Report 2003-07: Understanding USDA Corn and
Soybean Production Forecasts: An Overview of Methods, Performance
and Market Impacts
Updated: January 2004
L. Good and Scott
2003 by Darrel L. Good and Scott H. Irwin
All rights reserved. Readers may make verbatim copies of this document
for non-commercial purposes by any means, provided that this copyright
notice appears on all such copies.
The purpose of this report is
to improve understanding of USDA crop forecasting methods, performance
and market impact. A review of USDA's forecasting procedures and
methodology confirmed the objectivity and consistency of the forecasting
process over time. No changes in methodology occurred in 2003. Month-to-month
changes in corn and soybean production forecasts from 1970 through
2003 indicated little difference in magnitude and direction of monthly
changes over time. USDA production forecast errors were largest
in August and smaller in subsequent forecasts. There appeared to
be no trend in the size or direction of forecast errors over time.
On average, USDA corn production forecasts were more accurate than
private market forecasts over 1970-2003, with the exception of August
forecasts since the mid-1980s. Private market forecasts in soybeans
were more accurate than USDA forecasts for August, regardless of
the time period considered. As the growing season progresses the
USDA's relative accuracy in soybeans improved. USDA corn production
forecasts had the largest impact on corn futures prices in August
and recent price reactions have been somewhat larger than historical
reactions. For soybeans, the largest reactions in futures prices
occurred in August and September, but recent reactions have been
large in October. Overall, the analysis suggests the USDA performs
reasonably well in generating crop production forecasts for corn
There appears to be continuing
misunderstanding of US Department of Agriculture (USDA) motives,
methods and procedures used to arrive at production forecasts for
US corn and soybean crops. This was vividly illustrated by comments
from producers, commodity analysts and farm market advisory services
following the release of the August 2003 forecasts. For example,
we recently received the following e-mail inquiry from a farmer:
"I have a question concerning the August and the September
crop production reports. A friend told me that the numbers that
came out in the August report, which were lower than many predicted,
were utilizing a weather forecast for a hotter and drier 30 day
outlook, as of August 1 (the forecast would have been for the month
of August). He said that the USDA was trying to use a new system,
which would take into account the weather forecast, along with the
usual crop conditions and yield checks. I was under the assumption
that the August crop report took field surveys as of August 1, and
then assumed average weather for the rest of the growing season.
If my friend was correct, then this could potentially mean that
the dropping crop conditions have already been factored in, and
that the September report may only have a slight revision downward."
Market analysts, as represented below, also echoed these concerns:
"There has been considerable dismay in the industry as to
USDA's August corn and soybean estimates. Most do not see them as
real objective analysis
We think that NASS just missed it by
being too conservative with an immature corn and soy crop."
These comments nicely illustrate the importance placed on USDA
crop forecasts by market participants and the potential for misunderstanding
of the methods used to produce the forecasts. Some in the agricultural
community apparently even believe that the USDA manipulates crop
forecasts to fulfill some mystical objectives that are contrary
to the best interest of farmers. There is clearly a need for a better
understanding of all aspects of the USDA crop production forecasting
The objectives of this report are to 1) provide an overview of
the forecasting process for corn and soybean production used by
the USDA, 2) present monthly production forecasts for the 1970 through
2003 corn and soybean crops, 3) examine relationships in the monthly
changes in production forecasts, 4) examine errors in the USDA forecasts,
5) compare USDA forecasts to private market forecasts and 6) examine
the price response to USDA forecasts and the relationship of the
responses to report "surprises." This information should
improve understanding of USDA crop forecasting methods, performance
and market impact.
The USDA uses a highly sophisticated
and well-documented procedure to generate its crop production forecasts. 
All phases of the process are conducted by the National Agricultural
Statistics Service (NASS), an agency within the USDA. For corn and
soybeans, production forecasts are released in August, September,
October, and November.  Final estimates are published in January.
The USDA generates crop production forecasts based on estimates
of planted and harvested acreage and two types of yield indications,
a farmer-reported survey and objective measurements. The acreage
figures are obtained from the June Agricultural Survey, conducted
during the first two weeks of June and reported at the end of June.
