1. Supply and Demand H Why consider the topic? H Why should you care about the demand curve for your commodities?

2. P1Q1 Demand shifters

3. H Income H Population size, composition H Competitors supplies/prices H Processing/retail margins H Government policies H Tastes and preferences

4. Demand Changes H What changes in food consumption patterns have occurred in the last 10-20 years? Why? H Summarize the key factors influencing the demand for a food or agricultural product?

5. Demand/consumption changes H More vegetable fats and oils, sharply reduced animal fats, total fat declining in last decade to 33% of calories H More pizza and pasta, cheese H Less beef and lamb, more poultry H More fish

6. Demand/consumption changes H More soft drinks (esp.non- caloric) H Less fluid milk (esp. whole milk) H More alcoholic beverages H More beer (22 gal., less distilled liquor H Less eggs H More sweeteners (esp. corn sweeteners)

7. Demand/consumption changes H More fresh fruits and vegetables H Less cigarettes H Others you have noticed?? H Overall, higher incidence of overweight--exceeds 30% of US

8. Demand/consumption changes-- Why?? H Higher incomes H Changes in relative prices (chicken) H Age distribution, life styles H Home vs. away from home eating H Health and disease concerns H Cholesterol, saturated fat

9. Demand for Agricultural Products H Explain the farm demand-retail demand difference? H cost of processing H handling cost H transport cost H profit H Farm demand derived from retail!

10. Price elasticity of demand P1%X%Q

11. Price Elasticity of Demand % Change in Q 1 - - - - - - - - - - - = Usually between 0 and -1 % Change in P 1

12. Demand Elasticities H 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.)

13. ElasticitiesElasticities H Farm price elasticities are usually the same as retail price elasticity (if a percentage markup is used) (if a percentage markup is used) or more inelastic or more inelastic (if a constant dollar markup is used).

14. Price Cross - Elasticity % Change in Q 1 - - - - - - - - - - - = Usually positive if substitutes or competitors; negative if complements. % Change in P 2

15. Price flexibility of demand PX%1%Q

16. Price Flexibility of Demand % Change in P 1 - - - - - - - - - - - = Between -1 and -10 % Change in Q 1 If price elasticity is -.5, price flexibility is -2. (1/-.5)=-2

17. Using this in forecasting H 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

18. H Approximate price flexibilities: Hogs-1.9 Fed Cattle-1.6 Corn-2.0 Soybeans-2.5 Price Flexibility

19. % Change in P 2 - - - - - - - - - - - = Negative and big if % Change in Q 1 good substitutes - - - - - - - - - - - = Negative and big if % Change in Q 1 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

20. P 2 P 2-.6% 1% 1% Q 1 Q 1 Price Cross - Flexibility

21. H 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

22. H If other factors change too, use the same procedure and add up the percentage price changes to get the net price change expected. Price Cross - Flexibility

23. Income Elasticity of Demand H Engel’s Law: As income rises, a declining percentage is spent on food. H Why? H At low incomes, virtually all income has to be spent on essentials like food and shelter.

24. 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.

25. Income Elasticity of Demand H Income elasticity of demand for most food products is positive and less than 1. H Inferior goods (possibly dry beans, unprocessed potatoes) would have a negative income elasticity of demand.

26. H 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) Income Elasticity of Demand

27. Forecasting Exercise Assume that:flexibility cattle Q +4%-1.5 hog Q+2% -.3 income +3%+.3 poultry Q+5% -.2

28. Forecasting exercise The percentages are changes from last year when prices for fed cattle were $104 per cwt. in the beef. 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?

29. Forecasting Exercise Assume that: flexibility%chngP cattle Q +4%-1.5 -6 hog Q+2% -.3-.6 income +3%+.3 +.9 poultry Q+5% -.2 -1 104x(1-.067)=97 -6.7%

30. Forecasting exercise Assume that:flexibility cattle Q - 4% -.4 hog Q- 2% -1.9 income +1% +.3 poultry Q+5% -.2 Forecast change from $48 hogs last year.

31. Forecasting exercise Assume that:flexibilityP impact cattle Q - 4% -.41.6% hog Q- 2% -1.93.8 income +1%+.3.3 poultry Q+5% -.2-1.0 $48 x 1.047 = 50.256 4.7%

32. SupplySupply H What are the key factors affecting market supply? H Relative profits H Recent, expected input and output prices H Technology and management changes

33. SupplySupply H Weather --most dramatic effect-crops H Previous production levels H Expertise, specialized equipment, habit

34. H As the expected commodity prices increase, farmers will shift more of their productive resources into producing that commodity. Supply response

35. Supply Analysis H Potential supply is limited by the biological nature of agricultural production, and the time it takes to respond to incentives. H Short run, inventories in storage or in feedlot are the primary supply factors expected to influence price. H Longer run-change acres, sows, cows

36. H Behavioral lags: ä How long before you believe relative price changes are likely to persist? ä New technology, such as higher yielding crops, new growth promotants, global positioning systems, etc. Supply Response / Supply Shifters

