WORKING PAPER NO. 4
OPTIMAL STOCK FOR THE
PUBLIC FOODGRAIN
DISTRIBUTION SYSTEM
IN BANGLADESH
FRANCESCO GOLETTI
RAISUDDIN AHMED
NUIMUDDIN CHOWDHURY
INTERNATIONAL FOOD POLICY RESEARCH INsrlTUTE
Working papers of thelntematlonal food Policy Research In.titute encompall a
wide range of .ubl.cts drawn from ih research program• . Th. papers-primarily
data anaIYM., hl.torlcal description., or caM.tudle.-contaln Information that
IFPRI ben.v" may be of Interest to o'hers. Working popers undergo Informat
review but do no' neceaorlty present final r...arch reautts.
OPTIMAL STOCK FOR THE PUBLIC FOODGRAIN
DISTRIBUTION SYSTEM IN BANGLADESH
Francesco Goletti
Raisuddin Ahmed
Nuimuddin Chowdhury
Working Papers on Food Policy in Bangladesh, No.4
International Food Policy Research Institute
Washington, D.C.
December 1991
CONTENTS
Foreword
viii
l.
Summary
1
2.
Introduction
4
3.
Choice of Approach to the Optimal Stock Problem
9
4.
Components of Food Stock Policy.
12
5.
A Model of the Public Foodgrain Distribution System
in Bangladesh . . . . . . . . . . . . . .
29
6.
Policy Constraints and Policy Objectives
36
7.
Open Market Operations
39
8.
Specification of Policy Options
43
9.
Evaluation of Counterfactual Simulations
47
10.
Conclusions . . . . . . .
77
Appendix 1:
Procurement Supply
81
Appendix 2:
Has Procurement Been Effective at
Supporting Prices? . . . . . .
84
Appendix 3:
Derivation of Storage Equation
87
Appendix 4:
Nature and Sources of the Data
89
Appendix 5:
Food Budget
91
Appendix 6:
The Model for the Benchmark Policy
94
Appendix 7:
Approximation Policies
96
Glossary
97
Bibliography
98
- iii -
TABLES
. .
.5
1.
Nominal rice and wheat prices, 1972/73-1989/90
2.
Rice and wheat prices deflated by index of
manufactured goods, 1972/73-1989/90 . .
6
3.
Total foodgrain stocks, 1972/73-1989/90
7
4.
Rice and wheat stocks, 1972/73-1989/90
8
5.
Components of public distribution of foodgrains,
1972/73-1989/90 . . . . . . . . . . . . . . .
6.
Sources of public distribution of foodgrains,
1972/73-1989/90 . . . . . . . . . . . . .
13
7.
Total production of rice, 1972/73-1989/90 .
14
8.
Growth of foodgrain production per capita,
1972/73-1989/90 . . . . . . . . . . . . . .
15
9.
Growth of foodgrain production, 1972/73-1989/90
15
10.
Production trends of rice and wheat,
1972/73-1989/90 . . . . . . . . . . . . .
17
11.
Correlation matrix of crop residuals from
trend regression . . . . . . . . . .
18
12.
Yearly procurement of rice and wheat, 1973/74-1989/90
18
13.
Mean divergence with respect to market prices of
rice and wheat, 1972-89 . . . . . . . . . . . . .
19
14.
Yearly offtakes of rice and wheat, 1972/73-1989/90
21
15.
Estimated equations for imports of rice and wheat,
1975/76-1989/90 . . . . . . . . . . . . . . . .
24
16.
Coefficients of variation of world and domestic
prices of rice and wheat, 1973/74-1989/90
. . . . . .
25
- iv -
. .
12
17.
Correlation matrix of world and domestic
price levels for rice and wheat. . . . . . . . . . . . . .
26
18.
Correlation matrix of world and domestic
price differences for rice and wheat . .
26
19.
Yearly imports of rice and wheat, 1972/73-1989/90
28
20.
Estimated equations of the foodgrain system,
1975/76-1989/90 . . . . . . . . . . . . . . . . .
33
21.
Three-stage least squares estimation of price equations
of foodgrain system, constrained, 1975/76-1989/90
35
22.
Variables in the baseline, 1985-88
48
23.
Costs in the baseline, 1985-88
49
24.
Historical values of prices used in the baseline,
1985-88 . . . . . . . . . . . . . . . . . . . . .
50
25.
Historical values of quantities in the baseline,
1985-88 . . . . . . . . . . . . . . . . . .
51
26.
Variables in the price band policy, 1985-88
61
27.
Costs in the price band policy, 1985-88 . .
62
28.
Variables in the optimal price stabilization policy,
1985-88 . . . . . . . . . . . . . . . . . . . . .
63
29.
Costs in the optimal price stabilization policy,
1985-88 . . . . . . . . . . . . . . . .
64
30.
Variables in the import policy, 1985-88
65
31.
Costs in the import policy, 1985-88 . .
66
32.
Variables in the cost minimization policy, 1985-88
67
33.
Costs in the cost minimization policy, 1985-88
68
34.
Variables in the benchmark policy: price
stabilization cum cost minimization, 1985-88.
35.
Costs in the benchmark pol icy: pri ce stabil i zat ion
cum cost minimization, 1985-88.
. ..... .
- v -
. .
....
69
70
Variables in the benchmark policy with 30 percent
increase in world prices, 1985-88 . . . . . .
71
37.
Costs in the benchmark policy with 30 percent
increase in world prices, 1985-88 . . . . . .
72
38.
Variables in the benchmark policy when monetary
off takes are eliminated, 1985-88 . . . . .
73
39.
Costs in the benchmark policy when monetary
off takes are eliminated, 1985-88 . . . . .
74
40.
Variables in the approximation policy, 1985-88
75
41.
Costs in the approximation policy, 1985-88
76
42.
Summary of various policies . . . . . .
79
43.
Average stock and total cost of various policies
80
44.
Ordinary least squares estimation of rice and wheat
procurement supply . . . . . . . . . . . . . . .
83
45.
Three-stage least squares estimation of foodgrain
system with public food distribution
85
46.
Foodgrain nominal costs, 1976-89
92
47.
Foodgrain deflated costs, 1976-89
93
36.
- vi -
FIGURES
l.
Total rice production, by harvest season, 1972-89
15
2.
Rice production per capita, by harvest season,
1972-89 . . . . . . .
. ...... .
16
3.
Total rice production per capita, 1972-89
16
4.
Divergence between procurement and market prices
of rice, 1972-89 . . . . . . . . . . . . . . . .
20
5.
Divergence between procurement and market prices
..... .
of wheat, 1975-89 . . . .
20
6.
Divergence between ration and market prices
. ..... .
of rice, 1972-89 . . . .
22
7.
Divergence between ration and market prices
of wheat, 1973-89 . .
22
8.
Rice prices, 1972-89
27
9.
Wheat prices, 1973-89
27
10.
Actual and simulated values of the foodgrain system
with public distribution, 1975-89 . . . . . . . . .
41
11.
Policy options considered in the simulation exercises
44
12.
Pri ce band pol icy .
52
13.
Price stabilization policy
53
14.
Import pol icy. .
54
15.
Cost minimization policy
56
16.
Benchmark policy:
cost minimization
17.
Approximate versus optimal open market operations
price stabilization cum
- vi i -
57
60
FOREWORD
In early 1989, the International Food Policy Research Institute
entered into a contract with the U.S. Agency for International
Development (USAID), Dhaka (under Contract No. 388-0027-C-00-9026-00),
to conduct research on food policies and to extend technical assistance
to the Ministry of Food, Government of Bangladesh. The Bangladesh Food
Policy Project is the basis for a tripartite collaboration between
IFPRI, the Government of Bangladesh, and USAID, Dhaka. This project
consists of four subprojects and a large number of well-defined research
topi cs. The subprojects together const i tute a comprehens i ve approach
for addressing the food policy problems of Bangladesh. The subprojects
include- the following studies:
a price stabilization framework
encompassing public and private marketing, evaluation of the effects of
targeted distribution of foodgrains on consumption and nutrition,
diversification of agriculture as a source of sustained growth of
production, and capacity-building in food policy analysis.
This paper on determination of optimal publ ic stocks of foodgrains
for the purpose of price stabilization and targeted distribution is an
important study under the first subproject. The level of stock is a
significant determinant of the level of cost of the public distribution
system. It is hoped that this study on optimal stock will enable a
greater degree of efficiency in the use of stock in the public
distribution system than has been possible in the past.
Raisuddin Ahmed
Series Editor and Project Director
Bangladesh Food Policy Project
- vi i i -
1.
SUMMARY
The search for an estimate of the optimal stock of publ ic
foodgra in has been a constant and intense demand from donors and
pol icymakers in Bangladesh. The meaning of optimal ity has, however,
remained different to different persons. A general perception in these
debates is that there may be a preci se figure that represents the
optimal level of·public stock. Optimality implies minimization of cost
or maximization of net gains in achieving an objective. In the context
of the present exercise (that is, estimation of an optimal foodgrain
stock for the government), the optimal level of public foodgrain stock
is defined as the level of stock that ensures a number of objectives
such as a certain degree of price stabilization and a certain amount of
foodgrain supply through the rationing system and for the food-for-work
operations, vulnerable group development, and other relief programs at
minimum cost. The definition of optimality is somewhat limited in the
sense that the benefits from these public interventions are not
questioned and incorporated into the analysis. However, sensitivity to
changes in various types of interventions and their implications for the
estimates of optimal stock are shown in this paper. As a result, it is
possible to point out the optimal level of public stock for the present
degree of public interventions and the stock levels for reduced degrees
of public interventions or changes in policies. This procedure gives a
range of estimates of optimal stocks and the corresponding types and
degrees of public interventions, providing a space for gradual reform in
policies and management of interventions.
The estimation of the optimal public stock obviously requires a
comprehens i ve model that integrates a dynami c foodgra in sector with
chosen pol icy regimes and well-defined objective and cost functions.
Further, the mechanisms of simulation and sensitivity analysis are
requi red for exami nat i on of results with varyi ng assumptions. These
analytical elements are developed in the paper. The dynamic foodgrain
sector model captures the inherent seasonality of foodgrain prices, the
effects of private storage decisions, and government activities
involving procurement and off takes from public godowns. In defining the
objective function of the government the main concerns of price
stabil ity, minimal fiscal costs, and food security through targeted
distribution (rations, food-for-work, vulnerable group development, and
relief programs) were taken into consideration.
Because results of the analysis vary with the types of policies,
it is necessary to understand the pol i ci es well before readi ng the
estimates of stocks. Estimates of optimal stock relate to six types of
policies specified in this paper. These are price band policy, optimal
pri ce stabil i zat i on pol icy, import po 1icy approach to pri ce
- 2 -
stabilization, cost minimization policy, price stabilization cum cost
minimization (also called the benchmark policy in this paper), and
approximation to optimal price stabilization. An estimate with a norationing policy is also added at the end. The specific contents of
each of these policies can be gauged from the presentations in the main
text. A baseline picture is developed in order to show how each policy
simulation compares with the baseline.
The estimated stock requirements and costs for the specified
policies are shown in the following table.
Pol icy
Baseline
Price band
Optimal price stabilization
Import policy
Cost minimization
Benchmark: price stabilization
cum cost minimization
Approximation to optimal price
stabil i zat ion
No ration distribution
Average Total
Foodgrain Stock
Tota 1 Cost
(1,000 metric tons)
(Tkmillion)
1,075
1,452
1,128
847
686
17, 045
19,632
8,392
14,716
6,046
724
5,137
876
690
8,473
2,741
The baseline in the table is obtained by simulating the foodgrain
model for the period July 1985-June 1988. The price band is defined by
a plus or minus 4 percent margin around the target price. The optimal
price stabilization policy uses open market operations to minimize the
variance of rice prices around the target. The import pol icy uses
imports to minimize variance of rice prices around the target. The cost
minimization policy uses open market operations to minimize the total
cost of food operations. The benchmark refers to cost minimization cum
price stabilization, which uses open market operations and imports to
minimize the total cost of food operations subject to price
stabilization and foreign reserves constraints. The approximation to
optimal price stabilization was computed through stochastic simulations
of production shocks and ordinary least squares over rice production,
wheat production, and a lagged term. No ration distribution refers to
the benchmark when monetary off takes are eliminated. Total cost equals
procurement cost plus import cost minus ration sales minus open market
sal es.
- 3 -
The estimates in the table show that the optimal stock varies from
the level of 686,000 metric tons for the cost minimization policy to
1,452,000 tons for the effective price band policy. Cost minimization
implies allowing prices to go up in the peak price season in order to
make a profit by publ ic sale or to go down sharply in order to buy
grains at cheap prices. Price stabilization is of no concern. Such a
strategy forsakes the prime objective (that is, price stabilization) of
the public system. Therefore, it may not be acceptable to policymakers.
The policy of price stabilization cum cost minimization appears to be
one of the best options and can be further improved by elimination of
rationing if evaluation of the rationing scheme justifies such
el imination.
One interesting piece of evidence that emerges from this exercise
is that the cost and level of stock are higher for the price band policy
than for other policies. This result originates from the maintained
rigidity of a price band policy. When this assumption of a rigid price
band is abandoned; the policy becomes similar to the approximation to
optimal price stabilization, in which case both the stock level and cost
are substantially reduced.
For the sake of simplicity, the policies are specified discretely
and with somewhat narrower domain than would be dictated by the
exigencies of actual application. In actual application, some of these
policies would be combined to achieve multiple goals. But discrete
analysis provides a sense of direction of change in levels of stock and
costs due to these combinations. For example, some flexible price band,
import, open market operations, and cost minimization goals would be
implicit in an ideal price stabilization mechanism. In the present
context it is important that these policies, if applied in a balanced
and effect i ve manner, woul d not requi re a stock 1eve 1 above about
750,000 tons and would also cost much less than historically
experienced.
For low-cost operation of price stabilization, the analysis
indicates that use of three policy instruments, that is, import policy,
open market purchase, and open market sal e (purchase and sale are
defined as open market operations) have to be very judicious. In the
past, import of foodgrain has not been based on rational analysis. Open
market operations have also remained very timid. Moreover, management
of these operations (not specifically analyzed here) is known to have
caused inefficiency and high cost. The analysis here shows that private
trade is very sensitive in price speculation and stocking behaviors to
the public stock situation and operation. Therefore, erratic behavior
in the public sector will compound the adverse effects throughout the
foodgrain market.
.
This paper assumes that the public sector will continue in the
Bangl adesh foodgra in market and analyzes how the objectives of thi s
sector can best be achieved with optimal stock and lower cost. There is
of course a larger issue, which the paper does not address: Is the
public sector necessary at all? Inefficiency in the public sector may
generate the momentum for a comprehensive look at this larger issue.
2.
INTRODUCTION
The foodgrain sector in Bangladesh is characterized by the active
presence of the government sector, which is involved in various
operations related to domestic procurement, public distribution,
imports, and open market sales.
Central to this involvement is the management of public foodgrain
The main issue related to public stocks is the need to
stocks.
understand the policy principles informing the stock policy. The broad
concern of foodgrain stock pol icy is to guarantee food security at
minimum cost. Ways of mitigating this concern are examined in this
study.
Until as recently as 1988, the general guidelines of stock policy
in Bangladesh followed the recommendations of the World Bank expressed
in an influential report (World Bank 1979). That report suggested that
the total foodgrain stock be 1.5 million metric tons as of July 1 of
every year and 1.2 million tons as of November 1.1 As pointed out by
Chowdhury (1990), the World Bank's recommendation of a fixed stock on
July 1 of every year misses the point that the multiple crop pattern of
Bangladesh rice cultivation allows production downfalls that occur in
one crop season to be compensated for within the same year.
The
recommendations of the World Bank in 1979 appear to be overly cautious,
understandably so in light of the severe drought experienced in
Bangladesh in that year. Nevertheless, in the years following 1981,
government stocks have rarely exceeded the level of 1.2 million tons.
Taking into account the population growth, the per capita figures
of stock 1eve 1s have been much sma 11 er than those the Worl d Bank
recommended in 1979. Thi s situat i on has not prevented both nomi na 1
prices of rice and wheat and nominal prices deflated by the index of
manufactured goods to become more stable from the 1970s to the 1980s.
Tables 1 and 2 indicate both lower coefficients of variation of price
and small er yearly spreads between hi gh and low pri ces for ri ce and
wheat. The variability of total stocks decreased during 1972/73-1989/90
(Tables 3 and 4), even though Bangladesh experienced two of the worst
production calamities of its history in 1987/88 and 1988/89.
The foregoing observations suggest that stock policy guidelines
have to be revised substantially. During 1981-91 the foodgrain sector
of Bangladesh has witnessed a few remarkable changes: a changed pattern
of seasonality of production and prices (Ahmed and Bernard 1989;
Chowdhury 1987); a reduced role for subsidized distribution (Chowdhury
1990); increasing experience with open market sales (Chowdhury 1990);
1
All tons referred to in this report are metric tons.
- 5 -
Tabl e I--Nominal rice and wheat prices, 1972/73-1989/90
Rice Price
yearl
Average
c.v. b
(Tk/maund)
1972/73
1973/74
1974/75
1975/76
1976/77
1977 /78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
75
100
210
124
113
138
152
201
168
220
240
262
294
280
341
352
362
355
Wheat Price
Spreadc
(percent)
14
21
17
24
11
6
18
8
6
17
6
7
6
7
9
5
5
5
Average
(Tk/maund)
50
64
89
94
42
20
68
31
22
69
21
23
23
22
34
17
18
20
n.a.
62
141
77
79
91
91
124
111
135
162
167
170
181
209
215
224
233
c.v. b
Spreadc
(percent)
n.a.
35
22
34
12
9
10
15
3
15
9
9
8
7
5
6
5
3
n.a.
143
120
157
44
40
40
64
11
48
36
25
29
26
20
22
12
13
Source: Based on data from Bangladesh Bureau of Statistics. Monthly Statistical Bulletin. various
dates.
Note:
I
b
C
n.a. means not available.
The fiscal year starts in July.
C,v. ;s the coefficient of variation, computed with monthly prices.
Spread is the percentage difference between the highest and the lowest price of the year.
reduced gaps between market pri ces, ration pri ces, and procurement
prices (Abdullah 1989b); and reduced subsidies on agricultural inputs
such as fertilizers and irrigation equipment (Abdullah 1989a). At the
same time, the need for a new framework to analyze the foodgrain stock
problem has arisen. The initial attempts by Abbott (1988) for the FAD,
Ahmed and Bernard (1989) at IFPRI, and Chowdhury (1987, 1988, 1990) and
Shahabuddin (1990) for IFPRI form part of the growing literature. The
general direction of these studies is away from a passive endorsement of
quantity targets toward a more complete analysis of the food system of
Bangladesh that tries to capfure the complex interrelation between the
free market and government operations. Moreover, a new concern related
to the optimal stock problem has been emerging, where the word "optimal"
refers to some prespecified policy or welfare concept. In particular,
there is a growing awareness of the financial cost impl ications of
different stock levels.
- 6 -
Table 2-Rice and wheat prices deflated by index of manufactured goods,
1972/73-1989/90
Year-
Average
Rice Price
c.v. b
(percent)
(Tk/maund)
0.3.1
0.30
0.41
0.29
0.26
0.30
0.33
0.35
0.26
0.31
0.31
0.35
0.37
0.33
0.38
0.38
0.37
0.33
1972/73
1973/74
1974/75
1975/76
1976/77
1977/78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
19B8/89
19B9/90
Spread c
Jl
17
16
30
9
14
12
II
4
15
6
Jl
7
5
9
6
4
5
Average
Wheat Price
c,v. b
(Tk/maund)
42
58
73
126
37
57
48
42
16
60
22
42
30
17
34
19
16
19
n.a.
0.18
0.28
0.18
0.18
0.20
0.20
0.22
0.17
0.19
0.21
0.22
0.21
0.21
0.23
0.23
0.23
0.22
Spreadc
(percent)
n.a,
n.a.
31
22
40
9
20
10
18
5
12
9
109
124
189
38
87
33
80
15
36
40
37
35
26
25
25
20
13
Jl
10
8
6
7
6
3
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates.
Note:
a
b
C
n.a. means not available.
The fiscal year starts in July.
C.v. is the coefficient of variation, computed with monthly prices.
Spread is the percentage difference between the highest and the lowest price of the year.