The June Survey is based on a large farm operator list frame and
a separate and independent area frame survey. These acreage estimates
are used in subsequent production forecasts until there is evidence
(survey or other) to alter the acreage estimates.  The farmer and
objective yield "probability" surveys use the same sampling,
survey and estimation procedures from year-to-year. This allows
yield and production forecasts to be compared over time. Rich Allen,
Deputy Administrator for Programs & Products and Chair, Agricultural
Statistics Board, NASS, confirmed that there has been no change
in forecasting procedures for the 2003 crops (Allen, 2003).
The farmer-reported yield survey is conducted for states with significant
corn and soybean production. In 2003, 33 states were surveyed for
corn and 29 for soybeans. Farmers included in the yield survey are
randomly selected from the list frame (essentially a list of names,
addresses and phone numbers) of individuals that responded to the
June Agricultural Survey. This assures that farmers included in
the yield surveys are growing the crop of interest. Farmers are
asked monthly (August through November) for a subjective prediction
of their final corn and soybean yields. While the list frame changes
across years, reflecting changing farming arrangements, the same
individuals are surveyed each month for a particular crop year.
Farmer-reported yield surveys are conducted primarily by Computer
Assisted Telephone Interviewing (CATI), but some data are collected
by mail and by face-to-face interviews. The USDA has determined
that farmers tend to make conservative (low) yield predictions,
especially early in the season, so the survey results for each month
are compared to survey results at the same time during the past
10 years and the final average yields for those years. Thus, the
final farmer-reported yield for a given month is adjusted to reflect
that fact that farmers consistently are conservative over time.
The objective yield survey for corn and soybeans typically is conducted
only for the seven most important production states. These "speculative"
states generate about 70 percent of US production for each of the
crops. The objective yield survey is based on an area-frame sampling
design, where fields are randomly selected from the total land area
used in production of a given crop. Mirroring the procedure for
the farmer-reported yield survey, fields for the objective yield
survey are randomly selected from the larger number surveyed in
USDA's June Agricultural Survey. Note that sample fields are selected
with a probability proportional to their size.
Objective yields are obtained from two independently located plots
in each randomly selected field. Physical counts and measurements
of the number of plants and production per plant are conducted.
Yield per acre is generated for the field after standardizing for
row widths, moisture content and harvest loss. Objective yield indications
are derived from models based on observations over the last five
years for the corresponding months compared with end of season yields.
Separate monthly models are constructed by maturity stage so forecast
adjustments are automatically made for early or late maturing crops.
It is important to note that accuracy of the objective yield indications
can change through the growing and harvest seasons. Early in the
season, the yield indications are influenced by assumed relationships
between plant counts and fruit numbers, and an assumed fruit weight
adjusted for moisture content and harvest loss. As the season progresses,
fruit counts become known. At the end of the season, plots are harvested,
and yields are calculated based on actual grain weights and harvest
losses. In addition, an interview is conducted with the farm operator
immediately after harvest to determine acres actually harvested
and the yield realized in the sample field.
As noted earlier, yield forecasts are developed monthly from August
through November. The data on both yield surveys are collected during
the last week of the month previous to the survey month and the
first few days of the survey month, generally from the 25th of the
previous month through the 3rd of the survey month. Yield forecasts
then reflect crop conditions at the beginning of the survey month.
The crop production forecasts are based on the assumption of normal
growing conditions for the remainder of the season as reflected
by historical records. The USDA does not incorporate any weather
forecasts or factor in crop conditions as reflected by weekly crop
The farmer and objective yield indications are combined in a multistage
process employing statistical and judgmental techniques. Before
the actual "lock-up" that precedes the release of a crop
report, all available acreage data and farmer-reported yield indications
for non-speculative states are reviewed. One part of this review
is comparison of yield recommendations for a given state with adjoining
states to see if they demonstrate consistency, based on the weather
that has already occurred. If there is a need to discuss recommendations
with a state office, this can be done but no information is exchanged
about yield indications for other states. By the time lock-up occurs,
harvested acreage for all states and yields for non-speculative
states have been set.
