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The Response of Agricultural Production to Price and Other Factors

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P U R D U E U N IV E R SIT Y

THIS IS TO CERTIFY THAT THE THESIS PREPARED UNDER MY SUPERVISION

BY

Richard. Louis Kohls

e n t it le d

"The Response of Agricultural Production

to Price and Other F a c t o r s ”

COMPLIES WITH THE UNIVERSITY REGULATIONS ON GRADUATION THESES

AND IS APPROVED BY ME AS FULFILLING THIS PART OF THE REQUIREMENTS

FOR THE DEGREE OF

Doctor of Philosophy

P r o fesso r

H ead

April 8

of

in

Ch a r g e

School

or

of

T h e s is

D epartm ent

19 50

TO THE LIBRARIAN:----THIS THESIS IS NOT TO BE REGARDED AS CONFIDENTIAL,

\&vj V

GBAD, SCHOOL FORM ©—3.4 9— 1M

IS TCrklTTOfifiSrVTT T T PBOFESSOH EX B i

THE RESPONSE OF AGRICULTURAL PRODUCTION TO PRICE AND OTHER FACTORS

A Thesis

Submitted to the Faculty

of

Purdue University

by

Richard Louis Kohls

In Partial Fulfillment of the Requirements for the Degree

of

Doctor of Philosophy

lune, 1950

ProQuest Number: 27714156

All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is d e p e n d e n t upon the quality of the copy subm itted. In the unlikely e v e n t that the a u thor did not send a c o m p le te m anuscript and there are missing pages, these will be noted. Also, if m aterial had to be rem oved, a n o te will ind ica te the deletion.

uest ProQuest 27714156 Published by ProQuest LLC (2019). C opyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States C o d e M icroform Edition © ProQuest LLC. ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106 - 1346

ACKNOWLEDGMENTS

This study was prepared under the direction of Dr. Don Paarlberg,

I am deeply indebted to Dr. Paarlberg

for giving so freely of his time and ideas.

Acknowledgment

is also made to Mrs. Rae Sedlet for her assistance in the statistical analysis of the data.

I also wish to express

my appreciation to my wife, Irene, for the preparation of the final draft of the thesis.

TABLE OF CONTENTS Page ABSTRACT........

i

INTRODUCTION..........................................

1

Problem and Purpose of the Study................

4

Procedure and Methodology.......................

6

CHANGES IN ACREAGE OF TRUCK AND SPECIAL CROPS.

.....

13

Factors Associated With Changes in U. S. Acreage of Selected Truck Crops Grown For the Fresh Market.......................

14

Factors Associated with Changes in U. S. Acreage of Strawberries......................

18

Factors Associated with Changes in U. S. Acreage of Potatoes......................

21

Summary of Findings for Truck and Special ........ Crops

28

CHANGES IN ACREAGE OF FIELD CROPS....................

30

Factors Associated with Changes in the U. S. Acreage Planted to Wheat...............

30

Factors Associated with Changes in U. S. ............ Acreage Planted to Corn.

34

Factors Associated with Changes in U. S. Acreage Planted to Oats......................

37

Summary of Findings for Field Crops.............

39

CHANGES IN THE NUMBER OF CATTLE ON FEED..............

42

Factors Associated with Changes in U. S. Numbers of Cattle on Feed... ......

42

Relationship of Corn Production to Cattle on Feed in Different Areas.........

48

Changes in the Quality

of CattleMarketed.

....

32

Summary of Findings for Cattle on Feed ..........

56

TABLE OF CONTENTS (Continued) Page CHANCES IN NUMBER OF SOWS FARROWED...................

57

Factors Associated Numbers of Sows

with Changes in U. S. Farrowed in theSpring.......

58

Factors Associated Numbers of Sows

with Changes in U. S. Farrowed in theFall.........

66

Summary of Findings for Number of Sows Farrowed......................................

74

CHANGES IN THE NUMBER OF LAMBS ON FEED...............

77

Factors Associated with Changes in U. S. Numbers of Lambs on Feed ...................

78

Factors Associated with Changes in Numbers of Lambs on Feed in Different Areas........

84

Summary of Findings for Lambs on Feed............

85

CHANGES IN THE NUMBER OF HENS AND PULLETS ON FARMS....

8?

Factors Associated with Changes in U. S. Numbers of Hens and Pullets on Farms Ianuary 1 .....................................

87

Factors Associated with Changes in Numbers of Hens and Pullets in Different Areas...........

97

Factors Associated with Changes in Volume of U. S. Commercial Hatchery Operations......

98

Summary of Findings for Hens and Pullets on Farms and Commercial Hatchings..............102 CHANGES IN THE LEVEL OF U. S. EGG STORAGE HOLDINGS.... 104 Factors Associated with Changes in the Volume of May 1 and August 1 Egg Storage Holdings.... 105 Summary of Findings for Egg Storage Operations... 112 GENERAL SUMMARY CONCLUSIONS AND APPLICATIONS.......... 114 Summary of Crop Responses.

....................

114

Summary of Livestock and Poultry Responses....... 118

TABLE OF CONTENTS (Continued) Page Some General Conclusions........................

122

Some Possible Applications....................... 126 APPENDIX A:

SOME EXPLORATORY ANALYSIS OF THE RESPONSE OF REGIONAL ACREAGE PLANTED TO VEGETABLES....................

131

APPENDIX B:

RELATIONSHIP OF CHANGES IN PRICE ONE YEAR TO CHANGES IN PRICE THE NEXT YEAR... 136

APPENDIX C :

TABLES OF ESTIMATED AND ACTUAL CHANGES IN PRODUCTION...................

139

FIGURES OF PRODUCTION RESPONSE RELATIONSHIPS...........................

152

APPENDIX D:

BIBLIOGRAPHY.......................................... 163

LISTS OF TABLES AND FIGURES

List of Tables

Indexes of Variability of the Yearly Changes in Acreage and Corrected Price of Selected Truck Crops, 1927-1942....

14

Percent of Variation in U. S. Harvested Acreage of Selected Truck Crops Associated with Several Factors, 1927-1942. ......

15

Effect of Change in Price of the Preceding Year on U. S. Acreage Planted to Selected Truck Crops, 1927-1942...................

17

Percent of Variation in U. S. Strawberry Acreage Associated with Various Factors, 1925-1942................................

20

Percent of Variation in U. S. Acreage of Potatoes Associated with Different Factors, 1925-1942.......................

24

Effect of 10 Percent Increase in December and August Prices on U. S. Intended and Harvested Acres of Potatoes, 1925-1942....

25

Percent of Variation in U. S. Wheat Acreage Seeded Associated with Several Factors, 1922-1942................................

31

Percent of Variation in U. S. Corn Acreage Associated with Several Factors, 1925-1942............................... .

35

Percent of the Variation in U. S. Oats Acreage Associated with Several Factors, 1925-1942................................

38

Indexes of Variability of Different Factors Associated with Changes of U. S. Cattle Numbers on Feed , 1931-1947..... ..........

43

Percent of Variation in Numbers of Cattle on Feed January 1 in the United States Associated with Several Factors, 1931-1947................... .............

44

List of Tables (Continued) Table 12.

13♦

14.

15*

16.

17.

18.

19.

20. 21.

22.

Page Indexes of Variability of Cattle on Feed and Corn Production for Various Areas, 1931-1947...................................

50

Percent of Variation in Numbers of Cattle on Feed January 1 in Various Areas Associated with the Size of the Corn Crop in the Previous Year, 1931-1947............

51

Percent of Cattle Sold Out of First Hands in Chicago Falling Within Various Grades, 1930-1948 ...................................

54

Percent of Variation in the Grade Composition of Chicago Cattle Receipts Associated with the Size of Corn Crop in the North Central States the Previous Year, 1931-1947......

55

Percent of Variation in U. S. Number of Sows Farrowed in the Spring Associated with Several Factors, 1925-1947.................

58

Percent Changes in U. S. Spring Farrowings that would be Associated with Various Changes in Average Corn and Hog Prices.....

62

Percent of Variation in IT. S. Numbers of Sows Farrowed in the Fall Associated with Variation in Several Factors, 1925-1942....

67

Percent Changes in the U. S. Fall Farrowings that would be Associated with Various Changes in Spring Farrowing and Hog Prices..

70

Indexes of Variability of Lambs on Feed January 1, by Regions, 1932-1947...........

77

Percent of Variation in Number of Lambs on Feed January 1 in the United States Associated with Several Factors, 1931-1947 ..................................

78

Percent of Variation in Numbers of Lambs on Feed January 1 inthe United States Associated with Various Combinations of Factors, 1932-1942.........................

80

List of Tables (Continued) Table 23•

24•

25.

26.

27*

28,

29,

30,

31,

32,

33,

Page Relative Importance and Effect of Changes of Various Factors Affecting Changes in U* S. Number of Lambs on Feed, January 1, 1932-1942.......................

82

Percent of Variation in Number of Lambs on Feed January 1 in Different Regions Associated with Variation in Several Factors, 1932-1942.........................

85

Indexes of Variability of Different Factors Associated with Changes of U. s. Numbers of Hens and Pullets on Farms January 1, 1926-1942

88

Percent of Variation in Number of Hens and Pullets on Farms January 1 Associated with Several Factors,1926-1942.............

90

Percent of Variation in IT, S. Numbers of Hens and Pullets on Farms January 1 Associated with Different Combinations of Factors, 1926-1942

91

.Net Relationship of Various Factors to Changes in the Number of Hens and Pullets on Farms, United States,1926-1942.......

92

Percent Changes in U. S, Numbers of Hens and Pullets on Farms the Next January Associated with Various Changes in Chicken and Poultry Ration Prices, 1926-1942........

93

Percent of Variation in Volume of Hatchings February through June Associated with Different Combinations of Factors, 1931-1942..................................

99

Net Effect of Various Factors on the Volume of February-June Hatchings, United States, 1931-1942...................................

100

Percent of Variation in May 1 and August 1 Storage Holdings Associated with Several Factors, 1925-1942..........................

106

Percent of Variation in May 1 and August 1 Storage Holdings Associated with Different Combinations of Factors,1925-1942.........

108

List of Tables (Continued) Table 34.

35.

36.

Page Net Relationships of Various Factors to Changes in the Volume of Egg Storage Holdings, 1925-1942........................

109

Summary of the Significant Relationships and Response of Acreage of Various Crops to ....... Various Price Factors

. 115

Summary of the Significant Relationships and Response of Various Livestock and Poultry to Various Factors.................

119

List of Appendix Tables Appendix A Table 1.

2.

Percent of Variation in Regional Harvested Acreage of Selected Truck Crops Associated with Several Factors, 1927-1942 ....

133

Percent of Variation in Indiana Harvested Acreage of Cantaloup Associated with Various Factors, 1926-1942 .............

135

Appendix B Table 1.

Page

Percent of Variation in Changes of Prices One Period Associated with Changes in Prices of the Same Period the Following Year for Various Commodities, 1926-1942

Appendix C Table

Page

138

Page

1.

Indexes of Variability of Acreage of Selected Crops andNumbers of Livestock, XT. S ..........140

2.

Changes in Harvested Acreage of Various Truck Crops Grown for the Fresh Market as Estimated and as Actually Reported, U. S., 1927-1948.....

141

List of Appendix Tables (Continued) Appendix C Table 3•

4.

5*

6.

Page

Changes in Harvested Acreage of Strawberries as Estimated and as Actually Reported, U. S., 1925-1949............................

143

Changes in Harvested Acreage of Potatoes as Estimated, as Indicated by March 1 Intentions, and as Actually Reported, U. S., 1925-1949............................

144

Changes in Number of Cattle on Feed January 1 as Estimated and as Actually Reported, U . S . and Central States, 1931-1949.......

145

Changes in Number of Sows Farrowed in the Spring as Estimated, as Indicated by December Intentions and as Actually Reported, Ü. S., 1925-1949.................

146

7.

Changes in Number of Sows Farrowed in the Fall as Estimated, as Indicated by June Intentions, and as Actually Reported, U. S., 1925-1949............................ 147

8.

Changes in Number of Lambs on Feed January 1 as Estimated and as Actually Reported, U. S., 1932-1949............................ 148

9.

Changes in Number of Hens and Pullets on Farms January 1 as Estimated and as Actually Reported, U.S., 1926-1949........

149

Changes in Volume of February-June Commercial Chick Hatchings as Estimated and as Actually Reported, U. S., 1931-1948.......

150

10.

11.

Changes in Volume of Egg Storage Holdings as Estimated and as Actually Reported, tl. S., 1925-1948................................... 151

List of Figures

Figure 1.

2.

3*

4#

5.

6.

7.

8.

9.

10.

11.

Page Estimated Compared With Actual Changes in Harvested Acreage of Various Truck Crops for the Fresh Market, U, S., 1927-1948

19

Estimated Compared With Actual Changes in Harvested Acreage of Strawberries, U* S., 1925-1949.............................

22

Estimated Compared With Actual Changes in Harvested Acreage of Potatoes, U. S., 1925-1949...................................

2?

Deviation of Estimated Changes and March 1 Intentions From Actual changes in Harvested Acreage of Potatoes, U. S., 1925-1949...................................

27

Estimated Compared With Actual Changes in Number of Cattle on Feed January 1, IT. S., 1931-1949

49

Estimated Compared With Actual Changes in Number of Cattle on Feed January 1, East North Central States, 1931-1949............

53

Estimated Compared With Actual Changes in Number of Cattle on Feed January 1, West North Central States, 1931-1949..........

