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Growth Accounting for Sri Lanka’s Agriculture with Special Reference to Fertilizer and Non-Agricultural Prices: Do Policy
Reforms Affect Agricultural Development?
Running Title: Growth Accounting for Sri Lanka’s Agriculture
Mitoshi Yamaguchi Professor and COE Program Leader
e-mail : [email protected] Ph/Fax : +81-78-803-6828
And
M. S. SriGowri Sanker
COE Researcher e-mail : [email protected]
Ph : +81-78-803-6872, Fax : +81-78-803-6869
Graduate School of Economics, Kobe University 2-1 Rokkodaicho, Nada-Ku, Kobe
JAPAN 657-8501
This Research is partially supported by the Grants-in-Aid for 21st Century COE Program of Graduate School of Economics, Kobe University, Kobe, Japan.
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Growth Accounting for Sri Lanka’s Agriculture with Special Reference to Fertilizer and Non-Agricultural Prices: Do Policy
Reforms Affect Agricultural Development?
Abstract
The agricultural sector of Sri Lanka reacted sharply to the highly contentious policy reforms called Structural Adjustment Programs. We used a four sector general equilibrium model under growth accounting approach to find out the effect of the policy (exogenous) variable on the target (endogenous) variable. Here, we considered only the most important variables, and the overall results indicate that policy changes are favorable to overall agricultural development, although their impact on the domestic food sector is negative. The most serious negative determinant under the policy changes relates to fertilizer, and our study indicates that fertilizer prices considerably affect agricultural production; it especially has a negative impact on domestic food production. Secondly, this paper analyzed the impact of non-agricultural price and found that it positively helped the development of overall agriculture. Thirdly, agricultural exports increased under the new policy reforms and made large contributions to agricultural production.
Key Words: Structural Adjustment Policy (SAP); Sri Lanka’s Agricultural Sector; Domestic Food Sector; Four-Sector General Equilibrium Growth Accounting; Growth Rate Multiplier (GRM). JEL Classification: O11, O13, O41, Q18.
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I. Introduction
Many Asian countries are dependent on an agricultural economy. Sri Lanka is a
country which is located in the Indian Ocean and has a tropical climate. Rural
agricultural development and raising food production so as to achieve self sufficiency
were the main objectives of almost all the governments since independence. Although
substantial amounts of resources were allocated towards agriculture and irrigation
infrastructures for this purpose, the rural agricultural economy of Sri Lanka struggled to
gain momentum. Various problems such as the use of low quality seed, continuing use
of old cultivation practices, insufficient and improper use of fertilizers and agricultural
chemicals, inadequate agricultural production credits, a low rate of productivity along
with the absence of reasonably priced production inputs, as well as the inadequacy of
well-organized farmer-centered marketing facilities, further amplified this problem.
Since about 60%-70% of Sri Lanka’s population live in rural areas and depend on
agriculture and related activities, an increase in labor through population growth, would
contribute significantly to employment and income development in rural areas.
Meanwhile, rice and other subsidiary food items make up the majority of imports. Any
reduction in these imports could not only help to remedy the foreign exchange
imbalance, but could also allow these resources to be allocated for the import of goods
for other much needed development activities. This peculiar general scenario needed
urgent remedial measures. Therefore, restructuring the agricultural sector with special
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reference to the development of domestic agriculture has been a major policy issue of
successive governments since independence. Though there were many policy issues,
the most important one among them would be the Structural Adjustment Policies
(SAP), implemented in 1977. Due to the reasons mentioned above, it is essential to
estimate the effect of SAP on Sri Lanka’s Agriculture. In this paper, we define the effect
of SAP through following two actions. First is the performance of four policy variables
such as increase of agriculture exports (E1), decrease of food imports (M2), increase of
fertilizer price (PF) and non-agriculture price (PN), and second is the consequent change
in the economic structure by SAP using General Equilibrium Growth Accounting
approach where the latter is measured through the change in the Growth Rate
Multipliers(GRM) which is explained in the section 4. This combined effect gives us
the picture of overall effect of SAP and we obtained rather positive result which is
different from previous studies.
II. Structural Adjustment Policy in the context of Srilanka’s Agriculture
A. Evaluation of Structural Adjustment Policy
Although there are many frameworks to study the tendency of the Adjustment
Policy issues, we considered Sarris’s analytical framework targeting the Asian
economic structure as the most appropriate one. As Sarris (1990) discussed, the
majority of the adjustment programs came from a prevailing or expected decline in the
external balance, due to factors not likely to be inverted in the short-run and from an
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external deficit which was not sustainable in the medium term. Furthermore, these
adjustments required a shift in domestic demand and changing supply and the
production structure to eliminate the external deficit. Since demand can be reduced
more easily and faster by changes in the money supply and public expenditures, it
happens to be the focus of the first attempts at correcting economic decline. However,
the improvements of the supply side are more difficult and slower to remedy. Therefore,
there is a tendency for such efforts to be associated with medium term structural
adjustment efforts. As the removal of the external inequality is the crucial focus of
adjustment, trade policies appear significantly in all adjustment programs and they
usually include two sets of measures, such as export promotion and import
liberalization.
It is notable from various countries, which implemented adjustment policies to
develop their damaged economies that the results of the SAPs have created several
internal controversies. The most important one is whether the results are due to the
policy reforms, or occurred because of other reasons. Such a question brings out the
issue of counterfactual analysis, which consists of constructing a scenario for the
economy that would have prevailed in the absence of the SAP. This type of scenario
should include controls for exogenous shocks unrelated to the policy reforms.
Comparison of the observed and the counterfactual values of the economic variables
would then indicate the differential impact of the SAP on the economy. The problem is
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that the estimation of a detailed counterfactual path cannot be done in the absence of a
consistent multi-sector general equilibrium model (Sarris 1990). We consider that the
construction of such a model is rather difficult and a time-consuming task because of
the lack of proper and comprehensive data which is a constant difficulty in developing
countries such as Sri Lanka. Having understood this difficulty, especially in terms of Sri
Lanka’s economic structure, we proposed the General Equilibrium Growth Accounting
approach which captures the effect of changes in policy (exogenous) variables on target
(endogenous) variables, based on the initial framework as suggested by Sarris. For
simplicity, we concentrated on the effects of the two most important policy (exogenous)
variables (fertilizer and non-agricultural prices), with the support of another two policy
(exogenous) variables (agricultural export and food imports).
Let us now concentrate on the relevance of SAP to Sri Lanka which was among
the first developing countries to adopt SAPs in 1977. This program of economic policy
reforms were mainly designed and introduced by the World Bank. The major economic
policy reforms introduced in Sri Lanka included the provision of incentives to export
oriented sectors, a reduction in the protection provided to the import competing sectors,
exchange rate changes, and fiscal and monetary reforms. In addition, liberalization of
domestic factor and product markets from government intervention was carried out by
privatizing government owned enterprises, thus allowing the independent function of
market forces. Athukorala and Jayasuriya (1994), Bandara and Gunawardana (1989)
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mainly studied the historical process of economic reforms in Sri Lanka, particularly in
relation to the macroeconomic effects. The impact of such policy reforms on the
domestic food sector was not evaluated, although the sector’s importance can not be
neglected in terms of contribution to GDP and importance to the labor market.
Therefore, we have considered the domestic food sector in more detail here and further
divided this sector into three sub sectors.