The lock-up for USDA crop reports occurs the night before a report
is released. The recommendations and comments for speculative states
are transmitted as encrypted data files which are locked in a safe
until the lock-up area is secured. For these states, yield indications
are available from both the farmer-reported survey and the objective
yield survey. During lock-up, the Agricultural Statistics Board
reviews all the indications, and in consultation with commodity
statisticians, determines production forecasts for speculative states.
Regional production forecasts are then determined. The final step
is the generation of national production forecasts. The process
used to determine final production estimates is described by Gardner
(1992) this way:
"A NASS board in Washington then assesses all the indicators
of yield, including the estimates of a month earlier. This is not
done using a pre-specified formula---in which case a computer could
replace the NASS board---but through a consensus of the Board members
based on their experience and the full information before them.
After the Agricultural Statistics Board moves to another crop,
a commodity statistician, and usually one other Board member, completes
the review of individual state indications, recommendations, and
analyses and adjusts final state figures if necessary. For a complete
description of the production forecasting process, see "The
Yield Forecasting Program of NASS", SMB Staff Report Number
SMB 98-01, USDA, NASS, Statistical Methods Branch, July 1998.
USDA Forecast Performance
Corn and soybean production forecasts
provided by the USDA for the 34-year period covering 1970-2003 are
presented in Figures
1 and 2. Production forecasts are shown for August, September,
October and November of each year. As noted in the previous section,
a July forecast was made until the mid-1980s, but is not considered
here in order to have a consistent set of forecasts for the entire
period. USDA crop production estimates released in January of the
year after harvest generally are considered to be "final"
estimates. While January estimates may be subsequently revised based
on stocks reports or agricultural census data, such changes tend
to be rather small. 
Changes in the monthly production
forecasts relative to the previous month's forecast are presented
3 and 4 for corn and soybeans, respectively. 
Before proceeding further, it is important to emphasize that the
term "change in forecast" is not meant to imply that the
USDA revises monthly forecasts. As discussed in the previous section,
the USDA makes the best possible interpretation of production potential
each month based upon available information. In other words, the
USDA makes a "fresh" or "new" forecast each
Returning to Figures
3 and 4, the change in forecasts is presented in percentage
terms, rather than in bushels, in order to standardize for increasing
crop size over time. A positive change represents a larger forecast
in the current month relative to the previous month and vice versa.
The September change for both corn and soybeans was very large in
1983. For a given month, however, there appears to be little difference
in the magnitude of monthly changes over time. In addition, there
appears to be no change in the pattern or direction of monthly changes
over time. It is not surprising that the size of forecast changes
tends to diminish across the forecasting cycle (e.g., September
corn changes versus January corn changes).
5 and 6 illustrate the relationship between changes in monthly
production forecasts. The figures address the question of whether
the size and direction of change in October forecasts, for example,
is correlated to the size and direction of change in September forecasts.
The results indicate that there is a positive relationship in the
monthly changes for both corn and soybeans. The magnitude of the
relationship is indicated by the correlation coefficient (r). A
correlation coefficient of +1 indicates a perfect positive correlation
in monthly forecast changes and a coefficient of 0 indicates no
correlation in monthly changes (A coefficient of -1 indicates perfectly
negative correlation.) Correlations in corn are moderate for October
versus September and January versus November changes and high for
November versus October changes. The average correlation across
all three comparisons for corn is 0.54, which indicates substantial
"smoothing" of changes in corn production forecasts. Relationships
are more limited in soybeans, where the highest correlation is 0.50
(November versus October changes). The average correlation across
all three comparisons for soybeans is 0.35, indicating a moderate
amount of smoothing of soybean production forecasts across months.
7 and 8 illustrate the magnitude of monthly changes in corn
and soybean production forecasts relative to the changes expected
by private market analysts. For the period 1970 through 2000, the
expected private market changes are represented by an average of
the changes in production forecasts by Conrad Leslie and Sparks
Companies, Inc. Forecasts from these two firms are selected because
they generally were considered to be the most influential and were
widely-reported in the popular press during this period. The two
firms used different procedures and sources for estimating crop
size (Egelkraut et al., 2003). In addition, the history of forecasts
by these two firms is available for an extended period of time.
