Key Words: Price band stabilization; Private storage; Food subsidy; Multimarket equi- librium; India.
1. INTRODUCTION
Price support and stabilization schemes form an important ele- ment of domestic agricultural policy in many countries. In India, with agricultural output continuing to depend heavily on mon- soons, the government's price support policies play an important role in stabilizing the prices and output of foodgrains and income to farmers. Although there has not been a pre specified ceiling price, the government has kept the foodgrain prices from reaching exorbitant levels through buffer stock policies and tried to protect the consumption of the poor through distribution of grains at subsidized prices. The question that arises in the current debate
Address correspondence to Dr. Shikha Jha, lndira Gandhi Institute of Development Research, General A. Vaidya Marg, Goregaon (East), Bombay 400 065, India.
This is a revised version of the paper presented at the 1993 Far Eastern meeting of the Econometric Society, Taipei, Taiwan, June 25-27. We would like to thank the participants at that conference for providing helpful suggestions. We would also like to thank Professor Kirit Parikh for his comments. Any remaining errors and deficiencies should be attributed only to us.
Received October 1, 1995; final draft accepted March 1, 1996.
on agricultural reforms is whether such interventions are cost effective and if not, can better alternatives be found? We, there- fore, analyze in this paper using a dynamic simulation model as to what effects can private storage and subsidized food distribution have on price stabilization and as to how these elements influence the effects of government 's price stabilization policies. For this purpose, we use a multi commodity market equilibrium framework with three types of foodgrains viz. rice, wheat and coarse cereals.
The desirability of price stabilization and its effects on producer/ consumer welfare has been discussed in several analytical studies leg, Newbery and Stiglitz (1981)]. In our study we proceed on the assumption that price stabilization is a desired objective of the government and obtain the implications of price band policy for the stabilization of prices, producer revenue and consumption of grains as well as the associated fiscal cost to the government. One of the main issues addressed in this study is the relationship between band width, price variability and government costs and the effect of private storage on this relationship. For example, low band width would lead to low price variability and this could reduce private stocks which in turn could increase the cost of government storage. We also study as to how the results depend on other policy instruments of the government such as the procure- ment and public distribution schemes since these would affect both the supply and the demand behavior. What would be the consequences if the government did not undertake the price stabi- lization policy? Will private storage alone lead to adequate price stabilization? How would different agents be affected in such a situation? These are some of the questions addressed below.
It is a well-noted fact that a price band policy, the policy of keeping market prices between a ceiling and a support price, is much simpler to administer than optimal stock policies derived from optimization exercises. In general, derivation of operating rules for buffer stocks depends on the specification of objectives and the identification of the information set available to the gov- ernment. Rules based on market prices are more desirable than those based on outputs because the intervention authority usually has poor information on current output and even less on the size of private stockholding. The band width rule depends mainly on market price and hence there is no informational problem in operating this rule. 1
t The problem, however, with this rule is that it is myopic and takes no note of future expected prices. There is also the problem of choosing an appropriate price band.
FOODGRAIN PRICE STABILIZATION 589
Most of the existing studies have analyzed the effects of price band policies in the case of a single market. For example, Miranda and Helmberger (1988) have studied the stabilization effects in the U.S. soybean market taking into account private storage be- havior of risk-neutral competitive agents having rational expecta- tions of next year's price. The advantage with a multi commodity equilibrium framework is that it takes into account the simultane- ity in the determination of equilibrium prices in different markets and allows the study of effects of stabilizing one market on the prices in the other markets.
The plan of this paper is as follows. In the next section, we describe the model and the computational procedure used in our simulation exercises. Detailed description of the different simula- tions conducted under different scenarios is given in Section 3. In Section 4, we analyze the behavior of private and public stocks under different scenarios and the effects of private storage and distribution policy on price stability, consumption levels, govern- ment costs, and producer incentives. The relative benefits accruing to different agents is also discussed here. The policy implications that can be drawn based on our results are discussed in Section 5.