B. Agriculture and economic conditions prevailed during 1970-1994
The period of 1970-1977 could be considered as the pre-reform period, because
Sri Lanka followed a closed economic policy under which foreign exchange limitations
and restrictions on imports of food and agricultural inputs existed. During this period,
the government adopted a policy of food self-sufficiency under increased government
interventions in domestic factor and product markets. Many private business ventures
were put under government control and management, while vast areas of tea, rubber
and coconut cultivation land was nationalized under a land reform program1. Due to the
change in government in 1977, “a new economic reform policy” was introduced.
1. First Stage during 1978-1988: After the closed economy period, the new
government came to power in 1977 and implemented various policy reforms, aiming to
achieve accelerated economic growth, create employment opportunities, increase
capacity utilization, stimulate savings and investment, improve the balance of payments,
1 See Gunawardana, 1981.
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and achieve international competitiveness (Athukorala and Jayasuriya 1994). In order
to achieve these, the government took several measures, the most important of which
are outlined below. First, a new tariff system was introduced in place of non-tariff
measures. Second, the exchange rate was unified and allowed to be determined by the
market, and exchange controls were removed. Third, Sri Lanka’s currency (Rupee) was
substantially devalued. Fourth, many public sector investment programs were
introduced and fifth, export processing zones were introduced. As we saw earlier, trade
liberalization was a major component of the policy reform package. Accordingly, the
introduction of this open economy policy also led to the elimination of most of the
controls. Major fiscal policy reforms also included the removal of food subsidies, the
introduction of a targeted food stamp scheme in 1978, and the reduction of fertilizer
subsidies. Government concessions on agricultural credit were also reduced (Lakshman
1994).
2. Second Stage during 1989-1994: In 1989, the leadership of the government changed,
and the same government implemented the “second series of policy reforms” for
various reasons. Macroeconomic instability, compounded by government
mismanagement of the domestic economy, the escalation of ethnic violence and
insurgency all blocked the progress of the “initial stage of incomplete reforms and
liberalization” during the 1977-1983 period (Dunham and Kelegama 1994). The first
stage of reforms caused many problems in certain sections of the community. The
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social cost of the adjustment also forced the government to implement a converted
version of the policy in the second phase. This comprised two types of policy reforms
and initiatives; first, the technically important but low profile adjustments, and second,
high profile projects including the privatization of more public institutions. Thus, the
second phase placed further emphasis on export-oriented industrialization under a more
liberalized trade regime, and a major program of poverty alleviation. Also, the private
sector was allowed to carry out the import of fertilizers, the price of which was aligned
to the world market.2
III. Performance of major policy (exogenous) and target (endogenous) variables of
the study in the Sri Lankan context
As stated above, we observe two indices such as the change of Growth Rate
Multiplier (GRM) and the change of policy variables such as E1, M2, PF, and PN, and
used them as the principle variables to see the impact of the policy. Agricultural exports
increased under the policy reforms in Sri Lanka, and are considered to be the engine of
foreign exchange earning. The policy reforms also addressed this issue. Food imports
became open under the policy reforms, the impact of which was also widely felt by the
domestic food sector. Furthermore, fertilizer continued to play an important role under
the reforms. Gradually, as the subsidies were removed, the increase in usage and price
of fertilizer to the farmers became surprisingly high. Therefore, it is imperative to
2 See Dunham and Kelegama 1994 for detailed description of second wave policy reforms.
evaluate the impact of this. Non-agricultural sector performances are always portrayed
as a hurdle for agricultural development. Many of the policy reforms carried out in
other countries tried to use this sector to restructure the economy and neglected the
agricultural sector. So, in this paper we tried to see the impacts on the agricultural sector,
using the price of non-agriculture, fertilizer price, agricultural exports and food imports.
Table 1 and Figure 1 illustrate these trends clearly.
Table 1 Growth Rate of Major Target and Policy Variables
TargetVariables 1970-1974 1975-1979 1980-1984 1985-1989 1990-1996
Average1970-1996
GR(X1) 0.43 2.26 -0.53 -4.93 -1.11 -0.78
GR(X2) 4.02 8.72 2.89 -0.92 10.45 5.03
GR(X3) 3.76 6.89 1.12 0.78 8.73 4.26
GR(XA) 2.52 14.15 0.45 -2.31 7.35 4.43
GR(Cf) 1.35 4.23 -4.01 5.87 2.45 1.98
GR(P1) -11.61 1.66 17.79 -2.51 -40.93 -7.12
GR(P2) 12.01 14.24 30.72 4.26 32.61 18.77
GR(P3) 10.92 20.67 22.34 9.45 27.52 18.18
GR(GDP) 2.92 6.29 0.61 1.82 3.63 3.05
PolicyVariables 1970-1974 1975-1979 1980-1984 1985-1989 1990-1996
Average1970-1996
GR(E1) 0.31 26.94 0.09 -7.38 -2.41 3.51
GR(M2) -11.68 -6.94 -25.89 10.76 -1.87 -7.12
GR(PF) 5.73 -3.43 16.78 10.43 -3.62 5.18
GR(PN) 16.63 12.98 27.11 16.65 20.34 18.74
Note on Variable Explanation:
GR(X1) = Growth Rate of Agricultural Production from Sector 1 (Export Agriculture).
GR(X2) = Growth Rate of Agricultural Production from Sector 2 (Domestically Produced Import
Substitutable Agricultural Output).
GR(X3) = Growth Rate of Agricultural Production from Sector 3 (Domestically Produced and Consumed
Agricultural Output).
GR(XA) = Growth Rate of Aggregate Agricultural Production (Weighted Average of Production from three
Sectors).
GR(Cf) = Growth Rate of Food Consumption (Consumption only from Sectors 2 and 3).
GR(P1) = Growth Rate of Agricultural Price from Sector 1 (Export Agriculture).
9GR(P2) = Growth Rate of Agricultural Price from Sector 2 (Domestically Produced Import Substitutable
Agricultural Output).
GR(P3) = Growth Rate of Agricultural Price from Sector 3 (Domestically Produced and Consumed
Agricultural Output).
GR(GDP) = Growth Rate of Real GDP.
GR(E1) = Growth Rate of Agricultural Export.
GR(M2) = Growth Rate of Food Imports.
GR(PF) = Growth Rate of Fertilizer Price.
GR(PN) = Growth Rate of Non-Agricultural Price.
0.00
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96
Year
Index
Total fertilizer Usage( Index, 1970=100) Fertilizer Price Index
Figure 1 Fertilizer Price and Usage Change Pattern from 1970 to 1996.
Table 1 and Figure 1 show the structure of the economy and its performance quite
clearly. The ethnic conflict in 1983 and the internal unrest in 1987 and 1988 contributed
to the decreasing trend in exports and food imports. Furthermore, the devaluation of Sri
Lankan currency Rupee under the policy reforms also contributed to the increases in
agricultural exports and non-agricultural prices, and the decrease in food imports. With
this brief introduction of the policy reform scenario, we used the following analytical
framework to evaluate the major impacts of these reforms on the agricultural sector.
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IV. Structure of the analysis and model construction
So far there have been several studies dealing with the adjustment policy effects
on the economy of Sri Lanka. In two earlier works by Bandara (1989) and Cooray
(1998 and 1999), sub-sectors of the domestic food sector were not considered. We
divided the domestic food sector into three sub-sectors in this paper, and a three
sub-sectors model with Growth Rate Multiplier (GRM) approach is used to find the
major policy effects
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3 For detailed information about the model variable, see discussion paper 0407 of
Yamaguchi, M and SriGowri Sanker (2004).