53

Estimated Compared With Actual Changes in Number of Sows Farrowing in the Spring, U. S., 1925-1949.............

64

Deviation of Estimated Changes and March 1 Intentions From Actual Changes in Number of Sows Farrowing in the Spring, U. S., 1925-1949...................................

65

Estimated Compared With Actual Changes in Number of Sows Farrowing in the Fall, U. S., 1925-1949...........................

71

Deviation of Estimated Changes and March 1 Intentions From Actual Changes in Number of Sows Farrowing in the Fall, IT. S., 1925-1949..........................

73

List of Figures (Continued) Figure 11♦

12.

13.

14.

Page Deviation of Estimated Changes and March 1 Intentions From Actual Changes in Number of Sows Farrowing in the Fall, U. S., 1925-1949...................................

73

Estimated Compared With Actual Changes in Number of Lambs on Feed January 1, U. S., 1932-1949

83

Estimated Compared With Actual Changes in Number of Hens and Pullets on Farms January 1, IT.S., 1926-1949..................

94

Estimated Compared With Actual Changes in Commercial Hatchings, February-June, 1931-1948

101

15.

Estimated Compared With Actual Changes in Storage Stocks of Eggs on May 1, Ü. s., 1925-1948................................... Ill

16.

Estimated Compared With Actual Changes in Storage Stocks of Eggs on August 1, U. S. , 1925-1948...........................

Ill

List of Appendix Figures Appendix D Figure 1.

2.



Page

Relationship of Changes in Corrected Prices to Changes in Harvested Acreage of Certain Truck Crops One Year Later, U. S., 1927-1942

153

Relationship of Changes in Corrected Prices to Changes in Harvested Acreage of Straw­ berries One, Two, and Three Years Later, U. S. , 1925-1942...........................

155

Relationship of Changes in Corrected Prices to Changes in Harvested Acreage of Potatoes One and Two Years Later, U. S., 1925-1942................................... 156

List of Appendix Figures (Continued) Appendix D Figure 4e

5.



7.

8.

9.

Page

Relationship of Changes in Corn Production to Changes in Number of Cattle on Feed January 1, U. S., 1931-1947................

157

Relationship of Changes in Corrected Corn and Hog Prices to Changes in Number of Sows Farrowed the Following Spring, U. S., 1925-1942.....................

158

Relationship of Changes in Spring Sow Farrowings and Corrected Hog Prices to Changes in Number of Sows Farrowed the Following Fall, U. S., 1925-1942......

159

Relationship of Changes in Various Factors to Changes in Number of Lambs on Feed January 1, U. S., 1932-1942................

160

Relationship of Changes in Corrected Chicken and Poultry Ration Prices to Changes in Number of Hens and Pullets on Farms the Following January 1, U. S., 1926-1942......

161

Relationship of Changes in Various Factors to Changes in Storage Stocks of Eggs, August 1, U. S., 1925-1942.................

162

i

THE RESPONSE OF AGRICULTURAL PRODUCTION TO PRICE AND OTHER FACTORS

(Abstract of Thesis)

This study has been confined to the exploration of the effect of price and other pertinent factors on agri­ cultural production in the short-run— that is, from year to year.

The determination of the existence and degree

of the short-time response of agricultural products is of basic importance to the development of an adequate and useful science of agricultural economics. The degree of response, if any, of production to price and other factors would be of considerable import­ ance to the outlook economist.

Such knowledge would

provide him with tools which could increase the accuracy of his work.

Such knowledge would be of practical import­

ance to the individual farmer in his search for the highest profit combinations for his farm.

Better inform­

ation concerning these responses also is of increasing importance in the formulation of wise agricultural price and production policies. Procedure and Methodology A few commodities were chosen for study in each of the general groups of truck and special crops, field grain

il

crops, livestock and poultry.

In each instance, study

was further limited to that part of production over which the farmer had some measure of year-to-year control. The assumption was made that the best indicator of what prices will be in the future is the level of prices which has prevailed in the past.

It was also assumed

that responses were made not to absolute price changes, but rather to changes in prices relative to those of enterprises which offered alternative opportunities.

It

was further assumed that human nature, technology and available productive factors do not change materially from year to year, and that producers will react in the future much as they did in the past. Simple and multiple linear correlation analysis were used in analyzing the relationships between production and other factors.

Though the many objections to such

analysis were recognized, it was found that a linear relationship was quite representative within the limits of the actual data.

The use of this type of analysis

resulted in numerical relationships which could be applied to other data in a precise manner.

Changes in Acreage of Truck and Special Crops The response of harvested acreage to prices one and two years previous of seven truck crops--cabbage, cantaloup, green peas, onions, snap beans, tomatoes, and watermelons--

ill

was studied• Significant, positive relationships were found for cabbage, cantaloup, onions and watermelons.

In

almost all cases, changes in price of the immediately preceding season were the most closely related to changes in acreage. A 10 percent increase in price of the preceding season resulted in an increase of 2*9 percent in cabbage acreage, 2.3 percent in cantaloup, 1.9 percent in onions, and 2.1 percent in watermelons. Though significant relationships were found for four crops, less than half of the total variation of acreage was explainable by price changes. Prices one, two and three years previous considered together could be used to explain 52 percent of the vari­ ation in strawberry acreage harvested.

In this relation­

ship, prices two and three years previous were most important in explaining the variation in acreage. A 10 percent increase in price one, two and three years previous was , associated with 1.5 percent, 2.9 percent and 2.9 percent increases in acreage, respectively. August prices of the preceding year and December prices two years preceding could be used to explain 57 percent of the variation in potato acreage.

A 10 percent

increase in these two prices were associated with 0.7# percent and 0.65 percent increases in acreage, respectively. August prices were most closely associated with the acre­ age harvested early.

The December prices of two years

iv

previous were most closely associated with the acreage other than early.

These two prices could be used to give

an estimate in September of the change in acreage the next year which compared very favorably in reliability with the next March 1 intentions report.

Changes in Acreage of Field Crops The response of harvested acreage to price of wheat, corn and oats was studied.

Significant positive relation­

ships were found between some measure of price and seeded acreages of fall and spring wheat and the March intended acreage of corn. Changes in the July-September wheat prices of the preceding year and in the March price immediately preceding planting time were associated with 28 percent of the vari­ ability in spring seeded acreage.

Changes in the value

per acre immediately preceding planting and of the pre­ ceding year were associated with 29 percent of the vari­ ability in fall seeded acreage. No significant relationship was found between price and harvested acreage of corn.

However, the November-

January price of corn two years previous was associated with 29 percent of the variability in the March 1 intended acreage. No significant relationships were found between mea­ sures of price and either harvested or intended acreage of oats.

V

Changes In Number of Cattle on Feed The response of cattle production to price from year to year is largely limited to the changes in the number put on feed and the quality marketed.

Several factors

were found to be significantly related to changes in the number of cattle on feed. However, for all practical purposes corn production could be used alone as a reli­ able indicator of the number of cattle on feed the following year.

Two-thirds of the variability in numbers of cattle

on feed January 1 could be accounted for by changes in the corn production of the previous year.

A 10 percent increase

in corn production resulted in a 4 percent increase in cattle on feed.

The consideration of past feeding margins,

feeder-corn ratios and other factors added nothing signif­ icant to the corn-number on feed relationship. When smaller areas were considered, the association of corn production and numbers varied widely.

Seventy-

four percent of the variation in numbers of the West North Central States and 51 percent of those of the Hast North Central States could be explained by corn production in these areas.

The association was not significant for

the areas outside of the North Central Region. Corn production also was an important factor in influencing the quality of cattle marketed.

Changes in

corn production were associated with 41 percent of the changes in the portion of receipts which were of choice

vi

and prim© grades.

A 10 percent increase in corn production

resulted in a 7*9 percent increase in the relative numbers which were of the top grades.

Changes in Number of Sows Farrowed Changes in the number of sow farrowings were consid­ ered as the responsive factor in hog production to be determined largely by management decisions.

Various

combinations of prices were studied relative to changes in spring farrowings.

Changes in September through

November hog and corn prices explained 75 percent of the variation in numbers of sows farrowing in the spring. A 10 percent increase in hog prices resulted in a 2.2 percent increase in sow farrowings; a 10 percent increase in corn prices resulted in a 4.4 decrease in sow farrowings. Over a long period of years, this relationship has compared favorably with the December intentions (which explained 83 percent of the variability) as a method of anticipating the actual changes in spring farrowings. Of the various factors studied in relation to changes in fall farrowings, changes in the number of sows farrowing in the spring and in March-May hog prices were the most important.

These two factors explained 52 percent of the

changes in fall sow farrowings.

A 10 percent increase in

spring farrowings was associated with a 6.9 percent increase in fall farrowings; a 10 percent increase in spring hog

vil

prices resulted in a 5*5 increase in fall farrowings. This relationship has not given as adequate an indication of changes in fall farrowings as have the June intentions (which were associated with 66 percent of the variability in fall farrowings).

Changes in Number of Lambs on Feed Similar to cattle, the response of lamb production from year to year is largely limited to the number of lambs put on feed in the fall and winter. Many factors were studied in relation to the changes in number of lambs on feed January 1.

Only changes in the number of

lambs saved the previous July and the margin of the pre­ vious year between October feeder and March good and choice lamb prices were significantly related to changes in numbers on feed.

When changes in corn production the

previous year were considered together with these two factors, 68 percent of the variation in number of lambs on feed could be explained.

A 10 percent increase in

number of lambs saved resulted in a 12 percent increase in lambs on feed ; a 10 cent increase in margin resulted in 0.3 percent increase of lambs on feed, and a 10 percent increase in corn production resulted in an 0.8 percent increase in lambs on feed.

This same combination of

factors, however, could not be used to adequately explain changes of numbers on feed in the different regions.

viii

Satisfactory estimates of changes using these factors were not secured either for the war period or for the post war period.

The inadequacy of these estimates casts some

doubt over the validity of this method of estimation for future use.

Changes in Number of Hens and Pul le ts on Farms The months of December, January and February were considered as the critical months for factors which affected the number of hens and pullets on farms the next January.

The egg-feed and chicken-feed ratios,

chicken prices, poultry ration prices and corn prices were all significantly related to changes in numbers. However, the price of chickens and the price of the poultry ration considered as two separate factors were the most satisfactory combination found.

These two factors

explained 56 percent of the variability of numbers of hens and pullets on farms the following January.

A 10 percent

increase in chicken prices was associated with a 1.1 percent increase in numbers; a 10 percent increase in poultry ration prices was associated with a 1.9 percent decrease in numbers. The relationship of various factors to the changes in the February through June volume of hatchery operations was also studied.

Both the combinations of egg prices and

ration prices and of chicken prices and ration prices could

be used to explain a high percentage of the variation in hatchery volume (73 percent and 82 percent respectively)♦ Since both of these combinations of factors were so closely related to changes in hatchery volume, it was not safe to conclude that one was considered by farmers more than the other in determining future operations.

Changes in the Level of Egg Storage Holdings The number of hens and pullets on farms January 1, the margin between April-June (into storage period) and October-December (out of storage period) prices of the previous year, and the spread between the October future and the farm price on March 15 were all related to May 1 and August 1 storage holdings.

These three factors consid­

ered together could be used to explain 42 percent of the variability of the

May 1 holdings and 73 percent of the

August 1 holdings.

After eliminating the effect of the

other factors, the

spread between the future and farm

price during Marchexplained the greatest amount

of

the

net variability in May storage. However, the number of hens and pullets on farms January 1 explained the greatest amount of the net variability of August holdings.

It would

appear that though the outlook for profit in the storage operation may be primarily important in determining early operations, the level of production (as indicated by the number of hens and pullets) is most important in influ­ encing the total amount which finally goes into storage♦

X

General Conclusions and Applications Some General Conclusions The short-time supply response of agricultural pro­ ducts studied was quite complex,

A simple price-acreage

or price-numhers relationship which would explain a large proportion of the variability was not found for any com­ modity studied. Price alone is not an adequate indicator of the total crop production to follow.

Since a large portion of the

changes in acreage cannot be explained by price, it follows that price would not be an adequate indicator of total production volume♦ Factors which influence the scale of short-time live­ stock and poultry production are complex.

In many cases,

the level of corn production— or the effect of the level on price— is of prime importance•

By the use of selected

factors, advance estimates of how farmers in the aggregate will respond are possible. The short-time supply response of the various commod­ ities studied was, in general, inelastic in nature. Some Possible Applications Several tools for farmers, trade personnel and econ­ omists which could be useful in production planning and outlook work were developed.

Relationships which would

give some advance indication of acreage changes of cabbage.

xi

cantaloups, onions, watermelons, potatoes and strawberries were found. Advance estimates of considerable accuracy for changes in numbers of cattle and lambs on feed, sows farrowed and hens and pullets could be made from relationships discovered in the study.

Techniques for making advance estimates of

the volume of eggs going into storage were also found. Many of these findings could be of considerable value to the worker in the field of agricultural policy.

This

study points out that the raising or lowering of the rel­ ative price of a commodity will not necessarily increase or decrease the production of that commodity in the short run.

Changes in price alone would not be an adequate

measure to bring about changes in production of a partic­ ular crop.

These conclusions were for a system of rela­

tively free and fluctuating prices and might not apply in a system of guaranteed future prices.

Short-run production

of livestock is tied to many other factors besides price and is closely inter-meshed with crop production.

