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Benefits to world agriculture through remote sensing
Vol.6, pp. 1707-1715 PergamonPress Ltd., 1979. Printedin Great Britain Acta Astronautica
Benefits to world agriculture through remote sensing? A. C H A R L E S
BUFFALANO
NASA, Goddard Space Flight Center, Greenbelt, MD 20771, U.S.A. AND
PAUL KOCHANOWSKI Indiana University. Bloomington, IN 47405, U.S.A. Abstract--Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 30('1-400 million dollars anually for the rest of the world.
Introduction IT IS rapidly becoming possible to identify and measure crop acreage everywhere in the world from orbiting spacecraft. Such information can lead to significant improvements in the world's crop production estimates and these, in turn, can have substantial economic benefits. The National Aeronautics and Space Administration of the United States has recently completed several economic analyses to quantify these benefits and study policy questions surrounding the use of the data. Two results of these studies are particularly important. First, better information, freely distributed, leads to benefits for the United States and the rest of the world simultaneously. One does not gain at the expense of the other. Second, while one view is that the United States could gain by keeping the information to itself nevertheless free market arguments lead to the conclusion that price stabilization due to smoother foreign demand can also produce large benefits inside the United States. These results are important because they reinforce the view that producers and consumers around the world could share agricultural data without unduly compromising their economic welfare. ~Paper pre,,ented at the XXVIIth Astronautical Congre',~ of the International Astronautical Federation, Anaheim. California. 10-16 October 1976. 17117
1708
A.C. Buffalanoand P. Kochanowski
Economic principles The benefits estimated in this paper are derived from detailed, complex and sophisticated econometric models. However, the basic principles underlying these complex models can be spelled out in relatively simple terms. It is our purpose in this paper to present these basic principles We start by showing how benefits flow from imporved crop forecasts for a single country without trade. Building on this basic framework, we then add trade effects and show how benefits to the United States and the world accrue simultaneously when United States and foreign traders have improved information on world production and use it in the world's commodity markets. Benefits from improved information in a single country without trade We consider improved information benefits for an agricultural commodity "where production cannot be altered significantly in response to output predictions, but where there is an opportunity for inventory holders to adjust stocks. A good example happens in agriculture in the case of food and feed grains, (Hayami and Peterson, 1972). This class of analysis falls within the realm of uncertainty related economics where, with forecast errors having a symmetric probability distribution, a reduction in variance of these errors is equivalent to an increase in certainty (Horowitz, 1970). Given a social welfare function, this increase in certainty generates benefits. The process can be summarized in the following steps where the arrow indicates the direction of causation. I. Improved information from remote ~ Improved crop forecasts by a reducsensing tion in the variance of errors. 2. Improved crop forecasts
A different time patterns and level of inventory buildups and depletions, since crop forecasts are inputs into inventory holding decisions.
3. Different time pattern and level of__, Reduction in the variance of the inventory build-ups and depletions supply of the commodity available for consumption. 4. Reduction supply
in
the
variance
of--, Welfare gains.
Thus, improved information working through inventory decisions reduces the variance of the commodity's supply and thereby generates welfare gains. A special model of this process was presented by Hayami and Peterson (1972). The Hayami-Peterson model is powerful in that computations are simple and its results are easily elucidated through elementary graphical procedures. The model has the following assumptions: (1) Price adjustments are made twice a year, (2) inventory decisions are not explicitly modeled but the rule implied by the model is that holding decisions are based on the spread between futures and
Benefits to world agrictdture throggh remote sensing
1709
spot prices. (3) the forecast error is the error in the quantity of production as a fraction of the true production. (4) over and underages are the same size and equally probable, (5) the fractional form of the demand curve is linear, and (6) short-run supply is perfectly inelastic with respect to crop forecasts. Figure 1 graphically depicts the process whereby losses result from cyclical forecasting errors. It is the reduction of these losses that is the benefit from improved information. Assume that the actual supply available for consumption in a year will be OQ, with the corresponding equilibrium price OP. Imagine that an agricultural reporting agency erroneously forecasts a shortfall in the year's harvest at the beginning of the year. Inventory holders expect future prices to rise so they sell less from their inventories before the harvest and prices rise to O P ' with a supply available for consumption of OQ. When the actual harvest comes in, the error is recognized. The response of inventory holders how is to dump their abnormally large inventories onto the market after the harvest at a lower price OP" with a supply of OQ". The forecast error thus induces supply variability which transmits itself into welfare losses through reductions in producer and consumer surpluses relative to their levels in the perfect information case (Mishan, 1971). Consumer surplus is the benefit to consumers as a group derived from the fact that, for any given market price, there will be some consumers willing to purchase at higher prices. Thus they derive a "windfall" gain from the lower market price. Producer surplus is a similar concept and refers in the collective benefit that derives from the fact that, for any given market price, there will be some producers willing to sell at lower prices. Thus, they derive what can be termed a "windfall" profit from the market price. These surpluses are shown geometrically in Fig. 1 where the sum of the producer and consumer surplus is the area under the demand S'
Supply
S"
I I I p'
P I .w
p"
- -- --
2"
I
Dernond
I I I I I O'
0
Quantity
Fig. 1. Demandand welfare analysis.
