demand-driven. Since these assumptions are likely to be unrealistic, input-output models are more useful as guidelines to potential induced linkage, and as indicators of likely supply bottlenecks that may occur in a growing economy, than as predictive models.
Table 4.3 shows a simplified input-output table and accounts. It distinguishes three producers and shows the input-output flow matrix describing their transactions. The economy is viewed with each sector or industry listed horizontally as a consuming sector (j), and vertically as a supplying sector (i). The values in the square box represent intermediate consumption or
uses of products as inputs in the production process. The total input and the total output in each corresponding row and column must balance.
Table 4.3—Input-output Flow Table and Accounts
Sector 1
Sectors (j)
Sector 2 Sector 3 Final Demand Total output Sectors (i)
The input-output analysis became an economic tool when Leontief introduced an assumption of fixed-coefficient linear production functions relating inputs used by a sector or industry along each column to its output flow. The amount of sector ith’s output required for the production of sector jth’s output is assumed to be proportional to sector jth’s output, which is denoted by aij or an input coefficient. The first subscript in aij refers to the input, and the second to the output, so that aij indicates how much of the ith commodity is used for the production of each unit of the jth commodity. Specifically, the production of each unit of the jth commodity will require a1j amount of the first commodity, a2j of the second commodity, and anj of the nth commodity as can be seen in Table 4.4.
Table 4.4—Input Coefficient Table in General Terms
Sector 1
Sectors (j)
Sector 2 Sector 3 Final demand Total output Sectors (i)
The various elements of the final demand, which include final consumption expenditures and gross capital formation of the firm sector, the government sector and the exports minus imports, are considered as a single column vector f. The elements of value added, which are also referred as primary inputs, are considered as a single row vector v. Since the total input and total output must balance, they both are represented as vector x.
The values of input coefficients, they can be obtained by dividing the entries in the column by the total input of the consuming sector. For example, from the entries in Table 4.3, one can find the input coefficients a11, a21, a31, and v1 by calculating 10/100, 20/100, 20/100, and 50/100, respectively. The outcomes are shown in Table 4.5.
Table 4.5—Input Coefficient Table (inputs per unit of output)
Sector 1
Sectors (j)
Sector 2 Sector 3 Sectors (i)
Sector 1 0.10 0.08 0.21
Sector 2 0.20 0.00 0.24
Sector 3 0.20 0.38 0.12
Value added 0.50 0.55 0.44
The input coefficients in Table 4.5 indicate that, for example, one unit of output of sector 1 requires 0.10 unit of output of sector 1, 0.20 unit of output of sector 2, 0.20 unit of output of sector 3, and generates 0.50 unit of value added. Thus, in order to produce output x1, x2 and x3,
the total amount of sector 1’s output required as intermediate input in the production process of an economy is equal to
(4.1) a11x1 + a12x2 + a13x3 or 0.10x1 + 0.08x2 + 0.21x3
If the remaining value of the same product left for final demand is further added to intermediate consumption, the total output of sector 1 is obtained in Equation 4.2.
(4.2) a11x1 + a12x2 + a13x3 + f1 = x1 or 0.10x1 + 0.08x2 + 0.21x3 + 40 = 100
It is possible to check the equality property of Equation 4.2 by replacing the values of x1, x2 and x3 in table 1.1 by their actual values. The results are shown in Equation 4.3.
(4.3) 0.10 (100)+ 0.08 (200) + 0.21 (170) + 40 = 100
The utilization of products from sector 2 and 3 as intermediate inputs of production may be similarly calculated. Therefore, in a more general form with n sectors and n products, system of equation can be written as follows:
(4.4) a11x1 + a12x2 + a13x3 + ….. + a1nxn + f1 = x1 a21x1 + a22x2 + a23x3 + ….. + a2nxn + f2 = x2 a31x1 + a32x2 + a33x3 + ….. + a3nxn + f3 = x3 · + · + · + ….. + · + · = · an1x1 + an2x2 + an3x3 + ….. + annxn + fn = xn
In matrix form, Equation 4.4 can be written as follows:
(4.5) a11 a12 a13 · a1n x1 f1 x1 a21 a22 a23 · a2n x2 f2 x2
a31 a32 a33 · a3n x3 + f3 = x3
· · · · · · · · an1 an2 an3 · ann xn fn xn
The computation of the coefficient matrix can be described in the following mathematical form:
(4.6) aij = xij /xj or (4.7) xij = aij xj
where xij stands for the amount of sector ith output required for the production of sector jth’s output. Equation 4.5 can be written in matrix form as:
(4.8) Ax + f = x
The relationship in Equation 4.8 is the basic input-output system of equations. It is suitable for model-building or analysis. Matrix A is called the input coefficient matrix; vector x is the vector of outputs, and f is the vector of final demands. If the values of the coefficients and of final demands are known, then it is possible to solve this set of simultaneous equations in order to find the level of output of various industries or sectors necessary to satisfy the specified level of the final demands.
4.2.1.2 The Inverse Matrix
The inverse matrix is fundamental to input-output analysis as it shows the full impact of an exogenous increase in net final demand on all industries (or sectors). Mathematically, the vector of output x in the system of Equation 4.8 can be solved as follows:
(4.9) x – Ax = f (4.10) (I - A) x = f (4.11) x = (I – A)-1 f
where I stands for identity matrix, which is a square matrix where all the diagonal elements are equal to 1 and all other elements are equal to zero. (I – A)-1 is the Leontief inverse36 which can be calculated with some difficulty. At present, spreadsheet computer software can easily invert a large size matrix.
