Transcript Fundemental price forcasting

Supply and Demand
 Why consider the topic?
 Why should you care about the
demand curve for your
commodities?
Demand shifters
P1
Q1
Demand shifters
 Income
 Population size, composition
 Competitors supplies/prices
 Processing/retail margins
 Government policies
 Tastes and preferences
Demand Changes
 What changes in food consumption
patterns have occurred in the last
10-20 years? Why?
 Summarize the key factors
influencing the demand for a food
or agricultural product?
Demand/consumption
changes
 More vegetable fats and oils,
sharply reduced animal fats,
total fat declining in last decade to
33% of calories
 More pizza and pasta, cheese
 Less beef and lamb, more poultry
 More fish
Demand/consumption
changes
 More soft drinks (esp.non- caloric)
 Less fluid milk (esp. whole milk)
 More alcoholic beverages
 More beer (22 gal., less distilled
liquor
 Less eggs
 More sweeteners (esp. corn
sweeteners)
Demand/consumption
changes
 More fresh fruits and vegetables
 Less cigarettes
 Others you have noticed??
 Overall, higher incidence of
overweight--exceeds 30% of US
Demand/consumption
changes-- Why??
 Higher incomes
 Changes in relative prices (chicken)
 Age distribution, life styles
 Home vs. away from home eating
 Health and disease concerns
 Cholesterol, saturated fat
Demand for Agricultural Products
 Explain the farm demand-retail
demand difference?
 cost of processing
 handling cost
 transport cost
 profit
 Farm demand derived from retail!
Price elasticity of demand
P
1%
X%
Q
Price Elasticity of Demand
% Change in Q1
- - - - - - - - - - - = Usually between 0 and -1
% Change in P1
Demand Elasticities
 Economists usually only talk about
demand elasticities. For most food
products, it is between 0 and -1
(inelastic demand).
Very inelastic--eggs, milk
Less inelastic--chicken
(If relatively close substitutes,
usually less inelastic.)
Elasticities
 Farm price elasticities are usually
the same as retail price elasticity
(if a percentage markup is used)
or more inelastic
(if a constant dollar markup is
used).
Price Cross - Elasticity
% Change in Q1
- - - - - - - - - - - = Usually positive if
% Change in P2 substitutes or
competitors;
negative if
complements.
Price flexibility of demand
P
X%
1%
Q
Price Flexibility of Demand
% Change in P1
- - - - - - - - - - - = Between -1 and -10
% Change in Q1
If price elasticity is -.5, price
flexibility is -2.
(1/-.5)=-2
Using this in forecasting
 In price forecasting, you often have
information regarding the likely
change in supply, and want to know
the likely price change resulting from
it--you need to use the price flexibility.
e.g. A 10% change in Q (+) means a 20%
change in price (-) if the price flexibility
is -2
Price Flexibility
 Approximate price flexibilities:
Hogs
Fed Cattle
Corn
Soybeans
-1.9
-1.6
-2.0
-2.5
Price Cross - Flexibility
% Change in P2
- - - - - - - - - - - = Negative and big if
% Change in Q1
good substitutes
e.g. A 10% increase in beef quantity
marketed might cause a 6% drop in
pork price if the cross-flexibility is -.6
Price Cross - Flexibility
P2
-.6%
1%
Q1
Price Cross - Flexibility
 If you estimate Q change to be +5%
from last year, and other factors do
not change,
% P change = % Q change * P flex
% P change = +5 * -1.9 = - 9.5 %
If $50 last year, $50 - (.095 * 50) = $45.25
Price Cross - Flexibility
 If other factors change too, use the
same procedure and add up the
percentage price changes to get the
net price change expected.
Income Elasticity of Demand
 Engel’s Law: As income rises, a
declining percentage is spent on
food.
 Why?
 At low incomes, virtually all income
has to be spent on essentials like
food and shelter.
Income Elasticity of
Demand
At high incomes,
Do not need more food, but may
upgrade food somewhat (steak vs
hamburger), more eating out and
processed food.
Discretionary purchases--house, car-go first in recession.
Income Elasticity of Demand
 Income elasticity of demand for
most food products is positive and
less than 1.
 Inferior goods (possibly dry beans,
unprocessed potatoes) would have
a negative income elasticity of
demand.
Income Elasticity of Demand
 In forecasting, usually expect increases
in income to result in increased demand
for most “normal” goods.