1710
A . C . Buffalano and P. Kochanowski
curve from the origin to the quantity consumed. Before harvest, the loss from underestimating has three c o m p o n e n t s - - a r e a 2', area 3 and area 4'. This is the difference in producer and consumer surpluses between the perfect information supply and price of OQ and OP and the error induced supply and price of OQ' and OP'. Next the large supply of OQ" after harvest leads to consumer and producer surplus gains of area 2" and area 4", partially offsetting first period welfare losses. The sum of the gains and losses from misestimating over the two periods is a net loss of area 3. Algebraically, this area is: L O S S - e2pO a
where Q = true quantity of production P = true equilibrium price a = absolute value of price elasticity of demand e = fractional forecast error Q - Q~'
0
The value of improved information comes from reducing this loss by reducing the production forecast error. If the production error drops from a present value of e0 to an improved value of eI the benefit is: B E N E F I T = PQ (eo2 - er'-). a
Thus any nation which consumes its agricultural product obtains a benefit from reducing its own forecast error. But what is the value of improved information when countries are made interdependent by trade? Is it in a nation's interest to share production estimates? We will show that even if the United States domestic forecasts could not be improved, the United States would still benefit from improvements in foreign crop forecasts made possible by remote sensing technology. These benefits stem from the relationship between the stability of domestic commodity markets in the United States and the stability of foreign import demand. There is a direct causal link between fluctuations in foreign import demand and fluctuations in United States exports and consequently fluctuations in United States domestic supply available for consumption. In effect, a foreign component of United States domestic supply fluctuation exists, which is related to foreign crop forecast errors, and which like other types of fluctuations leads to United States consumer and producer surplus losses. The relationship between foreign crop forecast errors and United States supply fluctuations is relatively straightforward. The world price for a commodity is determined by the interaction of import demand and export supply functions. Foreign crop forecasts have an impact on import demand functions and hence world prices. To illustrate this, assume that because of forecast errors
Benefits to world agriculture through remote sensing
1711
a local shortfall of a commodity is anticipated by trade partners of the United States. An anticipated increase in foreign import demand and world futures prices results with United States inventory holders reacting to this anticipation of higher prices in the same manner as they react to error induced anticipation of higher United States prices. They sell less from their inventories until the difference between spot prices and future prices is eliminated, thereby reducing supply available for consumption below what it would be if the forecast error were not made. Following the harvest when the forecast error is discovered and world price increases do not materialize, United States inventory holders unload their large inventories on the market, thus increasing supply above what it would have been. The resultant error induced pattern of inventory holdings and depletions causes increased United States domestic supply fluctuations and increased price instability. And to the extent that these foreign crop forecast errors can be eliminated, there will be benefits to the United States. Because of its importance we derive this result more formally. Mathematically, the export supply and import demand functions are derived from domestic supply and demand functions in each country. These are given as: Du=b.P+c.; Ds = b f P +
Q;
S.=S.: St = Sf:
U.S. demand and supply Foreign demand and supply
where P is price, S is supply, and b and c are parameters specifying the demand function. Assuming the United States to be an exporter and the rest of the world an importer, the export supply ( E S ) and import demand functions ( I D ) are approximately: E S = S~ - b . P - c .
Equilibrium world price Pw is found from equating E S and I D so that p~. = (S! - $.) + (c. - c/)
br-b. Assume now that foreign production is underestimated by fl r units. The futures world price is now anticipated to rise by a P w = F~fl(b ~ - b~).