More specifically, here the economy was divided into two sectors such as agriculture
and non-agriculture. In order to evaluate the impact of plantation and other sectors, the
agricultural sector has been further divided into three sub-sectors. In our analytical
framework, the following assumptions are made. First, we assume that agriculture will
produce three products. The first one is agricultural exportable production (sector 1),
the second is import substitutable and domestically consumable production (sector 2)
and the final one is both domestically produced and consumable production (sector 3).
Second, we assume that aggregate agricultural production will depend on factors such
as land and capital, as well as variable factors such as labor and the imported input of
fertilizer. Here, the fertilizer price, which is considered as one of the important policy
variables in this study, is given for agriculture and will change under adjustment. Third,
we also assume that the price of the non-agricultural sector, which is another important
policy variable, will be determined by factors largely outside agriculture. This will
enable us to see the effect on the target (endogenous) variables.
The first framework of the model was initially done by Sarris in 1990, and we
made an almost completely different model by adding the following new equations to
remedy the inadequacies. First, Sarris did not specify the way to solve the equations in
order to fully capture the impact (effects) of the policy (exogenous) variables on target
(endogenous) variables. Second, the Sarris model also did not specify anything about
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iven below.
the non-agricultural sector. Third, he neglected the domestic consumption of exportable
goods which is very impractical in the case of Sri Lanka. Consequently, our model has
been developed remedying these shortfalls. In our static model, we have 23 equations
which include agricultural and non-agricultural, 2 production functions, 3 consumption
functions, equations for income and equations for labor allocation in both sectors4.
From these 23 equations, we obtained the dynamic model which is reduced to 21
equations as shown in Appendix Table 1. Here, the model uses the General Equilibrium
Growth Accounting Approach5 to find the impact of 11 policy (exogenous) variables on
21 target (endogenous) variables. Since the focus is on fertilizer and non-agricultural
prices, only these major results are discussed here.
The dynamic model, as given in the Appendix Table 1, has the general form Ax=b
where A is a matrix of order (21 X 21) of structural parameters, x is the column vector
of rates of change of 21 target (endogenous) variables (X1, X2, X3, XA, C1, C2, C3, Cf,
P1, P2, P3, Pf, PA, CPI, DEF, LA, Y, GDP, E, XN, LN) and b is the column vector of
rates of change of 11 policy (exogenous) variables ( E1, M2, d, e, TA, TN, PF, PN, L,
N ,LA0)6. The details of these variables and parameters are g
4 These 23 equations are shown in the place following Appendix Table 1. Please see the
discussion paper 0407 for full description of the model, the variables, and their effects. 5 Papers among these studies are Yamaguchi and Binswanger (1975), Yamaguchi (1982) and
Yamaguchi and Kennedy (1983).
6 Detailed description of the exogenous and endogenous variables can be seen from the
Discussion paper 0407 of Yamaguchi and SriGowri Sanker (2004).
Table 2 Variables and Parameters used in the Model.
Description Data Source
Target (Endogenous) Variables (21 variables):
1. Xi : Agricultural output of sector i, where i =1, 2, 3
2. X : Aggregate output of agricultural sector (sector 1, sector 2, and sector 3). A
A
3. C1 : Domestic Consumption of sector 1.
4. C2 : Domestic Consumption of sector 2.
5. C3 : Domestic Consumption of sector 3.
6. Cf : Food consumption from sectors 2 and 3.
7. Pi : Agricultural prices of three sub-sectors, where i = 1, 2, 3
8. Pf : Price of food consumption (sectors 2 and 3).
9. P : Agricultural price.
10. CPI : Consumer Price Index.
11. DEF : Deflator.
12. LA : Total agricultural labor force.
13. Y : Nominal GDP
14. GDP: Real GDP
15. E : Per capita income
2
16. XN : Non-agricultural output.
17. LN : Non-agricultural labor force.
Policy (Exogenous) Variable (11 variables):
18. E1: Exports of agricultural sector 1
19. M2: Food imports such as basic cereals that are perfect or near perfect substitutes.
20. d : Demand shifter of consumption (sector 1).
21. e : Demand shifter of consumption (food, sectors 2 and 3).
22. TA : Technical change in agriculture
23. TN : Technical change in non-agriculture.
24. PF : Fertilizer price.
25. P : Non-agricultural price. N
26. L : Total labor.
27. N : Population
28. LA0 : Initial value of agricultural labor.
Parameters
1. = Elasticity of production w.r.t Agriculture Labor. a
2. = Elasticity of production w.r.t Quantity of Fertilizer Used. b
3. η = Income Elasticity of Demand for Food.
4. ε = Price Elasticity of Demand for Food.
5. τ = Positive Elasticity of Transformation (CET Function).
6. = Price Elasticity of Cn 1.
7. = Income Elasticity of Cq 1. 3
8. σ = Elasticity of Substitution (CES Function).
9. s1 = C1/X1 = Ratio of Consumption from sector 1.
10. s2 = X2/C2 = Initial Self-Sufficiency Ratio of sector 2.
11. υ i = υ1
,υ 2,υ 3
Value of Shares of Each Agricultural Product in the Total
Value, . 3,2,1=i
12. μ A = Share of Agriculture in GDP.
13. Vf = Share of Food Products (Sectors 2 & 3) in the Total Consumer Budget.
14. λ 2 = Share of Sector 2 Agriculture to Total Consumption of Sectors 2 and 3.
15. ξ = Elasticity of Production (Non-Agriculture) w.r.t Non-Agriculture Labor.
16. γ 1 = Elasticity of TA w.r.t Agriculture Labor.
17. γ 2 = Elasticity of TN w.r.t Agriculture Labor.
18. γ 3 = Elasticity of L w.r.t Agriculture Labor.
19. = Share of Agriculture Labour Force to Total Labor (Ll A A/L).
20. = Share of Non-Agriculture Labour Force to Total Labor (LlB A/L)
Note:The data for this study was obtained from Annual Report of Central Bank of
Sri Lanka-Statistical Appendix, for various years, Socio-Economic Data of Sri Lanka
by Central Bank (various years) and HARTI Agrarian Data, through Time Series Data
of Sri Lanka Agriculture of Hector Kobbekaduwa Agrarian Research and Training
Institute (HARTI), Ministry of Agriculture, Government of Sri Lanka. Many of the
Parameters’ value were estimated and certain values were also obtained from
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Central Bank and HARTI.
The inverse matrix of A displays the Growth Rate Multipliers (GRMs )7 which are
obtained by calculating the inverse of the above matrix of structural parameters. Here
we can see that GRMs are affected by SAP through the parametric values of A matrix.
These effect values are given in Appendix Table 2 which allows us to find the influence
of the exogenous variables on the endogenous variables. As an example,
element is
2,81 )( −A
∧∧
∂∂
2MC f (we write this as CfM2) which indicates by how much the
rate of change of aggregate consumption of food Cf changes due to (or effects) an
increase or decrease in the growth rate of import substitute M2. Similarly, we could
attribute to another policy (exogenous) variables, such as ( )2
1∧
∧
∂
∂
M
X =(X1M2) is the
relevant GRM, which shows how much percentage (%) of X1 would increase when M2
increases by 1%. From Figure2, we can see how SAP affected the GRM. These effects
are described in section 5.1.