To give a very rough dimension of this financial cost, one may
think of the cost of 100,000 tons of foodgrains (35 percent of which
consists of rice and the rest of wheat) evaluated at average 1988/89
world prices. This cost, equal to US$20.8 million, or 671.2 million taka
(Tk), represents approximately 5.8 percent of the agricultural Annual
Development Programme (ADP) budget and 1.4 percent of the total ADP
budget.
The main purpose of this study is to present a general framework
for designing a cost-effective stock policy that addresses the
government's concerns related to ensuring price stability and the food
security of the vulnerable groups. The design of an optimal foodgrain
stock policy entails the construction of a dynamic model of the
foodgrain sector of Bangladesh and the use of programming techniques to
fac il itate the anal ys is of di fferent pol icy i ntervent ions (for a simil ar
approach applied to foodgrains in India, see Krishna and Chhibber 1983;
for other commodities, see Ghosh, Gilbert, and Hughes Hallett 1987).
- 7 -
Table 3-Total foodgrain stocks, 1972/73-1989/90
year8
Average
Total
Stocks
C.V. of
Total
Stocks b
(1,000 metric tons)
1972/73
1973/74
1974/75
1975/76
1976/77
1977 /78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
326
239
262
852
583
608
637
666
1,230
1.029
687
637
817
882
736
1,053
1.208
1,181
Spread of
Total
StocksC
(percent)
39
29
41
16
29
17
26
28
15
27
17
20
21
17
36
15
18
20
Average
Total Stocks
per Capita
Security
Daysd
(kilograms/person)
268
169
351
60
142
83
180
331
80
139
70
80
105
67
206
66
73
73
4.44
3.18
3.39
10.76
7.20
7.30
7.48
7.62
13.79
11.34
7.39
6.70
8.38
8.86
7.23
10.09
11.33
10.82
9
7
7
22
15
15
15
16
28
23
15
14
17
18
15
21
23
22
Source: Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various dates .
• The fiscal year starts in July.
b C.v. is the coefficient of variation, computed with monthly stocks.
C Spread is the percentage difference between the highest and the lowest stock of the year.
d Security days express the number of days that public stocks would guarantee to the population of
Bangladesh for that year a diet of 15.5 ounces of foodgrains.
In Chapter 3 the general approach to the design of stock policy is
explained and formal ized. In Chapter 4 the components of stock pol icy
are put in their historical context. Chapter 5 presents a model of the
foodgrain sector, incorporating decisions related to consumption and
private storage.
In Chapter 6 the pol icy constraints and pol icy
objectives are spelled out. Various policy options are specified in
Chapter 7, and the rol e of open market operations is di scussed in
Chapter 8.
In Chapter 9 the evaluation of policy simulations is
presented. Conclusions are given in Chapter 10. A series of appendixes
deal with the technical aspects of the paper.
- 8 -
Table 4-Rice and wheat stocks, 1972/73-1989/90
Rice Stocks
Year-
Average
cov,s
(1,000 metric tons)
1972/73
1973/74
1974/75
1975/76
1976/77
1977 /78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
44
38
63
382
311
234
200
294
453
481
312
213
268
400
215
350
540
619
(percent)
44
48
102
43
28
64
30
35
38
26
12
30
43
14
36
21
26
25
Wheat Stocks
Spreadc
Average
c.v,s
(1,000 metric tons)
271
689
4619
182
161
530
182
533
187
158
46
239
388
57
197
89
152
154
Source: Based on data from Bang ladesh Bureau of Stat i st; cs
dates .
282
201
200
470
272
373
437
372
777
548
375
424
549
482
520
703
668
562
I
Spread'
(percent)
45
39
45
17
33
35
39
34
25
32
27
29
21
26
41
14
21
44
433
260
312
80
157
200
250
312
116
148
143
172
113
163
355
68
116
368
Month ly Stat; st; ca 1 Bu 11et in. var iaus
• The fiscal year starts in July.
b C.v. is the coefficient of variation, computed with monthly stocks.
c Spread 1s the percentage difference between the highest and the lowest stock of the year.
3.
CHOICE OF APPROACH TO THE OPTIMAL STOCK PROBLEM
The search for an estimate of the optimal level of publ ic
foodgrain stock has been constantly demanded by donors and some
policymakers in Bangladesh. Optimality has, however, been understood
differently by different persons.
In these debates the general
perception is that there may be a precise figure that represents the
Optimality implies both minimization of cost and
optimal level.
maximization of gains in achieving an objective. In the context of the
present study, the optimal level of public foodgrain stock is defined as
the level of stock that helps attain certain objectives such as price
stabilization within given bands and a sufficient supply of foodgrains
through the public distribution system at a minimum cost.
This definition is somewhat limited, since the benefits of these
publ ic interventions are not questioned and incorporated into the
analysis. 2 However, various levels of these interventions and their
implications for the estimates of optimal stocks are covered in this
paper. This enables the study to recommend the optimal level of public
stock under the present degree of public interventions and under reduced
degrees of such interventions.
This procedure gives a range of
estimates of optimal stocks and the corresponding degrees of publ ic
interventions, providing room for gradual reform in public stock
management and interventions.
The estimation of the optimal public stock obviously requires a
comprehens i ve model that integrates a dynami c foodgra in sector wi th
chosen policy regimes and well-defined objectives and cost functions.
The techniques for simulation and sensitivity analysis are also required
for examination of results with varying assumptions.
Three stages are involved in the design of the optimal stock
The first stage consists of the specification,
policy problem.
identification, and estimation of a dynamic model of the foodgrain
sector. The second stage comprises the specification and solution of an
opt imi zat i on exerci se based on the dynami c model constructed in the
first stage. The third stage is the evaluation of the optimal stock
policy determined in the second stage.
2
The main reasons for not adopting a standard economic surplus approach are that. first,
theoretical difficulties related to the use of consumers' surplus as an appropriate indicator of
welfare still remain unanswered (Scandizzo and Bruce 1980; Scandizzo and Knudsen 1981; Cochrane 1980;
ladd 1987). Second, measures of consumers' surplus are of very limited value given the absence of
reliable information about foodgrain consumption on a monthly or even a quarterly basis. Third, the
object ives of food security and price stab;' izat ion are seen as the most re levant concerns for po 1icy
intervention, and their efficient implementation may be regarded as "optimal" policy,
- 10 -
The optimal stock problem may
some object i ve funct i on defi ni ng
subject to the constraints imposed
market.
Formally, the optimization
follows:
be formulated as the optimization of
the pri orit i es of the government,
by the feasible performance of the
problem [P] can be expressed as
,=T-l
[P]:
~
J t , T = min(x)
(ZTPZT +
L
W,),
T=t
subject to
1,
where
W,
. z, + B, • xr and
= A,
ZHI
~
ZI
z,
~
,
a,
(1)
(2)
u"
• z". + x' ,
. R, • x,
(3)
and the time index 1 = t, ... ,T.
In this notation z, is a vector of state variables, x is the
vector of control variables, with respect to which the government is
optimizing. T is the time horizon of the optimization exercise, and the
length of the optimization period is T - t + 1. P, A, and a are
matrices conformable with the vector Z; Band R 'are mathces
conformabl e with x .
'"
The current' period objective of the government is W" which is
assumed to be a quadratic form in the state and control variables; the
final period objective is Z/TPZT.
The state variables evolve according to the law of motion
specified in equation (1) and are subject to inequality constraints as
in equation (2). 1 is the lower bound and u is the upper bound for the
state variable z,.'
' *
The optimal policy is a sequence of T-t+l functions x satisfying
,
the problem [p].3
3 Because of the recursive structure of the problem. the optimal policy functions can be found
by applying Bellman's equation recursively:
Jt,T(Zt)
= minx,
Et [Wt(Xt,Zt) + Jt+"T(Zt+,)]
I
subject to
Zt-t1
= AtZ t
't : ;
+ StXt
Zt+1 S
and
ut '
In the numerical solution of the optimal policy options considered in the text, the GAMS software
has been used to find an open loop solution (Brooke, Kendrick, and Meeraus 1988).
- 11 -
Note that by specifying different government objectives and
instruments, the general model can be used to deal with many different
policy issues (see Chapter 7). The system in equation (1) represents
the structural model of the foodgrain private sector, which the
government is influencing by intervening through holding and
distribution of stock.
During the design of stock policy, the
government takes into account the reaction of the private sector implied
by a dynamic model of market behavior. At the same time, a set of other
inequality constraints is imposed as specified in equation (2).
Examples of these inequality constraints are capacity constraints,
minimum stock requirements for food security, foreign reserves ceilings
on food imports, and so on.
4. COMPONENTS OF FOOD STOCK POLICY
One way to gauge the extent of government operations in the
foodgrain sector is to consider the ratio of total offtakes to total
availability, the latter being defined as net domestic production (gross
production less 10 percent for wastage and feed) plus imports plus
opening stocks, for any particular year.
The dimension of government intervention in foodgrain distribution
has been substantial, ranging from 8 percent to 21 percent, with an
average value of 13 percent for the ratio of total off takes to total
availability (Table 5).
Table 5-Components of public distribution of foodgrains,
1972/73-1989/90
Net
Year-
Production Production b
Offtake
Procurement
Initial
Stocks
Ava 11Imports
(1,000 metric tons)
1972/73
1973/74
1974/75
1975/76
1976/77
1977/78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
10,023
11,832
11,226
12,780
11,825
13,120
13,140
13,362
14,975
14,598
15,312
15,719
16,086
16,083
16,498
16,462
16,382
18,656
9,021
10,649
10,103
11,502
10,643
11, 808
11, 826
12,026
13,478
13,138
13,781
14,147
14,477
14,475
14,848
14,816
14,744
16,790
2,657
1,756
1,785
1,679
1,374
1,863
1,762
2,203
1,686
1,840
1,893
1,896
2,426
1,419
1,820
2,016
2,685
1,981
0
72
129
503
320
559
358
354
1,034
303
192
272
340
361
188
374
408
962
Off take/
abi 1itye Availability
(percent)
303
269
215
761
836
422
601
210
794
1,208
615
611
800
1,008
976
751
1,498
905
2,871
1,719
2,401
1,488
825
1,665
1,165
2,809
1,089
1,234
1,840
2,069
2,580
1,198
1,767
2,911
2,138
1,534
12,195
12,709
12,848
14,254
12,624
14,453
13,949
15,399
16,394
15,883
16,428
17,099
18,197
17,042
17,779
18,852
18,788
20,191
21.8
13.8
13.9
11.8
10.9
12.9
12.6
14.3
10.3
11.6
11.5
11.1
13.3
8.3
10.2
10.7
14.3
9.8
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989, (Ohaka: BBS,
1990) .
• The fiscal year starts in July.
b Net production is 90 percent of production.
C
Availability
=
initial stock + net production + imports + procurement - off takes.
- 13 -
There are three sources of public supply:4 domestic procurement,
imports, and go,vernment stocks,
The relative importance of each of
these factors is illustrated in Table 6, which shows that the role of
domestic procurement was greater during the second half of the 1970s
than in the 1980s, The role of imports has always been crucial in
government, with an average ratio of total imports to off takes of
foodgrains equal to 90 percent over the period from 1972/73 to 1989/90,
Table 6-Sources of public distribution of foodgrains. 1972/73-1989/90
Year-
Procurement
Procurement
Ratlo b
(1,000
(percent)
(1,000
(percent)
0
4
7
30
23
30
20
16
61
16
10
14
14
25
10
19
15
49
0
72
129
503
320
559
358
354
1,034
303
192
272
340
361
188
374
408
962
Stocks
Change
(1,000
Stocks
Change
Ratio
(percent)
2,871
1,719
2,401
1,488
825
1,665
1,165
2,809
1,089
1,234
1,840
2,069
2,580
1,198
1,767
2,911
2,138
1.534
108
98
134
89
60
89
66
128
65
67
97
109
106
84
97
144
80
77
0
-34
-54
546
75
-415
179
-390
583
415
-593
-4
189
208
-32
-225
747
-593
1
3
-31
-4
30
-10
22
-26
-25
32
0
-10
-9
2
12
-37
22
0
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989,
1990) .
Offtake
(1,000
metric tons)
metric tons)
metric tons)
metric tons)
1972/73
1973/74
1974/75
1975/76
1976/77
1977/78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
Imports
Imports
Ratio
2,657
1,756
1,785
1.679
1.374
1,863
1,762
2,203
1.686
1.840
1,893
1,896
2,426
1.419
1.820
2,016
2,685
1,981
(Ohaka: 88S,
• The fiscal year starts in July.
b The ratios are taken with respect to off takes.
4
From the balance equation for stocks,
stock~
=
oj • stock i".1 + m~
+ qp~
- oftakes~
i
- oms T•
it ;s pas,sible to. see that ,the sources of off takes and open mar:ket sales are given by changes in
stocks (8' • stOCk~'1
- stock~).
imports (m~)
and procurement (qp~).
Divergences from the share of
the imputed sources and the actual figures come fram unreported losses and from omissions.
I
- 14 -
THE CONTEXT OF PRODUCTION
Rice is produced seasonally in Bangladesh. Within a year, three
main crops denoted aman (harvested from November to January), boro
(harvested from April to June), and aus (harvested from July to
September) are grown. Traditionally, aman has been the largest crop.
In the 1ast few years, however, boro production has been increasing
rapidly, taking its share from 21 percent of total production in 1973 to
35 percent in 1989, largely due to the diffusion of high-yielding
varieties (HYVs) and the extension of irrigation facilities. Aus and
aman shares have declined commensurately (Table 7).
Therefore,
production is now more evenly distributed over the year. Consequently,
arrivals in the market occur more smoothly, implying less need for
storage than in the past to mitigate seasonal shortfalls.
The annual growth of total ri ce product i on between 1972/73 and
1989/90 was 2.62 percent, with 3.08 percent in the 1970s and 2.57
percent in the 1980s (Tables 8 and 9; Figures 1 and 2). Moreover, total
product i on per capita does not exhi bit any trend. It has osci 11 ated
around its mean of 148 kilograms in a random fashion (Figure 3).
Table 7-Total production of rice, 1972/73-1989/90
Year~
Bora
Aman
Aus
Share of Total Rice Production
Boro
Aus
Aman
(1.000 metric tons)
1972/73
1973/74
1974/75
1975/76
1976/77
1977 /78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
5.587
6.699
6.000
7.045
6.906
7,422
7,429
7,303
7,964
7,209
7,604
7,936
7,930
8,542
8,267
7,690
6,857
9,202
2.071
2.220
2.250
2.286
1.650
2,239
1.929
2,427
2,630
3,152
3,546
3,350
3,909
3,671
4,010
4,731
5,831
6,166
(percent)
2.274
2.802
2.859
3.230
3,010
3,104
3,288
2,809
3,289
3,270
3,067
3,222
2,783
2,828
3,130
2,993
2,856
2,488
56
57
54
56
60
58
59
58
57
53
53
55
54
57
54
50
44
52
21
19
20
18
14
18
15
19
19
23
25
23
27
24
26
31
38
35
23
24
26
26
26
24
26
22
24
24
22
22
19
19
20
19
18
14
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989, (Dhaka: BSS,
1990) .
a
The fiscal year starts in July.
- 15 -
Table 8-Growth of foodgrain production per capita. 1972/73-1989/90
Rice
Bora
Aman
Period
Aus
Wheat
Total Rice
15.68
37.97
-3.51
2.62
3.08
2.57
(percent)
I. 72
3.66
1.08
1972/73-1989/90
1972/73-1980/81
1981/82-1989/90
6.83
1.50
8.49
0.09
2.91
-2.20
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989. (Dhaka: BSS,
1990).
Note:
Growth rates are derived from regression of logarithms of production on time and constant.
Table 9-Growth of foodgrain production. 1972/73-1989/90
Rice
Bora
Aman
Period
Aus
Wheat
Total Rice
13.05
34.71
-5.70
0.29
0.64
0.24
(percent)
-0.58
I. 21
-1.21
1972/73-1989/90
1972/73-1980/81
1981/82-1989/90
4.41
-0.90
6.03
-2.18
0.48
-4.42
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989. (Dhaka: BSS,
1990) .
Note:
Growth rates are derived from regression of logarithms of production on time and constant.
Figure I--Total rice production. by harvest season. 1972-89
6
"
4
2
n
~
~
~
77
~ ~
=
6'
YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook (Dhaka:
various years).
BSS,
- 16 -
Figure 2-Rice production per capita, by harvest season, 1972-89
Kg/CAPITA
,o~=-
eo
-
-BORO -
-..:
40
20
~
:,.."::"""
.• -:;;,...,
'."-:'
"
--
."- -. '.
_
~
~
_
~
_
_
~
e,
_
_
_
_
_
~
_
_
YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook (Dhaka:
BSS,
various years).
Figure 3-total rice production per capita, 1972-89
YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook (Dhaka:
various years).
BSS,
- 17 -
These facts are also borne out by a trend analysis over the period
1972-90 (Table 10). Except for boro production, the growth rates are
decelerating, as indicated by the negative sign of the quadratic trend
terms.
In the past, publ ic stocks have often shown a tendency to be
overreplenished in expectation of a big shortfall in one crop. This
tendency may be interpreted as a failure to understand the negative
correlation among foodgrain crops. As the negative correlation between
aman and boro and between aus and wheat shows (see Table 11), large
shortfalls in one crop are associated with opposite movements in another
crop, making the overall yearly production less variable than the
seasonal production. These negative correlations are the reflections of
adjustment mechanisms that are operative after a natural calamity. When
a crop failure occurs due to drought or flood, farmers tend to make an
above-normal effort to raise the subsequent crop in order to compensate
for the loss. Moreover, a flood that causes loss to the aman or aus
crop increases the supply of water for irrigation or in retained soil
moisture that enhances the yields of boro and wheat crops in the
subsequent dry season.
PROCUREMENT
Rice procurement was higher during the 1970s than during the 1980s
(Table 12). However, procurement was abnormally high in 1980/81 and
1989/90 foll owi ng major product ion shortfalls. Thus, procurement in
these years may be seen as an excessive reaction of the government, more
for the purpose of replenishing public stocks than to support a floor
price.
Table lO-Production trends of rice and wheat, 1972/73-1989/90
Aman
Variable
Constant
Trend
Trend 2
R'
SER
Mean of dependent variable
5.698.12
287.61
-8.61
0.64
549.90
7,421.78
Rice
Boro
2.343.41
-147.34
19.48
0.95
310.70
3,226.00
Aus
2,412.92
161.39
-8.41
0.55
199.58
2,961.22
Wheat
-400.75
217.15
-7.97
0.84
189.51
728.72
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989, (Dhaka: BBS,
1990) .
Notes:
The coefficients of the regression are all significant at least at 5 percent, except the
quadratic term for aman, whose t-statistic ;s -1.59.
The regression was done taking
production levels over a constant. a linear trend term, and a quadratiC trend term.
Production levels are measured in 1,000 metric tons.
SER;s standard error of regression.
- 18 -
Table ll-Correlation matrix of crop residuals from trend regression
Aman
Rice
Bora
Aus
Wheat
1.00
-0.02
-0.27
-0.07
-0.27
-0.03
1.00
0.14
-0.02
1.00
-0.03
-0.42
-0.07
-0.42
0.14
1.00
Crop
Rice
Aman
Bora
Aus
Wheat
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989, (Dhaka: BSS.
1990) .
Notes:
The residuals are obtained from a quadratic trend regression as computed from the results
in Table 10.
Table 12-Yearly procurement of rice and wheat, 1973/74-1989/90
Rice
of Production
Rice
per
capita
(1,000
(percent)
(grams)
Rice Procurement as Share
Year-
metric tons)
1973/74
1974/75
1975/76
1976/77
1977 /78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
72
129
503
317
548
306
228
855
290
168
154
130
231
136
288
364
919
0.6
1.2
4.0
2.7
4.3
2.4
1.8
6.2
2.1
1.2
1.1
0.9
1.5
0.9
1.9
2.3
5.1
957
1. 669
6,356
3,898
6,576
3,596
2,600
9,596
3,201
1,800
1.623
1,328
2,322
1,325
2,747
3,411
8,403
Wheat Procurement as Share
Wheat
per
Wheat
of Production
capita
(1,000
metric tons)
(percent)
(grams)
n.a.
n.a.
n.a.
n.a.
1.2
3.1
10.5
15.3
16.4
1.3
2.2
9.7
14.3
12.5
4.8
8.2
5.3
5.4
n.a.
n.a.
n.a.