Then the error induced inventory change in the United States will be b ~ f i r l ( b t bD and the loss to the United States from this error induced instability is: Induced loss = bu [(b t - b . ) S u J "
A C. Buffalano and P. Kochanowski
1712
Thus to the extent that l~ l can be reduced, the United States will gain through a reduction of these induced losses even if estimates of their own production do not improve. Benefit estimates N A S A ' s benefit estimates are obtained from a detailed analysis performed by ECON, Inc., Princeton, N. J.t The E C O N model is a massive extension of the Hayami-Peterson model which eliminates many of the deficiencies inherent in the simpler framework. Specifically, instead of the two-period analysis found in the Hayami-Peterson model, the E C O N model is based on monthly crop forecast improvements. Inventory holding decisions which are absent in the Hayami-Peterson analysis are explicitly modeled in the ECON work. Timeliness
YEAR
IUNE
JULy
AUG
SEPT
OCT
NOV
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
33.0 36.6 28.8 29.5 33.0 34.9 33.6 42.2 33.5 31.6 29.3 40.2 42.1 47.5 55.9
36.7 28.8 28.6 30.2 34.7 36.9 33.8 43.4 43.2 38.8 36.7 42.1 42.2 47.6 52.4
37. 1 32.8 28.9 31.3 35.0 37.5 35.0 41.1 43.7 39.7 36.9 43.6 42.0 46.7 51.6
37.2 32.9 29.8 33.6 35.1 37.0 35.3 42.0 43.5 39.7 37.0 44.2 42.4 47.0 4S.8
37.2 33.0 29.8 30.8 35.0 36.9 35.3 42.3 43.5 39.6 37.0 44.3 42.4 47.0 48.5
37.2 33.0 29.8 30.8 35.0 36.9 35,3 42,3 43.5 39.6 37,0 44,3 42,4 47,0 48.5
YEAR
DEC
/AN
FEB
MAR
APR
FINAL
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41,5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35,1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
36.9 33.5 29.7 31.2 34.9 35.8 35.5 41.0 42.4
39.3 36.8 44.0 42.1 46.6 48.8
Jll
Fig. 2. Forecasts of United States all wheat production in 1960-1974 and final estimates
of same (millions of metric tons).
Benefits to world agriculture through remote sensing
1713
as well as the accuracy of improved information is evaluated. Possible discontinuities in the value of information are recognized, modeled, and reflected in the ECON benefit estimates. And national economic systems, which are closed in the Hayami-Peterson model, are opened with respect to international trade. Through this trade all nations are made interdependent. An important input to the ECON model is an estimate of the monthly improvement in foreign forecast accuracy. At present, wheat production forecasting is conducted throughout the world under a wide variety of conditions. As a result accuracies vary considerably from nation to nation. Dealing with all these variations is beyond the model's capabilities so ECON has modeled the wheat economy with only two characters, the United States, and the rest of the worls as a single consuming entity. Figures 2 and 3 show the recent history of monthly forecasts and the final production estimates for the United States and the rest of the world's wheat. For our analyses, the forecast errors are taken to
YEAR
jtrNz
j~L~'
^uc
s ry_["
oct
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
178.8 183, S 182.9 192.2 189.0 195.9 197.3 207.1 218.6 242.8 235.5 250.8 253.7 272.4 270.8
178.8 183.2 188.5 189.6 189.0 199.3 197.8 212.4 218.6 242.8 235.5 250.8 254.7 275.3 272.8
178.8 185.0 188.5 192.6 190.9 201.2 199.8 212.4 218.6 242.8 235.5 250.8 254.1 272.6 284.6
178.8 174.9 203.1 200.9 193.8 209.1 208.1 212.1 228.2 243.2 228.5 259.3 264.1 272.6 285.7
178.8 172.7 202.3 201.6 193.8 208.5 208.4 215.1 227.4 243.4 227.7 260.3 264.7 269.8 275.7
YEAR
DEC
A~
FEB
MAR
APR
FINAL
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
178.8 172.7 202.1 200.6 193,8 207.2 208,6 231.7 231.4 246.0 243.4 259.1 265.1 288.9 275.6
177.3 172.7 203.3 202.8 198.9 205.2 210.6 228.2 231.4 246.0 239.8 259.1 266.1 288.9 269.3
177.3 172.7 204.1 205.9 201.2 204.8 209.8 228.1 230.8 246.2 240.2 257.5 270.3 289.1 269.3
177.3 172.7 204.9 205.9 201.2 193.9 211.2 228.1 230.8 245.2 240.1 257.5 270.3 289.1 269.3
178.2 174.9 204.9 205.9 202.6 191.9 263.3 228.2 233.9 245.2 240.1 257.5 265.0 289.1 269.3
179.0 175.0 207.6 179.5 220.4 195.1 260.0 219,5 262.1 240.2 248.7 269.8 257.5 296.2 273.0
Fig. 3
Nov 178.8 172.7 202.3 199.6 193.8 209.1 207.9 231.1 231.4 243.1 227.9 260.3 264.7 269.8 275.6
Forecasts of the rest of the worlds all wheat production in 1960-1974 and final estimates of same (millions of metric t o n s ) .