In addition, the contributions of exogenous (policy) variables to the endogenous
(target) variables are calculated by multiplying the GRMs of each year interval by the
corresponding rates of change of the exogenous variables. The calculated values of
these contributions are given in Appendix Table 3. For example, CX1M2 =
5
7 For further details of the application of GRM, see Yamaguchi (1982), Yamaguchi and
Kennedy (1984), and Yamaguchi and Binswanger (1975).
( )() 2
2
1 MGRM
X∧
∧
∂
∂ , where CX1M2 is the contribution of the agricultural food imports M2
to the agricultural production for exports X1. This will explain how much is contributed
by the rate of change in food imports into the rate of change of agricultural production
for exports. Here, ( )2
1∧
∧
∂
∂
M
X =(X1M2) is the relevant GRM, which shows what
percentage (%) of X1 would increase when M2 increases by 1% as shown before.
Detailed discussion on these results is given in the following section. From Figure 3,
we can also see how SAP affected both the GRM and the growth rate of policy
variables. Concrete example of this phenomenon is explained at the end of section5.2
using the calculated values of GRM and contribution.
V. Discussion on results
A. Discussion on effects
Appendix Table 2 details the values of effects in detail in relation to this model
based on the GRMs. It would take considerable space to describe the performance of all
the effects, hence, only the principal effects which are mentioned in the earlier sections
of this paper and clearly describe the policy effects are discussed here8. As mentioned
6
8 See the discussion paper 0407 of Yamaguchi and SriGowri Sanker (2004) for detailed
analysis and the performance pattern of the entire exogenous and endogenous variables of
the model.
7
above, GRMs are obtained by calculating the inverse of the above matrix of structural
parameters.
Fertilizer price and non-agricultural price have completely opposite effects on the
economy. First, we focus on the fertilizer price. It can be seen that changes in the
fertilizer price have a much more negative effect on the domestic food sector (X2PF <0
and X3PF <0) than on X1 (X1PF <0), due to its usage pattern. For example, a 100%
increase in fertilizer prices would bring down production of X1, X2 and X3 by 1%, 10%,
and 10% in 1970-1974 to 3%, 16%, and 15% in 1990-1996 respectively. It clearly
shows the effect of the increase of fertilizer price under SAP. For example, XAPF
indicates the effect of fertilizer price PF on aggregate agricultural production, XA. In
this way, we can understand the effects of other policy variables on target variables as
explained in Figure 2 and in Appendix Table 2.
Effect on Export Agriculture Production (X1)
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
70-74 75-79 80-84 85-89 90-96
X1PF X1PN X1E1 X1M2
Effect on Import Substitutable DomesticAgriculture Production (X2)
-0.30
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
70-74 75-79 80-84 85-89 90-96
X2PF X2PN X2E1 X2M2
Effect on Domestically Consumable DomesticAgriculture Production (X3)
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
70-74 75-79 80-84 85-89 90-96
X3PF X3PN X3E1 X3M2
Effect on Aggregate Agriculture Production(XA)
-0.20
-0.10
0.00
0.10
0.20
0.30
0.40
0.50
0.60
70-74 75-79 80-84 85-89 90-96
XAPF XAPN XAE1 XAM2
Effect on Export Agriculture Price (P1)
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
70-74 75-79 80-84 85-89 90-96
P1PF P1PN P1E1 P1M2
Efect on Import Substitutable DomesticAgriculture Price (P2)
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
70-74 75-79 80-84 85-89 90-96
P2PF P2PN P2E1 P2M2
Effect on Domestically Consumable DomesticAgriculture Price (P3)
-0.50
0.00
0.50
1.00
1.50
70-74 75-79 80-84 85-89 90-96
P3PF P3PN P3E1 P3M2
Effect on GDP (Real)
-0.05
0.00
0.05
0.10
0.15
0.20
70-74 75-79 80-84 85-89 90-96
GDPPF GDPPN GDPE1 GDPM2
Figure 2 Graphic Representations of Effects on Selected Target Variables.
Note: X1PF = Effect of fertilizer price PF on exportable agricultural production from sector 1 X1.
X1PN = Effect of non-agricultural price PN on exportable agricultural production from sector 1 X1.
8X1E1 = Effect of agricultural exports E1 on exportable agricultural production from sector 1 X1.
9
, due to the
chan
X1M2 = Effect of food imports M2 on exportable agricultural production from sector 1 X1.
Similarly other notations and trends can be understood.
The changing pattern of fertilizer prices always affects the prices of agricultural
products from all the three sectors (P1PF, P2PF, P3PF >0). Under the SAP, fertilizer
prices increased due to the reduction and removal of subsidies. This in turn, negatively
affected the production (X1PF, X2PF, X3PF <0), thus increasing the prices of
agricultural products. It severely affected agriculture after the policy reforms. This is
evident in the changing pattern of price indices of agriculture which registered an
alarming increase during 1990-1996 in comparison to that of 1970-1974 (e.g., P1PF
increased from about 0.79 to 1.32; P2PF increased from about 0.18 to 0.42; P3PF
increased from about 0.20 to 0.49). Hence, it could be concluded from this that a
considerably negative effect is felt on agricultural production and prices
ge in fertilizer prices.
On the other hand, we can also conclude that the expansion of the non-agricultural
sector does not adversely affect the agricultural sector. It is also worth mentioning that
the non-agricultural price (PN) decreased the agricultural exportable production (X1PN
<0) in the pre-reform period, but after the policy reforms, PN helped the production
from sector 1, X1 (X1PN >0. X1PN increases from about 0 to 0.03.). Positive effects
could be observed in the case of import substitute and domestic food sectors (X2PN >0,
X2PN increases from about 0.10 to 0.42. X3PN >0, X3PN increases from about 0.10 to
10
the policy reform stages in 1970-1979, it increased substantially in the
1990
y. However, the increase in fertilizer price has had a very
bad
0.40). Overall PN tends to increase the production of aggregate agriculture XA (XAPN
>0, XAPN increases from about 0.06 to 0.29). Although this effect was small in the
beginning of
-1996 period.
Increases in fertilizer price (PF ) decreases real GDP and decreases food
consumption (Cf ) although nominal GDP (Y ) increases because of the increases of P1,
P2, P3 (i.e., inflation due to the increase of fertilizer price). However, increases in
non-agricultural price (PN ) increases all the variables mentioned above, i.e., PN
increases nominal GDP (Y) and also increases real GDP (GDP) and increases food
consumption (Cf ) (see YPN>0, GDPPN>0 and CfPN>0 in Appendix Table 2).
Therefore, the expansion of the non-agricultural sector including PN does not always
adversely affect the econom
effect on Sri Lanka’s economy.
It is quite evident that the trend of agricultural exports E1 had a notable impact on
the agricultural production of both exportable and domestically produced and
consumed items (see X1E1, X2E1 and X3E1 in Figure 2 and in Appendix Table 2). The
effect in this regard is quite large compared to the two sectors, sectors 2 and 3. This is
expected under SAP but the effect of exports on sector 2 production is somewhat larger
than that of sector 3 (X2E1 > X3E1). Although these two effects are negative before
1975, the larger positive effects on sector 2 and 3 after 1975 clearly show that both
11
ll
agricultural production XA (XAM2<0) as shown in Figure 2 and in Appendix Table 2.