11
52
126
179
13
24
118
210
130
52
86
44
43
n.a.
n.a.
n.a.
37
133
604
1,432
1,998
147
256
1,231
2,143
1 .. 297
506
819
409
391
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989, (Dhaka: BBS,
1990) .
n.a. means not available.
Note:
• The fiscal year starts in July.
- 19 -
Wheat is much more dominant in public procurement than rice. As
a percentage of production, procurement of rice averaged 3 percent in
the 1970s and 2 percent in the 1980s, whereas wheat averaged 5 percent
in the 1970s and 7 percent in the 1980s. Moreover, in per capita terms,
ri ce procurement has been decl i ni ng, whereas wheat procurement has
exhibited an upward trend. Wheat is procured only in the three to four
months following the March-April harvest. Rice is procured throughout
the year, reaching its peak in December-January, during the aman
harvest, and in June-July, following the boro harvest. In the past few
years, because of the growi ng importance of the boro season, ri ce
procured duri ng May-Jul y has been greater than the procurement made
during the aman season.
The following general observations in terms of procurement prices
can be made. It seems that wheat procurement prices have been closer to
market prices than rice procurement prices (Table 13; Figures 4 and 5).
Moreover, both ri ce and wheat procurement pri ces foll owed a cl ear
pattern during the second part of the 1980s, consisting of a smoothening
of the devi at ions from market pri ces.
In the case of wheat, the
smoothening was associated with a general movement toward relatively
higher procurement prices. Nevertheless, as shown in the analysis of
procurement supply in Append i xl, procurement pri ces have not been
effective in stimulating procurement supply.
Table 13-Mean divergence with respect to market prices of rice and
wheat, 1972-89
Fiscal
Procurement
Ration
Years
Price
Price
World
Price
Sales Price8
Open Market
(percent)
Rice price divergences
1972-89
1970s
1980s
1980-84
1985-89
-14.4
-18.3
-11.3
-11.4
-11.3
-27.7
-45.1
-13.7
-18.2
-9.1
10.2
17.2
4.7
17 .5
-8.2
1.9
-2.5
2.3
4.4
0.3
Wheat price divergences b
1972-89
1970s
1980s
1980-84
1985-89
-8.3
-5.2
-9.8
-10.8
-8.8
-16.0
-28.7
-7.0
-9.7
-4.4
-5.4
-9.5
-2.4
0.0
-4.9
3.8
0.3
4.1
4.3
4.0
Source: Based on data from Bangladesh Bureau of Statistics. Monthly Statistical Bulletin, various
dates.
Notes:
The divergences are computed with respect to domestic market prices. The 1970s are from
July 1972 to June 1980; the 1980s are from July 1980 to June 1990; 1980-84 is from July 1980
to June 1985; and 1985-89 is from July 1985 to June 1990 .
• Data for open market sales mean divergences calculations are available fram July 1979 onward for
both rice and wheat.
b For wheat, data for ration price and world price mean divergences calculations are available from
July 1973 onward and for procurement from July 1975 onward.
- 20 -
Figure 4-Divergence between procurement and market prices of rice,
1972-89
PERCENT
·20
·40
-80L~
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin. various
dates.
Figure 5-Divergence between procurement and market prices of wheat,
1975-89
PERCENT
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletjn, various
dates.
- 21 -
OFFTAKES
The purported objective of a dual market system is to make
foodgrains available to those sections of the population that are most
sensitive to food prices and who, even in normal circumstances,
experience malnutrition and hunger, Unfortunately, in the past, most of
the public supply in Bangladesh has been geared to the needs of the
urban population and government employees, with a strong bias against
rural areas, where the food problems are often more severe, This longterm bias has been partly corrected in recent years through changes in
the rationing system (Chowdhury 1988; World Bank 1990; Goletti and Ahmed
1991),
Wheat offtakes have been growing both in absolute levels and in
per capita terms, Rice has exhibited an opposite trend, to the extent
that wheat off takes in the most recent years have been about three times
as much as rice offtakes (Table 14), The seasonal pattern of rice
off takes and wheat off takes is quite similar, with a peak before the
aman harvest (October-November) and before the boro season (March-May),
In terms of ration prices, the subsidies on both rice and wheat have
been gradually reduced (Table 13; Figures 6 and 7), and wheat ration
prices are exhibiting less divergence from market prices than rice,
Table 14-Yearly offtakes of rice and wheat, 1972/73-1989/90
Year 8
1972/73
1973/74
1974/75
1975/76
1976/77
1977/78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
Rice
Rice per Capita
Wheat
Wheat per Capita
(1,000 metric tons)
(grams)
(1,000 metric tons)
(grams)
425
125
182
502
717
600
569
695
450
589
533
426
360
309
339
340
522
655
5,794
1.660
2,356
6,339
8,830
7,218
6,683
7,962
5,049
6,479
5,743
4,478
3,710
3,106
3,322
3,271
4,890
5,990
2,232
1.630
1.603
1.177
656
1,263
1,193
1.508
1.236
1,251
1.360
1,470
2,066
1,110
1,481
1.676
2,163
1.326
30,348
21,639
20,768
14,902
8,086
15,195
13,978
17,290
13,867
13,752
14,623
15,431
21. 248
11,139
14,515
16,088
20,258
12,149
Source: Based on data from Bangladesh Bureau of Statistics. Statistical Yearbook 1989. (Ohaka: BSS,
1990) .
• The fiscal year starts in July.
- 22 -
Figure 6-Divergence between ration and market prices of rice, 1972-89
PERCENT
·20
·40
·60
---
·10L-~
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates.
Figure 7-Divergence between ration and market prices of wheat, 1973-89
PERCENT
20
·20
·40
·60
·80
·10~
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates.
- 23 -
The analysis of the demand for ration distribution in Appendix 2
shows that ration prices of rice have had a significant impact on ration
distribution, whereas for wheat ration prices this is not the case.
IMPORTS AND WORLD PRICES
Traditionally, imports of foodgrains in Bangladesh have been the
domain of public monopoly. Only recently, under pressure from donors,
some private imports have been allowed, but their importance is still
negl igible (USAID 1988, 1989). The most powerful factor affecting
imports has been food aid, which in turn has been responsive to both
public stocks and expected production shortfalls. From the analysis of
a simple model of import demand where imports are related to world
prices, public stocks, domestic production, and lagged imports, it seems
that imports have not been influenced by world prices, as indicated by
the low significance of the coefficients of world prices (Table 15).
The gap between worl d and doinest i c pri ces of ri ce has been fl uctuat i ng
considerably, with domestic prices losing competitiveness with
international prices in the last half of the 19805 (Tables 16-18;
Figures 8 and 9). Per capita imports of both rice and wheat have not
exhibited any definite trend. Most of the large arrivals occur in JulySeptember (Table 19).
- 24 -
Table 15-Estimated equations for imports of rice and wheat, 1975/761989/90
Coeff i c; eot
Variable
t-statistic
Rice imports equation
1.365
1.369
-0.297
-0.017
-0.002
0.237
Constant
R
WOPt
stOCk~.1
StOCk~1
q,R
R
ID t _,
1.80
0.62
-3.59
-0.23
-0.31
1.92
59
0.27
0.96
N
R'
SEE
Wheat imports equation
Constant
wop,":,
5.207
11.381
-0.497
-0.534
0.030
0.005
stOCk~.1
StOCk~1
q,R
m~1
2.10
0.90
-2.07
-2.19
2.15
0.03
59
0.28
2.67
N
R'
SEE
Source: Est imated by the authors based on data from Bang ladesh Bureau of Stat; 5t i cs r Month' y
Statistical Bulletin. various dates.
I
Definitions of terms:
wop~,
wop~
stOCk~.1'
m~1'
q~
StOCk~1
=
world prices of rice and wheat in period t;
'" opening public stocks of rice and wheat;
'" domestic rice production in period t;
m~1
= lagged imports of rice and wheat;
SEE = standard error of estimation.
- 25 -
Table 16-Coefficients of variation of world and domestic prices of
rice and wheat, 1973/74-1989/90
Average
Average
Difference Difference
of World/ of World/
World
World
Domestic
Domestic
Rice
Wheat
Domestic
Price
c.v.
Price
c,v.
Price
c.v.
Price
c.v.
Rice
Rice
Wheat
Domestic
Wheat
Prices
Domestic
c.v.!
Domestic
c.v.!
World
c,v. of
Rice
World
c.v. of
-8.38
-42.21
-20.63
-0.62
5.94
26.96
16.74
43.72
11. 25
0.79
-9.64
5.64
124.56
-19.01
9.49
36.08
10.12
17.87
-12.18
1.13
10.28
4.78
5.88
-11.37
34.25
30.67
-9.29
2.45
1. 01
1.02
1. 79
1.88
0.32
2.36
0.93
0.49
1.11
1. 21
1. 23
0.93
1.19
2.90
0.43
0.84
0.80
2.65
1.61
6.25
1.12
1.00
1.02
1.90
0.38
4.59
1.52
3.94
1.09
1.00
0.92
0.42
1.99
0.86
-2.84
-7.42
-23.27
5.68
11.53
14.20
30.17
12.98
2.14
14.52
1.20
1.43
1.02
1.14
1.24
1.90
2.91
1.08
2.43
1.05
Prices
Wheat
(percent)
1973/74
1974/75
1975/76
1976/77
1977/78
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
20.44
16.64
13.51
6.12
17.80
7.49
8.94
12.66
15.44
4.84
6.06
5.95
5.60
3.12
12.07
6.01
6.71
13.33
13.62
5.42
10.70
9.47
9.80
7.90
8.47
3.19
5.61
2.25
7.74
7.43
5.56
14.00
2.40
3.49
20.66
17.02
24.17
11.49
5.74
17.65
8.34
6.16
17.15
5.86
7.45
5.55
6.68
9.06
5.25
5.05
5.36
-32.70
50.75
-23.64
-24.09
-24.71
35.28
21.88
33.84
12.01
9.47
10.03
15.02
3.24
14.66
8.51
8.87
8.48
7.43
5.09
5.85
4.76
3.02
-17.79
Means
1973-89
1973-76
1977-80
1981-85
1986-89
9.96
14.18
11. 72
7.58
6.98
7.67
10.76
8.91
5.24
6.38
10.51
18.34
9.47
8.54
6.18
12.20
25.76
9.44
9.59
4.68
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin. various
dates; and World Bank, Conmodity Trade and Price Trends (Washington, D.C.: World Bank.
various years).
Notes:
World price of rice: 5 percent broken, white, milled, government st~ndar,
f.o.h. Bangkok
export price.
World price of wheat:
from July 1973 to September 1973. no.1 Canadian
Western Red Spring; from October 1973 to March 1985. na.1 Canadian Western Red Spring. 13.5
percent prate;n; from April 1985 to June 1990. St. Lawrence export. C.v. ;s the coefficient
of variation of monthly prices .
• The fiscal year starts in July.
- 26 -
Table 17-Correlation matrix of world and domestic price levels for
rice and wheat
War ld Price
of Rice
Item
1.00
World price of rice
World price of wheat
World Price
of Wheat
Domestic Price
of Rice
Domestic Price
of Wheat
0.85
0.75
0.78
I. 00
0.87
0.86
1.00
0.96
Domestic price of rice
Domestic price of wheat
I. 00
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates; and World Bank, Commodity Trade and Price Trends (Washington, D.C.: World Bank.
various years).
Notes:
World price of rice:
export price.
5 percent broken. white, milled. government standard, f.o.h. Bangkok
World price of wheat:
from July 1973 to September 1973, no.1 Canadian
Western Red Spring; from October 1973 to March 1985, no.1 Canadian Western Red Spring, 13.5
percent protein; from April 1985 to June 1990, St. Lawrence export. C.v. is the coefficient
of variation of monthly prices.
Table 18-Correlation matrix of world and domestic price differences
for rice and wheat
Wor ld Price
of Rice
Item
World price of rice
World price of wheat
Domestic price of rice
Domestic price of wheat
1.00
World Price
of Wheat
Domestic Price
of Rice
Domestic Price
of Wheat
0.18
-0.04
-0.01
1. 00
-0.04
-0.05
1.00
0.52
1.00
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates; and World Bank. CormlOdity Trade and Price Trends (Washington, D.C.: World Bank.
various years).
Notes:
World price of rice: 5 percent broken, white, milled, government standard, f.o.b. Bangkok
export price. World price of wheat: from July 1973 to September 1973, no.l Canadian
Western Red Spring; from October 1973 to March 1985, no.l Canadian Western Red Spring, 13.5
percent protein; from April 1985 to June 1990, St. Lawrence export. C.v. is the coefficient
of variation of monthly prices.
- 27 -
Figure 8-Rice prices, 1972-89
TAKA/MAUND
n n
n n n
~
00
~
81
M
~
M
~
M
~
U
00
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics. Monthly Statistical Bulletin, various
dates; and World Bank commodity prices.
Figure 9-Wheat prices, 1973-89
TAKA/MAUND
150
n
~
n
n
n
N
00
81
82
M
M
~
00
~
U
00
FISCAL YEAR
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates; and World Bank commodity prices.
- 28 -
Table 19-Yearly imports of rice and wheat, 1972/73-1989/90
Year-
Rice
Rice
per capita
Wheat
Wheat
per capita
(1,000 metric tons)
(grams)
(1,000 metric tons)
(grams)
396
83
270
394
195
304
57
723
85
148
316
185
695
35
260
583
75
300
1972/73
1973/74
1974/75
1975/76
1976/77
1977 /77
1978/79
1979/80
1980/81
1981/82
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
5,417
1,115
3,480
4,990
2,402
3,676
664
8,322
957
1,620
3,411
1,938
7,159
352
2,539
5,606
705
2,767
2,475
1,635
2,130
1.094
630
1,361
1,108
2,086
1,004
1,085
1.524
1,884
1,885
1.163
1,507
2,328
2,063
1,234
33,643
21,690
27,542
13,848
7,743
16,410
13,045
23,924
11,302
11,941
16,416
19,781
19,391
11,663
14,767
22,359
19,305
11,335
Source: Based on data from Bangladesh Bureau of Statistics, Statistical Yearbook 1989. (Dhaka: BBS,
1990) .
• The fiscal year starts in July.
5. A MODEL OF THE PUBLIC FOODGRAIN DISTRIBUTION SYSTEM IN BANGLADESH
INTRODUCTION
Foodgrain prices are determined by the interrelationship between
private sector decisions concerning production, consumption, storage,
and marketing, and government sector decisions related to public
distribution, procurement of domestic production, imports, and stock
management. Whereas, in describing the behavior of the private sector,
prices may be assumed as given, for the public sector this is not the
case, since a 1arge number of options for affecting pri ces are avail abl e
to the government. Therefore, in modeling the interaction between the
government and private sectors, there is an asymmetry of behavior in
relation to prices. The design of stock policy should take into account
this kind of asymmetry.
The foodgrain sector in Bangladesh is represented mainly by rice
and wheat. Whereas rice is predominant in production, contributing more
than 95 percent of total foodgrains, wheat is predominant in publ ic
distribution, mainly because of the quantities made available by food
aid. Given the substitutabil ity of rice and wheat (the cross price
elasticity of demand for rice with respect to wheat is 0.13 according to
Bouis 1989), the demand for these grains has to be determined
simultaneously.
Government operations, in both distribution and
procurement activities, affect prices of rice and wheat.
Both
commodities are storable and, especially for rice, there is a very
active network of intermediaries between farmers and consumers (Crow and
Murshid 1989). One fundamental aspect of this network is the presence
of storage along with a demand for storage generated by profit motives.
THE MODEL
In equil ibrium, demand for foodgrains is equal to marketable
supply,
(4)
where dl is the demand for grain i at time 1, and ms; is the marketable
supply bf grain i at time 1.
Marketable supply is given by production plus the net distribution
from the government, since exports of foodgrains are either not allowed
or are not yet feasible, and imports are monopolized by government. The
distribution by the government consists of monetized distribution
- 30 -
through rationing and open market sales, and in nonmonetized
distribution such as food-for-work, gratuitous relief, and vulnerable
group feeding.
To obtain the net distribution from public stock,
procurement has to be subtracted from total offtakes. Therefore,
msi7 = qiT + mofTi + nmof1i + omsir _ qpi7'
(5)
where
q;
production of grain i at time T,
mof1i
monetary off takes of grain i at time T,
nmof;
nonmonetary offtakes of grain i at time T,
oms 1i
open market sales of grain i at time T, and
qp;
procurement of grain i at time T.
Note that this equation allows computation of the demand for
foodgrains, which consists of both demand for consumption and demand for
storage. This can also be expressed by saying that the marketable
supply of foodgrains is either consumed or stored; that is,
(6)
where
ms;
the marketable supply of grain i as of time T,
c;
consumption of grain i as of time
T,
and
variation of private stocks of grain
as of
As it is, data on either consumption or private stock are not
ava il ab 1e on an aggregate bas is.
Therefore, both consumption and
private stock changes have to be expressed in terms of underlying
variables such as prices and income.
In part i cul ar, consumpt i on of grai n i wi 11 be expressed as a,
function of its own price, p', the price of the substitute grain, p;
(where i+j), and income, Y1: 1
(7)
- 31 -
Private storage will depend on the difference between expected prices
for the next period and current prices, so the change in private storage
can be expressed, as follows:
( 8)
where A is the difference operator, and pi+
is the price of grain i
expected to prevail at time T+l, based on t~
information available at
time 1The expression for the change in private stocks can be derived
from an underlying model of private storage that is reported in Appendix
3. As a result of this analysis, the behavior of the private sector can
be described by the following set of equations:
(9)
(10)
where the
are error terms.
The set u,i of instrumental variables is
~/s
(11 )
where stock i is ending period public stocks of grain i at time T, mi
denotes imports of grain i at time T, and lose~
denotes rice losses at
time 1A three-stage least squares estimation of the system is
implemented to take into account the simultaneity of the price of rice
and wheat.
The complete specification of the foodgrain dynamic system is
given below:
r
-r
(12)
+ a3m, + a4losses, + asy"
PHI al + a2stock~_1
-w
bl + b2stock~_1
PHI
pr,
r
ci + C2P,_1
+ C3P~+1
pW,
stockr
"
dl + d2P~_1
=
(13)
(14)
+ d5ms~
+ d6y"
+ mr + qpr _ mof r _ nmof r - oms r
+ d3P~+1
ljrstock r
+ b3mW, + b4losses, + bsy"
W
r
+ c4P, + csms, + c6Y"
1-1"
+ d4p~
7"
1
7"
,,'
(15)
(16)
- 32 -
W + mW + qpW _ mofw
stockrW= aWstock.,.-1
r
r
,.
_
w
nmofTw - oms 1"'
(17)
ms rr = qrr + mofrr + nmof1r + oms ,.r _ qprl' and
(18)
msW,. = qW1 + mof",. + nmof,.w + oms ,.w _ qpW1·
(19)
Equations (12) and (13) try to forecast the next period price by using
opening publ ic stocks, imports, forecast of rice losses, and income.
Equations (14) and (15) relate the current prices of both rice and wheat
to the lagged price, the forecast of future price, the marketable
surplus defined in equations (18) and (19), and income. Note that
income and current pri ce of the a lternat i ve foodgra income from the
demand for consumption, whereas the lagged and expected future prices
come from the demand for private stocks. Equations (16) and (17) give
the law of motion for public stocks.
ESTIMATION OF THE MODEL
The system specified above has been estimated by three-stage least
squares using seasonal observations from 1975/76 to 1989/90. Each year
contains 4 seasons, and 59 seasons have been used in the estimation.
Prices are deflated by the index of manufactured goods and quantities
are in per capita terms. For a description of the data see Appendix 4.
The first two equations reported i.n Table 20 give the instrumental
variable estimation of future price, p~+.
All the variables have the
expected sign and most of them are significant. In particular, opening
stocks have an important negat i ve effect on future pri ces. Si nce
imports add to the available supply, their coefficients are expected to
be negative; nevertheless, the coefficients are not statistically
significant. Losses in rice production that originate from cyclone,
drought, and flood affect future prices because of an expected shortfall
over the upcoming period. For rice, the effect of losses on prices is
significant, whereas the opposite is true for wheat, mainly because the
behavi or of expected wheat pri ces is not so heavily i nfl uenced by the
production of rice, given the predominant role of wheat imports in the
public distribution.
Income positively affects future prices by
increasing current consumption and lowering the supply available during
the coming period.