No part

of the pricing and production mechanism can be adjusted or changed without affecting many commodities in many ways. There also appears to be no basis for the often expressed assumption that as prices decline agricultural production expands.

1

THE RESPONSE OF AGRICULTURAL PRODUCTION TO PRICE AND OTHER FACTORS

INTRODUCTION

Economic theory has long given prime importance to the effect of the actions of the so-called "laws" of supply and demand.

The framework of economic theory

under perfect competition rests to no small extent upon the functioning of the price system through the inter­ actions of supply and demand. Price, under the competitive enterprise system, has the assigned role of allocation of resources*

Within the

framework of scarce resources, price is given the job of rationing out the existing production and of allocating the factors of production to the various types of pro­ ductive effort.

Competitive theory assumes that, working

ideally, price will do its job so that society will obtain maximum want satisfaction with the greatest efficiency and least cost. This study concerns itself with the agricultural supply side of the economic structure.

In a broad sense,

supply might be defined as that production which would be forthcoming in response to a wide complex of motivating factors*

The particular phase of production which would be

2

responsive, in the sense that it could be the result of man’s direction, will vary depending upon the product and upon the length of time being considered.

The complex of

factors to which the response is given will also vary depending upon the product and upon the institutional pattern being considered.

The simple graphic presentation

of this production response usually has been in the form of the classic supply curve which represents that series of amounts which will be offered at each of a series of prices considering a given unit of time• However, the element of time immediately complicates this type of analysis.

In the Marshallian framework of

analysis there are three broad time divisions made :

the

market supply curve which represents the response of amounts already produced and on hand for sale ; the shortrun supply curve which represents the response of amounts which can be produced within the existing framework of productive equipment; and, the long-run normal supply curve which represents the response of amounts over a period long enough for the productive capacity to be changed. i/

within

this framework of response periods, this study is concerned with the short-run analysis. The determination of existence and degree of the short-time response of the production of agricultural products to prices or other important factors is of basic 1/ Marshall, A., "Principles of Economics", eighth edition, Macmillan and Go. Limited, London, pp. 378-380.

3

importance to the development of an adequate and useful science of agricultural economics.

Price has long been

assumed to be the primary factor in the directing of production.

Empirical study of the supply-response of

agricultural production to price is necessary in order to evaluate the validity of this assumption.

If the assumption

is not valid, empirical study is necessary to ascertain the complex of factors to which responses are made* Such knowledge would be of considerable value to the outlook economist.

Since the potential production of a

given commodity is of great importance in predicting the relative prices of commodities, accurate production response data would greatly sharpen the economists’ tools for outlook work*

The degree of response which can be expected under

given conditions would be of use to the individual farmer* It should help the individual farm firm better to allocate its resources among various farm enterprises* Influence upon prices and production of the various government policies is of increasing importance,

supply-

response information is of fundamental importance in evaluating the outcome of these policies.

The impact of

support prices, acreage restrictions and marketingsquotas are directly concerned with the supply-response that farmers make*

k

The Problem and Purpose of the Study Though the aggregate scale of agricultural production is relatively stable from year to year % the production of individual commodities fluctuates considerably♦

Does the

production of individual commodities respond to price and other important factors in the short-run?

If it does,

what is the nature of this response? This field of study has received spasmodic attention during the past two or three d e c a d e s H o w e v e r , very little work has been done in recent years•

Within the

past several years, new data have been collected and improved techniques developed which permit more

compre­

hensive— and possibly more valid--re search * The difficulties of such analysis have long been recognized.

In 1924> John

difficulties♦-2/ He stated

D♦

Black wrote of these

that the large number of

variables in the problem was the chief difficulty* Acreage may be varied for many other reasons than price such as disease, insect damage, changes in prices or in costs of production of competing crops, and technological changes. He further observed that response may be in terms of greater intensity

of

cultural practices aswell

as increased acreages*

F*

Elliott also pointed outthat

P.

2/ Among the fir s t stud1e s demonstrating the response of agricultural production to price was made by H* L. Moore in 1917 ("Forecasting the Yield and Price of Cotton", Journal of Farm Economics, 1917, pp. 86-89). 2/ Black, John D ♦,"Elasticity of Supply of Farm Products Journal of Farm Economics, 1924, Vol. VI, No. 2, page 145.

5

a high price resulting from low yields due to climatic disturbances likely will not result in an increase in production the next year*4/

L. H. Bean in presenting

the results of his rather extensive supply-response studies in 1929 cautioned concerning his results as follows: "--although we shall present rather high degrees of corre­ lation between price and subsequent changes in acreage...* the results should not be taken as a complete explanation of those changes....because variations in price are often highly correlated with such factors as yields, profits per acre, etc., which may affect farmers’ responses ."S./ A recent study of factors which motivated farmers to change their production and marketing of hogs concluded tentatively that other factors, such as the labor supply, feed supply and production facilities, were more important than price .A/

it/ Elliott, f. F . , "The Nature and Measurement of the Elasticity of Supply of Farm Products", Journal of Farm Economics, Vol. 9 » No* 3* H. P. Hartkemeier followed through this idea of weather influencing production in a study of potatoes and corn with only a limited degree of success ("The Supply Function For Agricultural Commodities", University of Missouri Studies, 1932, Vol, VII, No* 4)• j>/

Bean, L. H*, "The Farmers’ Response to Price", Journal of Farm Economics, 1929, Vol* XI, No* 3, p. 369.

6/

"An Exploration of Factors Motivating Eog Farmers in Their Production and Marketing", Bureau of Agri. Econ., U.S.D.A., August, 1947.

Because of these many possible ramifications in the factors to which farmers respond, this study in many instances concerned the relationship of factors other than price to production.

In doing so it strives to

advance answers to the questions of the nature and amount of the short-time supply response. Procedure and Methodology No comprehensive study was made of any one commodity or group of commodities.

Instead a few were chosen in

each of the general groups of truck and special crops, field grain crops, livestock and poultry.

Study was

further limited to only that part of production over which the farmer had some measure of year to year control. Therefore, in the case of crops, total production was not considered, but rather intended acreage or acreage har­ vested .

In the case of livestock, cattle on farms or pigs

raised were not studied, but rather cattle on feed and sows farrowed•

The basic data were obtained from the many

sources of agricultural economic statistics with which the worker in this field is familiar. The theorectical supply price has been defined as that price the expectation of which would call forth a given supply*2/ 27

However, farmers work within an economic

Cassels, J. M . , "The Nature of Statistical Supply Curves", Journal of Farm Economics, 1933 > Vol. XV, No.

7

framework of uncertain future prices*

In this analysis,

the assumption was made that the best indicator that farmers have of what prices will be in the future is the level of prices which has prevailed in the past* It was recognized that the validity of this assump­ tion was open to question.

Upon testing, it was found

that generally the amount and direction of price changes of one year were not significantly related to the amount and direction of changes the following year. is presented in Appendix B*

This work

However, there probably is

no other indicator of future prices which is as univer­ sally available to the farmers as a guide.

There is

reason to believe that if the farmer does use prices as a guide, he turns for information to the immediate past* The periods which were considered as critical in determining the farmers’ plans were the marketing or harvest periods and periods immediately preceding planting or breeding times.

In all cases, efforts were made to use

periods far enough in advance of the time in which the farmers’ intentions must be put into effect to facilitate the use of the findings in prediction work*

This prohib­

ited the use of ”seasonal average prices” for many commod­ ities in which the season extended from one harvest period to the next* It was also assumed that responses usually were not to absolute price changes, but instead to changes in the prices relative to those of enterprises which offered

8

alternative opportunities*

Therefore, in most situations,

prices were measured relative to the level of all prices of competing enterprises.

For example, truck crop prices

were corrected by the truck crop index, since the oppor­ tunity to plant another kind of truck crop was assumed to be considerable.

Because an intimate knowledge of each

area and its opportunities was not available, in most instances, the study considered only the aggregate United States response to average United States prices.

With

some exceptions, this aggregate analysis does not limit the usefulness of the results.

With most of our crops

and livestock, the total supply available on a national basis is the important factor.

Only in the case of a

perishable commodity in which different regional pro­ duction comes to the market at different times does the aggregate analysis lack in its applicability. The assumption also was made that human nature, technology, and available productive factors do not change materially from year to year, and that producers will react to given situations in the future much as they did in the past.

Unless this assumption is valid, results

from such studies as this would be useless as tools for estimation and outlook work* In analyzing the relationships between production and other factors,simple or multiple linear correlation analysis was used.

It is recognized that many theoretical

9

objections can be raised to the results of such an analysis. One principal objection to the use of this method is that it assumes linear relationships.

Depending on the particular

relationship, this means that at zero price some production would still be forthcoming, or no production.

This of

at

course is

some price there wouldbe not in accordance withthe

theoretical concept of the supply curve which holds that no production would be forthcoming at zero price and that with infinitely higher prices there would be infinitely increasing production.

However, much of the data of this study fluct­

uated from year to year

within rather narrow limits.

the actual data limits,there was

Within

ample evidence that a

straight line relationship was quite representative. Another objection to linear multiple correlation is that it assumes the effects of the independent variables on the dependent variable to be separate and additive.

This

assumption is rarely completely true in empirical economic work.

However, careful consideration of the extent of inter­

relationship should prevent unwarranted conclusions. However, there are aspects to the use of linear cor­ relation which are definitely advantageous and which prob­ ably outweigh the disadvantages.

The use of linear simple

or multiple correlation results in a numerical result which can be applied to other data in a precise manner.

The

mathematical mechanics and explanation of the findings are much easier to comprehend than those of many other types of correlation.

10

In preparation for analysis, all data were converted to percentages of the preceding year.

This procedure has

the advantage of eliminating all but the most severe trends. It also converts all variables to a common denominator which greatly facilitates later application. Some researchers believe that it is desirable to discard those years in which the data are erratic and to use only the more uniform cases in order to increase the significance of the resuits.5/ followed♦

This practice was not

All cases were Included which fell within the

period under consideration.

Since such response actually

did occur, it was felt that it must be considered as part of the evidence of the study if the results were to be representative.

However, correlations in which prices

were involved did not extend to include either the World War I or II periods, since distortions of price patterns were considerable during those periods.

However,

in order to ascertain their value as tools for prediction purposes, estimates were made from these correlations through World War II and the immediate post war period * In presenting correlation results, the coefficient of determination was used (r^ or

).

This is a concrete

measure of the proportion of variability of the dependent variable which was associated with variation in the 8/

Mighel, R. L. and Allen, R. H . , MSupply Schedules— Long-time and Short-time” , Journal of Farm Economics, Vol. 2XII, No. 3, 1940, page 544*

11

Independent variable or variables.— ^

As such, it has

more meaning than the correlation coefficient (r or R ) . All results are noted if they are significant at the 95 percent level of probability. In presenting the variability of data, the index of variability was used.

This index is the coefficient

of variability based on the standard deviation of the percentages that the respective years were of the pre­ ceding years.

Because of the uniformity of method used

in presenting data as a percentage of the preceding year, direct comparison of these indexes is possible.

The

larger the index the greater the variability. Finally, it is recognized that significant corre­ lation results do not imply a cause and effect relation­ ship.

They merely state the degree of relationship

between the independent

and dependent variables.

However,

if the independent variables logically and theoretically could be causal and the relationship is statistically significant, responsible research should take a stand. 9/

Hartkemeier, H. f ., ôp. cit., explains the coefficient of determination as follows : "R2 measures the proportion by which the square of the standard error of estimating the dependent variable has been reduced by the use of the equation. If the relationship given by this equation were not known and no other correlation used, only one estimate could be given--the arithmetic mean of the factor, and the reliability of this estimate is measured by the standard deviation. The use of the equation to estimate the factor reduces the square of the standard deviation by R2 percent” .

12

In this study when the criteria of logic, theory and statistical significance are met, the independent vari­ ables are presented as "explaining” the dependent variable. None of these "explanations” however, is advanced either as the only or as the complete explanation, but rather as a useable hypothesis.

13

CHANGES IN ACREAGE OF TRUCK AND SPECIAL CROPS

Many of our commercially grown truck crops are marketed either to the consumer as fresh produce or to the processor for canning purposes.

This study

considered only that acreage which was grown for the fresh market.

The contracting mechanism of many of our

processors greatly influences the acreage that the farmer will plant to individual crops.

The factors affecting

acreage under these circumstances are not covered in this study. Most of the acreage data used were those of acre­ age harvested, since intended acreages or acreage planted were not available.

This does not present a strictly

accurate picture of how the farmers intended to respond to certain factors because weather conditions at planting time may have changed early planting intentions, or other developments during the growing season or at harvest time may have led to the abandonment of acreage already grown. The attempt was made to measure the aggregate acre­ age response to average seasonal prices.

This use of

annual acreages and the average seasonal price had its limitations.

Truck crop production is not a situation

of a large production area having a single marketing season, but rather different production areas with a series of marketing seasons.

Many of our fresh truck

14

crops come to the market early in the year from the southern areas, and as the season progresses, other geographic regions come into the picture.

Each of these

areas with its own set of alternate opportunities and prices presents individual acreage response problems which are not considered in this study.iS/ Factors Associated With Changes in U. S. Acreage of Selected Truck Crops Crown For the Fresh Market The U. S. acreage harvested and the corrected seasonal price of various truck crops varied consider­ ably from year to year.

In all cases the variation in

price was considerably greater than the variation in acreage (Table 1)• Table 1,

Indexes of Variability of the Yearly Changes in Acreage and Corrected Price of Selected Truck Crops, 1927-1942.