1714
A C. B u f f a l a n o and P. K o c h a n o w s k i
be normally distributed and therefore characterized by a mean value and a standard deviation. Typically the mean value of the error is small. That is, the forecast is just as likely to be an underestimate as an over-estimate. That leaves the standard deviation as the important measure of forecast performance. Figure 4 shows the standard deviation of the forecast error month by month throughout the year for the United States and for the rest of the world based on a straightforward analysis of the numbers in Fig. 2 and 3. As expected, the standard deviation error becomes significantly smaller as harvest approaches. Figure 4 shows targets for a future Landsat spacecraft with a proposed Thematic Mapper (Multi-Spectral Scanner) which has 30 resolution and 6 spectral bands for crop classification. At present, the United States Department of Agriculture, National Oceanic and Atmospheric Administration and NASA are conducting a joint experiment called the Large Area Crop Inventory Experiment (LACIE) to determine just what the actual technical performance will be. Tests in the United States have been very satisfactory but world wide tests are only beginning and will not be concluded for several years. Figure 4 shows two things. First, the present performance of the United States Department of Agriculture will not be improved upon by the new technology for wheat inside the United States. Second, sizeable improvements in foreign production estimates are expected. The benefits for these sizeable improvements in forecast accuracy as calculated by ECON are 200 million dollars per year for the United States and 300-400 million dollars per year for the rest of the world in wheat alone. U.S.A. Month
R.O.W.
i listortcal
Ta rgct
Historical
Target
May
1.87
3. l0
5.77
3.16
June
5.9~
3.03
8.24
3.03
Jtdy
5.93
2.89
8.49
2.89
August
,t. 5;~
2.74
8.30
2.74
SeptemDer
2.72
2,58
8.68
2.58
October
i. 90
2. -t2
8.33
2.42
Nov emtzer
1.87
2.24
8.23
2.24
December
1.87
2.04
8.29
2.04
Januai T
l . 87
i . 83
7.95
1.83
February
1.87
1.58
7.61
1.58
March
1.87
1.29
7.95
1.29
Aprl/
1.87
0.91
7.64
0.91
Fig. 4. E s t i m a t e d f o r e c a s t s t a n d a r d d e v i a t i o n % b y m o n t h w i t h i n c r o p y e a r for 1960-1974 and s i m u l a t e d L A C I E f o r e c a s t e r r o r %.
Benefits to world agriculture through remote sensing
1715
Implications Two important implications can be drawn from these estimates. First, it is apparent that even where the improvements in production forecasting are only for the rest of the world both the United States and the rest of the world gain simultaneously. This is the case since the rest of the world will directly benefit from improved information in terms of decisions impacting their domestic markets and those improved decisions will indirectly work towards stabilizing United States commodity markets. And second, because of this indirect benefit to the United States there is an important implication with regard to the value of proprietary versus public information. Much of the literature in investment and information analysis concludes that proprietary, or insider information, is always of greater value than public information. Thus one would expect that the United States government might some time in the furute find it in its interest to retain superior information about foreign crops in order to capatilize on its insider position. Yet, the results presented above show that by monopolizing the information the United States risks a loss rather than a gain since mistakes made in foreign commodity forecasts feedback in terms of increased instability in United States markets. In a global commodity trading environment where decision units are interdependent, the view that proprietary information is of greater value than public information does not hold based on this free market analysis. So during the next decade as improved crop forecasts from satellites become a reality it appears that both the United States and the rest of the world would benefit from having the information openly available.
References Andrews J. (1976) A Distrubution Benefits Model for Improved Information on Worldwide Crop Production, Vol. I and If, ECON, Inc. Princeton, New Jersey. Bradford D. and Kelejian H. (1974) The Value of Improved (ERS) Information Based on Domestic Distribution Effects of U.S. Agricultural Crops, ECON, Inc. Princeton, New Jersey. ECON Inc. (1974a) The Value of Information for Crop Forecasting in a Market System: Some Theoretical Results, Princeton, New Jersey. ECON Inc. (1974b) The Value of Information for Crop Forecasting with Bayesian Speculators: Theory and Empirical Results, Princeton, New Jersey. Hayami Y. and Peterson W. (1972) Social returns to public information services: Statistical reporting of U.S. farm commodities, American Economic Review, Vol. LXI1 No. l, pp. 119-130. Horowitz I. (1970) Decision Making and the Theory of the Firm, Holt, Rinehart and Winston, Inc., New York. Mishan E. J. (1971) Cost Benefit Analysis, Praeger, New York.