In terms of goodness of fit, the price equations explain a good
deal of the total variation of prices. For rice, the speculative effect
of future prices on current price is particularly important, as
demonstrated by the coefficient of P~+l
in Table 20. In fact, the
coefficient of future price is of the same order of magnitude as the
coefficient of lagged prices, indicating a support for the hypothesis of
profit maximizing demand for storage (Goletti 1990). Both wheat prices
- 33 -
Table 2O-Estimated equations of the foodgrain system, 1975/76-1989/90
Variable
Coefficient
t-Value
Equation for lead price of rice
Constant
stock~
mRt
losses t
Yt
Valid cases
R'
SEE
-0.0777
-0.0090
-0.0043
0.0031
0.0648
-1.1509
-3.9992
-1.1459
3.4254
6.5778
59
0.60
0.0314
Equation for lead price of wheat
Constant
stock":,
mw
t
losses t
Yt
Valid Gases
R'
SEE
-0.0520
-0.0040
-0.0011
0.0004
0.0413
-1.2435
-3.3182
-1.3023
0.7166
6.4386
59
0.46
0.02
Rice price equation
Constant
R
Pt-,
_R
Pt+1
p';'
ms~
Yt
Va 1 id cases
R'
SEE
0.0133
0.3577
0.3767
0.8059
-0.0007
-0.0094
0.3500
6.2749
4.4274
5.1137
-8.6816
-1.1840
59
0.88
0.17
Wheat price equation
Constant
w
Pt-1
P";'+1
p~
ms~
Yt
Valid cases
R'
SEE
-0.0174
0.2218
-0.4951
1.8096
-0.0673
0.3014
-0.0013
0.0145
-0.3135
2.2013
-1.3566
I. 8839
59
0.65
0.16
(continued)
- 34 -
Table 2O-Continued
Source: Estimated by the authors, with seasonal data.
Definitions of terms:
stock~
1>~+
stock of grain; at time t;
n\
imports of grain i at time t;
losses t
losses of rice during time t;
Y.
p~
income at time t;
price of grain; at time t;
1
ms~
instrumental variable estimation of price of grain i at time t+l;
marketable supply of grain; time t;
t
refers to season (season 1, Ju lY-October; season 2
SEE
season 3. March-April; season 4, May-June); and
standard error of estimation.
I
November-February;
and marketable supply have the expected signs. Wheat prices have a
positive effect on rice price due to the substitutability of rice and
wheat in consumption.
Income does not have a s i gni fi cant effect on current pri ces,
rna i nly because its i nfl uence is captured by future pri ces P~t'
For
wheat, it is noteworthy that the speculative effect is not sign,Ticant,
as pointed out by the coefficient of future price pW+l (Table 20). This
suggests a reestimation of the model with the 'constraint of zero
coefficient of future wheat prices. The reduced form of this estimation
is the one that is used in the simulations. The coefficients of the
estimation are reported in Table 21.
The model tracks the price of rice and wheat quite well. For rice
and wheat, the root mean square error for the overall period is 11 and
12 percent, respectively. For more recent samples, the performance
improves. For example, for the period 1985/86-1989/90 it is 4 and 5
percent, respectively.
Within this model, the tracking of stock
variables depends on the accuracy of the data on both procurement and
off takes. The balance equations for stock (given by equations [16] and
[17]) are the basis for the tracking of stock variables. The less than
perfect match between predi cted values and actual values is due to
unreported storage losses. By applying a storage decaying factor of 6
percent it is poss i bl e to improve the dynami c s imul at i on of stocks
considerably.
- 35 -
Table 21-ihree-stage least squares estimation of price equations of
foodgrain system, constrained, 1975/76-1989/90
Variable
Coefficient
t-Statistic
0.0130
0.3648
0.3789
0.7784
-0.0007
-0.0090
0.3436
6.4014
4.4535
4.9369
-8.7219
-1.1298
Rice price equation
Constant
R
p.,
P:+1
p,w
ms~
y,
59
0.8834
0.0170
N
R'
SEE
Wheat price equation
-0.0171
0.2385
0.2777
-0.0012
0.0129
Constant
w
Pt.'
p~
ms~
y,
-0.4868
-2.4379
3.4312
-1.9158
1.9261
59
0.6546
0.0164
N
R'
SEE
Source: Est imated by the authors.
Note:
The coefficient of future prices in the wheat price equation has been set equal to zero.
Definitions of terms:
income at time t;
price of grain i at time t;
instrumental variable estimation of price of grain; at time t+l;
;
ms,
marketable supply of grain i time t;
t
refers to season (season 1. Ju ly-October; season 2, November-February:
season 3, March-April; season 4, May-June); and
SEE
standard error of estimation.
6.
POLICY CONSTRAINTS AND POLICY OBJECTIVES
With reference to the general approach of Chapter 3, so far only
equation (1) has been made explicit by introducing the response of the
private foodgrain sector in Chapter 5. The specification of the policy
constraints, as in equation (2), and the objective function, as in
equation (3) of problem (P), remains to be done. This task is taken up
in this chapter.
THE POLICY CONSTRAINTS
The endogenous variables in the general framework introduced above
are constrained as in equation (2). Some of these constraints simply
state the non neg at i v.ity of some endogenous vari abl es, namely, pri ces and
stocks. Some other constraints are capacity constraints, imposed upon
stock variables to take into account the physical storage facilities
constraints. The capacity constraints are expressed as follows:
1
stockTi <
Gmax'
-
(20)
where i stands for either ri ce or wheat, 'f = t, ... , T, and G~ax
is the
maximum stock of grain i (assumed independent of time).
A third set of constraints on stock variables takes into account
mlnlmum stock requirements that may be related both to deadstocks (the
amount of stock needed for the system to be operat i ona 1) and to the
mi nimum stock 1eve 1s needed for food securi ty consi derat ions.
An
example of the latter is that the public food distribution system must
hold sufficient stocks to meet three months of offtake requests (505,000
tons), allowing the time frame necessary for importing foodgrains to
replenish the stock facilities.
These minimum stock requirements can be expressed as follows: 5
i
stock.,.i >
- G
min'
(21)
5 Note that both minimum and maximum stock requirements imply constraints for, decision
then
variables. For example, assuming that the decision variables are open market sales (oms~).
;s equivalent to
- 37 -
A fourth set of constrai nts is related to maximum domest i c
procurement and can be expressed as follows:
(22)
where qpi is procurement of grain i at time 1, and qi is production of
grain i 1t time 1, that is, maximum procurement is just a fraction, r,
of total production.
Finally, a fifth set of constraints that are considered in the
following policy exercises is related to foreign reserves. This type of
constraint can be expressed as follows:
wapi • mi . < Fi
'T
'T
-
l'
(23)
where wapi1 is the world price of grain i at time 1, and ~i is the maximum
amount of foreign exchange allocated to food imports m;;
THE OBJECTIVE FUNCTION
The objective function specification depends on the type of policy
pursued. In the following pol icy exercises, two main objectives are
considered: price stabilization and cost minimization. 6
The objective of price stabil ization is to be understood as
minimization of the variance of prices around a target price. In order
for such an objective to be made precise, a target price 8 has to be
specified for the period of the policy exercise going from ~=t
to 1=T.
The objective can then be expressed as follows:
T
L(p~
-8 1 )2/(T -t+l)
(24)
1=1;
The difficulty 1 ies with an appropriate specification of the target
price. Several elements will be taken into account in the specification
of the target price. First, a long-term trend of domestic prices;
second, a concern for seasonality fluctuations; third, the behavior of
6 Note that a third important objective of food stock policy ;s poverty reduction.
This
objective can be expressed by means of one commonly used poverty measure, such as that proposed by
Foster, Greer, and Thornbecke (1984). In order to do that, a value for the parameter a of the
severity of poverty has to be chosen.
Moreover, some parameters relative to rice and wheat
consumption of subgroups of the population have to be provided to make operational the computation
of the poverty index. In this context, note also that the objective of food security has already
been incorporated in the policy constraints, related to minimum stock requirements.
- 38 -
world prices. The target becomes a weighted average of these elements,
where the weights
reflect the relative importance attributed to them by
the government. 7
The objective of cost minimization can be readily specified, once
an expression for the cost is provided. The relevant cost expression
here is the operating balance of the food accounts. Basically this cost
refers to the difference between expenditures and revenues, as these
items have been defined in Appendix 5. For the time period of the
policy exercise, the expression of the cost is given by
T
:E :E
T=t
p'-t[wop;m;
+
pp;qp; - p;oms; - pr;mof;l.
(25)
i :::r,W
Expenditures are here simply given. by .the value, at international
prices, of food imports (the term ~op;
•.m;) and by the cash outlays for
domestic procurement (the term pp' • qp'). Revenues are given ~y the
monetary off takes evaluated at ration p?ices (the term pr; • mof;) and
br the value of open market sales, evaluated at market prices (the term
P, • oms;). Note that p is the parameter used to discount the future.
7
The expression for the weighted average is
1n(9,)
=
A, • 1n(p;) + A, • 1n(p:) + A, • 1n(wop~.
where p~ denotes the long-term domestic price of rice, p~ ;s the seasonal factor, and wop~
is the
world price of rice. Note that the target price considered here is the target for rice prices.
7.
OPEN MARKET OPERATIONS
In most of the policy exercises presented in the text, the policy
instruments controlled by the government are open market operations
(omo'). Open market operations are conducted at market prices. It is
posslble to express open market operations in terms of both open market
sales (oms;) and open market purchases (omp;) as follows:
(26)
Both open market sal es and open market operations are pos it i ve, but
their difference can be any sign. From this observation, it follows the
convention that positive open market operations have to be interpreted
as open market sales, and negative open market operations have to be
interpreted as domestic procurement.
The way the government has impl emented open market sal es and
domestic procurement so far can be schematically represented as follows:
sell oms; at price poms;;
buy qp; at price pp;.
The prices poms i are called "oms prices," and the prices ppi are called
prices
"procurement prlces." Note that both oms prices and procu~ment
are preannounced.
At this point there are some conceptual and practical problems.
What follows refers to procurement, but similar observations apply to
open market sales.
The,basic conceptual problem is, How can government ensure that an
amount qp' is procured at price pp'? Procurement depends on the capacity
and willihgness of the farmers anB traders to sell. Unless some forced
arrangement is put into effect, procurement is constrained by the supply
decisions of traders and farmers. These supply decisions depend, among
other things, on the differential between procurement prices and open
market prices. Following the model of Appendix 1, one can postulate a
relation of the type
(27)
- 40 -
The basic, point,to be made here is that the government can decide upon
either p~
or, qp~.
Wi,thin this contractual arrangement, it cannot decide
upon both pp' and qp'.
The procurement policy of the government then is reduced mainly to
the setting of procurement prices, while taking into account both the
effect of procurement prices on quantities actually procured (see
equation (27)) and the effect of procurement quantities on market prices
have to be
(see equations [5] and [10]). In fact, both these ef~ts
considered simultaneously, as is done in Appendix 2. The results given
in Table 45 in Appendix 2 show, among other things, that procurement
prices have not been a significant determinant of procurement.
Now a practical problem emerges. Even though the fit of price
equations is reasonably high (Figures lOa and lOb), in any estimation of
procurement supply and monetary off takes as in equation (27), the
goodness of fit is very low (Table 45, Appendix 2; Figures 10c-lOf).
This implies that use of such equations for planning purposes and for
the eval uation of different pol icies is bound to be very uncertain,
resulting in a large margin of error. Moreover, because of the linear
specification of equation (27) that is often used in many other studies,
there is no reason for the predicted value of this equation to be
positive. It may perfectly be the case that the predicted val ue of
procurement is negative, an outcome that does not make sense.
Supposedly, the intention of the government in setting procurement
prices is to support domestic prices, especially in periods immediately
after harvest. By announcing procurement prices in advance of harvest
time, the government cannot really know the level of market prices.
However, based on some predictions, it may still establish a reasonable
1eve 1 of procurement pri ces. Yet, as observed above, there is no
reliable way of estimating how much grain could be procured. This would
make any estimate of its impact on market prices even more unreliable.
Moreover, one should keep in mind that the way procurement activities
are actually implemented, mainly through a system of licensed dealers,
always generates rent-seeking activities that produce waste and make any
evaluation of the effects of procurement prices again very unreliable.
Because of all these observations, it seems appropriate to
consider open market purchases as an instrument to repl ace domest;ic
procurement (that is, in terms of the notation introduced above, qp' =
ompi). This would achieve the same purported effect of procuem~nt
activities as they are currently conducted, namely to support prices,
and their effect on prices could be calculated with a relatively higher
degree of reliability. Finally, this would reduce the opportunities for
rent-seeking activities, since the purchases will be conducted at market
prices.
In view of these considerations, by reca,ll ing that marketable
plus off takes (both
supply, ms!, is equal to domestic production, q~,
monetary and nonmonetary) plus open market sales minus domestic
procurement, the following equation is developed:
(28)
Figure lO-Actual and simulated values of the foodgrain system with public distribution, 1975-89
lOa-Rice price
n
Kg./CAPITA
TAKA/MAUND
TAKNMAUND
n
IOc-Rice procurement
IOb-Wheat price
n
~
00
M
ro
~
~ ~
M
~
M
M
~
n
n
~
00
m
ro
~
M
00
ffi
~
00
IOe-Rice monetized off takes
IOd-Wheat procurement
~
M
M
& M
~
ffi
M
~
00
~
~
.....
IOf-Wheat monetized offtakes
Kg./CAPITA
Kg./CAPITA
n n n
$
Kg./CAPITA
'"
u n n n
00
M
~
&
~ ~
~
~
•
~
M
n
~
N
00
M
~ ~ ~ ~
~
u
~ ~
n
n
n
N
00
M
~ ~
M
~
~
~
•
N
- 42 -
Since open market operations affect the domestic supply of foodgrains,
they directly affect prices, as can be seen from the price equation (10)
derived in Chapter 4. It is reproduced here for convenience:
Therefore, it is expected that open market operations (oms i - omp~)
have
a negative effect on prices insofar as they contribute to' augmentation
of the domestic supply.
8. SPECIFICATION OF POLICY OPTIONS
In the simulations of policy options for the foodgrain sector of
Bangl adesh, two types of exerci ses can be done. In the fi rst type,
counterfactual simulations of various policy options can be examined,
based on the historical values of exogenous variables. In the second
type, ex ante simulations can be performed, using stochastic simulation
for the exogenous vari abl es. In thi s paper, only the fi rst type of
simulation is reported.
Several elements have to be clarified at the outset of the
exercises. Among these elements are the time period of the simulations,
the initial conditions, the exogenous variables, the endogenous
variables, the control variables, and the objective of the policy. In
each policy, a baseline is computed in order to compare the effect of
different policies.
Six pol icies are evaluated:
price band; optimal price
stabilization; import approach to price stabilization; cost
minimization; price stabilization cum cost minimization (this is is
called the benchmark policy in this paper); and approximation to optimal
price stabilization.
A summary of these options is gi ven in Figure 11. A detail ed
description of each policy follows.
PRICE BAND POLICY
Establishing a price band mechanism implies setting a target
price, a price band, and a rule of intervention.
The target price is denoted by 8 , where the time index T varies
over the period of the pol icy exercise. Generally, the target price
chosen is a weighted average that takes into account the long-term trend
of domestic prices, seasonality, and the long-term trend of world prices
(Ahmed 1990). It is constructed in the same way as the target price
described in the definition of the price stabilization objective (see
Chapter 6).
The price band is defined with reference to the target price and
the specification of an upper and a lower intervention price that should
trigger open market operations. Usually, the upper ands lower trigger
prices are symmetrical in relation to the target price.
a Denoting these trigger prices by phigh and plow, they are related to the target price, 6T •
as follows:
phigh, = (1 + p) •
plow, = (1 + p) •
e,.
e,.
and
- 44 -
Figure Il-Policy options considered in the simulation exercises
Baseline
Simulation of the foodgrain model for the
period July 1985-June 1988. All exogenous and
control variables are taken at their
historical value.
Price Band
Uses open market operations to maintain a real
price band of plus or minus 4 percent around
the target.
Optimal Price
Stabilization
Uses open market operations to minimize
variance of prices around the target.
Import
Uses imports to minimize the variance of rice
prices around target.
Cost Minimization
Uses open market operations to minimize the
total cost of food operations.
Benchmark
Uses open market operations and imports to
minimize the total cost of food operations
subject to price stabilization and foreign
reserves constraints.
Approximation
Approximates the optimal price stabilization.
It is obtained by stochastic simulation of
production shocks, and by expressing open
market operations as a function of ri ce and
wheat production and of their own past.
Under the rule of intervention, open market sales are undertaken
by the government until either prices drop to the ceiling of the band or
public stocks reach the minimum operational level. The minimum stock
requirement is the same as the one mentioned in Chapter 6 that would
guarantee food security, and translates into equation (21).
Similarly, when prices in the absence of intervention tend to go
below the lower price of the band, open market purchases are undertaken
by the government until either the maximum stock capacity is reached or
The maximum stock
pri ces ri se to the lower 1eve 1 of the band.
requirement translates into equation (22).
Finally, when prices are within the band, no open market
operations are undertaken unless stock constraints are binding. When
this is the case, open market operations are undertaken in order to
satisfy the constraints.
- 45 -
The main advantage of a price band rule seems to be that the rule
can be simply stated, is relatively easy to implement, and is readily
understandable.
Therefore, it has desirable features from an
operational point of view. Nevertheless, the outcome is not optimal,
because it does not use all the available information. A price band
rule is a fixed rule, clearly suboptimal with respect to the rule that
can be computed as a solution of an optimization problem (Buiter 1981).
OPTIMAL PRICE STABILIZATION POLICY
The objective of this policy is to minimize the variance of rice
prices around a target price path as it was defined in Chapter 6. As in
the case of price band policy, the underlying motivation is to stabilize
prices.
But, unlike price band policy, the objective of price
stabilization is stated explicitly, and the policy is the outcome of an
optimization exercise.
The instruments available to the government are open market
operations.
Following the general approach of Chapter 3, the
constraints are given by the foodgrain model of Chapter 5, and the
constraints on open market operations that are implicit in equations
(21) and (22).
IMPORT POll CY
In this context,
stabil ization pol icy,
variance of rice prices
is in the instruments
imports of foodgrains.
trade policy is similar to the optimal price
insofar as the objective is to minimize the
around a target price path. The only difference
used. The control variables are now given by
It is assumed that no exports take place.
COST MINIMIZATION POLICY
In this case the explicit objective of the policy is to minimize
the present value of cost, as given in equation (25). The basic policy
issue here is to see how the public food distribution. assumed in the
baseline can be carried out at minimum cost. The instruments chosen are
again given by open market operations.
BENCHMARK:
PRICE STABILIZATION CUM COST MINIMIZATION POLICY
In this policy option all the previous considerations regarding
cost efficiency, price stability, and food security are included. The
objective is again to minimize the cost of operations, but new policy
instruments and constraints are now added.
- 46 -
The policy instruments are given by both open market operations
and imports. Besides the reaction of the private sector, given by the
system of equations in Chapter 5, constraints on minimum and maximum
stock requirements are specified. In addition to these constraints, two
more constraints related to price variabil ity and foreign exchange
reserves are considered. The constraint on price variability requires
that prices move in a plus or minus 4 percent band around the target
price. The foreign exchange constraint imposes a ceil ing on foreign
exchange that can be spent on imports. The ceil i ng is gi ven by the
foreign exchange equivalent of foodgrain imports in the baseline. The
formal expression of this policy is reported in Appendix 6.
APPROXIMATION POLICY
In general, the optimal paths of the policy instruments used for
the previous policies are not easily related to the underlying variables
of the system. It would be interesting to approximate the optimal
policies, with "simpler" policies, easily understood and implementable
(Pinckney 1988, 1989).9 Examples of these approximation policies are
linear feedback rules, expressed in terms of the current state of the
system. One specific way to get such an approximation is described in
Appendix 7.
9
To make this intuition clear, one should introduce a norm in some metric space of functions.
9.
EVALUATION OF COUNTERFACTUAL SIMULATIONS
In this case, the model of the foodgrain sector is used ex post to
do counterfactual simulations. The three-year period 1985/86-1987/88 is
considered in this exercise, for a total of 12 seasons, characterized by
the first two years as just above average in terms of production, and
the third as a "bad" production year (see rice production in Figure 3).