B.
learly shows
e percentage contribution of the policy variables to the target variables.
sectors, import substitute and domestic food production, are affected positively by
agricultural exports from the same period (1975-79). Nevertheless, the overall
agricultural production XA shows positive increasing effects since 1975-79 to 1980-84,
and again a declining trend until 1996 (see XAE1 in Figure 2 or Appendix Table 2). This
clearly illustrates the initial shift in the production of agricultural exports soon after the
implementation of the policy reforms and the decline in the later stages of the reforms
due to other exogenous factors affecting the exports and the production. Since the
opening of trade allowed the food imports M2, the negative effect of M2 became strong
in the domestic food production X2 and X3 (X2M2<0, X3M2<0) as well as on the overa
Discussion on contributions
Further changes on these effects can be clearly understood from analyzing the
results of contributions of the policy (exogenous) variables on target (endogenous)
variables, as given in graphically, in Figure 3 and in Appendix Table 3. The most
important variables, fertilizer and the non-agricultural prices, have also contributed
significantly to the agricultural output negatively and positively. Figure 3 c
th
12
Contribution of 4 Policy Variables toAggregate Agricultural Production (XA)
-6
-4
-2
0
2
4
6
8
10
12
14
16
70-74 75-79 80-84 85-89 90-96
Year
Perc
enta
ge C
ontr
ibuti
on
GR(XA) CXAPF CXAPN CXAE1 CXAM2
Contribution of 4 Policy Variables to ExportAgriculture Price (P1)
-50
-40
-30
-20
-10
0
10
20
30
70-74 75-79 80-84 85-89 90-96
Year
Perc
enta
ge C
ontr
ibution
GR(P1) CP1PF CP1PN CP1E1 CP1M2
Contribution of 4 Policy Variables to GDPGrowth (GDP-Real)
-2-101234567
70-74 75-79 80-84 85-89 90-96
Year
Perc
enta
ge C
ontr
ibuti
on
GR(GDP) CGDPPF CGDPPN
CGDPE1 CGDPM2
Contribution of 4 Policy Variables to ImportSubstitutable Domestic Agriculture Price (P2)
-10
0
10
20
30
40
70-74 75-79 80-84 85-89 90-96
Year
Perc
enta
ge C
ontr
ibuti
on
GR(P2) CP2PF CP2PN CP2E1 CP2M2
Contribution of 4 Target Variables toDomestically Consumable Domestic
Agriculture Price (P3)
-5
0
5
10
15
20
25
30
35
70-74 75-79 80-84 85-89 90-96
Year
Perc
enta
ge C
ontr
ibution
GR(P3) CP3PF CP3PN CP3E1 CP3M2
epresentation of Percentage Contribution of Policy Variables to
ution of fertilizer price PF to the performance of aggregate agricultural production XA.
Figure 3 Graphical R
the Target Variables.
Note: GR(XA) = Growth rate of aggregate agricultural production XA.
CXAPF= Contrib
CXAPN= Contribution of non-agricultural price PN to the performance of aggregate agricultural
production XA.
13
icy
varia
h
(CGDPPF <0, maximum negative contribution was -47.99% in the year of 1980-84).
CXAE= Contribution of agricultural exports to the performance of aggregate agricultural production XA.
CXAM2 = Contribution of food imports M2 to the performance of aggregate agricultural production XA.
Similarly, we can understand the other notations and trends. The growth rate of each
histogram (e.g., 2.52% of XA in 1970-74) is the sum of 4 contributions of 4 pol
bles in Figure 3, plus 7 other policy variables such as d, e, TA, TN, L, N and LA0.
First, as shown in the values of Figure 3 and Appendix Table 3, the fertilizer price
has about 235% of contribution to the decrease of the agricultural output (CXAPF
=-234.78%) in 1980-1994. The contribution of these policy variables is also shown in
the prices of the agricultural outputs XA in Figure 3. It is quite evident that the
contribution of fertilizer prices to the price of products of all the three sectors (CP1PF,
CP2PF, CP3PF ) is very large, reaching a high of 98.14% in sector 2 during 1985-89.
Mostly, the contribution of the fertilizer prices to P1, P2 and P3 was negative in the
beginning of the policy reform (1975-79) because of the decrease of fertilizer price
(-3.43%, see Table 1), but tends to increase later, thus increasing the prices of P1, P2
and P3. Since the small-scale farmers are often affected by this increase of PF, the
policy option here should be rationalizing the fertilizer subsidy based on the cultivation
size. Furthermore, the decrease in the growth rate of GDP was also evidenced here in
the period of 1985-89, following that of 1980-84. The negative contribution of the
decrease in agricultural exports to GDP (CGDPE1<0) is 48.20% in the period of
1985-89. Also, the fertilizer price increase negatively contributed to the GDP growt
14
e period (1975-1979). Also, the
large
the understanding of the performance of
It is noteworthy that the prices of products from sectors 2 and 3 (P2 and P3) are
also considerably affected by the non-agricultural price (PN) and the contribution from
this is quite strong (CP2PN and CP3PN are very large). This trend further endorses the
assumption that the development of the non-agricultural sector tends to increase its
prices, and this contributes positively to the agricultural products (CXAPN >0 in almost
all periods). The change of other policy variables given by E1 and M2 contributed to the
performance of agricultural output XA (CXAE1 and CXAM2). The biggest contribution of
exportable to agricultural output is in 1975-1979 just at the beginning of the policy
reform. Exports contributed almost 100% to the growth of XA (CXAE1 = 98.19 % in
1975-79). Also the biggest contribution of export to agricultural exportable price P1
(CP1E1) is 743% in 1975-1979. In the same way, E1 has the largest contribution to
other agricultural prices like P2 and P3 in the sam
st contribution of E1 to GDP is 65% in the same period.
However, the biggest contribution of import (owing to the decrease of import) to
agricultural output (CXAM2) is 88.89% in the 1980-1984. Also, the biggest contribution
of M2 to P1, P2 and P3 are in 1985-1989. Especially, the impact of M2 on P2, (i.e.,
importable and domestically produced) in 1985-1989 is the largest and decreased the
price to 137%. Consequently, inflation made GDP decrease in the same period. Hence,
the calculation of contribution further enriched
15
endo
eform (SAP) on the target variables. This gives
the overall picture of the SAP impact.
genous variables in relation to the GRM.
More specifically, Here we must know how much E1, M2 and PF increased or
decreased by SAPs. For PF, we can obtain 5.18% by calculating the growth rate of PF
from 1970 to 1996. In other words, the growth rate of PF would become zero if Sri
Lankan government controls the increase of PF. For E1 and M2, the situation is not so
simple, because of the influence of the devaluation of the Rupee9 on the increase of E1
and the decrease of M2. For simplicity, we assumed that the increase of E1 and decrease
of M2 are the same as the percentage of devaluation of the Rupee (i.e., 9.64%). Then,
we could obtain the growth rate of E1 as -6.13 (actual value is 3.51) %, and the growth
rate of M2 as 16.76 (actual value is 7.12) %. In other words, E1 increased and M2
decreased by 9.64%. Now, we can calculate how much these values (9.64, 9.64 and
5.18) for E1, M2 and PF contribute to the growth of XA by calculating (XAE1)*GR(E1),
(XAM2)*GR(M2) and (XAPF)*GR(PF). From our calculations, XAE1 = 0.44, XAM2 =
-0.04 and XAPF = -0.08, and the growth rates of E1, M2 and PF as 9.64, 9.64 and 5.18%.