For the period 2001 through 2003, the expected private market changes
are represented by changes in the "average trade guess"
as reported by Oster/Dow Jones (ODJ). The change was made because
Conrad Leslie discontinued his service after 2000. Note that Sparks
forecasts are included in the ODJ averages. For the most part, both
the direction and the magnitude of changes in monthly USDA corn
and soybean production forecasts have been well anticipated by the
private sector. This suggests that private analysts are able to
anticipate and incorporate any "smoothness" in USDA changes
into their own forecasts.
The previous analysis indicates
that the pattern of changes in USDA corn and soybean production
forecasts has been stable over time and that the private sector
anticipates the changes reasonably well. However, there is still
the question of the accuracy of monthly forecasts. Following previous
studies (e.g., Garcia et al., 1997; Egelkraut et al., 2003), the
accuracy of the August, September, October and November forecasts
is measured against the January estimate. The percentage errors
in each of the monthly forecasts are presented in Figures
9 and 10 for the 1970 through 2003 corn and soybean crops, respectively.
Not surprisingly, errors generally are largest in August and become
smaller in subsequent forecasts, reflecting improving information
on actual crop size. In every case, the average forecast error is
near zero, indicating USDA forecasts do not tend to be too high
or too low on average. There also does not appear to be any discernable
trend in the size of forecast errors through the years. Finally,
it is interesting to note that, on average, the magnitude of percentage
forecast errors for corn and soybeans in the same month are about
Corn and soybean forecast errors
for the USDA and private market are compared in Figures
11 and 12, respectively. The figures suggest that USDA and private
forecast errors are about the same magnitude, especially so for
soybeans. However, there are times when the forecast errors diverge
sharply. It turns out that there are some important trends in the
relative forecasting accuracy of the USDA and private market over
this period, but it can be difficult to see just looking at the
figures. The trends are more easily discernable in Table
1, which presents average absolute percentage errors for the
USDA and private market forecasts. These calculations treat negative
and positive forecast errors the same. In other words, the direction
of error does not matter, only the distance from the final value.
The average absolute error is reported for the entire 1970-2003
period and for two sub-periods, 1970-1984 and 1985-2003. 
In corn, the relative forecasting accuracy of the USDA was superior
in every case, except August in the latter sub-period. USDA forecasts
in corn also improved more quickly than the private market as the
growing season progressed. The one trouble spot for the USDA in
corn was August forecast accuracy since the mid-1980s. Since that
time, private market forecasts have been more accurate by an average
of 0.6 percentage points, not an inconsequential difference. This
reflects a sharp improvement in August private sector forecast accuracy
relative to the USDA over the last three decades.
The relative forecasting comparisons for soybeans are a bit more
surprising. Private market forecasts were more accurate than USDA
forecasts for August, regardless of the time period considered.
Paralleling the results for corn, private market forecasts of August
soybean production since the mid-1980s have been more accurate by
an average of 0.6 percentage points. As the growing season progresses
the USDA's relative accuracy improved, with the USDA having average
absolute percentage errors about equal to or smaller than the private
market for September, October and November soybean forecasts. 
Overall, the analysis presented in this section suggests the USDA
performs reasonably well in generating crop production forecasts
for corn and soybeans. There is nonetheless room for improvement.
Commenting on similar forecast accuracy results, Egelkraut et al.
(2003), offer this suggestion:
"The improved performance by the private agencies for August
for both crops during the most recent years, and the ability of
the private agencies to generate relatively accurate forecasts in
soybeans suggest that it might be useful for USDA to investigate
expanding the scope of their subjective yield analysis to incorporate
a wider range of market and industry participants. Such a strategy,
if proved effective, might lead to improved crop production forecasts."