2. DESCRIPTION OF THE MODEL
The model used to analyze the government's price band policies takes into account (1) consumption patterns given by the aggregate demand equations for foodgrains, (2) the supply response to prices of individual grains as depicted by the aggregate supply equations, and (3) the private storage activity undertaken by risk neutral, competitive agents who maximize expected profit. Buffer stocking is treated as an integral part of the government's foodgrain policy which includes part procurement of foodgrains output at pre- determined procurement prices and distribution of subsidized foodgrains to consumers through the Public Distribution System (PDS). For a more elaborate discussion of the Indian foodgrain policy see, for instance, Jha (1995).
2A. Variables
2A-1. CONSUMPTION. The total demand for each type of cereal is made to depend on the amount supplied through the PDS apart from prices and income. This is done by redefining total income
590 S. Jha and P. V. Srinivasan
to include the subsidy derived from the consumption of cereals through PDS at a price lower than the free market price.
2A-2. PRODUCTION. Producers' supply response is assumed to depend on lagged weighted average of the procurement and free market prices and on current variables such as irrigation and rainfall. The estimated demand and supply equations for the three types of cereals considered here are available in Jha and Srinivasan (1994).
2A-3. PUBLIC DISTRIBUTION SYSTEM. In order to protect the poor who suffer the most due to price increases, the government distributes a fixed quota per consumer of foodgrains at conces- sional prices through the PDS. The foodgrain requirements of the PDS are met mostly from the quantities procured and the balance is met through imports, free market purchases, or depletion of government stocks.
2A-4. PROCUREMENT. Procurement of foodgrains by the gov- ernment is, in general, in the form of a levy on producers. However, the success of procurement operations, in terms of the output procured, is very much responsive to the procurement price of- fered as well as the output produced. Procurement prices are revised based on, among other things, past trends in wholesale prices. In the present model, the relationship between quantity procured and procurement price and that between procurement price and past wholesale prices is specified based on the empirical estimates provided in Krishna and Raychaudhuri (1980).
2A-5. GOVERNMENT STORAGE. The government replenishes or depletes its stocks in order to maintain prices within the specified band. The closing stocks are constrained to be non negative. How- ever, in practice, the closing government stocks might not be allowed to go below a certain level for it needs some stocks for the smooth operation of the PDS and other welfare programs such as Food for Work. If the storage capacity constraint becomes binding, then the government may not be able to maintain the prices strictly within the band without depending on trade. For example, when the storage space is exhausted, foodgrains will have to be exported to keep prices from falling below the floor level. Similarly, if the government's stocks are exhausted, then the prices can be prevented from rising only through imports. The
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 591
storage constraint could be specified either in terms of total grains or individual grains. In the former case, one has to specify a rule as to which grain should be given priority when the storage constraint is binding. If the time of market arrival is different for different goods, then priority is automatically determined ac- cording to the time of arrival. In our model, we specify separate storage constraints for the individual grains. The average storage and administrative costs are obtained from trend projections and assumed to be exogenous.
2A-6. PRIVATE STORAGE. Private storage agents are assumed to be risk neutral and the amount they store is determined through expected profit maximization. Competition ensures that profits are not positive. Thus, private storage is determined by the following arbitrage conditions
Pt + k t /> (1 + r) -1 P~+I, spt = 0 ( l a )
Pt + kt = (1 + r) -1 P7+1, spt > 0 ( l b )
where Pt is the current price, kt the marginal cost of storage services (assumed fixed), P~+I the expected future price, the discount rate and spt the amount of private storage. These arbitrage conditions derived under the assumption of risk-neutrality will also hold as limiting propositions under risk aversion as the number of speculators becomes very large (Ghosh, Gilbert, and Hughes Hal- let, 1987, pp. 26-27). In the simulation exercises, P7÷I is approxi- mated by adaptive price expectations with a given speed of adjust- ment. The simulations were repeated for different speeds of adjustment, and the results were found to be robust.
2B. The Computational Procedure
In the single commodity case, it is easy to compute the quantities corresponding to the upper and lower ends of the price band using the demand curve. The difference between the actual availability of grain and these computed quantities is then treated as net additions to stocks or net imports. In the multi-commodity case, we have to work with the price bands directly because the quantities corresponding to the price band for a particular commodity de- pend on the prices of other commodities also.
Availability of grains in any period t is taken as the realized production in period t plus the private and government stocks carried over from the preceding period t-1 less the minimum levels
592 S. Jha and P. V. Srinivasan
of stocks held for convenience by the government agencies in each period. Given the availability of different foodgrains for the initial period and their estimated demand equations, the equilib- rium prices and private storage levels are computed simultane- ously, using a fixed point algorithm, taking into account the inter- dependence between private storage and market prices.