Benefits to world agriculture through remote sensing? A. C H A R L E S
BUFFALANO
NASA, Goddard Space Flight Center, Greenbelt, MD 20771, U.S.A. AND
PAUL KOCHANOWSKI Indiana University. Bloomington, IN 47405, U.S.A. Abstract--Remote sensing of agricultural land permits crop classification and mensuration which can lead to improved forecasts of production. This technique is particularly important for nations which do not already have an accurate agricultural reporting system. Better forecasts have important economic effects. International grain traders can make better decisions about when to store, buy and sell. Farmers can make better planting decisions by taking advantage of production estimates for areas out of phase with their own agricultural calendar. World economic benefits will accrue to both buyers and sellers because of increased food supply and price stabilization. This paper reviews the econometric models used to establish this scenario and estimates the dollar value of benefits for world wheat as 200 million dollars annually for the United States and 30('1-400 million dollars anually for the rest of the world.
Introduction IT IS rapidly becoming possible to identify and measure crop acreage everywhere in the world from orbiting spacecraft. Such information can lead to significant improvements in the world's crop production estimates and these, in turn, can have substantial economic benefits. The National Aeronautics and Space Administration of the United States has recently completed several economic analyses to quantify these benefits and study policy questions surrounding the use of the data. Two results of these studies are particularly important. First, better information, freely distributed, leads to benefits for the United States and the rest of the world simultaneously. One does not gain at the expense of the other. Second, while one view is that the United States could gain by keeping the information to itself nevertheless free market arguments lead to the conclusion that price stabilization due to smoother foreign demand can also produce large benefits inside the United States. These results are important because they reinforce the view that producers and consumers around the world could share agricultural data without unduly compromising their economic welfare. ~Paper pre,,ented at the XXVIIth Astronautical Congre',~ of the International Astronautical Federation, Anaheim. California. 10-16 October 1976. 17117
1708
A.C. Buffalanoand P. Kochanowski
Economic principles The benefits estimated in this paper are derived from detailed, complex and sophisticated econometric models. However, the basic principles underlying these complex models can be spelled out in relatively simple terms. It is our purpose in this paper to present these basic principles We start by showing how benefits flow from imporved crop forecasts for a single country without trade. Building on this basic framework, we then add trade effects and show how benefits to the United States and the world accrue simultaneously when United States and foreign traders have improved information on world production and use it in the world's commodity markets. Benefits from improved information in a single country without trade We consider improved information benefits for an agricultural commodity "where production cannot be altered significantly in response to output predictions, but where there is an opportunity for inventory holders to adjust stocks. A good example happens in agriculture in the case of food and feed grains, (Hayami and Peterson, 1972). This class of analysis falls within the realm of uncertainty related economics where, with forecast errors having a symmetric probability distribution, a reduction in variance of these errors is equivalent to an increase in certainty (Horowitz, 1970). Given a social welfare function, this increase in certainty generates benefits. The process can be summarized in the following steps where the arrow indicates the direction of causation. I. Improved information from remote ~ Improved crop forecasts by a reducsensing tion in the variance of errors. 2. Improved crop forecasts
A different time patterns and level of inventory buildups and depletions, since crop forecasts are inputs into inventory holding decisions.
3. Different time pattern and level of__, Reduction in the variance of the inventory build-ups and depletions supply of the commodity available for consumption. 4. Reduction supply
in
the
variance
of--, Welfare gains.
Thus, improved information working through inventory decisions reduces the variance of the commodity's supply and thereby generates welfare gains. A special model of this process was presented by Hayami and Peterson (1972). The Hayami-Peterson model is powerful in that computations are simple and its results are easily elucidated through elementary graphical procedures. The model has the following assumptions: (1) Price adjustments are made twice a year, (2) inventory decisions are not explicitly modeled but the rule implied by the model is that holding decisions are based on the spread between futures and
Benefits to world agrictdture throggh remote sensing
1709
spot prices. (3) the forecast error is the error in the quantity of production as a fraction of the true production. (4) over and underages are the same size and equally probable, (5) the fractional form of the demand curve is linear, and (6) short-run supply is perfectly inelastic with respect to crop forecasts. Figure 1 graphically depicts the process whereby losses result from cyclical forecasting errors. It is the reduction of these losses that is the benefit from improved information. Assume that the actual supply available for consumption in a year will be OQ, with the corresponding equilibrium price OP. Imagine that an agricultural reporting agency erroneously forecasts a shortfall in the year's harvest at the beginning of the year. Inventory holders expect future prices to rise so they sell less from their inventories before the harvest and prices rise to O P ' with a supply available for consumption of OQ. When the actual harvest comes in, the error is recognized. The response of inventory holders how is to dump their abnormally large inventories onto the market after the harvest at a lower price OP" with a supply of OQ". The forecast error thus induces supply variability which transmits itself into welfare losses through reductions in producer and consumer surpluses relative to their levels in the perfect information case (Mishan, 1971). Consumer surplus is the benefit to consumers as a group derived from the fact that, for any given market price, there will be some consumers willing to purchase at higher prices. Thus they derive a "windfall" gain from the lower market price. Producer surplus is a similar concept and refers in the collective benefit that derives from the fact that, for any given market price, there will be some producers willing to sell at lower prices. Thus, they derive what can be termed a "windfall" profit from the market price. These surpluses are shown geometrically in Fig. 1 where the sum of the producer and consumer surplus is the area under the demand S'
Supply
S"
I I I p'
P I .w
p"
- -- --
2"
I
Dernond
I I I I I O'
0
Quantity
Fig. 1. Demandand welfare analysis.