The baseline for these simulations is constructed by taking
exogenous values and predetermined variables at their historical values
(Tables 22-25) and running the reduced form of the model in order to get
the endogenous variables (prices and stocks). In the pol icy options
presented below, open market operations and imports are policy
instruments that, as such, are choice variables in the optimization
problems considered. Their counterparts in the baseline are open market
sa 1es, procurement quant i ties, and imports actually performed by the
government during the period 1985/86-1987/88. The total cost for the
pipeline is more than Tk 17 billion, and the average foodgrain stock
level is nearly 1.1 million tons.
The insight gained from this type of exercise facilitates
comparison of different policy options with the one that is already in
place from the perspective of the government's objectives of ensuing
price stability, cost efficiency, and food security.
The detailed results for each policy are given in Tables 26-39 at
the end of this chapter. The summary statistics of the various policy
options appear in Chapter 10.
PRICE BAND POLICY
This policy is very effective at stabilizing prices (the
coefficient of variation goes from 6.0 percent in the baseline to 4.4
percent), yet it is not cost-effective (Tables 26 and 27; Figure 12).
The total cost of operations is Tk 19.6 billion, which represents an
increase of 15 percent in relation to the baseline cost, mainly due to
the increased rol e of procurement (that is, open market purchases).
Note that by intervening to buy when prices are lower than the target,
the overall price path is altered, causing an accumulation of stocks
that puts a downward pressure on prices. The average foodgrain stock
for this policy is nearly 1.5 million tons. Therefore, the attempt to
stabilize prices above the floor of the band is frustrated by the rule
of operations of the policy. Clearly, this outcome could be avoided if
the government were allowing stocks to accumulate indefinitely, but this
is not possible given that public storage facilities have a limited
capacity (2 million tons is the level used in the simulations).
- 48 -
Table 22-Variables in the baseline, 1985-88
Price b
Year/
Season-
Rice
Stock
Wheat
Rice
Wheat
Winter
Bora
1986/87
Aus
Aman
Winter
Bora
Im[!orts
Rice
Wheat
(kilograms/capita)
(Tk/maund)
1985/86
Aus
Aman
agen Market Ogerations C
Rice
Wheat
33.7
30.7
35.0
36.0
20.9
20.5
20.7 .
22.2
3.67
3.98
3.64
3.32
6.66
3.22
4.39
6.12
0.07
0.01
0.06
0.04
0.35
0.14
0.00
0.00
0.12
0.09
0.14
0.00
4.42
1. 39
2.78
3.08
37.5
35.6
38.4
38.3
23.0
22.3
22.0
23.2
2.17
2.17
1.92
3.29
7.72
3.59
3.38
5.63
0.50
0.03
0.48
0.30
0.64
0.40
0.04
0.03
0.23
0.55
0.79
0.97
5.19
2.10
3.21
4.27
37.9
36.2
37.5
36.3
23.1
22.4
22.0
22.7
4.87
5.55
5.04
7.24
7.84
10.14
10.27
10.68
0.88
0.19
0.10
0.04
0.68
0.12
0.03
0.00
2.90
1.61
0.32
0.77
8.43
9.23
2.36
2.34
36.1
22.1
3.90
6.64
0.22
0.20
0.71
4.07
2.2
0.9
1.56
2.74
0.27
0.25
0.83
2.47
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The baseline is obtained by simulating the foodgrain madel for the period July 1985-June
1988 .
• The seasons are defined as follows: aus, July-October; aman, November-February; winter, March-
April; and boro, May-June.
b Prices are deflated by the index of manufactured goods.
C Positive open market operations have to be interpreted as open market sales: negative open market
operations have to be interpreted as domestic procurement.
Some of these undesirable outcomes may be avoided by planning a
more adequate price band width and a different target price. All that
is pointed out here is a caveat against an enthusiastic support of fixed
rul es of ope rat ions that do not a11 ow for a necessary degree of
flexibil ity in reacting to new information in an efficient way. The
substance that emerges from this analysis is that price bands are a very
complex policy to plan. One main criticism of price bands that should
be kept in mind is that, unless the band itself is changed periodically,
the buffer stock either tends to depl ete to a very low 1evel or to
accumulate, at times, to an unmanageably high level. In the simulation
presented here, for example, the capacity constraints are binding, since
the maximum stock level of almost 2 million tons is reached.
- 49 -
Table 23--tosts in the baseline, 1985-88
Year/
Procurement
Cost
Season-
Imports
Ration
Sales
Open Market
Sales
Totalb
Cost
(Tk million)
1985/86
Aus
Foreign
Exchange
(US$
Cash
OutflowC
million) (Tk million)
514
888
492
303
1,308
862
1,682
1,673
1,619
1,366
518
515
111
70
50
35
1,001
313
1,607
1,426
77
28
56
55
-1,087
-461
90
-98
47
169
107
1,021
2,353
1,237
1,913
2,464
1,515
1.790
984
804
813
244
472
313
72
-628
564
2,367
78
40
62
80
-1.918
. -1.550
-865
516
Aus
292
404
273
1,860
5,720
5,765
1,452
2,120
2,346
2,296
803
479
1,242
249
112
37
2,424
3,624
810
3,463
185
186
46
67
-684
212
-67
2,286
Total
6,380
29,548
15,035
3,848
17,045
959
-3,623
489
1,535
642
351
1. 274
50
1,047
Aman
Winter
Bora
1986/87
Aus
Aman
Winter
Bora
1987/88
Aman
Winter
Bora
Standard
deviation
Source:
Estimated
Note:
The baseline is obtained by simulating the foodgrain model for the period July 1985-June
1988 .
by
the authors.
• The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApr;l; boro, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
OPTIMAL PRICE STABILIZATION POLICY
In this case the objective is to mlnlmlze the variance of prices
around the target price; the policy instruments are open market
operations (Figures 13a, 13b, and 13c).
Stabil ization is perfect
(Figure 13a) and is achieved at approximately half the cost of the
baseline, that is, about Tk 8.4 billion (Tables 28 and 29). This
remarkable result was mainly due to an intensive use of open market
sales and domestic procurement. The variability of total cost is very
high across seasons in the simulation period. The standard deviation of
total cost is almost three times the level in the baseline. Note that
in thi s case both imports and monetary offtakes are kept at thei r
historical levels. If imports were eliminated it would not be possible
to sustain the level of off takes specified in the simulation. This is
because domestic procurement of wheat is insufficient to meet the demand
of wheat through both monetized and nonmonetized channels of the public
. food distribution system. It will also be seen in the following policy
exercises that if both open market operations and imports are rationally
used as policy instruments, wheat imports can be reduced substantially.
- 50 -
Table 24-Historical values of prices used in the baseline, 1985-88
Year/
Season-
Rice
Wheat
Price
Price
Rice
Wheat
Rice
Procurement Procurement Ration
Price
Price
Price
Wheat
Ration
Rice
World
Wheat
World
Price
Price b
Price b
(Tk/maund)
1985/86
Aus
Aman
Winter
Bora
278
259
303
317
173
173
178
196
263
255
255
260
162
162
175
180
262
268
269
273
173
179
181
187
235
255
238
228
191
216
214
201
336
318
340
362
207
199
194
219
265
274
284
300
180
180
190
200
283
283
283
283
192
192
192
192
235
230
244
246
157
156
157
154
346
334
351
347
211
207
206
218
300
308
308
308
198
200
200
200
288
301
313
315
196
201
204
208
279
331
357
351
149
166
170
206
1986/87
Au,
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various
dates .
• The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApril; bora, May-June.
b World prices are converted from U.S. dollars.
The result obtained from this policy analysis is that a flexible
policy approach to price stabilization, where open market operations are
used more intensively than in the case of price bands, brings about
sUbstantial improvements. The average foodgrain stock level is about
1.1 million tons.
IMPORT POLICY
Here imports are used to stabilize prices. Open market sales are
kept at their historical levels so that the effect of imports is felt
through future prices. Since imports negatively affect the expectations
of future prices, they also moderate current prices. The reduction of
price level and price variability is remarkable (Tables 30 and 31;
Figure 14). Compared with the case where open market operations were
the only policy instrument (that is, in the optimal price slabilization
option), the total cost associated with the import policy is now higher
(Tk 14.7 billion versus Tk 8.4 billion).
Table 25-Historical values of quantities in the baseline, 1985-88
Year/
Season
a
Product ion
Rice
Wheat
ImI10rts
Rice
Wheat
Procurement
Rice
Wheat
Monetary
Offtake
Rice
Wheat
Open Market
Stock
Sa les
Rice
Wheat
Rice
Wheat
(1,000 metric tons)
1985/86
Aus
Aman
Winter
Bora
3,084
8,286
367
3,304
0
0
1,042
0
12
9
14
0
437
138
278
310
70
130
9
22
7
0
92
31
99
61
27
27
199
193
67
63
7
1
6
4
35
13
0
0
378
413
344
351
620
275
401
619
3,378
8,019
401
3,609
0
0
1,091
0
23
56
81
100
525
214
329
439
6
23
0
107
1
0
21
30
68
62
35
24
194
256
139
121
50
3
49
31
65
41
4
3
178
175
119
241
728
274
268
506
3,224
7,459
473
4,258
0
0
1,048
0
300
168
34
81
872
962
248
246
35
49
0
204
2
0
51
33
54
96
43
17
367
284
81
60
91
20
10
4
70
12
3·
0
329
415
277
640
633
825
654
849
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Source: Based on data from Bangladesh Bureau of Statistics, Monthly Statistical Bulletin, various dates.
I
The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-April; boro, May-June.
01
......
- 52 -
Figure 12-Price band policy
12a-Prices of rice
AMAN
YEAR/SEASON
12b-Open market operations of rice
Kg./Caplta
4
2
-2
-4
AMAN
BORO
"
AMAN
BORO
YEAR/SEASON
'"
AMAN
BORO
AMAN
BORO
12c-Open market operations of wheat
Kg,/Capita
-2
AMAN
BORO
"
AMAN
YEAR/SEASON
BORO
",
- 53 -
Figure 13-Price stabilization policy
13a-Prices of rice
AMAN
BORO
II
AMAN
BOAO
YEAR/SEASON
"'
AMAN
BORO
13b-Open market operations of rice
Kg./Capita
8r:~mD]
-BASELINE
8
2
o t't"........-
___-7""
-4
-6
-8
-1 0
P---""-'--'4-'----'---"--t-""-'-'----+---'----'---'t--'--'-----'
I
AMAN
BORa
II
AMAN
BOAO
III
AMAN
BORO
YEAR/SEASON
13c-Open market operations of wheat
Kg ./Caplta
15
r-''------='''"'=
1or====-:'
-5
AMAN
BORO
II
AMAN
BORO
YEAR/SEASON
111
AMAN
BORO
- 54 -
Figure 14-1mport policy
14a-Prices of rice
Taka/Maund
AMAN
BORO
II
AM AN
BORO
YEAR/SEASON
"'
AMAN
BORO
"'
AMAN
BORO
14b-Imports of rice
-1
-2
AMAN
BORO
II
AM AN
BORO
YEAR/SEASON
14c-Imports of wheat
2
-1
AMAN
BOAO
II
AMAN
YEAR/SEASON
BORO
"'
AMAN
BORO
- 55 -
Nevertheless, the total cost of this policy option still
represents a 14 percent saving in relation to the baseline. The main
reason for this relatively high cost is that stocks are not used
efficiently. In other words, an import policy divorced from a stock
policy is not an effective tool. This suggests that in order to look
for a real improvement in both cost and stabilization, both trade and
stock policy have to be used judiciously. The average foodgrain stock
level for this policy is 847,000 tons.
COST MINIMIZATION POLICY
In this case the only objective of the policy is to minimize total
cost to carry out publ ic distribution. The outcome is a pol icy path
that results in a total cost equal to just 35 percent of the original
baseline cost, that is, Tk 6 billion (Tables 32 and 33; Figure 15). The
main instrument to be used intensively to get this result is open market
sales. Under this scenario, the government allows the prices to move up
to a relatively high level so as to make profits by selling part of the
imported grains in the open market. Note also that in this case open
market purchases (that is, domest i c procurement) are very small in
comparison with all previous cases. The average foodgrain stock level
in this case is only 686,000 tons. The effect of cost minimization is
to reduce the amount of public stock considerably.
BENCHMARK:
PRICE STABILIZATION CUM COST MINIMIZATION POLICY
With a total cost equal only to 30 percent of the baseline (that
is, Tk 5.1 billion), it is possible to achieve perfect stabilization
around the target price (Tables 34 and 35; Figure 16). The flexibility
of this policy allows use of both imports and open market operations to
take advantage of both the domestic and the international grain markets.
This implies a more effective import policy and more active open market
operations. The average foodgrain stock is 724,000 tons.
As in previous pol icy options, the capacity to implement the
benchmark policy depends on being able to predict the exogenous
variables of the policy exercise accurately enough. For this reason,
sensitivity analysis with respect to production and world prices
deserves some attention.
Given the extreme variability of world prices, it is important to
see how this policy is affected by different levels of world prices. In
particular, it is interesting to perform a simple exercise to compute
the benchmark pol icy when world prices are 30 percent higher. The
results are reported in Tables 36 and 37. The total cost of the policy
rises from Tk 5.1 bill ion to Tk 12.9 bill ion. Therefore, when world
prices rise by 30 percent across the period of the simulation, total
costs rise by 251 percent. This is mainly the result of lower revenues
from open market sales.
- 56 -
Figure 15-Cost minimization policy
15a-Prices of rice
42
r=-",.~
Taka/Maund
AMAN
BORO
"
111
AMAN
BORO
BORO
III
AMAN
BORO
BORO
III
AMAN
BORO
BORO
AMAN
YEAR/SEASON
15b-Open market operations of rice
4
2
AMAN
BORO
II
AMAN
YEAR/SEASON
15c-Open market operations of wheat
Kg./Capita
AMAN
BORO
"
AMAN
YEAR/SEASON
- 57 -
Figure 16-8enchmark policy:
price stabilization cum cost minimization
16a-Prices of rice
Taka/Maund
AMAN
BORO
"
AMAN
III
AMAN
BOAO
BOAO
III
AMAN
BORO
BORO
111
AMAN
BORO
BORO
YEAR/SEASON
16b-Open market operations of rice
AMAN
BORO
"
AMAN
YEAR/SEASON
16c-Open market operations of wheat
Kg./Caplta
-1
-2
-3
-4
AMAN
BORO
"
AMAN
YEAR/SEASON
- 58 -
Figure 16-Continued
16d-Imports of rice
6 \ - -_ _ _,-1,
4
AMAN
BORO
II
AMAN
BORO
111
AMAN
BORO
BORO
III
AMAN
BORO
YEAR/SEASON
16e-Imports of wheat
-2~4+
I
AMAN
BORO
II
AMAN
YEAR/SEASON
Another interesting sensitivity analysis of the benchmark case is
done by considering the situation where no ration distribution takes
place (Tables 38 and 39). The saving in total cost is noteworthy, about
50 percent of the benchmark case (the total cost is Tk 2.7 billion).
Yet the saving is not comparable to the loss of ration sales, which was
much higher (Tk 15 billion, as seen in Table 37).
What is the
explanation for this overcompensation of the revenue loss from ration
sales?
Clearly, procurement activities are lower than in the benchmark
case, because a lesser amount of public stock is needed for distribution
- 59 -
(only 690,000 tons). The import cost is almost the same, since the same
ceiling on foreign reserves is binding. The big difference lies in the
open market sales, since part of the stock that was previously
distributed at ration shops can now be sold in the open market.
APPROXIMATION POLICY
In the attempt to find an approximation to the optimal policies,
the methodology described in Appendix 7 has been applied to approximate
the optimal stabilization policy, pursued only with open market
operations. It is remarkable that the approximate pol icy tracks the
optimal solution quite well (Figure 17) and also that the total cost of
almost Tk 8.5 billion is extremely close to the level obtained in the
optimal policy (Tables 40 and 41). The average foodgrain stock level is
876,000 tons. This amount is less than in the optimal stabilization
policy, mainly because on average the open market sales are higher in
the approximation policy than in the optimal policy.
The result is very promising insofar as only a very limited number
of variables have been included as independent variables in
approximation. In fact, the feedback expression of the approximation
policy is the truncated (see Appendix 7) version of
oms ".i
=
f i (qrT' qWT' omo 7"-1
i ).
(29)
Therefore, only production and past open market operations are in the
feedback expression. If imports also are a policy instrument, then one
should include world prices as independent variables in equation (29).
- 60 -
Figure 17-Approximate versus optimal open market operations
17a-Rice
Kg./CAPITA
8~-'
6
4
2
-2
-4
-6
-8
-10~=4"
I
AMAN
BORO
II
AMAN
BORO
III
AMAN
BORO
BORO
III
AMAN
BORO
YEAR
17b-Wheat
Kg./CAPITA
15r7~C=-
10
5
-5
AMAN
BORO
II
AMAN
YEAR
- 61 -
Table 26--Variables in the price band policy, 1985-88
Price b
Year/
Season-
Rice
Open Market
Stock
Wheat
Rice
Wheat
(Tk/maund)
e
OQerat; cns
Rice
Wheat
ImQorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Boro
33.7
31.3
34.0
34.3
20.9
20.7
20.3
21.6
3.03
6.77
6.23
5.57
6.94
3.63
3.85
5.31
0.00
-4.68
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.09
0.14
0.00
4.42
1.39
2.78
3.08
35.7
33.6
36.9
35.4
22.5
21.7
22.0
22.4
4.73
4.87
6.90
7.23
7.60
3.87
8.80
10.46
0.00
-0.5
-1.96
0.00
0.00
0.00
-5.32
0.00
0.23
0.55
0.79
0.97
5.19
2.10
3.21
4.27
34.4
32.8
34.7
33.3
21. 7
20.9
20.8
21.5
7.65
7.65
7.65
7.65
11. 09
11. 09
11. 09
11.09
1.47
0.24
-0.54
0.15
1.95
2.22
-0.38
0.05
2.90
1.61
0.32
0.77
8.43
9.23
2.36
2.34
34.2
21.4
6.33
7.9
-0.49
-0.12
0.71
4.07
1.5
0.7
1.49
3.12
1.53
1.83
0.83
2.47
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The price band 1s defined by a plus or minus 4 percent margin around the target price.
a The seasons are defined as follows:
aus, July-October; aman. November-February; winter. March-
April; bora, May-June.
b Prices are deflated by the index of manufactured goods.
o Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
- 62 -
Table 27-Costs in the price band policy, 1985-88
Procurement
Cost
Year/
Season-
Ration
Imports
Sales
Open Market
Sales
Total
Cost b
(Tk mill ion)
1985/86
o
Aus
3,304
Aman
o
o
Winter
Bora
1986/87
o
Aus
Aman
Winter
407
4,607
o
Bora
1987/88
o
o
Foreign
Exchange
Cash
OutflowO
(US$ million) (Tk million)
2,308
862
1,682
1. 673
1,619
1,366
518
515
o
o
2,353
1. 237
1,913
2,464
1,515
1,790
984
804
o
2,346
2,296
803
479
2,352
1.391
689
2,799
1,164
1,158
77
28
56
55
-1,400
2,025
-352
-366
838
-146
5,536
1,660
78
40
62
80
-1,152
-1,068
4,107
-191
159
1,022
2,078
1,352
1,482
185
186
46
67
-2,086
-1,334
475
305
o
o
o
o
o
Bora
o
5,720
5,765
1,452
2,120
Total
9,020
29,548
15,035
3,902
19,632
959
-1,036
Standard
deviat ion
1,473
1,535
642
720
1,366
50
1,634
Aus
Aman
703
Winter
o
Source: Est imated by the authors.
Note:
The price band is defined by a plus or minus 4 percent margin around the target price .
• The seasons are defined as follows: aus, July-Octoher; aman, November-February; winter, MarchApril; bora, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
o Cash outflow = total cost - foreign exchange.