The fixed point map for prices is defined as follows
p,--*MinlMax[(p~ + z3,p,],~, } (2)
where p~ and ~ are respectively the support and ceiling prices and
zi denotes the excess demand for commodity i where the net storge demand by the government is excluded. 2 The fixed point of the above mapping is the equilibrium price. This price will be equal to the support price when the excess demand at this price is negative, and, similarly, it will be equal to the ceiling price when the excess demand at the ceiling price is positive. In either case, the net storage demand by the government is taken to be equal to -z~ so that markets clear at the equilibrium price (that is, total demand including the net storage demand by the government is equal to the total supply net of private storage). Because private storage is a function of current equilibrium prices as well as future expected prices, the private storage levels of grains are endoge- nously determined simultaneously along with the equilibrium prices. The following map is defined for private storage of good i (the time subscript is suppressed for notational simplification)
where sp~ is an upper bound on private storage, so that at the fixed point for this map private storage satisfies the arbitrage conditions (1). With finite storage capacity with the government, it may become infeasible at times to maintain the support price. For example, it is possible to have a long run of good years, and the storage space is exhausted. In such a situation, the surplus grain is exported. Similarly, if there is a run of bad years and government stocks are exhausted, then grain is imported.
The above calculations are repeated for several 5-year se- quences of rainfall indices to obtain the equilibrium prices and the
2 p, E'S are defined to be a certain percentage deviations from the target prices. The net storage demand of the government arises due to the operation of the price band policy.
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 593
corresponding government and private stocks and other variables over time. The different rainfall indices for rice, wheat, and coarse cereals are generated at random from discrete probability distribu- tions obtained from data relating to the years 1949-50 to 1985-86 (taken from Narayana, Parikh, and Srinivasan, 1991).
3. THE SIMULATION EXERCISES
In our exercises, we choose a stabilization period of 5 years (1990-91 to 1994-95). This is because the estimated demand and supply equations hold good only for the short run and may not be suitable for longer periods in the future. Also, we make the time period of this exercise coincide with that of the Indian planning exercise, which again is for 5 years. The simulations are conducted for a given set of trend projections of the exogenous variables in the system. The target stabilization path is taken to be the set of equilibrium prices generated for a string of normal (modal) rainfall years, the assumption being that output corresponding to normal rainfall is sufficient to maintain adequate consumption levels.
The effects of different price bands on consumption and prices are calculated on the basis of a randomly generated sample of 50 different 5-year sequences of rainfall indices. The exercise is repeated for different scenarios with and without private storage and with and without the PDS and procurement policies as listed in Table 1.
These scenarios are repeated for 5%, 10%, 15%, and 20% bandwidths and also for the case where there is no price band policy.
Table 1: A l t e r n a t i v e Scenar ios C o n s i d e r e d
Description
Price band Private PDS/procurement Scenario policy storage policy
1 yes yes yes 2 yes no yes 3 yes yes no 4 yes no no
594 S. Jha and P. V. Srinivasan
I ~- PubLLc -a- PrLvate --*- TotoL
5.6
4.2
2.B
1.4 J
0 5X bond
q
/ / /
Y / js /
IOZ bond 15Z band 2OX bond no band band width
Figure 1. Annual average stocks--scenario: with PDS/procurement.
4. THE RESULTS
4A. Public versus Private Stocks
Because the government's price band policy stabilizes prices across years, the private storage agents do not have much scope to derive arbitrage benefits by storing from one year to another. In the absence of such a policy by the government, however, there is adequate scope for year to year private storage as is revealed from our simulations. Even if there is no price band policy, if the government maintains a procurement cum distribution scheme for foodgrains, once again the scope for inter-year storage by the private storage agents is reduced. This is because the procurement cum distribution scheme has a stabilizing influence on prices (see the next subsection).
As is to be expected the average annual public stocks are higher for lower band widths and the private stocks show an opposite trend (see Figures 1-3). Private stocks are at their maximum when the government does not follow price band policy (the 'no band' case). Thus private stocks supplement public stocks. When prices are kept within a narrow band the scope for arbitrage benefits are low. This explains the zero or low private stocks for narrow bandwidths. The presence of private storage increases the quantity of total stocks held in the economy while marginally reducing the level of public stocks. This holds good for both the cases with and without PDS/procurement schemes.