1710
A . C . Buffalano and P. Kochanowski
curve from the origin to the quantity consumed. Before harvest, the loss from underestimating has three c o m p o n e n t s - - a r e a 2', area 3 and area 4'. This is the difference in producer and consumer surpluses between the perfect information supply and price of OQ and OP and the error induced supply and price of OQ' and OP'. Next the large supply of OQ" after harvest leads to consumer and producer surplus gains of area 2" and area 4", partially offsetting first period welfare losses. The sum of the gains and losses from misestimating over the two periods is a net loss of area 3. Algebraically, this area is: L O S S - e2pO a
where Q = true quantity of production P = true equilibrium price a = absolute value of price elasticity of demand e = fractional forecast error Q - Q~'
0
The value of improved information comes from reducing this loss by reducing the production forecast error. If the production error drops from a present value of e0 to an improved value of eI the benefit is: B E N E F I T = PQ (eo2 - er'-). a
Thus any nation which consumes its agricultural product obtains a benefit from reducing its own forecast error. But what is the value of improved information when countries are made interdependent by trade? Is it in a nation's interest to share production estimates? We will show that even if the United States domestic forecasts could not be improved, the United States would still benefit from improvements in foreign crop forecasts made possible by remote sensing technology. These benefits stem from the relationship between the stability of domestic commodity markets in the United States and the stability of foreign import demand. There is a direct causal link between fluctuations in foreign import demand and fluctuations in United States exports and consequently fluctuations in United States domestic supply available for consumption. In effect, a foreign component of United States domestic supply fluctuation exists, which is related to foreign crop forecast errors, and which like other types of fluctuations leads to United States consumer and producer surplus losses. The relationship between foreign crop forecast errors and United States supply fluctuations is relatively straightforward. The world price for a commodity is determined by the interaction of import demand and export supply functions. Foreign crop forecasts have an impact on import demand functions and hence world prices. To illustrate this, assume that because of forecast errors
Benefits to world agriculture through remote sensing
1711
a local shortfall of a commodity is anticipated by trade partners of the United States. An anticipated increase in foreign import demand and world futures prices results with United States inventory holders reacting to this anticipation of higher prices in the same manner as they react to error induced anticipation of higher United States prices. They sell less from their inventories until the difference between spot prices and future prices is eliminated, thereby reducing supply available for consumption below what it would be if the forecast error were not made. Following the harvest when the forecast error is discovered and world price increases do not materialize, United States inventory holders unload their large inventories on the market, thus increasing supply above what it would have been. The resultant error induced pattern of inventory holdings and depletions causes increased United States domestic supply fluctuations and increased price instability. And to the extent that these foreign crop forecast errors can be eliminated, there will be benefits to the United States. Because of its importance we derive this result more formally. Mathematically, the export supply and import demand functions are derived from domestic supply and demand functions in each country. These are given as: Du=b.P+c.; Ds = b f P +
Q;
S.=S.: St = Sf:
U.S. demand and supply Foreign demand and supply
where P is price, S is supply, and b and c are parameters specifying the demand function. Assuming the United States to be an exporter and the rest of the world an importer, the export supply ( E S ) and import demand functions ( I D ) are approximately: E S = S~ - b . P - c .
Equilibrium world price Pw is found from equating E S and I D so that p~. = (S! - $.) + (c. - c/)
br-b. Assume now that foreign production is underestimated by fl r units. The futures world price is now anticipated to rise by a P w = F~fl(b ~ - b~).