- 63 -
Table 28-Variables in the optimal price stabil i zat ion policy. 1985-88
Priceb
Year/
Season-
Rice
Open Market
O[!erat ions e
Stock
Wheat
Rice
Wheat
(Tk/maund)
Rice
Wheat
ImQorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.5
32.2
34.2
33.6
20.9
20.9
21.0
21.6
1. 47
8.83
8.07
6.08
6.61
3.32
8.76
9.93
1.56
-8.21
0.09
1. 23
0.33
0.00
-5.20
0.00
0.12
0.09
0.14
0.00
4.42
1. 39
2.78
3.08
34.8
34.6
38.5
35.7
22.2
21.9
22.5
21.3
1. 47
2.53
4.70
2.58
11.94
7.95
12.63
3.32
3.73
-1.22
-1.96
2.58
0.00
0.00
-5.32
10.75
0.23
0.55
0.79
0.97
5.19
2.10
3.21
4.27
36.2
35.7
36.5
33.9
21.9
21.7
21.5
21.8
3.47
6.93
7.42
1. 47
3.32
3.32
3.32
3.32
1. 29
-2.98
-0.99
6.12
3.01
2.68
0.08
0.52
2.90
1.61
0.32
0.77
8.43
9.23
2.36
2.34
35.0
21.6
4.58
6.48
0.10
0.57
0.71
4.07
1.7
0.5
2.77
3.65
3.64
4.09
0.83
2.47
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The optimal price stabilization policy uses open market operations to minimize the variance
of rice prices around the target .
• The seaso'ns are def; ned as fa 1lows :
aus, Ju ly-October; aman, November-February; wi nter. March-
April; bora, May-June.
Prices are deflated by the index of manufactured goods.
Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
b
C
- 64 -
Table 29-Costs in the optimal price stabilization policy. 1985-88
Procurement
Cost
Year/
Season
8
Imports
Ration
Sales
Open Market
Sales
Total
Cost b
(Tk million)
1985/86
Aus
Aman
Winter
Bora
5,955
2,549
1986/87
Aus
Aman
Winter
Bora
1,026
4,742
o
1,619
1,366
518
515
1,288
2,353
1,237
1. 913
2,464
1,515
1,790
984
804
3,151
0
5,720
2,737
951
0
5,765
1,452
2,120
17,961
1,979
o
o
-599
5,450
3,641
175
77
28
56
55
-2,688
4,677
2,125
-1,349
o
o
8,368
-2,314
473
5,671
-6,707
78
40
62
80
-4,304
-449
4,242
-8,558
2,346
2,296
803
479
2,843
1.497
46
5,834
531
4,710
1,554
-4,193
185
186
46
67
-2,577
1,298
677
-5,370
29,548
15,035
24,083
8,392
959
-12,276
1,535
642
2,560
3,682
50
3,769
1987/88
Aus
Aman
Winter
Bora
Total
Standard
deviation
Cash
OutflowC
(US$ million) (Tk m1111on)
2,308
862
1.682
1.673
o
Foreign
Exchange
o
72
983
Source: Est lmated by the authors.
Note:
The optimal price stabilization policy uses open market operations to minimize the variance
of rice price around the target.
The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApril; bora, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
a
- 65 -
Table 3O-Variables in the import policy, 1985-88
Priceb
Year/
Season-
Rice
Open Market
Ogerat ions e
Stock
Wheat
Rice
Wheat
(Tk/maund)
Rice
Wheat
Imgorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.6
30.8
34.7
34.6
20.9
20.5
20.5
21.7
2.84
2.71
6.31
5.61
3.32
3.32
3.32
3.32
0.07
0.01
0.06
0.04
0.35
0.14
0.00
0.00
0.00
0.90
4.10
0.00
1.16
4.62
2.53
1.60
35.8
33.9
37.2
36.6
22.4
21.7
21. 4
22.6
4.04
3.15
2.05
6.65
3.32
3.32
3.32
3.32
0.50
0.03
0.48
0.30
0.64
0.40
0.04
0.03
0.00
0.00
0.00
5.25
3.43
5.97
3.61
2.31
36.0
35.5
36.7
33.8
22.4
22.1
21.6
21.9
4.80
3.40
9.50
8.73
3.32
3.32
3.32
3.32
0.88
0.19
0.10
0.04
0.68
0.12
0.03
0.00
0.00
0.00
6.81
0.00
6.09
6.66
2.31
1.82
34.9
21.6
4.98
3.32
0.22
0.20
1. 42
3.51
1.8
0.7
2.42
0.00
0.27
0.25
2.47
1.90
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The imports pol icy uses open market operations to minimize the variance of prices around the
target .
• The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-
April; bora. May-June.
Prices are deflated by the index of manufactured goods.
Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
b
C
- 66 -
Table 31-Costs in the import policy, 1985-88
Procurement
Year/
Season 8
Cost
Imports
Ration
Open Market
Sales
Sales
Total
Cost b
(Tk million)
1985/86
Forelgn
Exchange
Cash
OutflowO
(US$ m; 11 ion) (Tk m; 11 ion)
o
o
o
o
584
3,277
4,077
866
1,619
1,366
518
515
210
70
50
33
-1,245
1,840
3,510
318
19
107
135
29
-1,777
-1,035
270
-471
o
o
o
o
1,459
2,536
1,555
4,530
1,515
1,790
984
804
783
237
457
300
-840
509
114
3,426
48
82
50
146
-2,115
-1,708
-1,245
1,102
Aus
o
Aman
Winter
Bora
o
o
2,512
3,092
7,924
1,058
2,346
2,296
803
479
1,189
245
110
35
-1,023
552
7,012
544
81
100
252
34
-2,744
-1,565
4,047
-181
o
33,469
15,035
3,719
14,716
1.083
-7,421
o
1,966
642
336
2,288
63
1,744
Aus
Aman
Winter
Bora
1986/87
Aus
Aman
Winter
Bora
1987/88
o
Total
Standard
deviation
Source: Est imated by the authors.
Note:
The imports policy uses open market operations to minimize the variance of rice prices
around the target .
• The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-
April; boro, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange,
- 67 -
Table 32-Variables in the cost minimization policy. 1985-88
Yearl
Price
Seas anti
Rice
b
Open Market
Stock
Wheat
Rice
O[!erat ions
Wheat
(Tk/maund)
Rice
e
Wheat
Im[!orts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.5
31.6
35.9
37.4
20.9
20.8
21.0
22.7
1.47
2.80
1.47
1.47
6.68
3.39
4.30
5.B2
1.56
-2.18
1.03
-0.37
0.33
0.00
0.24
0.12
0.12
0.09
0.14
0.00
4.42
1.39
2.78
3.08
39.2
36.9
39.5
38.8
23.7
22.9
22.4
23.2
1.47
1. 47
1.47
1.47
8.18
4.42
4.56
4.77
-0.60
-0.16
0.28
0.65
0.00
0.00
-0.36
1.99
0.23
0.55
0.79
0.97
5.19
2.10
3.21
4.27
38.5
37.6
39.9
38.8
23.0
22.5
22.7
23.5
1.47
1.47
1.47
1.47
4.71
4.62
5.03
5.24
2.24
0.61
-0.17
0.52
3.01
2.68
0.08
0.52
2.90
1. 61
0.32
0.77
8.43
9.23
2.36
2.34
37.3
22.4
1.58
5.15
0.28
0.72
0.71
4.07
2.5
1.0
0.39
1. 26
1.13
1.15
0.83
2.47
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The cost minimization policy uses open market operations to minimize the total cost of food
operations.
a The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApril; boro, May-June.
b Prices are deflated by the index of manufactured goods.
C Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
- 68 -
Table 33-Costs in the cost minimization policy. 1985-88
Ration
Procurement
Year/
Season'
Cost
Sales
Imports
Open Market
Sales
Total
Cost b
(Tk mi 1110n)
Foreign
Exchange
Cash
OutflowO
(US$ million) (Tk mi 1110n)
1985/86
Aus
Aman
Winter
Bora
0
1,558
0
327
2,308
862
1.682
1.673
1,619
1,366
518
515
1,289
0
980
65
-599
1.053
184
1.420
77
28
56
55
-2,688
279
-1,332
-104
571
141
195
0
2,353
1.237
1.913
2,464
1,515
1,790
984
804
0
0
265
1,863
1.409
-412
859
-203
78
40
62
80
-581
-1,334
-569
-2,054
0
0
179
0
5,720
5,765
1.452
2,120
2,346
2,296
803
479
3,931
2,138
49
860
-557
1.332
779
781
185
186
46
67
-3,664
-2,080
-98
-396
2,971
29,548
15,035
11,438
6,046
959
-14,622
430
1.535
642
1,156
748
50
1,149
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Total
Standard
deviation
Source: Estimated by the authors.
Note:
The cost minimization policy uses open market operations to minimize the total cost of food
operat 10ns .
• The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-
April; boro, May-June.
b
C
Total cost = procurement cost + import cost - ration sales - open market sales.
Cash outflow = total cost - foreign exchange.
- 69 -
Table 34-Variables in the benchmark policy:
cost minimization, 1985-88
Price b
Year/
Season8
Rice
Open Market
Dgerat ionse
Stock
Wheat
Rice
price stabilization cum
Wheat
(Tk/maund)
Rice
Wheat
ImQorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.6
32.0
34.9
35.0
20.9
20.9
21.1
22.0
1.47
6.37
3.69
1.47
3.32
3.32
5.02
3.32
1.44
-5.84
2.03
4.75
0.00
0.00
-4.23
0.00
0.00
0.00
0.00
3.03
0.80
4.48
0.00
0.00
36.0
35.4
38.7
37.2
22.6
22.2
22.4
23.0
1.47
2.38
1.47
3.69
3.32
3.32
3.32
3.32
6.30
-1.61
0.34
4.22
0.00
0.00
-3.57
0.00
7.13
0.00
0.00
6.76
2.79
5.57
0.00
2.28
37.7
37.2
37.7
35.2
22.8
22.6
22.5
22.5
3.98
7.43
6.86
1.47
3.32
3.32
5.26
3.32
-1.09
-4.60
-0.28
4.81
2.17
0.00
-4.22
0.00
0.00
0.00
0.00
0.00
7.58
6.54
0.00
0.00
35.9
22.1
3.48
3.62
0.87
-0.82
1.41
2.50
1.9
0.7
2.28
0.71
3.81
2.02
2.73
2.86
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The benchmark policy uses open market operations and imports to minimize the total cost of
food operations subject to price stabilization and foreign reserves constraints .
• The seasons are defined as follows:
aus, July-October; aman, November-February; winter. March-
April; bora. May-June.
Prices are deflated by the index of manufactured goods.
Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
b
C
- 70 -
Table 35--Costs in the benchmark policy:
minimization, 1985-88
Procurement
Cost
Year/
Season'
Imports
Ration
Sales
price stabilization cum cost
Open Market
Sales
Total
Cost b
(Tk million)
Foreign
Exchange
Cash
OutflowC
(US$ mi 11 ion) (Tk mi 11 ion)
1985/86
Aus
Aman
Winter
Bora
0
4,220
2,080
0
406
2,588
0
1,864
1,619
1,366
518
515
1.054
0
1.649
3,942
-2,267
5,442
-86
-2,592
14
84
0
62
-2,636
3,084
-86
-3,953
1986/87
Aus
Aman
Winter
Bora
0
1,390
1,946
0
5,728
2,366
0
5,541
1. 515
1,790
984
804
5,491
0
319
4,087
-1. 278
1,965
643
650
189
77
0
179
-4,195
-103
643
-2,087
1987/88
Aus
Aman
Winter
Bora
1,035
4,400
2,768
0
3,127
3,034
0
0
2,346
2,296
803
479
1,249
0
0
4,530
567
5,138
1,965
-5,009
101
98
0
0
-1,575
3,060
1,965
-5,009
17,839
24,654
15,035
22,321
5,137
803
-10,893
1,566
1,995
642
1.977
2,905
65
2,667
Total
Standard
deviation
Source: Estimated by the authors.
Note:
The benchmark policy uses open market operations and imports to minimize the total cost of
food operations subject to price stabilization and foreign reserves constraints .
• The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApril; bora, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
- 71 -
Table 36-Variables in the benchmark policy with 30 percent increase in
world prices. 1985-88
Year/
Season/!
Price
Rice
b
Open Market
Stock
Wheat
Rice
OI;!erat; on SO
Wheat
(Tk/maund)
Rice
Wheat
Imgorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Boro
33.6
32.1
34.6
35.0
20.9
20.9
21.1
22.0
1.47
7.33
5.69
4.95
3.32
3.32
5.02
3.32
1.44
-6.80
0.93
O.l!
0.00
0.00
-4.23
0.00
0.00
0.00
0.00
0.00
0.8
4.48
0.00
0.00
36.0
35.3
38.8
37.2
22.6
22.2
22.4
23.0
1.47
2.25
1.47
3.52
3.32
3.32
3.32
3.32
3.27
-1.48
0.22
4.45
0.00
0.00
-3.57
0.00
0.82
0.00
0.00
6.82
2.79
5.57
0.00
2.28
37.7
37.2
37.7
35.2
22.7
22.6
22.5
22.5
3.94
7.42
6.85
1.47
3.32
3.32
5.26
3.32
-1.21
-4.63
-0.28
4.81
2.91
0.00
-4.22
0.00
0.00
0.00
0.00
0.00
8.32
6.54
0.00
0.00
35.9
22.1
3.99
3.62
0.07
-0.76
0.64
2.57
1.9
0.7
2.41
0.71
3.41
2.13
1.96
2.98
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
II
The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-
April; boro, May-June.
b Prices are deflated by the index of manufactured goods.
Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
C
- 72 -
Table 37-Costs in the benchmark policy with 30 percent increase in
world prices, 1985-88
Year/
Season-
Procurement
Cost
Imports
Ration
Open Market
Sales
Sales
Total
Cost b
(Tk million)
Foreign
Exchange
Cash
OutflowO
(US$ million) (Tk million)
1985/86
Au.
Aman
Winter
Bora
0
4,923
2,073
0
527
3,364
0
0
1,619
1,366
518
515
1,054
0
749
92
-2,145
6,921
807
-607
18
110
0
0
-2,636
3,787
807
-607
0
1,276
1,947
0
2,222
3,075
0
7,257
1,515
1,790
984
804
2,851
0
203
4,309
-2,144
2,561
760
2,144
73
100
0
234
-3,910
-216
760
-2,286
1.148
4,430
2,769
0
4,462
3,944
0
0
2,346
2,296
803
479
1.669
0
0
4,527
1,596
6,078
1,967
-5,006
144
127
0
0
-I. 785
3,090
1,967
-5,006
18,567
24,852
15,035
15,453
12,931
806
-6,035
1,679
2,285
642
1,628
3,219
74
2,615
1986/87
Au.
Aman
Winter
Bora
1987/88
Au.
Aman
Winter
Bora
Total
Standard
deviation
Source: Estimated by the authors.
• The seasons are defined as follows: aus, July-October; aman, November-February; winter. MarchApril; bora, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
- 73 -
Table 38-Variables in the benchmark policy when monetary offtakes are
eliminated, 1985-88
~riceb
Year/
Season'
Rice
Open Market
Stock
Wheat
Rice
Ol2erationsCl
Wheat
(Tk/maund)
Rice
Wheat
Imgorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.8
32.3
35.6
35.0
21.2
21.2
21.3
22.1
1.47
4.87
1.47
1.47
4.53
3.32
4.35
3.32
2.44
-3.73
3.10
8.53
0.00
0.00
-2.89
0.00
0.00
0.00
0.00
8.62
0.00
1.40
0.00
0.00
36.0
35.6
39.0
37.2
22.9
22.6
22.6
23.1
1.47
1.47
1.47
3.75
3.32
3.32
3.32
3.32
7.84
-0.10
1.12
5.38
0.00
0.00
-2.21
0.47
8.00
0.00
1. 29
7.75
0.87
3.06
0.00
1.57
37.7
37.2
37.8
35.2
22.7
22.9
22.5
22.6
4.55
7.24
7.12
1.47
3.32
3.32
4.65
3.32
-1.07
-2.96
-0.31
5.22
6.11
0.00
-2.84
0.00
0.00
0.00
0.00
0.00
7.98
3.82
0.00
0.00
36.0
22.3
3.15
3.62
2.12
-0.11
2.14
1.56
1.9
0.7
2.29
0.54
4.01
2.31
3.63
2.41
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Boro
Mean
Standard
deviation
Source: Estimated by the authors.
• The seasons are defined as follows:
aus, July-October; aman, November-February; winter, March-
April; bora. May-June.
b Prices are deflated by the index of manufactured goods.
o Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
- 74 -
Table 39-Costs in the· benchmark pol icy when monetary off takes are
eliminated, 1985-88
Year/
Season-
Procurement
Cost
Imports
Ration
Sales
Open Market
Sales
Tota'b
Cost
(Tk million)
1985/86
Aus
Aman
Winter
Bora
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Tota'
Standard
deviation
Foreign
Exchange
Cash
OutflowO
(US$ million) (Tk mi llion)
0
2,716
1,437
0
0
809
0
5,303
0
0
0
0
1,800
0
2,576
7,077
-1,800
3,525
-1,138
-1,774
0
26
0
175
-1,800
2,788
-1,138
-5,645
0
83
1,216
0
5,466
1,299
861
5,914
0
0
0
0
6,836
0
1.060
5,489
-1,370
1,382
1,017
425
180
42
28
191
-3,803
247
661
-2,329
1,016
2,835
1,987
0
3,291
1,773
0
0
0
0
0
0
3,516
0
0
4,913
791
4,608
1,987
-4,913
106
57
0
0
-1,464
3,394
1,987
-4,913
11,291
24,717
0
33,267
2,741
806
-12,016
1.054
2,220
0
2,61B
2,490
73
2,B03
Source: Estimated by the authors.
• The seasons are defined as follows: aus, July-October; aman, November-February; winter. MarchApril; boro, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
- 75 -
Table 4O-Variables in the approximation policy. 1985-88
Open Market
~r;ceb
Year!
Season ll
Rice
Stock
Wheat
Rice
OQerat ions
Wheat
(Tk/maund)
Rice
e
Wheat
ImQorts
Rice
Wheat
(kilograms/capita)
1985/86
Aus
Aman
Winter
Bora
33.3
31.9
34.9
34.6
20.6
20.7
20.8
21.6
1.15
6.06
5.73
2.93
5.20
1.35
3.88
3.73
2.58
-4.43
-0.08
2.39
1.81
0.64
-1.25
1. 92
0.12
0.09
0.14
0.00
4.42
1.39
2.78
3.08
36.7
36.1
37.9
36.5
22.6
22.3
22.0
22.5
0.45
4.31
4.82
4.14
4.57
0.27
1.65
2.14
1.86
-3.73
-0.41
2.18
1.55
0.75
-1.35
1.89
0.23
0.55
0.79
0.97
5.19
2.10
3.21
4.27
36.3
35.7
36.2
34.1
22.3
22.0
21.6
21.8
4.38
8.17
7.81
8.42
3.65
5.43
7.03
5.86
2.18
-2.89
-0.21
1.46
1.60
0.88
-1.16
1.77
2.90
1. 61
0.32
0.77
8.43
9.23
2.36
2.34
35.3
21.7
4.86
3.73
0.08
0.75
0.71
4.07
1.7
0.7
2.57
2.04
2.52
1. 29
0.83
2.47
1986/87
Aus
Aman
Winter
Bora
1987/88
Aus
Aman
Winter
Bora
Mean
Standard
deviation
Source: Estimated by the authors.
Note:
The approximating policy was computed by dOing stochastic simulat10ns of production shocks
and ordinary least squares over rice production, wheat production, and a lagged term.
The seasons are defined as follows: aus, July-October; aman, November-February; winter. MarchApril; bora, May-June.
b Prices are deflated by the index of manufactured goods.
C Positive open market operations have to be interpreted as open market sales; negative open market
operations have to be interpreted as domestic procurement.
II
- 76 -
Tabl e 41-Costs in the approximation policy, 1985-88
Procurement
Cost
Year/
Season-
Imports
Ration
Sales
Open Market
Sales
Total
Cost b
(Tk million)
1985/86
Aus
Aman
Winter
Bora
Foreign
Exchange
Cash
OutflowQ
(US$ mill ion) (Tk mi 11 ion)
0
3.187
673
0
2.308
862
1.682
1.673
1.619
1.366
518
515
2.695
298
0
2.955
-2.006
2.385
1.838
-1. 797
77
28
56
55
-4.095
1.611
321
-3.321
Bora
0
3.280
1.100
0
2.353
1.237
1.913
2.464
1.515
1.790
984
804
2.498
408
0
3.175
-1.660
2.319
2.029
-1.515
78
40
62
80
-3.651
1.396
600
-3.366
1987/88
Au'
Aman
Winter
Bora
0
2.659
852
0
5.720
5.765
1.452
2.120
2.346
2.296
803
479
2.902
498
0
2.362
472
5.630
1.501
-722
185
186
46
67
-2.636
2.218
624
-1.899
11,751
29.548
15.035
17,791
8.473
959
-12.195
1.254
1.535
642
1.305
2.228
50
2.253
1986/87
Au,
Aman
Winter
Total
Standard
deviation
Source: Estimated by the authors.