Impact of USDA Forecasts
Theoretically, the price impact
of USDA corn and soybean production forecasts should be determined
by how well the market anticipates the forecasts. If the market
perfectly anticipates USDA production forecasts, then, under the
theory of efficient markets, prices will not change. If the market
does not perfectly anticipate the forecasts, prices will change
in relation to the degree that the market is "surprised"
by the new information. To compute surprises, a measure of market
expectations is needed. Once again, private market forecasts are
represented by an average of Conrad Leslie and Sparks Companies,
Inc. forecasts from 1970-2000 and ODJ averages for 2001-2003. 
13 and 14 show the percentage difference between monthly USDA
production forecasts and the monthly private market forecasts. 
This difference is an estimate of the market surprise for each crop
report. A positive surprise number is considered "bearish"
because the USDA forecast is larger than the market expectation.
Likewise, a negative surprise number is considered "bullish"
because the USDA forecast is smaller than the market expectation.
Earlier it was shown that the private sector anticipates much of
the information in crop reports (see Figures
7 and 8). However, this does not mean the private sector anticipates
the information entirely, as is dramatically illustrated in Figures
13 and 14. Market surprises tend to be largest in August and
smallest in November for both corn and soybeans. This makes sense
as there is more uncertainty about crop conditions earlier in the
growing season. There does not appear to be any obvious trends in
market surprises across crop years.
The price impact of corn and
soybean production forecasts is presented in Figures
15 and 16, respectively. Price impact is indicated by the reaction
of December corn futures and November soybean futures (as measured
by the first non-limit opening or closing price) immediately after
the release of the USDA production forecasts. 
For corn, the largest reaction in December futures occurs following
the August report. Interestingly, recent price reactions have been
somewhat larger than historical reactions, except for 1973. Reactions
have been relatively small in September, larger in October, and
very small in November, with a dramatic exception in 1993. For soybeans,
price reactions have had similar magnitudes in August and September.
Price reactions in October were relatively small through the 1980s
(with the exception of 1970), but have generally been larger in
recent years. Price reactions to the November forecasts have been
relatively small and the pattern has changed little over time. 
17 and 18 illustrate the relationship between price reactions
in the futures market and the calculated surprises in the USDA forecasts.
As expected, there is a negative relationship between the direction
of the surprise and the direction of price reaction for both corn
and soybeans. In other words, bullish reports (negative surprises)
tend to lead to price increases and bearish reports (positive surprises)
tend to lead to price decreases. The relationships are somewhat
stronger for corn than soybeans, with the variation of surprises
in the USDA production forecasts explaining 39 to 57 percent of
the variation of the immediate change in corn prices and 24 to 36
percent of the variation of the immediate change in soybean prices
(as indicated by R2 statistics). The strongest relationship is found
in November for corn and September for soybeans. Slopes of the estimated
lines vary by forecast month but equal, on average, about -1.00
for corn and -0.80 for soybeans. This means a one-percentage point
bearish (bullish) surprise leads, on average, to about a one-percentage
point decrease (increase) in corn futures prices and a 0.8 percentage
point decrease (increase) in soybean futures prices. The relatively
wide scatter of price reactions for a given level of surprise indicates
the approximate nature of these relationships.
Price impacts illustrated in this section provide strong evidence
that market participants view USDA corn and soybean production forecasts
as important new information.  This further suggests that USDA forecasts
improve economic welfare by moving prices closer to the "true"
market equilibrium. Having said this, it is important to point out
that earlier forecast performance results appear to contradict some
of the price impact results. The forecast performance results indicate
that private market forecasts early in the season (August) for both
crops are now more accurate than USDA forecasts. At the same time,
corn and soybean futures prices continue to react to the release
of these same USDA forecasts. There is some evidence that the price
reaction in corn has actually increased in recent years. Garcia
et al. (1997) suggest a plausible explanation for this difference
in results. They argue that market participants have different perceptions
of the riskiness of USDA and private market forecasts. Theoretical
models suggest that informed, private traders may behave strategically
with regard to the release of forecasts in advance of public announcements.
Thus, it may be reasonable for market participants to regard USDA
forecasts as less risky than private market forecasts. Since market
participants make decisions based on both expected return and risk,
USDA crop production forecasts that change perceptions of risk but
not expected return would nonetheless still impact prices. This
certainly is an issue that deserves further research.