Then the error induced inventory change in the United States will be b ~ f i r l ( b t bD and the loss to the United States from this error induced instability is: Induced loss = bu [(b t - b . ) S u J "
A C. Buffalano and P. Kochanowski
1712
Thus to the extent that l~ l can be reduced, the United States will gain through a reduction of these induced losses even if estimates of their own production do not improve. Benefit estimates N A S A ' s benefit estimates are obtained from a detailed analysis performed by ECON, Inc., Princeton, N. J.t The E C O N model is a massive extension of the Hayami-Peterson model which eliminates many of the deficiencies inherent in the simpler framework. Specifically, instead of the two-period analysis found in the Hayami-Peterson model, the E C O N model is based on monthly crop forecast improvements. Inventory holding decisions which are absent in the Hayami-Peterson analysis are explicitly modeled in the ECON work. Timeliness
YEAR
IUNE
JULy
AUG
SEPT
OCT
NOV
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
33.0 36.6 28.8 29.5 33.0 34.9 33.6 42.2 33.5 31.6 29.3 40.2 42.1 47.5 55.9
36.7 28.8 28.6 30.2 34.7 36.9 33.8 43.4 43.2 38.8 36.7 42.1 42.2 47.6 52.4
37. 1 32.8 28.9 31.3 35.0 37.5 35.0 41.1 43.7 39.7 36.9 43.6 42.0 46.7 51.6
37.2 32.9 29.8 33.6 35.1 37.0 35.3 42.0 43.5 39.7 37.0 44.2 42.4 47.0 4S.8
37.2 33.0 29.8 30.8 35.0 36.9 35.3 42.3 43.5 39.6 37.0 44.3 42.4 47.0 48.5
37.2 33.0 29.8 30.8 35.0 36.9 35,3 42,3 43.5 39.6 37,0 44,3 42,4 47,0 48.5
YEAR
DEC
/AN
FEB
MAR
APR
FINAL
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41,5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35.1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
37.1 33.6 29.7 30.9 35,1 36.1 35.7 41.5 42.7 39.7 37.5 44.6 42.1 46.6 48.8
36.9 33.5 29.7 31.2 34.9 35.8 35.5 41.0 42.4
39.3 36.8 44.0 42.1 46.6 48.8
Jll
Fig. 2. Forecasts of United States all wheat production in 1960-1974 and final estimates
of same (millions of metric tons).
Benefits to world agriculture through remote sensing
1713
as well as the accuracy of improved information is evaluated. Possible discontinuities in the value of information are recognized, modeled, and reflected in the ECON benefit estimates. And national economic systems, which are closed in the Hayami-Peterson model, are opened with respect to international trade. Through this trade all nations are made interdependent. An important input to the ECON model is an estimate of the monthly improvement in foreign forecast accuracy. At present, wheat production forecasting is conducted throughout the world under a wide variety of conditions. As a result accuracies vary considerably from nation to nation. Dealing with all these variations is beyond the model's capabilities so ECON has modeled the wheat economy with only two characters, the United States, and the rest of the worls as a single consuming entity. Figures 2 and 3 show the recent history of monthly forecasts and the final production estimates for the United States and the rest of the world's wheat. For our analyses, the forecast errors are taken to
YEAR
jtrNz
j~L~'
^uc
s ry_["
oct
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
178.8 183, S 182.9 192.2 189.0 195.9 197.3 207.1 218.6 242.8 235.5 250.8 253.7 272.4 270.8
178.8 183.2 188.5 189.6 189.0 199.3 197.8 212.4 218.6 242.8 235.5 250.8 254.7 275.3 272.8
178.8 185.0 188.5 192.6 190.9 201.2 199.8 212.4 218.6 242.8 235.5 250.8 254.1 272.6 284.6
178.8 174.9 203.1 200.9 193.8 209.1 208.1 212.1 228.2 243.2 228.5 259.3 264.1 272.6 285.7
178.8 172.7 202.3 201.6 193.8 208.5 208.4 215.1 227.4 243.4 227.7 260.3 264.7 269.8 275.7
YEAR
DEC
A~
FEB
MAR
APR
FINAL
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
178.8 172.7 202.1 200.6 193,8 207.2 208,6 231.7 231.4 246.0 243.4 259.1 265.1 288.9 275.6
177.3 172.7 203.3 202.8 198.9 205.2 210.6 228.2 231.4 246.0 239.8 259.1 266.1 288.9 269.3
177.3 172.7 204.1 205.9 201.2 204.8 209.8 228.1 230.8 246.2 240.2 257.5 270.3 289.1 269.3
177.3 172.7 204.9 205.9 201.2 193.9 211.2 228.1 230.8 245.2 240.1 257.5 270.3 289.1 269.3
178.2 174.9 204.9 205.9 202.6 191.9 263.3 228.2 233.9 245.2 240.1 257.5 265.0 289.1 269.3
179.0 175.0 207.6 179.5 220.4 195.1 260.0 219,5 262.1 240.2 248.7 269.8 257.5 296.2 273.0
Fig. 3
Nov 178.8 172.7 202.3 199.6 193.8 209.1 207.9 231.1 231.4 243.1 227.9 260.3 264.7 269.8 275.6
Forecasts of the rest of the worlds all wheat production in 1960-1974 and final estimates of same (millions of metric t o n s ) .