Hence, the contribution of E1, M2 and PF (i.e., (XAE1)*GR(E1), (XAM2)*GR(M2) and
(XAPF)*GR(PF)) are calculated as 4.24, 0.39 and 0.41%. Therefore, the total
contribution of SAPs comes to 5.04% if we add these values together. This way we
could capture the effect of the policy r
9 Rupee is the name of the Sri Lankan local currency.
16
unting approach. We
obtai
of SAP on agriculture is favorable for both agricultural and economic
deve
VI. Overall conclusion
We constructed the model of AX = b, where b has the policy variables and X has the
target variables as explained in the previous sections. The effect of the policy variables
on the target variables were, therefore, able to be obtained through this model with an
appropriate approach as elaborated in the presiding sections. Empirical appropriateness
and suitability for policy evaluation is justified through this analysis. Since this study is
originally growth accounting for Sri Lanka’s agriculture, policy impact (the effect of
SAP) was evaluated through two methods such as the change of GRM and the change
of policy variables as explained above under this growth acco
ned the positive overall effect of Sap as summarized below.
The fertilizer prices that change under the policy adjustments have fairly large
negative effects on the domestic agricultural economy. The positive impact of the
non-agricultural price on agriculture is fairly large. Since the positive impact of export
earnings compensates for the negative impacts of food import and fertilizer price, the
overall impact
lopment.
In two earlier notable works by Bandara (1989) and Cooray (1998 and 1999), they
argued that the SAP reforms were detrimental to the agricultural sector and
concentrated only on the domestic food sector. We have carefully studied this fact
17
bined. Therefore, SAP had a positive effect, in total, on the Sri Lankan
econ
verall
agric
through dividing agriculture into three sub-sectors. It is proved from our study that SAP
had a comparatively bad effect on domestic food sectors, such as sector 2 and sector 3,
although SAP had a good effect on the exportable agriculture sector. The effects of M2
and PF were negative but the positive effect of E1 was larger than these two negative
effects com
omy.
As seen above, the negative fertilizer contribution, due to the increase of PF, was
considerably higher in the 3rd (1980-84) and 4th (1985-89) periods of SAP
implementation. Therefore, the Sri Lankan government advocated restoring the
fertilizer subsidy. The period of 1990-96 clearly shows that the decrease in the fertilizer
price positively contributed to agricultural development. Due to this policy, the o
ulture sector developed positively and GDP also recorded a positive trend.
Therefore, we have to control the fertilizer price in case of its escalation. Also, it
can be understood that an increase in non-agricultural price has a rather positive
contribution on agriculture too. This once again reinforces the importance of the growth
of non-agriculture for agriculture. However, we should not forget the importance of the
contribution of export of agriculture from sector 1 in the earlier periods, especially in
the period of 1975-79 as shown in Figure 3. The decrease in food import also
contributed positively to the growth of Sri Lankan agriculture. These increases in
exports and decreases in imports were made through the devaluation of the Rupee. In
18
valuation of local currency are extremely important for every
developing country.
short, we can reconfirm again that an effectively balanced combination of agricultural
and non-agricultural development, using the control of fertilizer price, the importance
of non-agricultural development, the importance of increasing exports and decreasing
imports, and the de
19
Macroeconomic Policies,
ic and Social
of Sri Lanka-Statistical
Socio-Economic Data of Sri Lanka. Colombo: Central Bank of Sri
ence
raining Institute. Ministry of Agriculture,
aper no. 6/89. Australia:
oach to the Sri Lankan Case” Regional Development
ysis and Planning:
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Development Paper no. 95, Rome: Food and Agriculture Organization.
Central Bank. Various Years. Annual Report of Central Bank
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Central Bank. 2002.
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Studies 4: 37-63.
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20
l
Japan: 1880-1965.” American Journal of Agricultural
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chool of Economics, Kobe University.
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S
Appendix Table 1 Dynamic Form of the Model
Equation Number Equations
(1) from equation A-10 where s11111 )1(∧∧∧
+−= CsEsX 1=C1/X1
(2) from equation A-11 where s222 )1( 22
∧∧∧
=−+ CMsXs 2=X2/C2
(3) from equation A-12 33
∧∧
= CX
(4) from equations A-8,A- 9 where υiiA
iPP ∑
=
∧∧
=3
1υ i = PiXi(P1X1+P2X2+P3X3)
(5) from equation A-22 + + ∧∧∧
+−= EqPnC 11 N d∧
+ NPn
(6) from equation A-4 )(111
1FAAAA PP
bbL
baT
bX
∧∧∧∧∧
−−
+−
+−
=
(7) from equation A-19 + A0 ∧∧∧∧
++= LTTL NAA 321 γγγ L
(8) from equation A-15 )( 22 ff PPCC∧∧∧∧
−−= σ
(9) from equation A-15 )( 33 ff PPCC∧∧∧∧
−−= σ
(10) from equations A-13, A-16 where, 3222 )1(∧∧∧
−+= PPP f λλ
λ2 = P2X2/(P2C2+P3C3)
(11) from equation A-17 + + )()( NfNf PPPYC∧∧∧∧∧
−−−= εη N e
(12) from equations A-5, A-18
))(1(11
111
1NNAFAAAA XPP
bbP
bL
baT
bY
∧∧∧∧∧∧∧
+−+⎥⎦⎤
⎢⎣⎡
−−
−+
−+
−= μμ
where Aμ = share of agriculture in GDP
(13) Nfff PPICP∧∧∧
−+= )1( νν
(14) NAAA PPFED∧∧∧
−+= )1( μμ
(15) from (6), (20) of Appendix Table 1
NAFAAAA XPPb
bLb
aTb
PDG∧∧∧∧∧∧
−+⎥⎦⎤
⎢⎣⎡ −
−+
−+
−= )1()(
1111 μμ
(16) from equation A-8 )( 11 AA PPXX∧∧∧∧
−+= τ
21
(17) from equation A-8 )( 22 AA PPXX∧∧∧∧
−+= τ
(18) from equation A-8 )( 33 AA PPXX∧∧∧∧
−+= τ
(19) from equation A-23 ∧∧∧
=−→= NEPDGNGDPE /
(20) from equation A-21 NNN LTX∧∧∧
+= ξ
(21) from equation A-20 where lNA LlLlL NA
∧∧∧
+= A=LA /L, lN=LN /L
From this Appendix Table 1, we can derive the model in the matrix form AX = b as
follows.