USDA forecasts and corresponding
private market forecasts for 2003 are presented in panel A of Table
2. The final January estimate for corn and soybeans in 2003
also is presented for comparison purposes. For corn, the USDA forecast
was smaller than the private forecast in August, larger in September
and October and smaller in November. For soybeans, USDA forecasts
were smaller or equal to private forecasts in each of the four months.
These patterns are consistent with the long-run tendency of market
surprises to be mildly correlated across release months. The average
month-to-month correlation of surprises is about 0.40 in the corn
market and about 0.30 in the soybean market. Whether this tendency
is economically significant has yet to be determined.
Forecast errors associated with
USDA and private production forecasts for 2003 are presented in
panel B (million bushels) and panel C (percent) of Table
2. The comparisons reveal that the USDA generally provided more
accurate forecasts of corn and soybean production in 2003. In six
of the eight possible comparisons, forecast errors for the USDA
were substantially smaller (in absolute terms) than private market
errors. This outcome was not surprising for the October and November
forecasts given the long-term accuracy trends for later season forecasts.
What did stand out was the superior performance of the USDA for
early season forecasts in both corn and soybeans, which contrasts
with the long-term trends in accuracy for these months. In corn,
the USDA August 2003 forecast error was 1.3 percentage points smaller
(in absolute terms) than the private market forecast error, the
best relative performance by the USDA over the last decade. In soybeans,
the USDA August 2003 forecast error was 3.3 percentage points smaller
(in absolute terms) than the private market forecast error, the
best relative performance by the USDA over the entire 1970-2003
time period. Relative performance for September 2003 soybeans, where
the USDA had a 4.7 percentage point smaller forecast error, also
was the best since 1970. Overall, the forecasting performance of
the USDA in 2003 relative to the private market was quite strong.
Further perspective on the 2003
USDA corn and soybean crop production forecasts is provided by the
information found in Table
3. Four key indicators are presented: 1) change in forecasts
(where applicable), 2) forecast errors, 3) market surprises and
3) resulting price reactions. The value for 2003 is compared in
each case to the previous high and low values over 1970-2002. Based
upon a comparison of the absolute value in 2003 to the absolute
value of previous highs and lows, none of the 2003 values in corn
fell outside the historical ranges found in the table. 
In other words, the magnitude of changes in forecasts, forecast
errors, market surprises and price reactions in 2003 for the corn
market were well within the historical experience of the last three
decades. Results are more striking in soybeans. In four cases (August:
forecast error; September: forecast error; September: market surprise;
October: change in forecast) magnitudes were record large. Several
other cases were near record highs in terms of magnitude. It is
important to note than even in the cases where new records were
set in soybeans, with one exception, the difference between the
new record value and old record value was relatively small. The
exception is the August forecast error which was 2.9 percentage
points larger than the previous record forecast error for in that
month. While the August 2003 forecast error for the USDA in soybeans
certainly was large by historical standards, as discussed above,
it was nonetheless substantially smaller than the private market
forecast error for August. Therefore, it seems reasonable to argue
that even though 2003 saw some major surprises with regard to USDA
soybean production forecasts, the experience generally was not dramatically
different than what has been seen before.
Additional perspective is provided
by the price reaction comparisons found in Table
4. The actual price reaction for each of the 2003 production
forecasts is the same as that presented in Table
3. Predicted price reactions for each month are based on the
regression equations estimated from historical data (presented earlier
17 and 18). In each of the eight cases, the direction of price
reaction predicted by the regression equations is the same as that
actually observed. In six of the eight cases, the magnitude of actual
price reactions is reasonably close to the predicted magnitude.
In the other two cases (August 2003 corn and September 2003 soybeans),
the actual magnitude is substantially underestimated. It
is not surprising that some of the predictions are off substantially,
given the relatively modest "fits" of the estimated regression
models. However, the large errors in these two cases are within
historical experience, which can be seen through inspection of Figures
17 and 18.
Overall, despite many claims to the contrary, the results presented
in this section indicate 2003 USDA corn and soybean production forecasts
generally were within historical ranges in terms of magnitude of
changes, forecast errors, market surprises and price reactions.