1714
A C. B u f f a l a n o and P. K o c h a n o w s k i
be normally distributed and therefore characterized by a mean value and a standard deviation. Typically the mean value of the error is small. That is, the forecast is just as likely to be an underestimate as an over-estimate. That leaves the standard deviation as the important measure of forecast performance. Figure 4 shows the standard deviation of the forecast error month by month throughout the year for the United States and for the rest of the world based on a straightforward analysis of the numbers in Fig. 2 and 3. As expected, the standard deviation error becomes significantly smaller as harvest approaches. Figure 4 shows targets for a future Landsat spacecraft with a proposed Thematic Mapper (Multi-Spectral Scanner) which has 30 resolution and 6 spectral bands for crop classification. At present, the United States Department of Agriculture, National Oceanic and Atmospheric Administration and NASA are conducting a joint experiment called the Large Area Crop Inventory Experiment (LACIE) to determine just what the actual technical performance will be. Tests in the United States have been very satisfactory but world wide tests are only beginning and will not be concluded for several years. Figure 4 shows two things. First, the present performance of the United States Department of Agriculture will not be improved upon by the new technology for wheat inside the United States. Second, sizeable improvements in foreign production estimates are expected. The benefits for these sizeable improvements in forecast accuracy as calculated by ECON are 200 million dollars per year for the United States and 300-400 million dollars per year for the rest of the world in wheat alone. U.S.A. Month
R.O.W.
i listortcal
Ta rgct
Historical
Target
May
1.87
3. l0
5.77
3.16
June
5.9~
3.03
8.24
3.03
Jtdy
5.93
2.89
8.49
2.89
August
,t. 5;~
2.74
8.30
2.74
SeptemDer
2.72
2,58
8.68
2.58
October
i. 90
2. -t2
8.33
2.42
Nov emtzer
1.87
2.24
8.23
2.24
December
1.87
2.04
8.29
2.04
Januai T
l . 87
i . 83
7.95
1.83
February
1.87
1.58
7.61
1.58
March
1.87
1.29
7.95
1.29
Aprl/
1.87
0.91
7.64
0.91
Fig. 4. E s t i m a t e d f o r e c a s t s t a n d a r d d e v i a t i o n % b y m o n t h w i t h i n c r o p y e a r for 1960-1974 and s i m u l a t e d L A C I E f o r e c a s t e r r o r %.
Benefits to world agriculture through remote sensing
1715
Implications Two important implications can be drawn from these estimates. First, it is apparent that even where the improvements in production forecasting are only for the rest of the world both the United States and the rest of the world gain simultaneously. This is the case since the rest of the world will directly benefit from improved information in terms of decisions impacting their domestic markets and those improved decisions will indirectly work towards stabilizing United States commodity markets. And second, because of this indirect benefit to the United States there is an important implication with regard to the value of proprietary versus public information. Much of the literature in investment and information analysis concludes that proprietary, or insider information, is always of greater value than public information. Thus one would expect that the United States government might some time in the furute find it in its interest to retain superior information about foreign crops in order to capatilize on its insider position. Yet, the results presented above show that by monopolizing the information the United States risks a loss rather than a gain since mistakes made in foreign commodity forecasts feedback in terms of increased instability in United States markets. In a global commodity trading environment where decision units are interdependent, the view that proprietary information is of greater value than public information does not hold based on this free market analysis. So during the next decade as improved crop forecasts from satellites become a reality it appears that both the United States and the rest of the world would benefit from having the information openly available.
References Andrews J. (1976) A Distrubution Benefits Model for Improved Information on Worldwide Crop Production, Vol. I and If, ECON, Inc. Princeton, New Jersey. Bradford D. and Kelejian H. (1974) The Value of Improved (ERS) Information Based on Domestic Distribution Effects of U.S. Agricultural Crops, ECON, Inc. Princeton, New Jersey. ECON Inc. (1974a) The Value of Information for Crop Forecasting in a Market System: Some Theoretical Results, Princeton, New Jersey. ECON Inc. (1974b) The Value of Information for Crop Forecasting with Bayesian Speculators: Theory and Empirical Results, Princeton, New Jersey. Hayami Y. and Peterson W. (1972) Social returns to public information services: Statistical reporting of U.S. farm commodities, American Economic Review, Vol. LXI1 No. l, pp. 119-130. Horowitz I. (1970) Decision Making and the Theory of the Firm, Holt, Rinehart and Winston, Inc., New York. Mishan E. J. (1971) Cost Benefit Analysis, Praeger, New York.