Crop

Index of Variability

Cabbage Cantaloup Creen Peas Onions Snap Beans Tomatoes Watermelons

10/

Acreage

Price

16 9 15 15 10 11 12

37 20 20 40 13 19 26

Some exploratory analysis was made of regional pro­ duction responses. The results of this work are given in Appendix A*

15

These changes in acreage from year to year were studied in relation to changes in the seasonal average price the farmers received.

The prices were studied

relative to the average TJ. S* Truck Crop Price Index for the year*

Table 2.

(Table 2)

Percent of Variation in U. S. Harvested Acre­ age of Selected Truck Crops Associated with Several Factors, 1927-1942.

Crops and factors

Percent of variability associated with factor

Cabbage : Price preceding year Price two years preceding Price preceding year and two years preceding

54* 13

Cantaloup: Price preceding year Price two years preceding Price preceding year and two years preceding

27* 3

Green Peas: Price preceding year Price two years preceding Price preceding year and two years preceding

2 0

Onions: Price preceding year Price two years preceding Price preceding year and two years preceding Snap Beans: Price preceding year Price two years preceding Price preceding year and two years preceding Continued

54*

51*

4 27* 33* 9 9

16

Table 2.

Continued•

Crops and factors

Percent of variability associated with factor

Tomatoes: Price preceding year Price two years preceding Price preceding year and two years preceding

1 2

Watermelons: Price preceding year Price two years preceding Price preceding year and two years preceding

23* 2

2

28

* Statistically significant at the 95 percent or better probability levels.

Relationships close enough to be considered statistically significant were found for cabbage, canta­ loup, onions and watermelons. Relationships found for green peas, snap beans and tomatoes were so small that they easily might have occurred from chance alone.

In

almost all the cases, changes in price of the immediately preceding season were the most closely related to changes in acreage.

In all cases, the changes in price two years

preceding the planting were not significantly related to acreage changes.

Only in the ease of cantaloups did the

consideration of the price of both the preceding season of the two years preceding increase considerably the amount of acreage variability explained.

17

The fact that price changes of the preceding season were more closely related to acreage changes than still earlier price changes is not illogical.

Changes in

planting of crops of this type can .he done quickly. Rotation patterns in vegetable production are not as rigid as in grain operations. The changes in acreage which occurred in response to a 10 percent increase in the price of the preceding season are given in Table 3 •

Cabbage acreage was the

most responsive ; onion acreage the least.

The responses

of cantaloup and watermelon acreages were quite similar to each other.

Table 3»

Effect of Change in Price of the Preceding Year on TJ. S. Acreage Planted to Selected Truck Crops, 1927-1942.*

Crop

Cabbage Cantaloup** Onions Watermelons *

Percent increase in acreage with a 10% increase in price 2.9 2.3 1.9 2.1

Only those which had a significant relationship are considered • ** When both the preceding year and the second preceding year were considered a 10 percent increase in the price of preceding year resulted in a 3*5 percent acreage increase ; a 10 percent increase in the second preceding year in a 2.5 percent increase.

18

The acreage changes of cabbage, cantaloups, onions and watermelons which were estimated from the price changes were compared with actual changes which occurred over a period of 21 years (Figure 1).

Since less than

half of the total variation of acreage of these crops was explainable by price changes, a highly accurate estimate of the changes which actually occurred could not be expected.

However, in most cases, the estimate

was a good indication of the direction of change which occurred. During the war years of the 1940* s , acreages fluctuated more violently than during the pre-war period. With the exception of cabbage, the estimates of change during this period were still less reliable than for the earlier years.

It was not possible to tell whether the

relationships of the pre-war period would be adequate for the post-war period• Factors Associated with Changes in U. S. Acreage of Strawberries The acreage planted to strawberries and the corrected price received for them fluctuated considerably from year to year.

The indexes of variability for the period 1925-

1942 were 12 and 18 for acreage and price respectively. Strawberry prices were corrected by the IT. S. index of crop prices for June.

Relationships were found between

acreage and corrected prices received for the preceding season and for two and three preceding years. (Table 4)

19

Percent of Previoua Year Cabbage

HO Actual—

120

Estimated

100

80 120

Cantaloup

100

‘Estimated xZ

80 160

Onions

HO Estimated

120 100

80

Ho

Watermelon

120 100

‘Estimated

80 1927

1930

Figure 1,

1935

1950

Estimated Compared With Actual Changes in Harvested Acreage of Various Truck Crops for the Fresh Market, U.S., 1927-1943.*

* For data and relationships see Appendix C, Table 2

20

Table 4,

Percent of Variation in U, S. Strawberry Acreage Associated with Various Factors, 1925-1942♦

Factor

Percent of variability associated with factor

Price preceding year Price two years preceding Price three years preceding Prices for one and two years preceding Prices for one, two and three years preceding

2 26* 24* 27 52*

* Statistically significant at the 95 percent or better probability levels* Though the price received during the preceding season was not closely related to acreage changes, prices received for the second and third preceding years were closely associated with acreage changes*

This amount of lag is

no doubt due to the nature of strawberry cultivation. Plantings do not reach full production until two and three years after planting.

When prices for the three

preceding years were considered together over one-half of the total variability in acreage could be explained* When considered in their net effects, a 10 percent increase in price one year previous resulted in a 1.5 percent increase in acreage; a 10 percent increase in price two years previous in a 2*9 percent increase in acreage; and a 10 percent increase in price three years previous in a 2*9 percent increase in acreage.

21

Changes in acreage which were estimated from changes in price of the preceding three seasons were compared with the changes which actually occurred (Figure 2). During the 25 years considered, the estimated direction of change was right 18 times.

During the decade of the

thirties, the estimates were a good indication of the amount of actual change as well as the direction.

During

the war period, this price relationship resulted in a series of poor estimates. Factors Associated with Changes in TJ. 5, Acreage of Potatoes U, S, acreage of potatoes fluctuated somewhat less from year to year than the other truck and special crops studied.

The index of variability for the period 1925-

1942 was 8,

However, in studying the response of acreage,

total U. S. acreage was divided into the acreage of the early commercial crop and all other potato acreage except that for the early crop.— /

When acreage data were con­

sidered in these two categories, the index of variability 11/

These two figures are not exactly comparable. Data are available for the early commercial acreage, but not for the total late commercial acreage. The data for all other potato acreage were obtained by sub­ tracting the early acreage data from the TJ. S, total acreage data. This means that some early acreage which was not grown for commercial sale is included in the all other potato acreage data. However, these data probably are an adequate indicator of changes in late potato acreage.

#

22

Percent of Previous Year 130

120

Estimated-^/ /

no 100

30 70 1925 Figure 2.

1930

1935

Estimated Compared With Actuel Changes in Harvested Acreage of Strawberries, U.S., 1925-1949**

* For data and relationships see Appendix C, Table 3*

1950

23

of the early acreage was considerably greater than that of the remaining acreage (14 as compared to 7)« Since 1924, data concerning the March 1 intentions of farmers to plant potatoes have been available as well as data concerning the total acreage harvested.

Inten­

tions give a more accurate picture of the response of farmers to factors influencing their decisions than does acreage harvested, since acreage harvested is influenced by weather and other factors outside the control of the farmer.

For the period 1925-1942, March 1 intended acre­

age has been associated with 60 percent of the variability in actual total acreage harvested, price Both the August price and the December/were studied in relation to the harvested acreage and intended acreage. The August price was used as indicative of the price at which the early crop was sold and also as a price which partially reflected the size of the coming late crop.

The December

price was used as indicative of the price at which the bulk of the late potato crop was sold.

In all cases,

prices were corrected by using the U. S. index of crop prices (Table 5). Changes in the August price of the preceding year could be used to explain a highly significant amount of the variability in the early commercial acreage harvested. Changes in neither the preceding December prices nor the December prices of two years preceding were significantly

24

associated with changes in the early acreage.

Using the

August price alone, more than three-fifths of the changes in early acreage the next year could be explained.

With

a 10 percent increase in August prices, early commercial acreage the following year increased 2.0 percent (Table 6). Table 5*

Percent of Variation in U. S. Acreage of Potatoes Associated with Different Factors, 1925-1942.

Factor considered

Percent of variability associated with factor

Early Commercial Acreage Harvested December price preceding year December price two years preceding August price preceding year August price and December price, preceding year

19 4 63* 63*

All Other Acreage Harvested Except Early December price preceding year December price two years preceding 35* August price preceding year 13 August price preceding year and December price two years preceding 46* Total U. S . Acreage Harvested December price preceding year December price two years preceding August price preceding year August price preceding year and December price two years preceding

36* 24* 57*

March 1 Intended U. S . Acreage December prTce preceding year December price two years preceding August price preceding year August price preceding year and December price two years preceding "

-— .

m —

50* ■- ,

■—

■■■.,

i ■■—

- ......

.

y

37* 16

.

Statistically significant at the 95 percent or better probability levels.

24A

Changes in the December price two years preceding were most closely associated with the variability in the acreage of potatoes harvested excluding the early crop acreage.

Dec­

ember prices of the previous year had little or no relation­ ship to acreage changes.

August prices of the previous year

were associated with only a small amount of the variability of the late acreage.

December prices two years previous to­

gether with August prices of the previous year could be used to explain over two-fifths of the variability of the late acreage harvested « December prices of the previous year had little or no relationship to either intended acreage or total acreage harvested.

December prices two years previous, however, were

associated with 38 percent of the variability of intentions and with 36 percent of variability of the acreage harvested. August prices of the previous year were associated with a smaller amount of the variability.

The association of August

prices to total acreage changes was due largely to their relationship to changes in the acreages planted for the early crop*

The lack of association of the previous December

price and the considerable association of the December price of two years preceding probably indicated that the later acreage was tied in with crop patterns which could not be changed substantially between December and the immediately following planting period. The most satisfactory explanation of variability in both intended and total harvested acreage was found by

25 Table 6*

Effect of 10 Percent Increase in December and August Prices on U. S. Intended and Harvested Acres of Potatoes, 1925-1942»

Factor considered

Percent increase In acreage with a 10 percent increase in factor*

Early Commerical Acreage Harvested August price preceding year

2.0

All Other Acreage Harvested Except Early December price two years preceding August price preceding year

0.65 0.56

Total U. S. Acreage Harvested December price two years preceding August price preceding year

0.65 0.78

March 1 Intended Acreage December price two years preceding August price preceding year

0.57 0.54

gross relationship, the effect of each factor is shown as measured after the effect of the other factors has been eliminated. considering December prices two years previous and August prices one year previous.

This combination explained 50

percent of the variability in intended acreage and 57 percent of the variability in harvested acreage.

The amount of change

in acreage relative to changes in price is shown in Table 6. This combination of appropriate December and August prices explained 57 percent of the variability in total acreage harvested.

This explanation compared very favor­

ably with the March intentions report(which was associated with 60 percent of the total acreage harvested variability) as an indicator of the number of acres to be harvested. However, acreage estimates using this relationship have the

26

added advantage of being available in the September prior to next years planting Figure 3 compares the estimatedchanges with the changes which actually occurred.

In only twoyears during

the period 1925-1949 was the estimated direction of change in error.

The estimations were poor during 1943, 1944,

and 1947.

Much of this discrepancy probably was due to

the government programs affecting both price and acreage. In Figure 4 the deviations of both the estimated and the March intended acreage from the actual harvested acreage are shown.

Both the estimated and intended acre­

age changes were slightly less than the actual harvested acreage during the early 1930*3; both were usually a little high during the latter part of the 1930* s.

Both

were poor indicators of actual harvested acreage during some of the war and post war years. 12/

Pubols, Ben H. and Klaman, Saul B. found that 76 percent of the variation of U. S. potato acreage har­ vested could be explained by the seasonal average price, which had been corrected by the index of prices received, one and two years preceding. (Farmer’s Response to Price in the Production of Potatoes 1922-41**, B.A.E., U.S.D.A,, July 1945). However, this relationship is somewhat false as a measure of the response of farmers in planning their acreages, since the seasonal average price extends from July through June. This means that some of the prices included were not available until after much of the planting had been completed. Thus, this relationship is not useful as a tool for anticipating acreage change in advance of planting. It does con­ firm, however, the tendency of potato acreage to be quite responsive to price changes during the preceding two years. The study also found that practically the same amount of the variability in acreage harvested could be explained by the corrected seasonal prices one and two years preceding for 18 surplus late states (73 percent) and Idaho (71 percent).

27

Percent of Previous Year

120

Actual—

110 100 Es time ted 80

1930 Figure 3»

1950

1935

Estimated Compared With Actual Changes in Harvested Acreages of Potatoes, U.S., 1925-1949•*

* For data and relationships see Appendix C, Table 4«

Percentage Points 15 Intentions-

10

t

iii fpf

1 "a

JEUL

1

-5

i I n]

-10 -15 Estimate-

-20 -25 1925

J

Figure 4-

I I 1930

1----1____I____ ___

*

I

'

I___ I --- u 1935

J I L 1940

1945

1950

Deviation of Estimated Changes and March 1 Intentions From Actual Changes in Harvested Acreage of Potatoes, U.S., 1925-1949.*

* For data see Appendix C, Table 4*

28

Summary of Findings for Truck and Special Crops The degree of relationship between price and acreage changes varied widely among the nine truck and special crops studied♦

The acreage changes of six were signifi­

cantly related to price changes.