37. H Government restrictions on technology or acreage H Restricted chemical use, “free range” chicken H Government tax and farm program incentives for some enterprises, acreage restrictions in some farm programs Supply Response / Supply Shifters

38. H 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 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

39. H 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). 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

40. H 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. In grains, little change possible unless a new crop becomes available, and that crop size can’t be affected much by producers. Supply Analysis

41. H 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. 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

42. H Next year: In grains, producers could change acreage and fertilization, etc. to change size of next crop. In grains, producers could change acreage and fertilization, etc. to change size of next crop. Supply Analysis

43. H 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. 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.

44. The Cobweb Theorem H Quantity supplied now is the response to earlier price and profit signals.

45. The Cobweb Theorem H 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.

46. The Cobweb Theorem H 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.

47. Cyclical production H Slow reactions or overreactions to prices recently lead to production changes later H Cattle cycle--9-10 years H Hog cycle--3-4 years H Broiler cycle--less than a year

48. Fundamental forecasting H Based on supply/demand factors H Seasonal patterns H Balance sheet methods--grains H Price flexibility methods H Price forecast equations H Analagous years

49. Fundamental forecasting H Seasonal price patterns Futures--often different patterns Cash prices-- often strong seasonal H Indirect effects on related commodities via input or output price chages

50. Fundamental forecasting H Attempt to forecast likely direction and amount of price change H Probabilities are much higher for success in direction than amount H When little information is known yet, accuracy is not high

51. Analagous years H Find a similar supply - demand setting and see how prices behaved then H Primarily used for unusual situations--short crop years, embargos, shocks with few precedents

52. Seasonal patterns H Which commodities have strong seasonal production patterns? H Which food products have strong seasonal demand variations?

53. Seasonal Price Patterns H What causes them? Seasonal consumption eating habits cooking practices Holidays

54. Seasonal Price Patterns H What causes them? Weather Seasonal production batch production -- crops risk or cost differences -- livestock

55. Seasonal patterns H Either or both can cause seasonal patterns in cash prices which you can use to advantage H Storing grain H Timing feeder cattle or pig purchases H Timing cash sales

56. 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

57. Balance sheet aproach Beg. inventory + production + imports Tot. Supply Tot. supply - tot. use = carryover Feed use ExportsSeedIndustrial Tot. Use Use price flex to get price

58. Grain Price Forecasting H Forecast likely changes in use without price changes H Then, calculate % change in carryover H Multiply by price flexibility to get price percentage change

59. Prob. %Yields Probability Distribution of Forecasts

60. H Needed for marketing strategy choice H Long tail on left of yield distribution curve H Long tail on right of price distribution curve H Distribution curve is compressed as growing season advances

61. Grain Price Forecasting H Critical factors: H Beginning inventory H Production Acres, Yields H Use Exports Feed Use

62. Grain Price Forecasting H Expected change in ending inventory vs. last year H Carryover/use ratio is biggest influence on price H Need ~ 3 weeks inventory at end of mktg. year

63. Grain Price Forecasting H Forecast the crop mktg. year price, then use seasonal patterns for short/long crop years for shorter term prices. H Price flexibilities: H -2.5 Soybeans H -2.0 Corn

64. 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: 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.

65. Assignment 7 H Use the DTN Farmdayta screen in 174 or 468 Heady H Describe two most useful types of information for an agribusiness you select. Is this service worth the cost?

66. Forecasts of Monthly Crop Price H First concentrate on season average price, U.S. H U.S. average typically above IA by relative constant amount H Season average price adjusted to monthly via historical monthly pattern -two distinct patterns: normal & short crop

67. Grain Price Forecasting H Market information sources: H Reports on weather, soil moisture, crop condition, acreage, production, inventories, exports, livestock numbers, crops and use elsewhere H Government policies re acreage set aside, CRP, trade, target or loan prices, etc. less important now.

68. Feeder livestock prices H Why are prices so volatile? H Are there unusual factors which influence their prices?

69. Fed cattle price change H $10/cwt. live weight up = $110/hd. H $110/hd more for feeder steer $110 / 6 cwt. = $18.33 per cwt. for feeder animal; almost twice the impact per cwt.

70. Market hog price change H $5/cwt. price change = $12.50 per head Willing to pay $12.50 more per head for feeder pigs?

71. If input price, what is the effect on feeder cattle or pig price? Example Corn Price Feeder Cattle Price Corn Price Feeder Pig Price Input price impacts

72. Corn price change H Corn price up $1/bushel. H Effect on fed cattle price now? Little, weight effect only? H Effect on fed cattle later? Fewer on feed, weight effect.

73. Corn price change H Feeder cattle effect H Feedlot operators reduce bids to maintain profits near earlier levels 60 bushels of corn=$60/head $60 / 6cwt.= $10/cwt. price drop

74. Technology change H Determine profit change per head or cwt. of final product caused by technology changes in industry H.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

75. Forecast Changes H Would those forecast changes necessarily be accurate? Presumes that feedlot operators look at current price changes and expect similar changes in prices later.

76. Forecast Changes And presumes that the competitive process will bring the related markets back to previous profit levels. And presumes that the competitive process will bring the related markets back to previous profit levels.

77. EndEnd