X1 X2 X3 XA C1 C2 C3 Cf P1 P2 P3 Pf PA CPI DEF LA Y GDP E XN LN
(1) 1 0 0 0 (-s1) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
(2) 0 s2 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
(3) 0 0 1 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0
(4) 0 0 0 0 0 0 0 0 v1 v2 v3 0 -1 0 0 0 0 0 0 0 0
(5) 0 0 0 0 1 0 0 0 (n) 0 0 0 0 0 0 0 0 (-q) 0 0
(6) 0 0 0 -1 0 0 0 0 0 0 0 0 b/1-b 0 0 a/1-b 0 0 0 0 0
(7) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
(8) 0 0 0 0 0 1 0 -1 0 σ 0 (−σ) 0 0 0 0 0 0 0 0 0
(9) 0 0 0 0 0 0 1 -1 0 0 σ (−σ) 0 0 0 0 0 0 0 0 0
(10) 0 0 0 0 0 0 0 0 0 λ2 1−λ2 -1 0 0 0 0 0 0 0 0 0
(11) 0 0 0 0 0 0 0 -1 0 0 0 (−ε) 0 0 0 0 η 0 0 0 0
(12) 0 0 0 0 0 0 0 0 0 0 0 0 μA/1-b 0 0 aμA/1-b -1 0 0 1-μΑ 0
(13) 0 0 0 0 0 0 0 0 0 0 0 Vf 0 -1 0 0 0 0 0 0 0
(14) 0 0 0 0 0 0 0 0 0 0 0 0 μA 0 -1 0 0 0 0 0 0
(15) 0 0 0 0 0 0 0 0 0 0 0 0 bμA/1-b 0 0 aμA/1-b 0 -1 0 1-μΑ 0
(16) -1 0 0 1 0 0 0 0 τ 0 0 0 (−τ) 0 0 0 0 0 0 0 0
(17) 0 -1 0 1 0 0 0 0 0 τ 0 0 (−τ) 0 0 0 0 0 0 0 0
(18) 0 0 -1 1 0 0 0 0 0 0 τ 0 (−τ) 0 0 0 0 0 0 0 0
(19) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 -1 0 0
(20) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
(21) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 l1 0 0 0 0 l2
1P
AL
NXNL
( ) 11 ˆ1 Es−
( ) FA PbbTb
ˆ1/ˆ1
1−+
−
( ) ( ) NAAAA PPbbT
bF ˆ1ˆ1/ˆ
1−+−+
−μμ
μ
( ) Nf PV ˆ1−
( ) NA P1−μ
N
NT
L
00
0
0
00
00
ζ−
2P3PfPAP
1X
2X3XAX
E
( ) FAAA PbbT
bˆ1/ˆ
1−+
−μμ
Y
FED
=
( ) 22ˆ1 Ms −
IPCˆ
PDG
∧∧∧∧
−−− NePP NN εη
∧∧∧∧
+++ 0321 ANA LLTT γγγ
∧
1C∧
2C∧
3C∧
fC
∧∧∧
++ NPnNd
22
These 21 equations in Appendix Table 1 are derived from the following 23 equation
(see discussion paper 0407 for more details).
---------------------------------------------------------------------------------------------------------
23
FAAA
FFAAA
F FAA
A FAA
FAAAA
ba XLTX = a,b >0 a+b <1 (A-1)
Max V (A-2) XPXP −=
=X (TAbbba bPPL −−− 1/11/11/1 )/() (A-3)
=X (TAbbbbba bPPL −−− 1/1/1/1 )/() (A-4)
V (A-5) bbbbbba bbPPLT −−−− −= 1//)1(1/11/1 )1()(
X (A-6) ∑=
−−−=3
1
)1/(/)1( )(i
iiA X τττττα
Max (A-7) ∑=
3
1iii XP
X i = 1, 2, 3 (A-8) ττα )/( AiAii PPX−=
P (A-9) ∑=
++−=3
1
)1/(11 )(i
iiA P τττα
X1 = E1 + C1 (A-10)
X2 + M2 = C2 (A-11)
X3 =C3 (A-12)
C (A-13) )1/(/)1(33
/)1(22 )( −−− += σσσσσσ ββ CCf
Min (P (A-14) )3322 CPC +
C i =2, 3 (A-15) σσβ −= )/( fiifi PPC
P (A-16) ∑=
−−=3
2
)1/(11 )(i
iif P σσσβ
Cf =f(N, Y, Pf, PN) = eN(Y/PN)η(Pf /PN )-ε ( e: demand shifter) (A-17)
Y = ( NNANNFFAA XPVYXPXPXP +=⇒+− ) (A-18)
LA = g(TA, TN, L) = LA0TAγ1TNγ2Lγ3 γ1 ,γ2 <0 γ3 >0 (A-1
9
XN = TNLNξ
-------------------------------------------------------------------------------------------------------
)
L = LA + LN (A-20)
(A-21)
qnN EPPdNC −= )/( 11 (d: demand shifter) (A-22)
E = GDP / N (A-23)
--
24
25
Effect on X1 70-74 75-79 80-84 85-89 90-96 Effect on X2 70-74 75-79 80-84 85-89 90-96
X1PF -0.01 -0.01 -0.02 -0.02 -0.03 X2PF -0.10 -0.11 -0.12 -0.14 -0.16
X1PN 0.00 0.00 0.00 0.01 0.03 X2PN 0.10 0.11 0.11 0.13 0.42
X1E1 0.75 0.75 0.74 0.71 0.65 X2E1 -0.02 0.18 0.28 0.29 0.28
X1M2 0.00 0.00 0.00 0.00 -0.01 X2M2 -0.02 -0.04 -0.06 -0.11 -0.20
Effect on X3 70-74 75-79 80-84 85-89 90-96 Effect on XA 70-74 75-79 80-84 85-89 90-96
X3PF -0.10 -0.11 -0.11 -0.13 -0.15 XAPF -0.06 -0.05 -0.06 -0.09 -0.12
X3PN 0.10 0.11 0.11 0.13 0.40 XAPN 0.06 0.04 0.05 0.08 0.29
X3E1 -0.02 0.17 0.27 0.27 0.27 XAE1 0.32 0.52 0.52 0.44 0.39
X3M2 0.00 0.00 -0.01 -0.05 -0.12 XAM2 0.00 -0.01 -0.02 -0.04 -0.11
Effect on Cf 70-74 75-79 80-84 85-89 90-96 Effect on P1 70-74 75-79 80-84 85-89 90-96
CfPF -0.08 -0.09 -0.09 -0.08 -0.05 P1PF 0.79 0.96 1.06 1.19 1.32
CfPN 0.08 0.09 0.09 0.07 0.12 P1PN 0.12 -0.04 -0.12 -0.26 -1.08
CfE1 -0.02 0.15 0.22 0.16 0.08 P1E1 5.78 4.47 3.52 3.07 2.66
CfM2 0.17 0.14 0.18 0.39 0.67 P1M2 -0.01 0.01 0.04 0.14 0.41
Effect on P2 70-74 75-79 80-84 85-89 90-96 Effect on P3 70-74 75-79 80-84 85-89 90-96
P2PF 0.18 0.29 0.37 0.40 0.42 P3PF 0.20 0.32 0.41 0.45 0.49
P2PN 0.81 0.70 0.62 0.59 1.56 P3PN 0.79 0.67 0.59 0.54 1.38
P2E1 0.59 0.67 0.49 0.30 0.21 P3E1 0.60 0.62 0.41 0.20 0.09
P2M2 -0.16 -0.25 -0.36 -0.54 -0.84 P3M2 0.02 -0.01 -0.05 -0.15 -0.35
Effect on Y 70-74 75-79 80-84 85-89 90-96 Effect on GDP 70-74 75-79 80-84 85-89 90-96
YPF 0.11 0.19 0.19 0.17 0.15 GDPPF -0.02 -0.02 -0.02 -0.02 -0.03
YPN 0.87 0.79 0.80 0.82 1.63 GDPPN 0.02 0.01 0.01 0.02 0.07
YE1 0.91 1.01 0.72 0.48 0.32 GDPE1 0.09 0.15 0.14 0.12 0.10
YM2 -0.01 -0.01 -0.02 -0.05 -0.09 GDPM2 0.00 0.00 0.00 -0.01 -0.03
Appendix Table 2: Effects of Exogenous Variables on Endogenous Variables
26