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 595
10.4
f [ + PubLLc ~ - P r t v a t e -x- TataL ]
7.8
5.2
2.6
0 57. band
]
lOX band 157, band 20Z band no bond b a n d w i d t h
Figure 2. A n n u a l average s tocks- - scenar io : wi thout PDS/p rocu remen t .
4B. PDS/Procurement and Price Stability 3
From Table 2 we see that PDS/procurement schemes increase market prices and decrease mean consumption levels and pro- ducer revenues (compare scenario 1 with 3 and 2 with 4). This result holds irrespective of whether there is private storage or not. The variability in prices decreases due to PDS and procurement policies.
Al though PDS provides an income subsidy that can lead to a higher demand for grains, the procurement scheme means a lower weighted average price to the farmers and, hence, a lower output. The net effect is, on an average, higher free market prices and lower consumption. The results for the individual grains follow the same pattern as that for all cereals.
The average public stocks needed to maintain a price band policy are lower when the PDS/procurement scheme exists (Figure 3). This, once again, implies that PDS has a stabilizing influence on prices; this is reflected in the historical fact that the introduction
The means and coefficients of variation of all the variables are calculated from equilib- rium values generated from different simulations with different rainfall indices. For prices the variability is obtained as the standard deviation of equilibrium prices from the target prices. Because a stabilization period of 5 years is chosen, these averages are generated from 250 data points corresponding to 50 5-year sequences of rainfall indices generated randomly.
596 S. Jha and P. V. Srinivasan
r~
0
10.4
7.8
5.2
2.6
] -~ wLth PD5 -a-wLthout PO5 ]
0 SX bend 107. band 157. bend
band width 207. bond no bond
Figure 3. Annual average public stocks--scenario: no private storage.
of PDS/procurement policy was more with a view to stabilize prices than as a measure to help the poor.
4C. Private Storage and Price Stability
If we compare scenario 2 with scenario 1, we get the effects due to private storage. As has been noted above, for smaller bandwidths, there is not much scope for private storage, and, hence, we see, for these cases, very marginal changes in prices, consumption, and producer revenue. Therefore, we can concen- trate mainly on the 'no band' case. Here we see that private storage raises mean prices and producer revenue, and reduces mean con- sumption. As regards variability, we see that private storage re- duces the variability in cereal prices and consumption, and in- creases that in producer revenue. The effects are very similar when there is no PDS and procurement policy (compare scenarios 3 and 4); the difference being that now the producer revenue is more stable with private storage.
The above discussion shows that private storage reduces the variation in prices. The question, however, that arises is how much price stabilization can be achieved by leaving storage activity entirely to the private storage agents. Comparing the price band with the no band simulations, we see that the variation in both prices and consumption is considerably higher in the latter case. Also, the mean price is higher and the mean consumption margin- ally lower. Thus, private storage agents clearly do not provide
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 597
Table 2: Mean Levels and Variability (CV) of Cereal Prices. Consumption and Producer Revenue
Bandwidth
5% 10% 15% 20% Scenario band band band band No band
Scenario 1: there is private storage and PDS/procurement policy.
Scenario 2: there is no private storage but PDS/procurement policy cxists.
Scenario 3: there is private storage but no PDS/procurement policy.
Scenario 4: there is no private storage and no PDS/procurement policy exists.
Prices are measured in Rupees per quintal, consumption in million tonnes and producer revenue in Rupees crores.
The parentheses ( ) provide the coefficient of variation (CV) which is calculated in the standard fashion for consumption and producer revenue. However, for prices, the numera- tor of CV is calculated as the standard deviation of equilibrium prices from the target price path. These results relate to rice, wheat and coarse cereals taken together.
598 S. Jha and P. V. Srinivasan
~OOO
Scenarios 1 -+- 1 - a - 2 - x - 3 - v - 4
3200
2 2~oo o
{ m~ 1600
800
5Z b o n d iOZ b o n d 15% b o n d b a n d w i d t h
20X bond no bond
Figure 4. Trade off curves: total costs vs price variability.
the same amount of price stabilization as that provided by the government 's price band policy. The consumers lose due to higher mean prices and lower mean consumption levels while the produc- ers gain from higher revenues though with higher volatility. The outcome is the same when PDS/procurement schemes are absent.