Over one-half of the

acreage variability of cabbage, cantaloup, strawberries and potatoes was associated with price changes♦ No significant relationships were found between the acreage changes and price of green peas, snap beans and tomatoes. Changes in price the preceding season were the most important in explaining the variability in acreage of cabbage, cantaloup, onions and watermelons•

Price changes

for periods prior to the preceding season contributed very little toward explaining acreage changes of these crops• Prices changes one, two and three years previous all added to the explanation of the variability in straw­ berry acreage♦ A measure of prices during the two pre­ ceding years were important in explaining the changes in potato acreage.

Changes in December prices two years

previous along with changes in the previous August prices gave a September indication of the total harvested potato acreage which was, for all practical purposes, as accurate as the next March 1 intentions report. The differences in response time lag of from one to three years, no doubt, were due to the differences in the nature of the crop itself and also the flexibility of the

29

management situation under which it was grown.

Most

truck crops probably can be quickly substituted for one another and for other crops.

This apparently is not as

true in the case of either strawberries or potatoes. There are many factors which influence the volume of production of a given crop.

Acreage planted and harvested

is one of the few over which the farmer has some measure of control.

The relationships found between price and

acreage indicated that, in many instances, farmers attempted to adjust production to price by increasing or decreasing the acreage devoted to a particular crop. This does not assert that total production is responsive to price.

Total production is influenced by many factors

other than acreage. Even in most cases in which a signif­ icant price-acreage response relationship was found, the amount of acreage variability explained was not enough to give a highly accurate indication of this one factor influencing production. The small degree— or apparent lack--of response of the acreage of some crops to price changes does not necessarily mean that farmers were working against their best interests.

Only if the price changes of the previous

period were good indicators of the future would farmers lose by not responding properly to that change. Exploratory analysis indicates no significant relationship between the price changes one year and the price changes the following year for these crops (See Appendix B ) .

30

CHANGES IN ACREAGE OF FIELD CROPS

The total yearly production of a crop depends on the acreage planted and the yield per acre.

Some of the

factors affecting yield, such as rate of fertilization and intensity of care given to the growing crop, are subject to the control of the farmer• However, many of these factors affecting yield, such as weather, are largely beyond the control of the farmer.

The decision

of how many acres are to be planted to each crop is probably the most important single decision influencing crop production which is under the control of the farmer. Even this decision may be changed at planting time by weather conditions which do not permit the farmer to carry out his original plans.

Therefore, in this study

the intentions to plant as well as the harvested acreage were considered as measures of the responsiveness of different crops to price change. Factors Associated with Changes in the U. S. Acreage Planted to Wheat The acreage planted to wheat in the U. S. is composed primarily of two different plantings— that sown in the fall and that sown in the spring.

Acreage seeded data are the

best indication available concerning what, the farmers intended to do.

Even these data could be distorted by

weather conditions which prevailed at planting time.

31

The total acreage seeded to wheat in the U. S* does not fluctuate greatly from year to year♦

The index of varia­

bility for the total acreage seeded for the period 1922 through 1942 was 8; that for fall acreage 9, and that for spring acreage 12* The relationship of changes in prices and other factors to changes in acreage were tested.(Table 7) Table 7*

Percent of Variation in U* S* Wheat Acreage Seeded Associated with Several Factors, 19221942*

Factor or combination

Percent of variability associated with factor

Total Seeded Acreage Corrected July-September prices one and two years preceding Actual July-September prices one and two years preceding Spring Seeded Acreage Corrected July-Septemtier prices one and two years preceding Corrected July-September prices preceding year and corrected March price of planting year Value per acre preceding year and corrected March price of planting year** Fall Seeded Acreage Corrected July-September price of same year and preceding year Corrected July-September price same year, one year and two years preceding Value per acre same year and preceding year** Value per acre same year, one year and two years preceding** *

7 4

8 28* 25

15 17 29* 29

Statistically significant at the 95 percent probability levels. ** Value per acre = corrected luly-September price times the yield of fall or spring wheat per acre.

32

The United States average wheat prices for the period July through September were used as representative of the price at which the bulk of the wheat crop was sold and also of the price situation immediately before fall planting,

March prices were used as an indicator of the

price situation immediately before spring planting.

Most

prices were corrected by the U. S. index of crop prices for the corresponding period. Neither corrected nor actual wheat price for one or two years prior to planting was significantly related to the U. S. seeded acreages. Corrected prices during the previous marketing season together with the corrected price immediately prior to planting were associated with 28 percent of the variability of spring wheat acreage.

This relationship was close

enough to be statistically significant.

Of these two

factors changes in the March price were the most important. With the effect of the other factors eliminated, changes in March prices explained 27 percent of the net varia­ bility; changes in the July-September price only 7 percent of the net variability.

Both factors in their gross

relationship were positively related to acreage.

However,

in their net relationships a 10 percent increase in the July-September price was associated with a 2.0 percent decrease in acreage ; a 10 percent increase in March price

33

was associated with a 4.3 percent increase in acreage*13/ The July-September price, which represented both the price at harvest and also immediately before planting time, considered either for two or three preceding years was not significantly associated with changes in the acreage seeded in the fall*

However, when a measure of

the per acre value of the fall crop was used instead of price alone a significant relationship was found *

This

would imply that the success or failure of the preceding crops was a factor in influencing the farmers’ decisions* Changes in the per acre value for the year of the seeding and for the preceding year were associated with 29 percent of the variability in acreage• statistically significant*

This relationship was

The additional consideration

of the second preceding year did not add to the explanation* With the effect of the other factor eliminated, acre value changes immediately preceding planting explained 16 per­ cent of the net variability; value changes the previous year, 26 percent of the net variability*

In their net

effects, a 10 percent increase in acre value Immediately preceding planting resulted in a 1*9 percent increase in 13/

Warren, G* F * , and Pearson, F* A., (Cornell Bulletin 466, "Interrelationship of Supply and Price", page 68) found a somewhat similar relationship between Decem­ ber 1 corrected prices for one and two years previous and acreage of spring wheat in North Dakota for the years, 1892-1915♦ These factors were associated with 28 percent of the change, The study also found that price of the second preceding year had more effect on acreage than did price the first preceding year*

34

acreage; a 10 percent increase in acre value of previous year resulted in a 2.4 percent increase in acreage• Though significant relationships were found which would substantiate the assumption that acreage seeded does respond to price or acre value changes, the relation­ ships did not explain enough of the variability to be of much value in predicting the amount of change.Üt/ Factors Associated with Changes in TJ. S * Acreages Planted to Corn The March 1 intentions to plant corn are probably the best available measurement of how farmers desired to respond to price or other factors.

The acreage harvested

is a less reliable measure since various factors beyond the farmers’ control both during and after planting time may have resulted in a different response than was origin­ ally intended.

The difference between intentions and

results is illustrated by the fact that for the period 1925 through 1942, changes in March 1 intentions to plant were associated with only 48 percent of the changes in 14/

Lyon, L. S. and Rossieur, T. E . writing in the Journal of Political Economy, Vol. 32, No. 6, December, 1924» page 707» on the "Price Responsive­ ness of Wheat Growers" concluded that spring wheat acreage is more influenced by price changes than winter wheat acreage. They pointed out that winter wheat growers are little influenced by price changes at any time, but spring wheat growers are definitely influenced by price both at the time of planting and during the 13 preceding months. These researchers used tabular analysis of percent change in acreage and different price periods for the years 1896 to 1920.

35

acreage harvested.

Though neither fluctuated greatly,

planting intentions fluctuated less from year to year than did the acreage harvested♦

The index of variability

of intentions for the period 1925-1942 was 4 while the index for harvested acreage was 7» In exploring relationships, the United States average corn price received by farmers during the principal market­ ing months of November through January was used.

Most of

the prices were corrected by the average U. S# index of crop prices for the corresponding period, (Table 8) Table 8,

Percent of Variation in U, S* Corn Acreage Associated with Several Factors, 1925-1942*

Factor or combination

Percent of variability associated with factor

March 1 Intended Acreage Corrected NovemBer-January prices for the preceding year 2 Corrected November-January prices for two years preceding 25*** Corrected November-January prices for one and two years preceding 25 Corrected November-January prices for the one, two, and three 32 preceding years Value per acre one and two years 18 preceding** Acreage Harvested Corrected November-January prices for 8 the one and two years preceding year 3 Corrected March-April prices of the same * The period 1922 to 1942 was used for acreage harvested, ** Value per acre equals corrected November through January price times average yield, ***Statistically significant at the 95 percent probability levels.

36

The only significant relationship was between prices and the intended acreage two years later.

When price in­

creased 10 percent the intended acreage two years later increased 0.7 percent.

The consideration of two or three

preceding years did not yield relationships which were significant.

Changes in value per acre did not give a

significant relationship.

The relationship of the March-

April pre-planting price was not significant.

The hog-

corn ratio of the previous year, studied as a measure of the demand for corn, was not related to acreage changes. Though it can be said that farmers did intend to respond to price, the relationship was not close enough to permit satisfactory predictions. Relationships between harvested acreage and price were not significant.

Since there was some interference with

acreage plans during the thirties, the period 1922-1942 was divided into two shorter periods 1922-1932 and 19331944 for study.

Though prices for the two preceding years

explained somewhat more of variability in the acreage harvested (13 percent) during the earlier period than during the later period (5 percent), neither relationship was close enough to be considered significant. The U. S. acreage harvested was then broken down into the North Central States acreage and the acreage of all other states.

The relationship between price and acreage

changes was too small to be significant in both instances.

37

When the acreage considered was limited to a smaller area with price data refined to consider the most important alternate opportunities in the area, there was reason to believe that different relationships would result•iS./ , However, only 19 percent of the variability in the plant­ ing intentions of Indiana farmers were associated with changes in Indiana November-December prices of the two preceding years which were corrected by the Indiana index of grain prices•

Only 15 percent of the acreage harvested

was associated with these factors.

Neither of these

relationships was close enough to be significant. Factors Associated with Changes in U. S. Acreage Planted to Oats As with corn, March 1 acreage intentions were prob­ ably the best measure of the farmers’ response to price or other factors.

For the period 1925 through 19A2,

changes in intentions and changes in acreage harvested have not been significantly related.

Actual acreage

harvested varied more from year to year than did intended acreage.

The index of variability for harvested acreage

was 11; that for intended acreage, 5* 15/

Warren, G. P. and Pearson, F. A., op. cit., page 51, for the period 1895 to 1913 found that changes in the corrected December Iowa corn price for the three preceding years was associated with 36 percent of the variability in Iowa corn acreage ; however, the price of corn was associated with only 9 percent of the variability in Texas corn acreage and only 3 percent of the Kansas acreage, 1902 to 1926.

38

The average U. S. farm prices for the principal marketing months of July through September were used. These prices were corrected by the appropriate index of U. S. crop prices.

The resulting relationships are

shown in Table 9* Table 9*

Percent of the Variation in U. S. Oats Acreage Associated with Several Factors, 1925-1942*

Factor or combination

Percent of variability associated with factor

March 1 Intended Acreage Corrected July-September prices one and two preceding years Corrected July-September prices one, two, and three preceding years

23

Acreage Harvested Corrected July-September prices one and two preceding years Corrected July-September prices one, two, and three preceding years

24

*

26

26

The period 1922-1942 was used for acreage harvested. None of the above relationships was close enough to

be considered statistically significant.

The second pre­

ceding year was the most closely associated with varia­ bility in both intended and harvested acreage.

The

relationships with price changes of the previous year were extremely small.

There was also no relationship

between changes in the previous February prices and March 1 intentions♦

39

Because of the outside interference with acreages of some crops during the thirties, the period 1922-1942 was broken into two periods, 1922-1932 and 1933-1942. Price changes during the two preceding years were assoc­ iated with 24 percent of the harvested acreage variability for the period 1922-1932 and with 37 percent of the varia­ bility for the 1933-1942 period. However, considering the short length of the series, these relationships could not be considered significant. Summary of Findings for Field Crops Many of the factors which influence the production of grains are outside the individual* s control.

The

principal response which the individual farmer can make to favorable or unfavorable situations is by planting more or fewer acres to a particular crop.

Even his intentions

to plant and harvest may be thwarted by unfavorable weather conditions♦ Significant, positive relationships were found between some measure of price and seeded acreages of fall wheat, spring wheat and the March intended acreage of corn.

Changes in March prices immediately before

planting time were most important in explaining spring wheat acreage changes.

Changes in price considered along

with yields for the two preceding harvest.periods were significantly related to changes in fall wheat acreages. Changes in the price during the second preceding harvest

40

period were the most important factors in explaining changes in the intended corn acreage.

Though no signif­

icant relationship to either intended or harvested oats acreages was found, the closest relationship found was with the price during the second previous harvest period. The time lag in the responses of field grain acre­ age to price was different from those of vegetable crops* In vegetable crops, the price of the preceding season was the more important in explaining acreage changes.

In

field crops, the price of the second preceding season was the more important.

Much of this difference is probably

due to the difference in cropping practices of these two types of crops*

Most of our field crops are grown in

rotation with other crops or under management practices which cannot be immediately changed with ease* Considering the results of the crops studied, it could not be said that prices of a particular crop guided U, S. aggregate production of that crop in the short run. The association of price with acreage variability was so small that no satisfactory prediction of either intended or harvested acreage could be made.

Since acreage is only

one of many variables influencing total production, it would logically follow that no reliable prediction of aggregate production could be made* From this it cannot be concluded that price does not influence production*

However, in the short run the

41

Influence is very small.

It does not necessarily follow

that this lack of short time responsiveness worked against the farmers’ better interests.