The inverse matrix can be interpreted as a chain of interactions. If the final demand in a given sector i increases by, say fi, initially production increases by the same amount, xi1
= fi . However, this increase in production raises the intermediate demand for all sectors, including i itself, by xj2
= ∑ajixi1. To produce these intermediate inputs, however, more intermediate inputs are needed, and there is a third round of effects xj3
= ∑ajixi2
. This obviously leads to more and
more rounds of effects. In other words, the exogenous shock f gives impact to input requirement of any increase in output, or the coefficient matrix A, for the first round as Af, the second round as A2f, the third round as A3f, and the nth round as Anf, so that the total impact is
(4.12) (I + A + A2 + … + An) f, which (4.13) I + A + A2 + … + An = (I – A)-1.
Thus, sectoral outputs keep rising as a result of the higher intermediate-goods demand each round of effects generates. However, in each round output increases become smaller and smaller such that their total always has a limit. Therefore, (I – A)-1 is a multiplier which can be used to calculate overall changes in sectoral outputs which result from changes in final demands.
With the inverse matrix (I-A)-1 it is possible to unravel the technological interdependence of the productive system and to trace the generation of output demand from final assumption which is part of final demands throughout the system. It is then possible to calculate what output levels would be required to meet various postulated levels of net final demand and consequently how output levels would be required to change to meet postulated changes in net final demand.
In chain reactions in input-output analysis, the first exogenous shock is assumed to be initiated by an exogenous increase in final demands, like an increase in export demand, or an increase in fixed capital formation. This assumption is made mainly for the sake of simplicity of exposition. Actually, the first shock can happen anywhere. It can be an increase in domestic production of intermediate consumption to replace imports, an increase in indirect taxes, a change in technology represented by changes in input structures, etc (United Nations 1999: 8).
4.2.1.3 Competitive- and Noncompetitive-Import Type Input-Output Tables
Typically, input-output data are presented with imports classified as either competitive, that is perfect substitutes, or as noncompetitive. If they are noncompetitive, then they are not
grouped with domestic products but are viewed as a nonproduced input into a sector, analogous to labor and capital. Figures 4.3 and 4.4 present features of competitive-import type and noncompetitive-import type input-output tables, respectively.
Figure 4.3—Competitive-Import Type Input-Output Table
A F E -M X
VA
X
From a material balance equation:
(4.14) X = A + F + E – M where
X = gross output vector
A = input coefficient matrix of domestic and import transaction
F = vectors of final demands of domestic and import transactions which includes private consumption (PVC), government consumption (GC), gross fixed capital formation (FK), and increase in stock (ST)
E = export demand vector
M = vector of total import of intermediate use and final use
VA = vectors of value-added which includes wage and salary (W), operating surplus (OS), depreciation (DP), and indirect tax less subsidy (TAX).
In the competitive-import type input-output table, imports of commodity i, Mi, are demanded for intermediate use (Ami) and for final use (Fmi). In Equation 4.14, they appear in
the total import supply (M) and as part of both intermediate (A) and final demand (F). Let ui a
and ui f
stand for the domestic supply ratios (the proportion of intermediate and of final demand produced domestically). Substituting these ratios in equation 4.14, we obtain the material balance equation for domestic production:
(4.15) Xi = ui a∑j aij Xj + ui f Fi + Ei and similarly for imports:
(4.16) Mi = mi a Ai + mi f Fi
where the import coefficients are defined as mi = (1 – ui) for both intermediate and final goods.
From Equations 4.15 and 4.16, it is important to note that, first, the formulation implicitly assumes that imports and domestic goods with the same sector classification are alternative sources of supply and are perfect substitutes in all uses. But for many intermediate and capital goods such an assumption might be incorrect. Second, exports are netted out of production in defining the domestic supply ratios. This is appropriate when there is no direct re-export of imports. Third, the domestic supply ratio for intermediate use, ui a, is assumed to be the same for all sectors using commodity i as an input but to be different from the domestic supply ratio for final use, ui f
(Kubo, Robinson, and Syrquin 1986: 123).
Equation 4.15 and 4.16 can be conveniently restated in matrix notation as:
(4.17) X = ûa AX + ûf F + E (4.18) M = m^a AX + m^f F
where ^ over a variable denotes a diagonal matrix.
From the information in Equations 4.17 and 4.18, we can distinguish imports from intermediate use and final use when using a competitive-import type input-output table by:
(4.19) X = [I-(I-M^)A]-1 [(I-M^)F + E]
where ^ over M denotes import matrix where the diagonal elements are import coefficients and other off-diagonal elements are all zero.
Equation 4.19 was used in the demand side decomposition of the factors of growth in Chapter II. The competitive-import type input-output tables will also be used in the key sector analysis in Section 4.2.2.
In some countries, including Thailand, the noncompetitive-import type input-output table is also available. With this type of table, a full import matrix is provided as shown in Figure 4.4.
Figure 4.4—Noncompetitive-Import Type Input-Output Table
Ad Fd E X
Am Fm M
VA
X
In the noncompetitive-import type input-output table, the A matrix, which represents the technology of interindustry relations, can be separated into a domestic component and an imported one as:
(4.20) A = Ad + Am where
Ad = domestic input-output matrix Am = import matrix of intermediate use
The final demand can also be separated into domestic and import components as:
d m
where
Fd = vectors of final demands of domestic transaction Fm = vectors of final demands of import transaction
For the domestic material balances, Ad is the relevant matrix to yield the domestic production needed to satisfy a specific level of domestic and export demand with a given technology, A, and import structure Am. Therefore, the output balance equation used with a
For the domestic material balances, Ad is the relevant matrix to yield the domestic production needed to satisfy a specific level of domestic and export demand with a given technology, A, and import structure Am. Therefore, the output balance equation used with a