4D. Government Costs and Price Variability
Figure 4 shows how total government costs vary with the band- width of the price band policy. As can be seen from Table 2, price variability is directly related to the bandwidth. The higher the bandwidth the higher is the variability in prices. In the scenarios with PDS/procurement policy (scenarios 1 and 2), total costs de- crease initially and then rise as the bandwidth increases. This is due to the fact that while the stocking and trade costs decrease almost monotonically, the PDS/procurement costs increase mono- tonically. The annual average government costs are at a minimum for a bandwidth of about 10% deviation around the target price path. It is worth noting that these min imum costs, which are about Rupees 1700 crores per annum, are much lower than the actual cost of food policy operation, which exceeded Rupees 2500 crores for the base year of the study. Government costs are not affected by the presence of private storage for smaller bandwidths. For larger bandwidths and in the 'no band' case, however, the absence of private storage raises these costs substantially.
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 599
It is interesting to note that, if it has to maintain the PDS/ procurement scheme, the government incurs almost the same costs whether it pursues a 5% price band or no band policy (scenario 1). 4 It can save on its costs by abandoning the price band policy only if PDS/procurement scheme is absent (as in scenarios 3 and 4). The break up of the net government costs according to different operations viz. PDS/procurement , stocking and foreign trade, ex- plains why this happents. The major costs are due to PDS/procure- ment, and these increase substantially when there is no price band policy since as noted above the mean prices are higher in this case. Thus, total government costs increase even though the trade and stocking costs decline to zero as the bandwidth increases.
4E. Relative Benefits to Different Agents
For the quantification of welfare benefits from stabilization we follow the procedures suggested in Ghosh, Gilbert, and Hughes Hallet (1987).
Letting V denote the indirect utility function, which is a function of price p and income m, a first order approximation to the consum- er's benefit in any period can be obtained as
A V = £~(~3V/Op~)Ap~, i = rice, w h e a t a n d c o a r s e cerea ls . (4)
Denoting the variables in the changed scenario with a ..... we have Ap~ = (p'~ - P0. Using Roy's identity (taking derivative at the mid point) and assuming OV/0m = 1 we have
~XV = - £ ~ ( l /2)(x, ' + x0 (p~' - p~) (5)
where x denotes demand. This expression corresponds to the first order approximation to consumer surplus used in Ghosh, Gilbert, and Hughes Hallet (1987) which we adjust suitably to incorporate the effects of changes in subsidy due to PDS. When there is PDS in both the initial and changed scenarios, then Equation 5 will include a term for the change in subsidy due to a change in price.
AV = E~[--(1/2)(xj ' + x 3 + rq~(1 - c<)](p~' - p~) (6)
where rq is the ration quantity and oq is the ratio of ration price to free market price. If PDS exists only in the changed scenario,
Ray (1987) also questions the "'wisdom of a large storage programme" given the trade off between price and farm income stability and high financial cost of stabilization to the government.
600 S. J h a a n d P. V. Sr in ivasan
then the expression will include a term to capture the effects due to a change in income due to the PDS subsidy.
AV = £ i [ - ( 1 / 2 ) ( x ( + x~)(p( - P3 + rqi(1 - re)P(] (7)
In the absence of supply response, the producer's benefit would be obtained as the difference in revenues between the changed and reference scenarios. However, because we model supply re- sponses of the producers to changes in prices the approximate producer surplus is obtained by using Hotelling's lemma as
AFI = - ~ ( 1 / 2 ) ( y ( + y~)(p( - p~) (8)
where II denotes the profits and y the output. Benefits to the government, AG, are calculated by subtracting
the net expenditure in the changed scenario from that in the reference scenario. Apart from storage and administrative costs, the government incurs, in any scenario, costs due to
p r o c u r e m e n t : pp~ × pqi,
impor t s : mp~ × mqi and
f ree m a r k e t pu rchases : ~i Pi [rqi + Asgi + eqi - mqi - Pqi]-
where Asg denotes the net additions to government stocks, pp and mp denote procurement and import prices, respectively, and pg, mq, and eq denote, respectively, procurement, import, and export quantitites. Storage costs are obtained as a product of average storage costs and closing stocks. Administrative costs are obtained by taking the product of average administrative costs and quantity procured. The government derives revenue from selling through PDS and from exports. Net costs are obtained by subtracting total revenue from total costs.