Only if past price changes

were accurate indicators as to the future price situation would the lack of responsiveness work against the farmer. There is evidence that past price behavior of a particular crop was not an accurate guide to the future.

Neither

the changes in November-December corn prices, nor the changes in July-September oats and wheat prices of one year were significantly related to price changes of these crops the following year.

(See Appendix B)

42

CHANGES IN THE NUMBER OF CATTLE ON FEED

The response of cattle production to price from year to year is largely limited to the changes in the number and quality of cattle in the feed lots*

Changes in over­

all cattle numbers on farms occur in a slower and more regular fashion.

These longer time cyclic and secular

changes are not considered in this analysis*

Farmers

must make yearly decisions as to whether they will expand or contract their feeding operations•

These decisions

affect to a considerable extent the quantity and quality of beef which is available for consumption in any one year*

Therefore, any factor or factors which are closely

associated with changes in the numbers of cattle on feed and are measureable in advance of the feeding period would be of considerable value to both the individual farmer and the trade* Factors Associated with Changes in U* S. Numbers of Cattle on Feed The number of cattle on feed January 1 in the United States has changed as much as 45 percent from one year to the next*

Various factors were studied in relation to

these changes to determine which might be important in influencing the farmer to increase or decrease his feeding operations. year.

All of these factors fluctuated from year to

From Table 10, it can be seen that the price margin

43

was the most variable of any of the factors*

All factors

varied more than the number of cattle which were put on feed • Table 10*

Indexes of Variability of Different Factors Associated with Changes of U* S. cattle Numbers on Feed, 1931-1947*

Factor considered

Index of variability

U, S. Cattle on feed ü* S, Corn Production plus October carry-over U. s* Corn Production October feeder-corn ratio, Chicago Margin between October feeder and May good cattle prices, Chicago** Margin between October feeder and May choice cattle prices, Chicago** October feeder prices, Chicago**

12 22 27 39 69 60 22

*

With the exception ofthe price margins which are in cents per cwt*, these indexes are coefficients of vari­ ability based on standard deviations of the percentage that each year was of the preceding year* ** Corrected for the changes in prices received by U* S. farmers* The relationship of the various factors to changes in numbers of cattle on feed are shown in Table 11, Corn pro­ duction, considered separately, was more closely related to the number changes than was the measure of total corn supply, production plus carry-over factor*

Variation in

U* S* corn production alone was associated with two-thirds of the total variability of the number of cattle on feed. When corn production increased 10 percent, numbers of cattle on feed increased 4 percent.

44

Table 11.

Percent of Variation in Numbers of Cattle on Peed January 1 in the United States Associated with Several Factors, 1931-47.

Factor considered

Percent of variability associated with factor*

U. S. Corn Production plus October carry over, previous year U. S. Corn Production, previous year** October feeder-corn price ratio, Chicago Margin between October feeders and May Good Cattle, Chicago, previous year*** Margin between October Feeders and May Choice Cattle, Chicago, previous year*** October Feeder Prices****

58 66 43 35 32 67

*

All results are significant at the 95 percent or better probability levels. ** Corrected 8eptember~Novem.ber average corn prices explained only 26 percent of the variability for the period 1931-42. This was not significant. *** The margin was corrected for the change in price level by using the January 1 index of prices received by U. S. farmers. The uncorrected margin gave slightly higher correlations. The differences were not signif­ icant, however. **** Corrected by the October index of prices received by U. 8. farmers. The October feeder-corn price ratio was studied as a measure of the cost of feeders as compared with the price of corn.

The month of October was used as representative

of the time of the year when farmers usually make their feeding decisions.

The relationship of this ratio to

cattle numbers was highly significant.

When the ratio

increased 10 percent (100 pounds of feeders would purchase more bushels of corn) cattle on feed increased slightly more than 2 percent.

However, 76 percent of the changes in the

45

feeder-corn price ratio could be explained by changes in corn production.

The feeder-corn price ratio was,

for all practical purposes, another measure of changes in corn production. The margin between October feeder prices and the May prices of good and of choice cattle was used as a measure of the profitableness of the previous year*s feeding operation.

Changes in the amount of margin

between October feeders and May good cattle explained 35 percent of the changes in numbers on feed ; the margin between October feeders and May choice cattle, 32 percent# As the margin between October feeder and May good cattle prices (corrected by the 1935-39 index of prices received levels) increased 10 cents per hundred pounds the number of cattle on feed increased 0.5 percent. Changes in the corrected October feeder prices were associated with changes in numbers of cattle on feed in a highly significant manner.

However, this association

probably was a result of other relationships.

It was not

logical to conclude that high feeder prices caused an increase in numbers of cattle on feed.

It would be more

in accordance with cattle feeding practice to assume that an increased corn crop increased the farmers’ desire to feed more cattle.

This situation would result in an

increased demand, and therefore a higher price, for feeder cattle.

This reasoning was substantiated by the high

46

degree of relationship between corn production and feeder cattle prices♦

Changes in corn production were

associated with 46 percent of the changes in October feeder cattle prices*

With an increase of 10 percent in

corn production corrected feeder prices increased 5 per­ cent. The changes in the index of prices received by farmers from October to October were used as a measure of general price level movement.

No significant relation­

ship was found between changes in the price level and changes in the number of cattle on feed. Similarly no significant relationship was found between the number of all cattle on farms and the number of cattle put on feed the next year.

The number of all

cattle on farms did not effectively act as a limiting factor of cattle going on feed probably because of the 11two way” possibilities of a part of our cattle supply* When the demand for feeders is active, many of this type of cattle may move into feed lots ; when the feeder demand is slight, they may move as slaughter cattle.

This means

that a relatively flexible supply of feeders can be made available from a given number of cattle on farms. The combined effect of three of the more important of these factors was related to changes in number of cattle on feed the following year.

The three factors

considered were the U. S. corn production, the October

47

feeder-corn price ratio and the margin between October feeder and May good cattle prices*

This combination of

factors was associated with 71 percent of the variability of numbers of cattle on feed• The feeder-corn ratio added nothing of significance to the explanation of number variability.

The feeder-corn

explained only 2 percent of the remaining variation in numbers on feed after the effect of corn production and margin was eliminated.

In fact, the corn crop and margin

considered without the feeder-corn ratio were associated with the same amount of the variability in numbers on feed, 71 percent, as when all three were considered. The margin in prices explained only 15 percent of the remaining variability in numbers on feed after the effect of corn production was eliminated. a significant addition.

This was not

When considered separately in

their gross effects, these other factors were significantly related to numbers on feed ; however, when considered in their net relationships they explained no significant part of the variability in numbers.

For all practical purposes,

corn production could be used alone as a reliable indicator of the number of cattle on feed the next year.JLâ/ 16/

To further substantiate this, the relationship of the margin and the North Central states corn production to numbers on feed in the North Central region was studied. The margin contributed nothing to the explan­ ation of number variability after the effect of corn production was eliminated•

48

The changes of U. S. cattle on feed January 1 which were estimated from the corn production of the previous year were compared with the actual changes which occurred, 1931-1949 (Figure 5)•

The estimated direction of change

was correct in sixteen of the nineteen years considered. The poorest results were obtained during the war years, 1940 through 1945♦

During this period, with one exception,

actual numbers increased more than the estimated change• During this period, the liquidation of the accumulated feed stocks of the late 1930’s probably led farmers to expand more than in the past.

In the periods both pre­

ceding and following these years, the estimated and actual changes have moved closely together.

For the three post­

war years, 1947, 1948, and 1949, estimates were within 4 percent of the actual changes which occurred » The Relationship of Corn Production to Cattle on Feed in Different Areas Cattle feeding operations in the United States are carried on under a wide variety of feed and farm manage­ ment conditions.

In some areas, the operation is a

marginal one while in others it is an integral part of the farm organization.

Though variation in U. S. corn

production explained two-thirds of the variation in U. S* cattle numbers in feed, this relationship was not valid for different areas. The great bulk of the cattle feeding operations are

49

Percent of

130 120 110 100

/ Estimated 80 Actual 70 1931

1935

1940

1950

Figure 5. Estimated Compared With Actual Changes In Number of Cettie on Feed January 1, 9.8., 1931-1949•* * For data and relationships see Appendix C, Table $.

50

carried on in the North Central States,

Even within this

region feeding operations are carried on with different degrees of dependence on corn.

Cattle numbers on feed and

corn production fluctuate with different degrees of magni­ tude in the different areas (Table 12). Table 12.

Indexes of Variability of Cattle on Feed and Corn Production for Various Areas, 1931-1947. dattie on Feed

Corn Production

United States

14

27

North Central States West North Central States East North Central States All States except North Central

15 18 10 17

36 48 27 17

Indiana Iowa Nebraska

12 14 33

29 43 53

Areas

The relationship of corn production to cattle on feed also varied among areas (Table 13).

The size of the corn

crop explained a greater amount of the variation in cattle on feed in the North Central States than either in the IT. S. as a whole or in the states other than this area. An increase of 10 percent in the corn production of the North Central area resulted in an increase of more than 3 percent in the number of cattle on feed.

The degree

of fluctuation in corn production of the other states outside this area was much less, and the association of corn production to numbers on feed was not significant.

51

These findings further substantiated the importance of the size of the corn crop in explaining the number of cattle on feed•

The close relationship found in the

North Central States and the lack of relationship in the rest of the U* S. corresponded logically with feeding practices in these areas♦ Table 13•

Percent of Variation in Numbers of Cattle on Feed January 1 in Various Areas Associated with the Size of the Corn Crop in the Previous Year, 1931-1947.

Area considered for cattle and corn production

Percent of Percent increase variability in cattle numbers associated with with a 10 percent corn production increase in corn __________________________________________ production_______

United States

66

4*2

North Central States West North Central States East North Central States All States except North Central States

71 74 51

3*3 2.9 2.4

13*

0.4*

Iowa Indiana Nebraska

75 44 10*

2.7 2.6 1.8*

*

Relationships are not statistically significant. Within the North Central region there was a consid­

erable difference

between the eastern and western areas.

In the East North

Central States bothcorn production and

the number of cattle fed fluctuated considerably less than in the West North

Central States•

corn production explained

In the eastern section,

only a little more than one-half

52

of the variation in numbers of cattle on feed.

In the

more variable western section corn production explained almost three-fourths of the total variation. These differences were further emphasized when indi­ vidual states were considered.

In Iowa, a state in which

corn is of primary importance but whose production fluct­ uates considerably, changes in the corn production explained 75 percent of the variability of numbers on feed.

In

Indiana, another state in which corn is also of great importance but whose production is somewhat more stable from year to year, corn production explained only 44 per­ cent of the fluctuations in cattle on feed.

In Nebraska,

a state which has both range and corn belt characteristics and whose corn production is very erractic, no significant relation was found. Figures 6 and 7 compare the changes which were esti­ mated from the corn-number relationships for the East and West North Central States with the actual changes which occurred♦ Changes in the Quality of Cattle Marketed The quality of the cattle sent to market varies con­ siderably from year to year.

The quality of cattle sold

out of first hands at Chicago was used as a measure of this change (Table 14).

The index of variability of the

percentage of these cattle which were choice or prime was 43; for good grades, 13; for medium grades, 21; and for

53 Percent of Previous Year

130

A^— Actual

120

— Estima ted

110 100

1950

1935 Figure 6 ,

Estimated Compared With Actual Changes In Number of Cattle on Feed January 1* East North Central States, 1931-1949

* For data and relationships see Appendix C, Table 5« Percent of Previous Year

150

140

4,— Es time ted

130

120 110 100

80

1931 Figure 7#

1935

1950

Estimated Compared With Actual Changes in Number of Cattle on Feed January 1, West North Central States, 1931-1949**

* For data end relationships see Appendix C, Table 5*

54

common grades 45#

The top and bottom grades showed the

greater fluctuation while theproportion which were good or medium fluctuated much less. Table 14*

Percent of Cattle Sold Out of First Hands in Chicago Falling Within Various Grades, 1930-194#*

Year

Choice and Prime percent

1930 1931 1932 1933 1934

13.7 12.1 13.5 19.2 23.6

41.6 44.5 37.6 48.1 49.1

33.8 33.0 35*6 23*6 19.2

10.9 10.4 13.3 9.1 8.1

1935 1936 1937 193# 1939

14.1 29.1 18.3 31.3 28.4

51.8 38.4 47.2 46.4 46.6

25.3 24*9 26.1 19.0 21.4

8.8 7.6 8.4 3.3 3.6

1940 1941 1942 1943 1944

26.7 30.8 22.1 2-7*9 16.8

45*6 44.7 51.3 49.4 56.4

24.0 22.2 24.8 20.7 22.3

3*7 2.3 1.8 2.0 4.5

1945 1946 1947 1948

36.0 31.3 18.1 21.1

46.2 45.0 51.9 55*4

15.8 22.4 27.7 19.4

2.0 1.3 2.3 4.1

Source :

Good percent

Medium percent

Common percent

Livestock Market News, Statistics and Related Data, U.S .D.A., P.M.A.

The size of corn crop of the North Central States (which makes up the large bulk of the area shipping to Chicago) was related to the variations in grades(Table 15)* More than two-fifths of the changes in the proportion of the choice and prime cattle receipts can be explained by

55

changes In corn production.

When corn production increased

10 percent, the relative numbers of top grade cattle increased 7-9 percent.

Relationships with none of the

other grades were close enough to be significant.

Though

the relationships of the other grades were not close, it was logical to believe that the negative nature of these relationships was valid.