The September and October soybean forecasts were major market surprises,
and the market's price reactions confirmed this, but they were not
Recent comments from producers
and others suggest that there has been an ongoing misunderstanding
of the USDA's methodology for arriving at corn and soybean production
forecasts. The purpose of this report is to improve understanding
of USDA crop forecasting methods, performance and market impact.
The USDA uses a highly sophisticated and well-documented procedure
to generate its crop production forecasts. For corn and soybeans,
production forecasts are released in August, September, October,
and November, with final estimates published in January. The USDA
generates production forecasts based on estimates of planted and
harvested acreage and two types of yield indications, a farmer-reported
survey and objective measurements. A review of USDA's forecasting
procedures and methodology confirmed the objectivity and consistency
of the forecasting process over time. No changes in methodology
occurred in 2003.
Month-to-month changes in USDA corn and soybean production forecasts
from 1970 through 2003 indicated little difference in magnitude
and direction of monthly changes over time. The size of the monthly
changes tended to diminish across the forecasting cycle (August
through November). There was a positive relationship in the size
and direction of forecast changes across months in both corn and
soybeans, with the largest correlations found in corn. Monthly changes
in USDA forecasts have been anticipated reasonably well by the private
sector. As measured against the production estimate in January after
harvest, USDA production forecast errors were largest in August
and smaller in subsequent forecasts. There appeared to be no trend
in the size or direction of forecast errors over the study period.
On average, USDA corn production forecasts were more accurate than
private market forecasts over 1970-2003. One exception in corn was
the August forecast in the most recent time period, 1985-2003. The
forecasting comparisons for soybeans were a bit more surprising.
Private market forecasts in soybeans were more accurate than USDA
forecasts for August regardless of the time period considered. As
the growing season progresses the USDA's relative accuracy improved,
with USDA forecast errors in soybeans about equal to or smaller
than private market errors for September, October and November.
USDA corn production forecasts had the largest impact on corn futures
prices in August and recent price reactions have been somewhat larger
than historical reactions. For soybeans, the largest reaction in
futures prices occurred in August and September, but recent reactions
have been large in October. As predicted by economic theory, there
was a negative relationship between the direction of forecast surprises
and the direction of price reactions for both corn and soybeans,
with a somewhat stronger relationship for corn than for soybeans.
Overall, the forecasting performance of the USDA in 2003 relative
to the private market was quite strong, particularly for early season
corn and soybean production forecasts in August and September. Furthermore,
despite many claims to the contrary, the August, September, October
and November 2003 USDA corn and soybean forecasts generally were
within or near historical ranges in terms of magnitude of changes,
forecast errors, market surprises and price reactions. The September
and October soybean forecasts were major market surprises, and the
market's price reactions showed this, but they were not unprecedented.
The analysis presented in this report suggested the USDA performs
reasonably well in generating crop production forecasts for corn
and soybeans. There was strong evidence that market participants
view USDA corn and soybean production forecasts as important new
information. There is nonetheless room for improvement. In particular,
the USDA may want to consider expanding the scope of the subjective
yield surveys to incorporate a wider range of market and industry
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US Department of Agriculture, April 2003. http://usda.mannlib.cornell.edu/data-sets/crops/96120/
NASS. Price Reactions After
USDA Crop Reports. National Agricultural Statistics Service,
US Department of Agriculture, Pr Rc 1(03), March 2003. http://www.usda.gov/nass/pubs/histdata.htm.
NASS/SMB. The Yield Forecasting
Program of NASS. National Agricultural Statistics Service, US
Department of Agriculture, Staff Report SMB 98-01, 1998.
Change in USDA
in USDA Forecasts:
Market Forecast Error:
Finally, note that the computational
formula for price reaction technically only applies to crop reports
released between May 1994 and October 2003. During this time period,
reports were released at 8:30 am EST, before the start of futures
trading on the release date. The computational formula is changed
slightly for crop reports released between August 1970 and April
1994. During this earlier time period, reports were released at
3:00 pm EST, after the close of trading on the release date. As
a result, day t-1 has to be re-defined as the date a crop report
is released and day t as the day after release.