Benefits to private storage agents, AS, are obtained by sub- tracting the net purchase cost of stocks plus the storage cost in the changed scenario from that in the reference scenario. The stocks held in the last period are evaluated at the market price and subtracted from the net purchase costs.
AS, = Yi{(Pitbspit - p(tAsp/t)+kit(spit - spa't)}, t = 1 . . . . . 4 and
Giving equal weights to all agents, the total benefits in period t are obtained as
Bt = AVt + AIIt + AGt + ASt (10)
F O O D G R A I N P R I C E S T A B I L I Z A T I O N 601
and the net present value, NPV, of the benefits derived in the stabilization period of 5 years is obtained as
NPV = ~,8,B, (11)
where 5 is the discount factor. The averages of these present value benefits taken over the different simulations are given in Table 3. The NPV described above corresponds to what is defined as transfer benefit in Newbery and Stiglitz (1981); this arises due to a change in the mean level of prices. The other type of benefi t -- the risk reduction benefit--is due to the variability in prices. This benefit is mot relevant to producers. In our exercises, we ignore these benefits with the implicit assumption that producers are risk neutral.
The simulation results allow us to obtain benefits due to differ- ent aspects of the model. Private storage in the presence of PDS/ procurement policy, for example, leads to positive benefits to the government and negative benefits to the consumers and producers, and the overall benefit is negative. In the absence of PDS/procure- ment also private storage yields overall negative benefits, and the losses are substantial in this case. Because there is not much scope for private storage in the presence of a government 's price band policy, we considered only the cases where there is no price band policy to obtain the benefits from private storage.
Government ' s price band policy in the presence of PDS/pro- curement policy benefits everyone except the producers and pri- vate storage agents, while the overall benefit is positive. However, when there is no PDS/procurement policy, the benefits due to government storage are negative to the government as well, with a negative overall benefit. The consumers are the only beneficiaries in this case. As was noted earlier in the discussion on government costs, the benefits to the government in the former case accrue mainly through a reduction in the costs of the PDS/procurement operations.
Irrespective of whether there is a price stabilization policy or not, the PDS/procurement policy leads to substantial negative benefits to everyone. It is interesting to note here that, while the government incurs costs, no one benefits from this. Hence, the merits, if any, of the PDS/procurement scheme lie in the redistribu- tire benefits it brings about to the consumers, which the present model does not capture. The last column in Table 3 gives the benefits derived from replacing the PDS/procurement with a price
tO
Tab
le 3
: R
elat
ive
Ben
efit
s to
Dif
fere
nt
Ag
ents
(R
up
ees
Cro
res)
Ben
efit
s fr
om
10%
pri
ce b
and
poli
cy
PD
S/p
rocu
rem
ent
poli
cy
Pri
vate
sto
rage
w
itho
ut
wit
hout
R
epla
cing
wit
h w
itho
ut b
oth
w
ith
PD
S/p
roc
wit
h a
10%
pr
ice
ban
d
PD
S/p
roc
PD
S/p
roc
PD
S/p
roc
PD
S/p
roc
poli
cy b
ut
pric
e b
and
po
licy
but
po
licy
wit
h bu
t no
pri
ce
and
pri
ce
poli
cy a
nd
wit
h pr
ivat
e po
licy
and
w
ith
priv
ate
a 10
% p
rice
ba
nd p
olic
y b
and
pol
icie
s pv
t st
orag
e st
orag
e pv
t st
orag
e st
orag
e ba
nd p
olic
y (5
--6)
(7
.-8)
(1
-5)
(3-7
) (1
-3)
(5-7
) (3
-5)
Con
sum
ers
- 50
90.5
2 -
4075
.24
6730
.85
5675
.57
3187
.54
- 42
06.1
5 98
61.5
0 P
rodu
cers
-
1668
.68
6266
.06
- 89
58.6
9 -
6396
.83
- 64
50.8
7 -
3888
.90
2507
.76
Pri
vate
sto
rers
11
9.21
28
2.89
-2
39.1
8 -7
38.0
5 -3
51.6
0 -6
25.1
4 23
7.22
G
ov
ern
men
t 56
13.1
6 0.