Year GR(X1) GR(X1) (%) CX1PF CX1PF (%) CX1PN CX1PN (%) CX1E1 CX1E1 (%) CX1M2 CX1M2 (%)1970-1974 0.43 100.00 -0.06 -13.55 -0.01 -3.30 0.23 53.89 -0.161975-1979 2.26 100.00 0.05 2.04 0.01 0.62 2.01 89.09 0.00 0.051980-1984 -0.53 100.00 -0.27 51.76 0.07 -13.05 0.07 -12.46 0.02 -3.621985-1989 -4.93 100.00 -0.22 4.48 0.09 -1.88 -5.21 105.58 -0.03 0.661990-1996 -1.11 100.00 0.17 -15.42 0.63 -56.77 -1.89 170.34 0.02 -1.80
Year GR(X2) GR(X2) (%) CX2PF CX2PF (%) CX2PN CX2PN (%) CX2E1 CX2E1 (%) CX2M2 CX2M2 (%)1970-1974 4.02 100.00 -0.58 -14.55 1.70 42.34 -0.01 -0.18 0.27 6.711975-1979 8.72 100.00 0.39 4.47 1.44 16.52 4.78 54.79 0.27 3.101980-1984 2.89 100.00 -2.00 -69.37 3.10 107.13 0.03 0.87 1.56 54.071985-1989 -0.92 100.00 -1.46 158.54 2.22 -241.74 -2.13 231.90 -1.13 123.321990-1996 10.45 100.00 0.99 9.49 10.10 96.63 -0.82 -7.88 0.40 3.81
Year GR(X3) GR(X3) (%) CX3PF CX3PF (%) CX3PN CX3PN (%) CX3E1 CX3E1 (%) CX3M2 CX3M2 (%)1970-1974 3.76 100.00 -0.57 -15.13 1.66 44.03 -0.01 -0.18 -0.05 -1.241975-1979 6.89 100.00 0.38 5.46 1.39 20.17 4.61 66.89 0.02 0.231980-1984 1.12 100.00 -1.92 -171.10 2.96 264.24 0.02 2.16 0.35 31.381985-1989 0.78 100.00 -1.38 -177.09 2.11 270.03 -2.02 -259.04 -0.50 -64.711990-1996 8.73 100.00 0.93 10.65 9.47 108.53 -0.77 -8.85 0.25 2.85
Year GR(XA) GR(XA) (%) CXAPFCXAPF
(%) CXAPN CXAPN (%) CXAE1 CXAE1 (%) CXAM2 CXAM2 (%)1970-1974 2.52 100.00 -0.35 -13.79 0.93 36.91 0.10 3.90 0.04 1.761975-1979 14.15 100.00 0.18 1.28 0.58 4.08 13.89 98.19 0.05 0.341980-1984 0.45 100.00 -1.06 -234.78 1.44 320.55 0.05 10.38 0.40 88.891985-1989 -2.31 100.00 -0.95 41.18 1.36 -58.70 -3.28 142.02 -0.48 20.631990-1996 7.35 100.00 0.71 9.71 6.93 94.31 -1.13 -15.38 0.22 3.00
Year GR(Cf) GR(Cf) (%) CCfPF CCfPF (%) CCfPN CCfPN (%) CCfE1 CCfE1 (%) CCfM2 CCfM2 (%)1970-1974 1.35 100.00 -0.47 -35.14 1.38 102.25 -0.01 -0.42 -1.98 -146.751975-1979 4.23 100.00 0.32 7.60 1.19 28.10 3.94 93.18 -0.99 -23.421980-1984 -4.01 100.00 -1.54 38.49 2.38 -59.44 0.02 -0.48 -4.75 118.561985-1989 5.87 100.00 -0.80 -13.66 1.22 20.84 -1.17 -19.99 4.22 71.881990-1996 2.45 100.00 0.27 11.14 2.78 113.50 -0.23 -9.26 -1.35 -55.23
Year GR(P1)GR(P1)
(%) CP1PF CP1PF (%) CP1PN CP1PN (%) CP1E1 CP1E1 (%) CP1M2 CP1M2 (%)1970-1974 -11.61 100.00 4.53 -39.05 2.08 -17.88 1.77 -15.28 0.10 -0.851975-1979 1.66 100.00 -3.29 -198.38 -0.48 -29.16 12.33 742.92 -0.04 -2.431980-1984 17.79 100.00 17.77 99.88 -3.39 -19.03 0.32 1.77 -0.94 -5.281985-1989 -2.51 100.00 12.43 -495.27 -4.35 173.47 -2.67 106.48 1.53 -60.951990-1996 -40.93 100.00 -8.00 19.54 -25.84 63.12 -7.71 18.83 -0.82 2.01
Year GR(P2) GR(P2) (%) CP2PF CP2PF (%) CP2PN CP2PN (%) CP2E1 CP2E1 (%) CP2M2 CP2M2 (%)1970-1974 12.01 100.00 1.03 8.55 13.51 112.48 0.18 1.52 1.90 15.821975-1979 14.24 100.00 -1.00 -7.05 9.03 63.40 7.96 55.87 1.75 12.321980-1984 30.72 100.00 6.23 20.29 16.79 54.67 0.04 0.14 9.35 30.441985-1989 4.26 100.00 4.18 98.14 9.85 231.33 -2.19 -51.52 -5.82 -136.531990-1996 32.61 100.00 -2.53 -7.76 37.28 114.33 -0.59 -1.82 1.70 5.22
Year GR(P3) GR(P3) (%) CP3PF CP3PF (%) CP3PN CP3PN (%) CP3E1 CP3E1 (%) CP3M2 CP3M2 (%)1970-1974 10.92 100.00 1.13 10.34 13.21 120.96 0.18 1.68 -0.21 -1.911975-1979 20.67 100.00 -1.10 -5.30 8.69 42.04 16.83 81.43 0.06 0.281980-1984 22.34 100.00 6.82 30.54 15.88 71.10 0.04 0.16 1.28 5.711985-1989 9.45 100.00 4.70 49.69 9.07 95.98 -1.44 -15.25 -1.62 -17.121990-1996 27.52 100.00 -2.94 -10.68 33.13 120.37 -0.25 -0.92 0.71 2.57
Year GR(GDP)GR(GDP)(%
) CGDPPFCGDPPF
(%) CGDPPNCGDPPN
(%) CGDPE1CGDPE1
(%) CGDPM2 CGDPM2(%)1970-1974 2.92 100.00 -0.10 -3.38 0.26 9.06 0.03 0.96 0.01 0.431975-1979 6.29 100.00 0.05 0.86 0.17 2.71 4.10 65.15 0.01 0.231980-1984 0.61 100.00 -0.29 -47.99 0.40 65.52 0.01 2.12 0.11 18.171985-1989 1.82 100.00 -0.26 -14.03 0.36 19.92 -0.88 -48.20 -0.13 -7.001990-1996 3.63 100.00 0.17 4.74 1.71 47.13 -0.28 -7.68 0.05 1.50
Appendix Table 3: Contribution of Exogenous Variables to the Endogenous Variables
Percentage Contribution of Exogenous Variables to Value of Production of Exportable Commodities
-0.00
(X1)
Percentage Contribution of Exogenous Variables to Value of Production of Import Substitute Food Commodity (X2)
Percentage Contribution of Exogenous Variables to Value of Production of Domestically Produced and Consumed Food Commodity (X3)
Percentage Contribution of Exogenous Variables to Average Price of Domestically Produced and Consumed Food Commodity (P3)
Percentage Contribution of Exogenous Variables to GDP
Percentage Contribution of Exogenous Variables to Agricultural Output(XA)
Percentage Contribution of Exogenous Variables to Food Consumption (Cf)
Percentage Contribution of Exogenous Variables to Average Price of Export Agricultural Output(P1)
Percentage Contribution of Exogenous Variables to Average Price of Import Substitute Food Commodity (P2)