Darrel L. Good and Scott H. Irwin are Professors in the
Department of Agricultural and Consumer Economics at the
University of Illinois at Urbana-Champaign. The authors
appreciate the research assistance of Thorsten Egelkraut
and Olga Isengildina in assembling the data used for this
study. Rich Allen of NASS provided valuable information
about NASS crop forecasting procedures. This material
is based upon work supported by the Economic Research
Service, U.S. Department of Agriculture, under Project
No. 43-3AEK-8-80106. Any opinions, findings, conclusions,
or recommendations expressed in this publication are those
of the authors and do not necessarily reflect the view
of the U.S. Department of Agriculture.
This section draws heavily from Egelkraut et al.
 The USDA also published corn and soybean production
forecasts for July until the mid-1980s.
The USDA announced on September 29, 2003 that it
will begin using the Farm Service Agency's (FSA) certified
acreage information for the October crop report. Previously,
this information was not available until the end of the
year, and thus, could only be incorporated into January
 The official track record of USDA crop production
forecasts can be found in the publication at:
Please see the appendix to this report for
all computational formulas.
See Isengildina, Irwin and Good (2003) for
a thorough analysis of the relationship between forecast
changes in both corn and soybeans. They find that the
positive correlations in forecast changes are statistically
significant. This is consistent with Gardner's (1992)
argument that, "If the current estimate is substantially
different from earlier estimates there is a tendency not
to adjust the prior NASS estimates fully to rely only
on the current month's information." (p. 1068) Isengildina,
Irwin and Good discuss several possible explanations for
the observed smoothing of changes in USDA corn and soybean
The 1984/1985 breakpoint is suggested by empirical
results found in Fortenbery and Sumner (1993) and Garcia
et al. (1997).
See Egelkraut et al. (2003) for a thorough analysis
of USDA forecast accuracy in both corn and soybeans. Their
investigation is based on several measures of forecast
accuracy, including the average absolute error measure
considered here. Results are not sensitive to which measure
of forecast accuracy is considered. They also conduct
statistical tests of the differences in forecast accuracy
and examine in detail the question of structural change
in relative forecast accuracy.
Both firms typically release their forecasts to
customers five to seven days prior to the release of USDA
crop reports. This should allow the market adequate time
to digest the information and incorporate it into prices.
Market surprises are not presented for January
crop reports due to limited availability of data on private
market expectations for this month.
Data on the cash price reaction to the release
of USDA crop production forecasts for a number of commodities,
including corn and soybeans, can be found in the publication
 From 1970-1984, only USDA corn and soybean production
forecasts were announced on report release dates, and
therefore, the price impact shown in Figures
15 and 16 over this time period can be attributed
solely to the USDA production forecasts. From 1985 onwards,
USDA corn and soybean production reports were released
simultaneously with World Agricultural Supply and Demand
Estimate (WASDE) reports. This means price reaction over
1985-2003 may be attributed to the information contained
in both the corn and soybean production forecasts and
WASDE estimates. While it is impossible to disentangle
the differential impact of the production forecasts and
WASDE estimates with available data, the consistency of
the price reactions over the entire 1970-2003 time period
suggests the bulk of the price impact over 1985-2003 should
be credited to the USDA corn and soybean production forecasts.
For a detailed discussion of this issue see Irwin et al.
 The analysis in this report focuses only on the
reaction of futures prices to the release of USDA crop
reports. Market participants' uncertainty about future
price levels can also be impacted by USDA forecasts. Irwin
et al. (2002) find that implied volatility in options
markets declines sharply after the release of corn and
soybean production forecasts, indicating that the forecasts
not only impact the level of prices but also reduce uncertainty
about future price levels.
This comparison treats positive and negative values
Two changes can be made to the regression models
that may improve the accuracy of the predicted price changes.
Garcia et al. (1997) recommend including market surprises
for both crops in the regression models (e.g., corn price
reaction is based on both corn and soybean market surprises)
and pooling observations across all forecast months. Using
this revised model, the August corn price change is predicted
to be 3.2 percent, closer to the observed price reaction,
but still substantially smaller.
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