00
3298
.94
-195
5.39
-5
871.
51
-111
25.8
4 91
70.4
5 T
otal
-
1026
.84
- 10
058.
42
831.
92
- 34
14.7
0 -
1586
1.51
-
1984
6.04
16
761.
40
Not
e: T
he c
alcu
lati
on o
f ne
t pr
esen
t va
lue
bene
fits
der
ived
by
mov
ing
from
an
init
ial
scen
ario
to
a ch
ange
d sc
enar
io i
s ex
plai
ned
in s
ecti
on
4E.
For
exa
mpl
e, (
5~
) de
note
s a
mo
vem
ent
from
sce
nari
o 6
to s
cena
rio
5. D
escr
ipti
on o
f th
e di
ffer
ent
scen
ario
s is
giv
en i
n se
ctio
n 3.
Sce
nari
os
5 to
8 a
re t
he s
ame
as s
cena
rios
1 t
o 4
but
wit
hout
a p
rice
ban
d po
licy
.
t~
< f~
FOODGRAIN PRICE STABILIZATION 603
stabilization policy. All agents except for the producers gain, and the overall benefit is positive and substantial.
5. POLICY IMPLICATIONS
Two important policy questions can be answered from our simu- lations. The first is, if PDS/procurement policy is abolished, can price stabilization alone support adequate consumption levels? The second is whether the government can afford not to intervene in the market in order to stabilize prices. That is, can private storage alone lead to adequate price stabilization? The answers to these questions depend on the consequent effects on the levels and variations in prices, consumption, and producer revenue as well as on government costs under these situations.
Our results show that if PDS/procurement policy is removed, the average cereal consumption levels can in fact be maintained at higher levels through the price band stabilization program. The benefit calculations show that producers are the only losers, and the overall benefit is substantial. The costs to the government are less and the prices received by farmers, as well as their revenues, decrease in the case of the 10% band policy. Consumers gain due to lower prices and higher consumption levels, though, of course, the distributional implications could be different. Therefore, the decision to remove the PDS/procurement scheme should be based on whether any negative impacts on the distributional objectives outweigh the efficiency gains shown to be occurring.
The consequences of abandoning the price stabilization policy can be different depending on whether or not the government is maintaining a procurement cum public distribution scheme. We find that if procurement and PDS policy is maintained, then it is desirable that the government continues with its price stabilization program, as it would not save much on its costs otherwise. In contrast, the costs increase when there is no private storage in the system. Further, private storage agents do not provide the same amount of price stabilization as that provided by the government 's price band policy. Also, when the government leaves price stabili- zation to private storage agents, foodgrain consumption decreases and producer revenue increases. The benefit calculations also re- veal that consumers lose and producers gain. This is irrespective of whether there exists a PDS/procurement scheme or not.
Jha, S. (1995) Foodgrains Price and Distribution Policies in India: Performance, Problems and Prospects, Asia-Pacific Development Journal 2, No. I (formerly the Economic Bulletin for Asia and the Pacific).
Jha, S., and Srinivasan, P.V. (1994) Effects of Private Storage and Subsidized Food Distribu- tion on Price Band Stabilization Policies. Discussion Paper No. 94-112, Bombay, India: Indira Gandhi Institute of Development Research.
Krishna, R., and Raychaudhuri, G.S. (1980) Some Aspects of Wheat and Rice Price Policy in India. World Bank Staff Working Paper No. 381, Washington, D.C.
Miranda, M., and Helmberger, P. (1988) The Effects of Commodity Price Stabilization Programs. American Economic Review 78:46--58.
Narayana, N.S.S., Parikh, K.S., and Srinivasan, T.N. (1991) Agriculture, Growth and Redis- tribution of Income: Policy Analysis with a General Equilibrium Model of India. North Holland/Allied Publishers.
Newbery, D.M.G., and S tiglitz, J.E. (1981) The Theory of Commodity Price Stabilization. Oxford: Oxford University Press.
Ray, S.K. (1987) Stabilization through Food Stock Operation. Journal of Quantitative Economics 3:101-115.