Note:
The approximating policy was computed by dOing stochastic simulations of production shocks
and ordinary least squares over rice production. wheat production, and a lagged term .
• The seasons are defined as follows: aus, July-October; aman, November-February; winter, MarchApril; bora, May-June.
b Total cost = procurement cost + import cost - ration sales - open market sales.
C Cash outflow = total cost - foreign exchange.
10.
CONCLUSIONS
The paper has presented a general approach to analyzing the
optimal stock problem for Bangladesh. The approach chosen is responsive
to the needs of a policymaker whose broad concern is to guarantee food
security and price stability at minimum cost.
A dynamic model of the foodgrain sector has been constructed,
taki ng into account the deci s ions of the pri vate sector regardi ng
consumption and private storage. A set of policies, characterized by
different objectives and constraints, have been defined and evaluated.
The summary statistics of the various policy options are given in
Tables 42 and 43. The main conclusions are as follows:
•
The higher the number of pol icy instruments available to the
government, the more effective the policy becomes in achieving the
objectives of price stabil ization, cost efficiency, and food
security. The policy instruments that have been analyzed in the
paper are open market sales, domestic procurement, and food
imports.
•
In order to keep the foodgrain distribution system going, imports,
especially of wheat, cannot be eliminated. At the same time, a
policy that would rely only on imports to stabilize prices would
not be as cost-effective as a policy that relied on an effective
management of open market operations (that is, domestic purchase
and sale).
•
The benchmark for optimal pol icy is given by a pol icy whose
objective is to minimize cost, subject to several constraints
including food security, price stabilization, and the reaction of
the pri vate sector.
The benchmark is characteri zed by its
flexibility in adapting to changes in both the domestic economy
(for example, production shocks) and in the world economy (for
example, world commodity prices). Fixed rules, such as price band
schemes, even if effective in reducing price variability, are not
likely to be cost-effective, and, vice versa, when they are cost
effective, they are not likely to stabilize prices.
•
Price stabilization around a target can be effectively achieved at
a relatively low cost in comparison with historical performance.
The main instruments to be used for this purpose are open market
operat ions and imports. In part i cul ar, open market ope rat ions
have to be used much more intensively than in the past.
Table 42--Summary of various policies
Policy
Variables
Rice price
Wheat price
Open market
sales
Base 1ineAvg
Std
323
198
19.7
8.1
44
b
Price Band
Avg
Std
306
192
13.4
6.3
52
Price Stabi1izat ione
Std
Avg
314
194
15.2
4.5
289
Approimation
to Price
Stab; lizationd
Std
Avg
316
194
15.2
6.3
216
.
Cost Mini-
mization
Std
Avg
Iml20rt Pol lei:'
Avg
Std
BenchmarkG
Avg
Std
334
201
313
194
322
198
22.4
9.0
135
16.1
6.3
17.0
6.3
221
44
Bencha30
Avg
Std
h
No ration i
Std
Avg
322
198
323
200
17.0
6.3
154
17.0
6.3
342
Open market
purchases
Rice stock
Wheat stock
R; ce imports
Wheat imports
0
398
677
72
415
159.1
279.5
84.7
251.9
114
646
806
72
415
152.0
318.2
84.7
251.9
220
467
661
72
415
282.5
372.3
84.7
251.9
132
496
380
72
415
262.1
208.1
84.7
251.9
33
161
525
72
415
39.8
128.5
84.7
251.9
0
508
339
145
358
246.8
0
251.9
193.8
216
355
369
144
255
232.6
72.4
278.5
291.7
224
407
369
65
262
245.8
72.4
199.9
304.0
137
321
369
218
159
233.6
55.1
370.3
245.8
Std
Total
Std
Total
Std
Total
Std
(Tk million)
Total
5td
Total
Std
Std
.....
Std
Total
std
Total
8,473 2,228
6,046
748
14,716 2,288
959
50
959
50
959
17,961 1,979 11.751 1,254
2,971
-12,276 3.769 -12,195 2,253 -14,622
50
430
1,149
Total
Total
Costs
Tota 1 cost
Foreign
17,045 1,274
19,632 1,366
exchange
959
50
6,380
489
-3,623 1.047
959
50
9,020 1,473
-1.036 1.634
Procurement
Cash outflow
8,392 3,682
5,137 2,905
1,083
63
803
65
0.00 0.00 17,839 1,566
-7,421 1.744 -10,893 2,667
12,931 3,219
2.741 2,490
806
74
806
73
18,567 1. 679 11,291 1. 054
-6,035 2,615 -12,016 2,803
Source: Computed by the authors.
Notes: Avg = average; Std = standard deviation.
Prices are in taka/maund. not deflated. Quantities are in 1,000 metric tons. Costs are in million taka .
• The baseline is obtained by simulating the foodgrain model for the period July 1985-June 1988.
b The price band is defined by a plus or minus 4 percent margin around the target price.
~ The optimal price stabilization policy uses open market operations to minimize the variance of rice prices around the target.
d The approximation to price stabilization was computed through stochastic simulations of production shocks and ordinary least squares over rice production.
wheat production. and a lagged term .
• The cost minimization policy uses open market operations to minimize the total cost of food operations.
f The import policy uses imports to minimize the variance of rice prices around the target.
g Benchmark refers to price stabilization cum cost minimization.
It uses open market operations and imports to minimize the total cost of food operations
subject to price stabilization and foreign reserves constraints.
h Bencha30 refers to the benchmark with a 30 percent increase in world prices.
i No ration refers to the benchmark when monetary off takes are eliminated.
(X)
- 79 -
Table 43-Average stock and total cost of various policies
Po 1icy
Average Total
Foodgrain Stock
lota 1 Costa
(1,000 metric tons)
(Tk million)
Base 1ineb
Price band c
Optimal price stabilizat;on d
Approximation to optimal
price stabilizat;on 8
Cost min imizat ion f
Import po 1icyQ
Benchmark: price stabilization
cum cost minim;zation h
No ration distribution i
1,075
1,452
1.128
17,045
19,632
8,392
876
686
847
8,473
6,046
14,716
724
5,137
2,741
690
Source: Computed from information in Table 42.
a Total cost = procurement cost + import cost - ration sales - open market sales.
The baseline is obtained by simulating the foodgra;n model for the period July 1985-June 1988.
C The price band ;s defined by a plus or minus 4 percent margin around the target price.
d The optimal price stabilization policy uses open market operations to minimize the variance of rice
prices around the target.
S The approximation to price stabilization was computed through stochastic simulations of production
shocks and ordinary least squares over rice production, wheat production, and a lagged term.
f The cost minimization policy uses open market operations to minimize the total cost of food
operations.
9 The imports policy uses imports to mi.nimize the Variance of rice prices around the target.
n Benchmark refers to price stabilization cum cost minimization. It uses open market operations and
imports to minimize the total cost of food operations subject to price stabilization and foreign
reserves constraints.
i No ration refers to the benchmark when monetary off takes are eliminated.
b
•
The attractiveness of fixed rules as compared with more complex
rules is deceiving, A price band, to be effective, may need as
much careful planning as a seemingly more complex rule involving
an optimization process. Nevertheless, the effort to simplify
must be pursued, In particular, what is still interesting is the
effort to approximate optimal poliCies with policies that are more
easily implementable and are of a feedback type, that is, they can
be formulated as a function of the current state of the system.
An attempt in this direction has been made in this report, and the
results seem promising,
•
The average foodgrain stock needed to support the optimal policy
pursued through both open market operations and imports is equal
to 724,000 tons, In the case of approximation policy, which has
also been considered in the report, the level goes up to 876,000
tons as a consequence of a lesser degree of flexibility allowed to
the policy instruments,
APPENDIX 1:
PROCUREMENT SUPPLY
The quantity actually procured by the government depends on the
capacity and willingness of the former to sell (Gulati and Sharma 1990).
The capac i ty to sell depends on the marketable surplus, whereas the
will ingness to sell depends on the differential between procurement
pri ces and open market pri ces. In order to study the procurement
supply, a simple model is introduced. For the sake of simplicity,
superscripts denoting grains will be dropped in the following
discussion.
At the beginning of each time period t, farmers are endowed with
an amount, qt' of foodgrains. They have to decide how much to sell to
the market, ~t'
at the market price, Pt' how much to sell to the
government procurement station, qPt' at price PPt' and how much to store,
xt+I ' The objective of farmers is to maximize expected profit, which is
given for a two-period problem by
(30)
where
o<p < 1
discount parameter,
Pt+l, t
c1
price at time t+l, expected to prevail as of time t,
c2
cost of bringing crops to the procurement station,
and
cost of storing stock.
The constraints faced by the farmers are that all the abovementioned quantities are non-negative and that they do not exceed the
initial amount owned by the farmer:
(31)
It is possible to derive a closed-form solution for this problem
if the cost funct ions c1 and c2 are taken to be convex in thei r
respective arguments. Namely,
(32)
c1(qPt) = fo + f1qpt + 2- 1 • f2qp~,
and
1
(33)
C2(X t+l ) = go + glx t +1 + 2- • g2X~+1'
- 82 -
where f and g2 are both positive.
It is ~ent
possible to express the solution for this problem as
foll ows:
Xt+l
=
max [0, -g/g2 + (,BPt+l.t - Pt)/g2], and
qPt = max [0, -f\/f2 + (pPt - pt)/f21,
(34)
(35)
where
In this formulation, procurement supply is positively related to
the difference between procurement price and market price.
It is conceivable that costs of adjustment must be paid in order
to change the amount supplied to the procurement station from period to
period, and also that the higher is the amount qt' the lower is the
procurement cost. In such a case, the cost function c1 can be expressed
as
c1 (qPt,qPt-l'qt) = q~a
• [fo + fl (qPt - 'YqPt-)
+ 2-1
•
f 2( qp t - 'Y qp t_l)21,
(36)
where a and 'Yare positive constants.
With this modification the procurement supply is
(37)
Now the amount procured is positively related to its lagged value,
to the difference between procurement price and market price, and to the
amount initially owned by farmers.
A procurement equation derived from the previous model has been
estimated in the following linear specification:
(38)
For both ri ce and wheat, procurement pri ces do not appear wi th a
significant coefficient (Table 44). This seems a bit surprising given
that the rationale for introducing procurement prices is to stimulate
procurement and support farmers' prices as a result. In Appendix 2 it
will be shown that, at least for rice, procurement has been effective in
sustaining prices, even though the level of support has been negligible.
Here the puzzle of why procurement prices did not stimulate procurement
- 83 -
supply, as one would expect a priori, has to be explained. A possible
interpretation for the limited significance of procurement prices
follows. Since procurement takes place through a system of 1icensed
dealers, rent-seeking behavior may generate a process whereby the level
of procurement prices does not become critically important. In any
case, profits could be made by altering the qual ity of rice, the
moisture content, and the quantities actually procured. However, it is
clear that when market prices increase, the incentives to sell to the
procurement station diminish, since the marketplace becomes more
attractive.
Table 44-Ordinary least squares estimation of rice and wheat
procurement supply
Variable
Coefficient
t-Statistic
0.8416
-10.4006
8.1230
0.5385
-2.7895
1.1644
5.2532
I. 2672
Rice
Constant
R
p,
PP:
R
0.0274
0.1363
q,
R
QPt-1
59
0.5215
0.9697
N
R'
SEE
Wheat
Constant
P':'
p~
w
q,
qp~l
-0.1749
-2.7553
4.1656
-0.4626
-1.8274
0.0461
0.2478
5.2330
2.2205
59
0.4512
0.2603
N
R'
SEE
Source: Estimated by the authors.
Definitions of terms:
p~
price of grain; at time t;
procurement price of grain i at time t;
p~
i
production of grain i at time t;
q,
i
QPt-1
SEE
quantity of grain procured at time t-l; and
standard error of estimation.
I. 6868
APPENDIX 2: HAS PROCUREMENT BEEN EFFECTIVE AT SUPPORTING PRICES?
To answer this question a simultaneous system is needed where the
decisions of the private sector related to consumption and storage are
combined with the response to the government activities involving
procurement supply and demand for monetary offtakes.
Procurement supply has been modeled in Appendix 1. To model the
demand for monetary offtakes (net of open market sales), a distinction
in the public distribution system has to be made between channels aimed
at poverty alleviation, and those that target relatively high income
groups. All of these latter channels have been lumped together in the
monetary off takes category. Since individuals in this group have the
option of drawing their quota at the ration price, a model of demand for
rationed distribution can be postulated as follows:
(39)
where pr; refers to the ration price of grain i at time r. When the
di fference between market pri ce and rati on pri ce decreases, monetary
off takes are also expected to decrease.
Putting together equation (39) with the equations for prices,
procurement supply, stocks, and marketable supply, the following
foodgrain system is obtained:
(40)
(41)
(42)
(43)
i
stock, =
.
i i i
cS ' stock,_l + m, + qp,
_ i
ms,
i i i
- mof, - nmof, - oms"
i i i
q,
+
nmof,
+
oms,.
and
(44)
(45)
- 85 -
The results in Table 45 show that the coefficient of rice procurement is
statistically significant in the price equation. Nevertheless, as was
seen in Appendix 1, procurement prices did not show any significant
effect on the quant ity actually procured. For wheat procurement, as
well as for wheat offtakes, it seems that their effect on price is
perverse. A possible interpretation of this perverse effect is that the
positive effect of procurement on prices is nullified by the
contemporaneous public distribution of wheat in the same areas where
most of wheat production takes place.
On the other hand, rice ration prices are a significant instrument
for controll ing the total amount of offtakes. In the case of wheat,
monetary off takes are not affected by ration prices, but by market
prices. Nevertheless, the predictive power of the off takes equation is
too low to be used with any reliability in the simulation of policy
exercises (see Figures lOe and lOf).
Table 45-fhree-stage 1east squares estimation of foodgrain system with
public food distribution
Variable
Coefficient
t-Stat;stic
Variable
Rice lead price equation
Constant
stock~
m,I
losses t
y,
N
R'
SEE
-0.0593
-0.0097
-0.0047
0.0022
0.0628
-0.9303
-5.1157
-1.517
3.2626
6.7155
P:'1
~+1P
p';'
ms~
mof~
qp~
y,
N
R'
SEE
Constant
stock";'
m,w
losses t
0.3726
1. 2418
-0.0012
-0.0102
0.0178
-0.0273
59
0.7973
0.0225
-0.0542
-0.0052
-0.0016
0.0005
y,
0.0428
N
59
0.4789
0.0198
59
0.59
0.03
0.0807
0.2981
t-statistic
Wheat lead price equation
R'
SEE
-1.3078
-4.7093
-1.9719
0.9579
6.7673
Wheat price equation
Rice price equation
Constant
Coefficient
1. 2105
4.4211
3.781
4.9768
-8.0873
-1.313
4.3942
-2.3025
Constant
w
Pt-1
P~+1
p~
ms";'
mo{";"
qp,w
y,
N
R'
SEE
-0.044
-0.0152
-1.5183
-0.2636
0.4016
0.2211
0.0009
0.0108
-0.0243
0.011
3.7353
3.132
1. 6571
5.8335
-2.7853
2.1681
59
0.7259
0.0146
(continued)
- 86 -
Table 45-Continued
Coefficient
Variab 1.
t-Statistic
Variab 1e
-0.6918
-0.8692
0.9443
6.361
1. 5733
Constant
Rice procurement supply
-0.9602
-3.7084
6.2543
0.0311
0.1428
Constant
R
Pt
R
PPt
R
qt
R
qPH
R'
SEE
-0.5399
1. 5748
-11.3929
0.5798
0.2401
P~
R
prt
Yt
mof~1
R'
SEE
p~
q';'
qp7.,
R'
SEE
-0.2682
0.7632
-4.1771
1.5468
2.2724
59
0.4584
0.56
N
P';'
N
Rice demand for monetary off takes
Constant
Constant
P';'
pr";'
Yt
mof;:,
N
R'
SEE
Definitions of terms:
I
q:
qp~
p~
rp ~
Yt
mof~
nmof~
oms~
nfs~
m~
stock~
losses t
SEE
0.1383
-0.9889
0.5059
0.0475
0.2816
0.4115
-0.615
0.2445
5.8107
3.4151
59
0.4259
0.2547
Wheat demand for monetary off takes
Source: Estimated by the authors.
Pt
t-statistic
Wheat procurement supply
59
0.4732
0.9733
N
Coefficient
price of grain i at time t;
production of grain; at time t;
quantity of grain i procured at time t;
procurement price of grain i at time t;
ration price of grain i at time t;
income at time t;
monetary off takes of grain i at time t;
nonmonetary off takes of grain i at time t;
open market sales of grain; at time t;
q~ + nmof! + oms~;
import of grain; at time t;
stock of grain i at beginning of time t;
rice losses at time t; and
standard error of estimation.
2.4591
38.0694
-1.7188
-1. 2517
0.241
59
0.3734
1. 0734
0.7412
5.564
-0.9494
-2.2331
2.6141
APPENDIX 3:
DERIVATION OF STORAGE EQUATION
The agents responsible for private storage are assumed to be riskneutral and profi t-maximi zi ng.
That is, they sol ve the foll owi ng
problem:
max ~
•
L fJ'-t [p,( ,=t
xT +1 + x,) - c(x,+d],
subject to
where
stock demanded by the end of period T,
price of the grain,
storage cost associated with stock X,+I' and
expectation operator, based on information available at
time t.
For simplicity of notation, the superscript referring to the grain is
omitted.
Assumi ng the storage cost funct i on to be quadratic in the 1eve 1 of
stocks, that is,
(46)
and assuming rational expectations (Wickens 1982; Ravallion 1985;
Goletti 1990), so that where c,+1 is the expectational error and I, is
the information available at time T, it follows that
(47)
with
E[c7+11 I,]
=
0, and
- 88 -
(48)
where g is a linear function of its arguments.
T~us,
putting equation (48) together with the express i on for
consumption contained in equation (7) and the equilibrium condition in
equation (6), it is possible to derive a price equation that can be
estimated in the form
(49)
where
fl!
msir
the marketable supply of grain
Yr
the income at time
1
71 r
a linear function,
1,
at time
1,
and
the error term.
Note that in th~
latter equation the error term is bound to be
correlated with p~+1'
.
To avoid correlation between the er~o
term 71; and the price p;+!,
an instrumental variable estimation for pl+! has been ~sed.
Therefore,
denoting by
the set of instrumental variables for p;+!, the following
simultanous system is readily obtainable:
a;
(50)
(51)
where the 71'S denote error terms.
APPENDIX 4: NATURE AND SOURCES OF THE DATA
The organi zat i on of the data in thi s paper draws heavily from
Shahabuddin (1990). The data related to the monthly distribution by
categories under the public food distribution system were collected from
the Food Planning and Monitoring Unit, Ministry of Food, for the period
1972/73-1987/88.
Those data were converted into seasonal fi gures
corresponding to the different seasons: Season 1, July-October; Season
2, November-February; Season 3, March-April; and Season 4, May-June.
This way of defining the seasons tries to match the ideal basis
for defining the seasons with the presentation of the results by fiscal
year (see also Shahabuddin 1990). The procurement and ration prices for
both rice and wheat, with the effective dates for the different periods,
were collected from the Bangl adesh Bureau of Stat i st i cs Stat i sti ca I
Yearbooks, and from Food Situation Reports published by the Food
Planning and Monitoring Unit. These were distributed over the different
seasons using the effective dates for each price. Data on the monthly
price of rice (coarse, wholesale variety) were compiled from the
Directorate of Marketing, Government of Bangladesh. All these nominal
prices were deflated by the index of prices of manufactured consumer
goods to convert them into real prices.
Data on foodgrain production, both r.ice and wheat, as well as
income (GNP at constant 1972/73 prices) were available from the
Bangladesh Bureau of Statistics Statistical Yearbooks annually by fiscal
year (July to June). These data were converted into seasonal figures by
the following procedure.
Estimates of the quantities of rice harvested each month were
derived on the basis of the historical percentages of crops harvested
each month in the World Bank (1979) study on food pol icy issues in
Bangladesh.
The following monthly percentages for the three rice crops, aus,
aman, and boro, and for wheat have been used.