Thus, the income effect on price or
quantity purchased will usually be
positive, but often not significantly
different from zero in high income
countries like the U.S. (+2% income
implies +.4% price change)
Forecasting Exercise
Assume that:
cattle Q
+4%
flexibility
-1.5
hog Q
income
+2%
+3%
-.3
+.3
poultry Q
+5%
-.2
Forecasting exercise
The percentages are changes from
last year when prices for fed cattle
were $104 per cwt. in the beef.
What price would you expect for the
same time this year?
Forecasting Exercise
Assume that:
flexibility %chngP
cattle Q
+4%
-1.5
-6
hog Q
income
+2%
+3%
-.3
+.3
-.6
+.9
poultry Q +5%
104x(1-.067)=97
-.2
-1
-6.7%
Forecasting exercise
Assume that:
cattle Q
- 4%
flexibility
-.4
hog Q
income
-1.9
+.3
- 2%
+1%
poultry Q +5%
-.2
Forecast change from $48 hogs last
year.
Forecasting exercise
Assume that: flexibility
cattle Q
- 4%
-.4
P impact
1.6%
hog Q
income
3.8
.3
- 2%
+1%
-1.9
+.3
poultry Q +5%
-.2
$48 x 1.047 = 50.256
-1.0
4.7%
Supply
 What are the key factors affecting
market supply?
 Relative profits
 Recent, expected input and output
prices
 Technology and management
changes
Supply
 Weather
--most dramatic effect-crops
 Previous production levels
 Expertise, specialized equipment,
habit
Supply response
 As the expected commodity prices
increase, farmers will shift more of
their productive resources into
producing that commodity.
Supply Analysis
 Potential supply is limited by the
biological nature of agricultural
production, and the time it takes to
respond to incentives.
 Short run, inventories in storage or in
feedlot are the primary supply factors
expected to influence price.
 Longer run-change acres, sows, cows
Supply Response / Supply Shifters
 Behavioral lags:
How long before you believe
relative price changes are likely to
persist?
 New technology, such as higher
yielding crops, new growth
promotants, global positioning
systems, etc.

Supply Response / Supply Shifters
 Government restrictions on
technology or acreage
 Restricted chemical use, “free
range” chicken
 Government tax and farm program
incentives for some enterprises,
acreage restrictions in some farm
programs
Supply Analysis
 In a few days or a week:
grain supplies in storage could
rapidly be marketed if a favorable
price change occurred, but limited
to the old crop size plus carryover
from prior year
Supply Analysis
 In a few days or a week:
livestock at or near normal market
weight could be sold, but limits on
acceptable product characteristics
would limit possible supply
increases (borrow from tomorrow
to market today).
Supply Analysis
 In a few months
In grains, little change possible
unless a new crop becomes
available, and that crop size can’t
be affected much by producers.
Supply Analysis
 In a few months
In livestock, producers could feed
more head, feed to heavier
weights, or sell breeding stock,
but basic number of head
available is already determined.
Supply Analysis
 Next year:
In grains, producers could change
acreage and fertilization, etc. to
change size of next crop.
Supply Analysis
 Next year:
In livestock, could breed more
hogs, turkeys, egg producing
chickens, and keep more dairy
heifers in the herd, and increase
market suppliers in a year, but
breeding more cows would not
change beef suppliers in a year.
The Cobweb Theorem
 Quantity supplied now is the
response to earlier price and profit
signals.
The Cobweb Theorem
 Farmers tend to react as if the
prices they observe today are the
best indicator of the prices they will
experience next year, and often fail
to consider the effect which their
and their neighbor’s production
changes will have on prices then.
The Cobweb Theorem
 In agricultural commodity markets,
this results in a pattern of high
prices now causing higher
production and lower prices later,
followed by lower production and
higher prices,and so on.
Cyclical production
 Slow reactions or overreactions to
prices recently lead to production
changes later
 Cattle cycle--9-10 years
 Hog cycle--3-4 years
 Broiler cycle--less than a year
Fundamental forecasting
 Based on supply/demand factors
 Seasonal patterns
 Balance sheet methods--grains
 Price flexibility methods
 Price forecast equations
 Analagous years
Fundamental forecasting
 Seasonal price patterns
Futures--often different patterns
Cash prices-- often strong seasonal
 Indirect effects on related
commodities via input or output
price chages
Fundamental forecasting
 Attempt to forecast likely direction
and amount of price change
 Probabilities are much higher for
success in direction than amount
 When little information is known
yet, accuracy is not high
Analagous years
 Find a similar supply - demand
setting and see how prices behaved
then
 Primarily used for unusual
situations--short crop years,
embargos, shocks with few
precedents
Seasonal patterns
 Which commodities have strong
seasonal production patterns?