An increase of 10 percent in

corn production resulted in a 3*3 percent increase in the number of cattle on feed in the North Central States (Table 13), and a 7.9 percent increase in the proportion of the Chicago receipts which were choice and prime.

This

was strong evidence that the proportion of the other grades, especially those grading medium or better, would be decreased. Table 15.

Percent of Variation in the Grade Composition of Chicago Cattle Receipts Associated with the Size of Corn Crop in the North Central States the Previous Year, 1931 to 1947.

Grade

Choice and Prime Good Medium Common *

Percent of variability explained

Percent the proportion of cattle included in the specified grade changed with 10 percent increase in corn crop

41 15* 15* Y*

7.9 -1.4* -2.1* -3.0*

Not statistically significant.

56

Summary of Findings For Cattle on Feed Many different factors when considered separately can be used to explain considerable amounts of the variation in cattle numbers on feed• However, corn production explained more of the number changes than any other single factor, and when these other factors are combined with corn production little or no additional explanation is gained♦ Changes in U. S. corn production can be used to explain two-thirds of the changes in II* S. cattle numbers on feed. However, when smaller areas were considered, the association of corn production and numbers varied widely.

The U. S. relationship is not strictly applicable

to the North Central States, nor that of the North Central States to the East North Central States, nor that of the East North Central States to individual states. Changes in corn production were also associated closely with changes in the proportion of the cattle which were marketed in the choice and prime grades. The size of the corn crop generally is known in the fall prior to the purchase of feeder cattle.

This means

that some knowledge of the size of the forthcoming feeder operations and of the degree of finish that these cattle will carry can be available at this time.

The alert

farmer could use this advance information in planning his operations so as to make the most of his particular sit­ uation.

These relationships can also furnish a more

refined tool for more accurate agricultural outlook work in cattle marketing.

57

CHANGES IN NUMBER OF SOWS FARROWED Because of the relatively short time required to increase or decrease hog numbers, the ability of hog pro­ ducers to react to short-time changes in various factors is quite great.

However, since the size of the pig crop

can be influenced by factors outside the control of the farmer, change in the number of sow farrowings rather than change in the number of pigs raised or the number of hogs marketed is considered the responsive factor to be deter­ mined largely by management decisions. The number of sows farrowed in any one year is made up of those which farrowed in the spring and those which farrowed in the fall.

The number of sows farrowed in the

spring fluctuated somewhat less from year to year than the number farrowed in the fall.

The index of varia­

bility for the total annual number of U, S, sow farrow­ ings was 14; for the number of U, S. spring sow farrow­ ings, 14; and for the number of U. S. fall sow farrowings, 17•

The changes in number of spring and fall sow farrow­

ings in any one year may be in the same or opposite directions.

In order to study the short-time response of

hog production, factors associated with changes in both spring and fall farrowings were studied.

58

Factors Associated with Changes in U. S. Numbers of Sows Farrowed in the Spring Decisions to increase or decrease the number of sows which are to farrow in the spring must be made in the late fall and winter.

The months of September, October, and

November probably are the critical months during which the farmer must make his decision.

Various factors for this

period were studied in relation to the number of sows farrowed the following spring (Table 16). Table 16.

Percent of Variation in TJ. S. Number of Sows Farrowed in the Spring Associated with Several Factors, 1925-1947♦ Percent of variability associated with factor

Factor considered

u. S. corn production previous year

35

u. S. average hog-corn ratio, previous September-November

59

u. S. average hog prices, previous September-November**

19*

Ü. S* average corn prices, previous Sep tember-November* *

63

* **

Not statistically significant. All other relationships are highly significant. Corrected by the average September-November index of prices received by TJ. S. farmers. The period is for the years, 1925-1942. Changes in IT. S. corn production alone were associated

with 35 percent of the variation in the numbers of sows farrowed in the spring.

When corn production increased

59

10 percent the number of sows farrowed the following spring Increased 3*3 percent* Changes In the average hog-corn ratio during the months of September through November were associated with nearly three-fifths of the variation in spring farrowing numbers.

The ratio during these months reflected two

factors in which the farmer was then very much interested-the price he was receiving for his current pig crop and the size of the new corn crop*

An increase in the ratio

of 10 percent resulted in a 3*5 percent increase in farrowings the following spring.iZ/ When the hog-corn ratio was broken down into its component parts, hog prices and corn prices, it was found that the changes in the corrected corn price could explain more of the variability in spring sow farrowing than the ratio itself.

The relationship of corrected hog

prices to sow farrowings was not close enough to be sig­ nificant. 17/

The effect of the hog-corn ratio on some phase of hog production has received the attention of many researchers. F. F. Elliott studied the response of hog producers in different sections of Illinois. (Illinois Station Bulletin 293, "Adjusting Hog Production to Market Demand", 1927)* He found that 72*1 percent of the variation of Chicago hog receipts, 1898 to 1916, could be accounted for by changes in the hog corn ratio considered for various preceding periods. 0. V. Wells, using graphic mul­ tiple correlation, found a close relationship between the change in hog slaughter and the hog-corn ratio for one and two preceding years. ("Farmer’s Response to Price in Hog Production and Marketing", Technical Bulletin 359, U.S.D.A., 1935).

60

The relationship of different combinations of these factors to the variability in spring sow farrowing was studied• TJ. S. corn production considered together with the hog-corn ratio was associated with 66 percent of the variability in spring farrowings.

However, the inter­

relationship between corn production and the ratio was great.

The consideration of corn production did not

explain any significant part of the net variability after the effect of the ratio was eliminated. TJ. S. corn production, when considered together with the corrected hog price, was associated with 40 percent of the variability of spring sow farrowings. After the effects of the corn production were eliminated, the amount of the net variation in sow farrowings associated with hog prices was not significant. The greatest amount of the variability in spring sow farrowings was explained by considering corrected September through November TJ. S. corn price and corrected September through November TJ. S. hog price as two independent variables.

These two factors acting together explained

75 percent of the total variability.

The statistical

significance of the two individual parts was appreciably greater than their combined affect when treated as a ratio (75 percent compared to 59 percent).

The use of a

ratio automatically assigns equal importance to its components.

In this case, the two components were not of

61

equal importance.

After eliminating the effect of hog

prices, corn prices accounted for 69 percent of the remaining variability in spring sow farrowings.

However,

hog prices were associated with only 32 percent of the net variability after eliminating the effect of corn prices. Corn price changes affected spring sow farrowings more than hog price changes.

A 10 percent increase in

corrected corn prices resulted in a 4.4 percent decrease in sow farrowings; a 10 percent increase in corrected hog prices resulted in a 2.2 percent increase in sow farrowings. Even though the gross relationship of corn production to farrowings was considerably less than that of corn price to farrowings (see Table 16), there is reason to believe that physical corn supplies are of major basic importance. There is a high degree of correlation between corn supply changes and corn prices.iÊ/ 18/ Be K. Meeker, Department of Agricultural Economics, Purdue University, in an unpublished study (MAn Economic Analysis of Price Support Programs with Particular Reference to Corn” ) found that corn supplies and the price level explained 87 percent of the variability in corn prices. With the effect of the price level elim­ inated, supply explained two-thirds of the net varia­ bility in corn prices. Also, a study conducted by G-. Bui ter and R. N. Weigle (nBig Corn Crop Means More Hogs in 1949” , Economic and Marketing Information for Indiana Farmers, November 194$) found that 46 percent of the variation in spring sow farrowing in Indiana could be. explained by changes in the preceding year’s corn supply. A 10 percent increase in corn supply resulted in a 5 percent change in spring sow farrowing. The relationship between the Indiana hog-corn ratio of the preceding fall with Indiana spring sow farrow­ ings was not statistically significant.

62

Griven changes in the average corrected corn and hog prices for the preceding September through November would result in changes in spring sow farrowings as shown in Table 17. Table 17*

Percent Changes in U. S. Spring Farrowings That Would be Associated with Various Changes in Average Corn and Hog Prices*

Percent changes in corrected Sept. to Nov. corn prices from preceding Sept. to Nov.

Percent changes in corrected Sept. to Nov. hog prices from preceding Sept. to Nov.

-15

-10

10

-5

15

Percent change in spring sow farrowings _________ from preceding spring_________ -15 -10 - 5 0 5 10 15 *

3*3 1.1 -1.1 -3*3 -5*5 -7.7 -9.9

4*4 2.2 0 -2.2 -4*4 —6 .6 -8.8

5*5 3*3 1.1 —1.1 -3.3 -5.5 -7*7

6.6 4*4 2.2 0 -2.2 -4*4 -6.6

7*7 5*5 3*3 1.1 -1.1 -3*3 -5*5

8.8 6.6 4*4 2.2 0 —2 *2 -4*4

9.9 7.7 5*5 3*3 1.1 -1.1 -3*3

When corrected corn prices and corrected hog prices are considered together, a 10 percent increase in corrected corn prices was associated with a 4*4 percent decrease in sow numbers; a 10 percent increase in hog prices with a 2.2 percent increase in sow numbers• Seventy-five percent of the variation in number of sows farrowed in the spring was explained by these two factors, making this a highly significant relationship. The estimates of spring sow farrowing changes made

from changes in the corn and hog prices are compared to the actual changes which occurred in Figure 8.

Estimates

were in opposite directions from the actual changes for only three of the twenty-five years during the period

63

1925 through 1949»

The poorest estimations occurred

during the periods 1929 through 1932 and 1942 through 1943 *

The first period occurred during the very dis­

ruptive early years of the great depression. period was during the World War II period.

The other During the

war period changes which actually occurred were greater than those which were estimated.

Much of this was prob­

ably due to the disruption of the price mechanism by O.P.Ae and the utilization of large pre-war corn stocks. Since 1925, the TJ.S.D.A. has published farmers’ intentions to breed sows for spring farrowing in the December pig crop report.

These intentions to farrow

were associated with 83 percent of the actual changes in sows farrowed which occurred the following spring. The changes in corn prices and hog prices were like­ wise related significantly to farmers’ intentions to farrow.

These two factors were associated with 63 percent

of the variation in farmers’ intentions (compared to 75 percent of the variation in numbers actually farrowed). Here again corn prices were associated with much more of the net variability (56 percent) than hog prices (18 percent). Both the average September-Hovember corn and hog prices and the December intentions were excellent guides to the number of sows farrowed the next spring.

The

deviations of the estimates and the announced intentions from the actual farrowings were measured (Figure 9).

u

Percent of Previous Year 130 120

U0 100

^--Estimated

BO 70 1930

Figure 8.

1935

1950

Estimated Compared With Actual Changes in Humber of Bows Farrowing in the Spring, U.S., 1925-1949.*

* For data end relationships see Appendix C, Table 6.

65

Percentage Pointe f Intentions Estimate

-20

-

1925

1930

1935

1940

1945

1950

Figure 9« Deviation of Estimated Changes and March 1 Intentions From Actual Changes in Number of Sows Farrowing in the Spring, U.S., 1925-1949.* * For data see Appendix C, Table 6*

66

In a few years, large errors were made by both indicators in foretelling the number of sows to farrow.

Prior to

about 1935* the report on farmers* intentions had an upward bias, and was often wrong. accuracy has improved considerably.

Since that time, Excepting this, there

did not appear to be any logical pattern in the errors. For some years, the best results were obtained by esti­ mation from the corn and hog prices ; for others the announced December intentions were the better guide.

In

any case, an estimate based on prices would be available at least a month before the U.S.D.A. report on farmers’ intentions and in time for farmers to alter the scale of their operations.

Factors Associated with Changes in U. S . Numbers of Sows Farrowed in the Fall Decisions to increase or decrease the number of sows which are to farrow in the fall must be made no later than in the late spring.

Various factors which

might affect the farmers* decision of how many sows to breed for fall farrowings were studied. given in Table 18.

The results are

67

Table 18.

Percent of Variation in U. S. Numbers of Sows Farrowed in the Fall Associated with Variation in Several Factors, 1925-1942*

Factor considered

u. u. u.

Percent of variability associated with factor

S. corn production, previous year

3**

S. hog-corn ratio, SeptemberNovember , previous year

19

S. hog-corn ratio, March-May compared with year previous

27

u.

S. average hog prices, SeptemberNovember , previous year

u.

S. average hog prices, March-May, compared with year previous

u.

S. average hog prices, March-May, compared with previous SeptemberNovember

y**

16**

Ü.

S. average corn prices, March-May, compared with year previous

5**

Ü.

S. average corn prices, March-May, compared with previous SeptemberNovember

y**

u. * **

S* spring sow farrowings

25

Except for corn production and the ratios which cover the period 1925-47• All prices used are corrected by using the level of prices received by U. S. farmers. Results are not statistically significant. Corn production of the previous year was not signif­

icantly related to fall sow farrowings•

Changes in the

size of the current year’s crop normally will have little effect, since its size is unknown at the time when most of the sows are bred♦

Both the hog-corn ratio of the previous

fall and in the spring were significantly related to

68

changes in numbers.

However, the average ratio from

March through May, when a considerable proportion of the hogs produced during the previous fall were being sold and when sows were being bred for fall farrowing, was the more important.

Changes in the spring hog-corn ratio

were associated with 27 percent of the changes in fall numbers.

Changes in neither hog prices nor corn prices

when treated separately were closely associated with changes in numbers.

Changes in the number of sows farrowed

in the spring were associated with one-fourth of the varia­ bility of fall farrowings.