July:
August:
September:
October:
November:
December:
35 percent of aus
55 percent of aus
10 percent of aus
3 percent of aman
50 percent of aman
42 percent of aman
January:
February:
March:
April :
May:
June:
5 percent of aman
no harvest
55 percent of wheat
45 percent of wheat
and 10 percent of boro
65 percent boro
25 percent of boro
- 90 -
These monthly percentages were then applied to the yearly
production of aus, aman, and boro rice, and to wheat as published in the
Bangladesh Bureau of Statistics Statistical Yearbooks to derive
estimates of the rice harvested by each month, which were then
distributed over different seasons as defined earlier.
These monthly percentages of crops harvested provide the following
seasonal shares (as defined in this paper) for the different rice crops
harvested in Bangladesh: Season 1, 100 percent of aus and 3 percent of
aman; Season 2, 97 percent of aman; Season 3, 10 percent of boro and 100
percent of wheat; and Season 4, 90 percent of boro.
The annual figures on GNP (at constant 1972/73 prices) collected
from the Bangladesh Bureau of Stati st i cs Statist i ca I Yearbooks were
distributed over different seasons by taking the average real GNP per
capita for every season.
APPENDIX 5:
FOOD BUDGET
From a broad, public finance perspective, it is important to
accurately assess the aggregate cash deficit on the food account, which
is simply the difference between cash revenues and cash expenditures.
Cash savings can be used for financing development planning. It is only
recently that the government of Bangladesh has started to rearrange the
food budget in such a way that it is possible to identify the annual
budgetary impact of food operations and integrate it into the
consolidated public account.
From an efficiency point of view, the food-security objectives of
the government should be pursued, keeping in mind minimization of the
total cost of food operations. To measure the total cost, cash revenues
have to be subtracted from cash expenditures.
For the foodgra in
operations, the following definitions have been used:
Cash Expenditures
Procurement Cost + Value of Imports
Cash Revenues
Revenues from Open Market Sales and
Ration Distribution
Total Cost
Cash Expenditures - Cash Revenues
Cash Outflow
Cash Expenditures - Cash Revenues - Value
of Food Aid
Using the notation previously introduced,
Cash Expenditures(1)
=
Z; wop~
• m~
+ p~
qp~,
and
Cash Revenues(1)
In the definition of cost adopted here, administrative costs are not
included; similarly, other type of costs, such as those related to
storage, losses, and pi lferage, are not taken into account. Yet thi s
first attempt at looking at the structure of the food budget is still
useful to give a first rough idea of the behavior of some of the budget
components (see Tables 46 and 47).
- 92 -
Table 46-Food9rain nominal costs, 1976-89
Open
Year
Procurement Import
Cost'
Cost b
lata 1
ExpenditureC
Market
Sa les d
Revenue'
Cost"
Food
Aid"
Outflowl
2,447
3,348
3,352
4,687
3,936
5,405
6,034
6,194
7,248
4,403
6,857
7,572
8,493
9,150
581
2,348
536
6,590
4,382
873
2,947
4,403
6,949
4,392
2,392
10,289
9,296
10,329
1,531
2,692
2,565
3,906
2,467
4,012
4,127
6,452
5,759
5,949
6,131
8,557
9,738
6,162
-950
-344
-2,029
2,684
1.915
-3,139
-1,180
-2,049
1.190
-1.558
-3,739
1. 732
-442
4,166
Total
Rat 10n
Sa les'
Cash
(Tk mill ion)
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Sources:
1,039
1.960
1,206
1,406
4,513
1,447
1,021
1,358
1,812
2,219
1,349
2,829
3,336
8,500
1,989
3,736
2,682
9,871
3,805
4,832
7,960
9,238
12,385
6,577
7,899
15,032
14,452
10,979
3,028
5,696
3,888
11,277
8,318
6,279
8,981
10,597
14,197
8,795
9,248
17,861
17,788
19,479
0
0
0
370
0
348
719
852
1,117
391
1,763
1,652
2,135
1,320
2,447
3,348
3,352
4,317
3,936
5,057
5,314
5,342
6,131
4,012
5,094
5,920
6,357
7,831
Based on unpublished data from Bangladesh Ministry of Food; authors' calculations.
• Procurement cost ;s obtained by taking procurement prices times procurement quantities.
Import cost 1s computed at world prices converted 1n domestic currency.
C Expenditure = procurement cost + import cost.
d Open market sales (OMS) revenues are computed by taking OMS prices times OMS quant it ies .
• Ration sales are computed by taking ration prices times monetary off takes.
, Revenue = OMS revenue + rat ion sa les.
g Cost = expenditures - revenues.
h Food aid is computed from total imports. subtracting the commercial imports.
I Cash outflow = cost - food aid.
b
- 93 -
Table 47-Foodgrain deflated costs, 1976-89
Open
Procurement
Year
Costa
Import
Cost b
Total
ExpenditureO
Market Ration
Sa lesd
Sales'
Revenue f
Total
CostQ
Food
Aidh
Cash
Outflow'
136
495
115
1145
680
123
382
588
876
518
266
1113
953
959
357
567
552
679
383
563
535
862
726
701
681
926
999
572
-222
-73
-436
466
297
-441
-153
-274
150
-184
-415
187
-45
387
(Tk mi 11 ion)
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
243
413
259
244
700
203
132
181
228
262
150
306
342
789
464
787
577
1715
590
679
1032
1234
1561
775
877
1626
1482
1019
707
1200
836
1960
1290
882
1164
1415
1789
1037
1027
1932
1825
1808
0
0
0
64
0
49
93
114
141
46
196
179
219
123
571
705
721
750
610
710
689
713
773
473
566
640
652
727
571
705
721
815
611
759
782
827
913
519
762
819
871
850
Sources:
Based on unpublished data from Bangladesh Ministry of
Note:
The deflator used is the index of manufactured goods.
Food; authors'
calculations.
• Procurement cost 1s obtained by taking procurement prices times procurement quantities.
b Import cost ;s computed at world prices converted in domestic currency.
o Expenditure = procurement cost + import cost.
d Open market sales (OMS) revenues are computed by taking OMS prices times OMS quantities .
• Ration sales are computed by taking ration prices times monetary off takes.
f Revenue = OMS revenue + ration sales.
g Cost = expenditures - revenues.
h Food a1d is computed from total imports, subtracting the commercial imports.
I Cash outflow = cost - food aid.
APPENDIX 6:
THE MODEL FOR THE BENCHMARK POLICY
As formally expressed below, the benchmark policy, price
stabilization cum cost minimization, consists of choosing a path for
imports, open market sales, and open market purchases of both rice and
wheat to minimize the cost of food operations:
T
min
L L
r=t
..
p'-t[wo~m
i
1;
;
1
1
PromPT - Proms, - pr,mof,]'
+
; =r,W
subject to equation (51):
P~+l
f~(a,TJ.)
and
(52)
where
_;
ms,
=
i
q,
.
stock~
+
;
6' stock,_l
+
;
stock~
I P~ -
r,w and
1
(53)
; m;
PT' T
t, ... ,T.
(54)
G~;n'
(55)
~
G~ax'
(56)
m;,
0T
FT,
~
(57)
;
'Y
~
~
;
- omp,),
~
Z; wop~
omp;,
;
mT - offtakes, - (oms~
stock~
where
;
i
;
offtakes, - (oms, - omPT) ,
(58)
qT'
I
~
0,
0.04
. 0"
and
(59)
(60)
- 95 -
These choices are subject to the constraints given by the dynamic
system of the foodgrain private sector (equations [51]-[54]); minimum
stock requirements to guarantee the flow of stock operations
(deadstocks) and food security (equation [55]); capacity constraints of
maximum stocks (equation [56]); foreign exchange constraints (equation
[57]); constraints on maximum domestic procurement (equation [58]);
constraints on price variabil ity (equation [59]); and non-negativity
constraints (equation [60]).
The parameters used in the model are
G~ax
7.65, corresponding to 805,000 metric tons;
G~ax
11.09, corresponding to 1,168,000 metric tons;
G~in
=
G: in
1.47, corresponding to 155,000 metric tons;
3.32, corresponding to 350,000 metric tons;
'Y
0.5;
Ii
0.94; and
Fr
la, corresponding to US$956 million.
APPENDIX 7: APPROXIMATION POLICIES
If x* is the optimal solution of a policy problem such as the one
described In equations (51)-(60) in Append\x 6, the problem becomes the
need to fi nd a path x' that approximates x. In part i cul ar, one woul d
1ike to have a feedback pol icy, express edT as a function of the state
variables, that behaves "similarly" to the optimal policy. An appealing
approximation would be a linear rule, for its simplicity in calculation.
This linear approximation can be expressed as a function of a subset rT
of the set of state vari abl es z. The vari abl es in r shoul d be
considered particularly useful to lonvey information upon which an open
market operations mechanism can be based. For example, these variables
could be production, losses, rainfall, imports, and lagged endogenous
variables. Nevertheless, in trying to get a linear feedback rule, the
possibility that some inequality constraints may be binding has to be
taken into account. Therefore, a truncated version of a linear rule is
more likely to be the case.
Using the notation of the general approach of Chapter 3, the
control variables, xT ' have to satisfy the law of motion,
ZT+I = AT
and the inequality constraints,
IT 5
.
Z1
+ 81
•
xr '
5 uT'
Then the approximating policy rule is given by
L • rT
x'T = B+T
(1HI - AT
B+
( uT+I - AT
ZT)
ZT
if 1HI < AT
ZT
+ BT
AT
if 1HI >
-
ZT
+ BT
LrT < uT+l' (61)
(62)
LrT' and
(63)
LrT,
if UHI 5 AT ZT + BT
where B+ is the generalized inverse of B.
The matrix L is obtained by performing a stochastic simulation of
exogenous variables in r and computing the optimal policy numerically.
Then the coefficients of a regression of this numerical solution over
the variable in r give the vector L. Equations (62) and (63) define a
to take into account the inequality constraints.
truncated linear ~ule
T
ZT)
GLOSSARY
1
d,i
ms;,
~q
mof,i
nmof~
oms;,
omp;,
omo;,
qp~
C,i
;
xH !
Il.X~+!
P~
y,
i
PH!"
stock~
losses,
oftakes~
poms~
pr~
WOpi,
denotes grain; it can be either rice (r) or wheat (w)
denotes time; 1 = t, ..• , T
demand for grain i at time 1
marketable supply of grain at time 1
production of grain i at time 1
monetary offtakes of grain i at time 1, net of open market
sales
nonmonetary offtakes of grain i at time 1
open market sales of grain i at time 1
open market purchases of grain i at time 1
open market operations of grain i at time 1
omo;, = oms,i - ompi,
quantity of grain i procured at time 1
is the consumption of grain i as of time 1
ending period private stock of grain i as of time 1
refers to vari at i on, such as Il.X~
= X~+!
- X~
price of grain i at time 1
income at time 1
the price of grain i expected to prevail at time 1+1, based
on the information available at time 1
stock of grain i at beginning of time 1
rice losses at time 1.
ration.distribution and nonmonetary off takes (that is, mof;
+ nmof;) of grain i at time 1
oms price of grain i at ·time 1
ration price of grain i at time 1
world price of grain i at time 1
import of grain i at time 1
BIBLIOGRAPHY
Abbott, P. C. 1988. A methodology for evaluating national grain
stockpiling strategies. Food and Agriculture Organization of the
United Nations, Rome. Mimeo.
Abdullah, A. A. 1989a. Fertilizer pricing and distribution policy, in
Bangladesh Sector Review, compendium volume IV, sponsored by
United Nations Development Programme, March 1989.
1989b.
Foodgrain pnclng policy:
procurement, sales,
imports, and public stocks, in Bangladesh Sector Review,
compendi urn volume iv, sponsored by United Nat ions Development
Programme, March 1989.
Ahmed, Raisuddin.
1981. Agricultural price policies under complex
soci oeconomi c and natura I constraints: The case of Bangl adesh.
Research Report 27. Washington, D.C.: International Food Policy
Research Institute.
. 1990. An outl ine for determining procurement price of
Internat i ona 1 Food Pol icy Research
---'f;:"""oograi ns in Bangl adesh.
Institute, Washington, D.C. Mimeo.
Ahmed, Raisuddin, and Andrew Bernard. 1989. Rice price fluctuation and
an approach to price stabilization in Bangladesh. Research Report
72. Washington, D.C.: International Food Policy Research
Institute.
Alamgir, M. 1980. Famine in South-Asia: Political economy of mass
starvation in Bangladesh. Cambridge, Mass., U.S.A.: Cambridge
University Press.
- 99 -
Bangladesh Bureau of Statistics.
Dhaka: BBS.
Various dates.
1990.
Statistical yearbook 1989.
Monthly statistical bulletin.
Dhaka:
BBS.
Bigman, David.
1985.
Food policies and food security under
instability: Modelling and analysis. Lexington, Mass., U.S.A.:
Lexington Books.
Bouis, Howarth E. 1989. Prospects for rice supply/demand balances in
As i a.
Fi na 1 report submi tted to the Rockefell er Foundation.
International Food Policy Research Institute, Washington, D.C.
Mimeo.
Brooke, A., D. Kendrick, and A. Meeraus. 1988. GAMS: A user's guide.
Redwood City, Calif., U.S.A.: The Scientific Press.
Buiter, Willem H. 1981. The superiority of contingent rules over fixed
rules in models with rational expectations. Economic Journal 91
(September): 647-670.
Chow, G. C. 1975. Analysis and control of dynamic economic systems.
New York: Wiley.
1981.
Wil ey.
Econometric analysis by control methods.
New York:
Chowdhury, Nuimuddin.
1987.
Seasonal ity of foodgrain price and
procurement program in Bangladesh since liberalization:
An
explanatory study. The Bangladesh Development Studies 15 (March):
105-128.
. 1988.
Where the poor come last: The case of modified
------r-ationing in Bangladesh. The Bangladesh Development Studies 16
(March): 27-54.
- 100 -
____ . 1990. Optimal foodgrain stock for Bangladesh: Policy issues
and some evidence. Bangladesh Ministry of Food, International
Food Policy Research Institute, and Bangladesh Institute of
Development Studies, Dhaka. Mimeo.
Cochrane, Willard. W. 1980. Some nonconformist thoughts on welfare
economics and commodity stabilization policy. American Journal of
Agricultural Economics 62 (August): 508-511.
Crow, Ben, and K. A. S. Murshid. 1989. The finance of forced and free
markets: Merchants' capital in the Bangladesh grain trade. DPP
Working Paper 18. Milton Keynes, England: Open University.
Farruk, Muhammad Osman. 1970. The structure and performance of the
rice marketing system in East Pakistan. Occasional Paper 31.
Ithaca, N.Y., U.S.A.: Cornell University, Department of
Agricultural Economics.
Foster, James, Joel Greer, and Erik Thorbecke. 1984. A class of
decomposable poverty measures. Econometrica 52 (May): 761-766.
Gardner, Bruce L. 1979. Optimal stockpiling of grain.
Mass., U.S.A.: Lexington Books.
Lexington,
Ghosh, S., C. L. Gilbert and A. J. Hughes Hallett. 1987. Stabilizing
speculative commodity markets. Oxford: Clarendon Press.
Goletti, Francesco. 1990. Speculative activity in rice markets in
Bangladesh.
International Food Policy Research Institute,
Washington, D.C. Mimeo.
Goletti, Francesco, and Raisuddin Ahmed.
1991.
Food grains in
Bangladesh.
Past trends and projections to year 2000.
International Food Policy Research Institute, Washington, D.C.
Mimeo.
- 101 -
Gulati, Ashok, and Pradeep K. Sharma 1990. Prices, procurement and
product ion:
An anal ys is of wheat and ri ce.
Economi c and
Political Weekly, March 31, 1990.
Gustafson, R. L.
1958.
Carryover levels for grains: A method for
determining amounts that are optimal under specified conditions.
U.S. Department of Agriculture Technical
Bulletin 1178,
Washington, D.C.
Krishna, Raj, and Ajay Chhibber. 1983. Policy modeling of a dual grain
market:
The case of wheat in India.
Research Report 38.
Washington, D.C.: International Food Policy Research Institute.
Kydland, Finn E., and Edward C. Prescott. 1977. Rules rather than
discretion:
The inconsistency of optimal plans.
Journal of
Political Economy 85 (June): 473-491.
1987. The food marketing system: The relevance of
Ladd, George W.
economic efficiency measures. A discussion.
In Economic
efficiency in agricultural and food marketing, ed. R.L. Kilmer and
Ames, Iowa, U.S.A.:
Iowa University
W.J. Armbruster, 32-36.
Press.
.
Massell, Benton F. 1969. Price stabilization and welfare.
Journal of Economics 83 (May): 284-298.
Nerlove, Marc.
1979.
Quarterly
The dynamics of supply: Retrospect and prospect.
American Journal of Agricultural Economics 61 (December):874-888.
Newbery, David M. G. and Joseph E. Stiglitz.
1981. The theory of
commodity price stabilization: A study in the economics of risk.
Oxford: Oxford University Press.
Osmani, S. R. 1987. The food problem of Bangladesh. WIDER Working
Paper 29. Hel s inki : Worl d lnst itute for Development Economi cs
Research of the United Nations University.
- 102 -
Pinckney, Thomas C. 1988. Storage, trade, and price policy under
production instability: Maize in Kenya. Research Report 71.
Washington, D.C.: International Food Policy Research Institute.
. 1989. The demand for public storage of wheat in Pakistan.
---;R=-esearch Report 77. Washington D.C.: International Food Pol icy
Research Institute.
Rahman, A., M. S. Haque, and M. Ahmad. 1984. Production, procurement
and agricultural price policy in Bangladesh. Dhaka: Centre for
Integrated Rural Development for Asia and the Pacific, Institute
of Business Administration.
Ravallion, Martin. 1985. The performance of rice markets in Bangladesh
during the 1974 famine. The Economic Journal 95 (March): 15-29.
1987.
Press.
Markets and famines.
New York:
Oxford University
Scandizzo, Pasquale L., and Col in Bruce. 1980. Methodologies for
measuring agricultural price intervention effects. World Bank
Staff Working Paper 394. Washington, D.C.: International Bank
for Reconstruction and Development.
Scandizzo, Pasquale L., and Odin K. Knudsen. 1981. The evaluation of
American Journal of
the benefits of basic needs pol icies.
Agricultural Economics 62 (February): 46-57.
Scandizzo, Pasquale L., Peter Hazell, and Jock Anderson. 1984. Risky
agri cu ltura I markets.
Boul der and London: Westv'j ew Repl i ca
Edition.
Sen, Amartya K. 1981. Poverty and famines: An essay on entitlement and
depri vat i on.
Oxford: Clarendon Press and Oxford Uni vers i ty
Press.
- 103 -
Shahabuddin, Quazi. 1987. Factors affecting stocking decisions of rice
traders in Dhaka City: Findings of a sample survey. Bangladesh
Journal of Agricultural Economics 10 (June): 51-62.
_ _----;;-. 1990. Report on a disaggregated model for the stabil ization
Washington, D.C.:
of the prices of rice in Bangladesh.
International Food Policy Research Institute. Mimeo.
Turnovsky, Stephen J. 1974. Price expectations and the welfare gains
from price stabilization.
American Journal of Agricultural
Economics 56 (4): 706-716.
USAID (United States Agency for International Development).
1988.
PL480, Title III: Bangladesh Food for Development Program, Annual
evaluation for FY 1988. Washington, D.C.: USAID.
__-"._. 1989. PL480, Title III: Bangladesh Food for Development
Program, Annual Evaluation for FY 1989. Washington, D.C.: USAID.
Waugh, F. V. 1944. Does the consumer benefit from price instability?
Quarterly Journal of Economics 58 (August): 602-614.
Wickens, M. R. 1982. The efficient estimation of econometric models
with rational expectations. Review of Economic Studies 59 (1):
55-67.
Worl d Bank. 1979.
World Bank.
Bangl adesh food po Ii cy issues.
Washi ngton, D. C:
1989. Bangladesh: Recent economic developments and shortterm prospects. Report No. 7596-BD. Washington, D.C.: World
Bank.
__--=-.
1990. Managing the adjustment process: An appraisal.
Report No. 8344-BD. Washington, D.C.: World Bank.
IFPRI
1776 MASSACHUSETTS AVENUE, N.W.• WASHINGTON, D.C. 20036. U.S.A.
1-202/862-5600 • FAX. 1-202/467-4439 • CABLE IFPRI • TELEX: 440054