 Which food products have strong
seasonal demand variations?
Seasonal Price Patterns
 What causes them?
Seasonal consumption
eating habits
cooking practices
Holidays
Seasonal Price Patterns
 What causes them?
Weather
Seasonal production
batch production -- crops
risk or cost differences -- livestock
Seasonal patterns
 Either or both can cause seasonal
patterns in cash prices which you
can use to advantage
 Storing grain
 Timing feeder cattle or pig
purchases
 Timing cash sales
Forecast equations
P = f(Prod, Beg Inv, Q comp, Inc,
Export Q, Livestock Q, etc.)
Estimate price impacts of historical
variations in key factors, then plug
in todays best estimates to
calculate likely price
Balance sheet aproach
Beg. inventory
+ production
+ imports
Tot. Supply
Tot. supply - tot.
use = carryover
Feed use
Exports
Seed
Industrial
Tot. Use
Use price flex to
get price
Grain Price Forecasting
 Forecast likely changes in use
without price changes
 Then, calculate % change in
carryover
 Multiply by price flexibility to get
price percentage change
Probability Distribution of Forecasts
Prob.
%
Yields
Probability Distribution of Forecasts
 Needed for marketing strategy choice
 Long tail on left of yield distribution
curve
 Long tail on right of price distribution
curve
 Distribution curve is compressed as
growing season advances
Grain Price Forecasting
 Critical factors:
 Beginning inventory
 Production
Acres, Yields
 Use
Exports
Feed Use
Grain Price Forecasting
 Expected change in ending
inventory vs. last year
 Carryover/use ratio is biggest
influence on price
 Need ~ 3 weeks inventory at end of
mktg. year
Grain Price Forecasting
 Forecast the crop mktg. year price,
then use seasonal patterns for
short/long crop years for shorter
term prices.
 Price flexibilities:
 -2.5 Soybeans
 -2.0 Corn
Forecasting exercise
Crop condition reports in July
suggest that soybean crop may be
5% smaller than most recent
forecast. If your last price forecast
was 6.80/bushel for the marketing
year, how would you forecast:
(a) the next year’s average price
(b) the price at harvest time.
Assignment 7
 Use the DTN Farmdayta screen in
174 or 468 Heady
 Describe two most useful types of
information for an agribusiness you
select. Is this service worth the
cost?
Forecasts of Monthly Crop Price
 First concentrate on season
average price, U.S.
 U.S. average typically above IA by
relative constant amount
 Season average price adjusted to
monthly via historical monthly
pattern
-two distinct patterns:
normal & short crop
Grain Price Forecasting
 Market information sources:
 Reports on weather, soil moisture,
crop condition, acreage, production,
inventories, exports, livestock
numbers, crops and use elsewhere
 Government policies re acreage set
aside, CRP, trade, target or loan
prices, etc. less important now.
Feeder livestock prices
 Why are prices so volatile?
 Are there unusual factors which
influence their prices?
Fed cattle price change
 $10/cwt. live weight up = $110/hd.
 $110/hd more for feeder steer
$110 / 6 cwt. = $18.33 per cwt. for
feeder animal; almost twice the
impact per cwt.
Market hog price change
 $5/cwt. price change =
$12.50 per head
Willing to pay $12.50 more per head
for feeder pigs?
Input price impacts
If input price , what is the effect on
feeder cattle or pig price?
Example
Corn Price
Feeder Cattle Price
Corn Price
Feeder Pig Price
Corn price change
 Corn price up $1/bushel.
 Effect on fed cattle price now?
Little, weight effect only?
 Effect on fed cattle later?
Fewer on feed, weight effect.
Corn price change
 Feeder cattle effect
 Feedlot operators reduce bids to
maintain profits near earlier levels
60 bushels of corn=$60/head
$60 / 6cwt.= $10/cwt. price drop
Technology change
 Determine profit change per head or
cwt. of final product caused by
technology changes in industry
 .5 lbs. feed less / lb. gain =
$.07 x .5 lbs. x 180 lbs. gain =
$6.30 less cost passed on to
feeder pig suppliers as higher price
Forecast Changes
 Would those forecast changes
necessarily be accurate?
Presumes that feedlot operators
look at current price changes and
expect similar changes in prices
later.
Forecast Changes
And presumes that the competitive
process will bring the related
markets back to previous profit
levels.
End