It was evident that the factors

which could be used to explain changes in spring farrowings could not satisfactorily be used in the same manner to explain changes in fall farrowings. The factors, spring sow farrowings, corrected hog prices during March through May compared with the previous fall, and corrected corn prices during March through May compared with the previous fall, taken together were associated with 54 percent of the variation in fall sow farrowings.

However, after the effect of the number of

sows farrowed in the spring and the corrected hog prices was

eliminated, the corrected corn price did not explain

a significant proportion of the remaining net variation. The two factors, spring sow farrowings and corrected March-May hog prices compared to average prices during September-November explained 52 percent of the total

69

variation in fall sow farrowings.

Therefore, for all

practical purposes, corn prices added nothing to the explanation.

Spring farrowings explained 43 percent of

the net variability after the effect of hog prices was eliminated.

After the effect of spring farrowings was

eliminated, corrected hog prices explained 36 percent of the remaining variation in fall farrowings. Evidently the decisions of farmers with respect to their spring farrowings are also important in determining the number of sows to farrow in the fall.

It would

appear that when farmers see the size and price of the new corn crop, they make a basic decision for both the next spring and fall farrowings.

Changes in the price

situation in the spring may influence them to modify these earlier decisions for fall farrowings somewhat* However, basic changes will not be made until the fall when the size of the new corn crop is known.

A 10 percent

increase in spring farrowings was associated with a 6.9 percent increase in fall farrowings.

A 10 percent

increase in corrected spring hog prices over the preceding fall was associated with a 5.5 increase in fall farrowings. Given changes in spring sow numbers and spring hog prices would result in changes in fall sow farrowings as shown in Table 19*

70

Table 19.

Percent Changes in the U* S. Fall Farrowings that would be Associated with Various Changes in Spring Farrowing and Hog Prices*

Percent changes in corrected March to May hog prices from preceding Sept. to Nov. -15 -10 - 5 0 5 10 15 *

Percent changes in spring sow farrowings _____ from preceding spring__________ -15

-10

10

-5

15

Percent change in fall sow farrowings _________ from preceding fall_________ -18.5 -15 *8 -15.0 -10.3 - 7.6 — 4.8 - 2.1

-15.1 -12.4 - 9.6 - 6.9 — 4*2 — 1.4 1.3

-11.6 - 8.9 - 6.1 - 3.4 - 0.7 2.1 4*8

—8.2 -5.5 -2.7 0 2.7 5.5 8.2

—4 •8 -2.1 0.7 3.4 6.1 8.9 11.6

-1.3 1.4 4.2 6.9 9.6 12.4 15.1

2.1 4.8 7.6 10.3 13.0 15.8 18.5

When spring farrowings and corrected hog prices were considered together, a 10 percent increase in corrected hog prices was associated with a 5•5 percent increase in fall farrowings; a 10 percent increase in spring farrowing was associated with a 6.9 percent increase in fall farrowings. Fifty-two percent of the variation in number of sows farrowed in the fall was explained by these two factors. This was a highly significant relationship. The estimation of changes in fall farrowing were

made from these factors and compared with the actual changes which occurred for the period 1925 through 1949 (Figure 10).

In six of the twenty-five years of this

period the estimates of change were in the opposite direction from that which actually occurred♦ In many of the cases in which the estimates were in the wrong direction or in which the estimates were con­ siderably different from the actual farrowings (more than

71

Percent of Previous Year 130 120

no 100

Estimate \ 80 70

1925 Figure 10,

1930

1935

1950

Estimated Compared With Actual Changes in Number of Sows Farrowing in the Fall, U,S,, 1925-1949•*

* For data and relationships see Appendix C, Table 7,

72

one standard error of estimate, 7*4 percent), corn pro­ duction for that same fall changed considerably over the previous year *

In years in which the corn production

increased considerably, the estimates of change were low, for example in 1931, 1932, 1935, and 1948.

In years in

which the corn production decreased considerably, the estimates of change were high, for example in 1930, 1933, 1934, 1936, and 1947.

This situation probably indicates

late adjustments to the current situation.

In years in

which the new corn crop was larger more sows were bred later in the season.

In years in which the new corn crop

was smaller, bred sows were marketed before farrowing. This could explain the relatively poor estimates during the early 1930*s which were years of extremely erratic corn production. The TJ.S.D.A. fall farrowing intentions which were published in June were associated with 66 percent of the

/

variability in actual farrowings for the period 1925 through 1947.

Figure 11 shows the deviations of the

estimates and the announced intentions from the actual changes in fall farrowings.

Excluding the earlier years

in which intentions were consistently high, farmers’ intentions have been a better indicator than the estimation from spring farrowings and hog prices.

However, June

intentions reports are made available too late for the farmer to adjust his scale of operations.

An estimate

73

Percentage Points

1950 Figure 11.

Deviation, of Estimated Changes and March 1 Intentions From Actual Changes in Number of Sows Farrowing in the Fall, U.S., 1925-49**

* For data see Appendix C, Table 7.

74

based on price and the number of spring farrowings, though not as accurate as the intentions report, could be avail­ able at an earlier date. Summary of Findings for Number of Sows Farrowed In studying the short-time response of the U. S. numbers of sows farrowed it was necessary to consider factors associated with changes in spring farrowings and in fall farrowings separately.

Of these two, the number

of sows farrowed in the fall fluctuated most. Several single factors were found to be associated significantly with variation in the number of sows farrowed in the spring.

The two factors, U. S. average corrected

hog prices and U. S. average corrected corn prices for the period September through November, explained 75 percent of the total variation in the number of sows farrowed in the spring.

Of these two factors, corrected corn prices was

the more important.

Since variations in corrected corn

prices were closely associated with variations in the corn supply, it was logical to assume that corn production indirectly was one of the main factors influencing the expansion or contraction of sow farrowings. Variations in fall farrowings were more difficult to explain.

The most satisfactory combination of factors,

the number of sows farrowed in the spring and the average corrected March through May hog prices compared with prices the previous September through November, could be used to

75

explain 52 percent of the fall farrowing variation. Spring corn prices or corn production of the previous year had little or no relationship to fall farrowings. Because of the tendency for fall farrowings to change in the same direction as the spring farrowings (opposite changes occurred in only 4 out of 24 years), it would seem that the basic decisions for both spring and fall farrowings are made in the late fall of the previous year.

At this time the size of the corn crop is known

and feeding plans are made.

If relative hog prices change

in the spring, adjustments may be made in the fall breeding schedules.

But it seems that, in most cases, the fund­

amental decisions for fall farrowings are made along with the decisions for spring farrowings, and a drastic change from these is unusual. The surveys of farrowing intentions released in December and June have over the years been somewhat more closely associated with the actual number of sows farrowed than have the estimates made with the above factors.

In

most cases the estimates and intentions have moved fairly closely together.

However, such estimates could be made

available in advance of the intentions reports.

Any

conditions which would hinder the market place from accurately appraising the corn and the hog situation through relatively free prices will make the estimations of farrowing from these factors less accurate.

Some of

these conditions could be large government crop loan operations, price control, or exceptional disturbance of the market through strikes..12/

19/

A survey study has been made by the Bureau of Agri­ cultural Economics ("An Exploration of Factors Moti­ vating Hog Farmers In Their Production and Marketing" August 1947) in which farmers were asked what factors influenced the number of spring pigs they raised. Facilities, labor etc., feed factors other than price luck and disease were the most common reasons given. Price was not considered by farmers to be important. These findings do not invalidate the above findings, but merely point up the difference between what an individual thinks he is responding to and how a group does respond. Many of these factors such as labor and facilities tend to offset each other between individuals, and the group as a whole may respond to factors which are not considered important by individuals.

77

CHANGES IN THE NUMBER OR LAMBS ON FEED

Similar to cattle, the response of lamb production from year to year is largely limited to the number of lambs put on feed in the fall and winter♦

The farmer

must make yearly decisions as to whether he should expand or contract his feeding operations. The longer time movements in sheep numbers are not responsive to such yearly changes and are not considered in this analysis * Lamb feeding operations are not as concentrated as are the cattle feeding operations.

Since 1930, about

three-fifths of the lambs on feed January 1 have been in the North Central States and about two-fifths in other areas.

The magnitude of the fluctuation from year to

year in numbers on feed in the U. S. has been considerable, though less than for either cattle on feed or sows farrow­ ing (Table 20).

Because of differences in feeding prac­

tices and farm organization, the extent of fluctuation differed somewhat from one region to another. Table 20.

Indexes of Variability of Lambs on Feed January 1, by Regions, 1932-1947•

Region United States North Central States West North Central States East North Central States States other than North Central

Index of Variability 7 10 13 12 9

78

Factors Associated with Changes in U. s. Numbers of Lambs on Feed Many factors were studied in relation to the changes in the numbers of lambs on feed January 1 in the United States* Table 21,

Some of the results are shown in Table 21, Percent of Variation in Number of Lambs on Feed January 1 in the United States Associated with Several Factors, 1931-47.

Factor considered

Percent of variability associated with factor

U, S. lambs saved previous July

22

Western lambs saved previous July

14*

U, S. corn production previous year

7*

October corn price, Chicago**

3*

Margin between October feeder and March good-choice lamb prices, Chicago, uncorrected, previous feeding period***

30

Margin between October feeder and March good-choice lamb prices, Chicago, corrected, previous feeding period***

12*

* **

Association not statistically significant♦ Corrected by October index of prices received by U. S. farmers, *** The period here considered was 1932-42. The uncor­ rected margin considered the actual cents per hundred­ weight; the corrected margin was the cents margin per hundredweight which had been corrected by the index of prices received by U, S. farmers. A constant of $3,00 was added to the uncorrected series and a constant of $2,00 to the corrected series to remove the negative margins for some years. This, of course, does not affect the degree of association.

79

The number of lambs saved the previous spring was considered a measure of the supply of available feeders in the fall.

As the age of fed lambs is an important

quality and price factor, probably the possibility of "two way" animals is not so important a supply factor as in feeder cattle.

These changes in U. S. numbers saved

were associated with more than one-fifth of the variability in numbers on feed.

The number of western lambs saved

taken separately was associated with considerably less of the variability of U. S. numbers on feed.

From this it

would appear that changes in number of lambs saved and available the previous spring may be a limiting factor to the changes of the number on feed the next January. The margin between October feeder prices and the price received the next March for good and choice lambs at Chicago was used as a measure of the profitability of the previous feeding operation.

Though other points may

be more important as lamb markets, the changes at Chicago were assumed to be indicative of the changes of margins in general*

The actual margins were associated with 30

percent of the total variability in Ü. S. lambs on feed the following January.

When the effect of changing price

levels were considered, the resulting margins were assoc­ iated with only 12 percent of the variability. Other factors which might be associated with changes were studied.

Corn production and corn prices were not

80

significantly associated with numbers on feed. An October feeder lamb-corn ratio was not significantly related to changes in numbers on feed.

Also, there was no significant

relationship between numbers on feed and an October feeder cattle-feeder lamb ratio, which was used as a measure of the relative price of these two feeding alternatives. Changes in the price level for the preceding year also were not related to changes in numbers on feed. Table 22.

Percent of Variation in Numbers of Lambs on Feed January 1 in the United States Associated with Various Combinations of Factors, 1932-42*

Combinations of factors

Percent of variability associated with combination

Actual margin between October feeder and March good-choice lamb prices in Chicago previous year ; U. S. corn production, previous year

18**

Number of U. S. lambs saved, previous July; U. S. corn production, previous year

45**

Number of U. S. lambs saved, previous July; Actual margin between October feeder and March good-choice lamb prices of the previous year

60

Number of U. S. lambs saved, previous July; Actual margin between October feed and March good-choice lamb prices, previous year; U. S. corn production, previous year.

68

*

**

This short period of time was necessary because of the short length of time some of the data were available and also because of the disruption of some factors caused by war-time price controls. Not significant statistically.

81

In the attempt to increase the amount of explained variability, various combinations of factors were studied in relation to the number of lambs on feed (Table 22). The combination of actual margins and corn production was not significantly associated with numbers. Neither did the number of U. S. lambs saved considered with the corn production explain a significant amount of the variability in numbers on feed.

The number of lambs saved together

with the price margin, however, was associated with 60 percent of the variability in numbers on feed.

When corn

production was added to this combination, 68 percent of the total variability in numbers on feed could be explained. These factors, lambs saved, price margin, and corn production, make a strongly logical explanation for changes which might occur.

The number of lambs saved represents

to a considerable degree limitation on available feeder supply.

The margins are a measure of the profitability of

the feeding operations of the previous season.

The corn

supply is a measure of the amount of feed available for different types of livestock for the coming year. The relative importance of these three factors in explaining the net variability of changes in numbers is shown in Table 23. important factor.

The number of lambs saved was the most The margin was second in importance.

Corn production explained the least of the net variability. A given change in number of lambs saved resulted in a much

82

greater change in numbers than a like change in corn production or a 10 cent increase in margins. Table 23•

Relative Importance and Effect of Changes of Various Factors Affecting Changes in ü, S* Number of Lambs on Feed, January 1, 1932-42# Percent of net variation explained by each factor*

Factor

Percent increase in number of lambs on feed with a 10 percent increase in factor*

Lambs saved previous July

61

Margin between October and March prices

42

0.3**

Corn production previous year

20

0.8

*

**

12.0

After eliminating the effect of the other two factors, The three factors considered together explained 68 percent of the total variability in numbers# This was a statistically significant association# Change in numbers with a 10 cent increase in actual margin. The estimates of changes in lambs on feed made when

considering these three factors compared to the changes which actually occurred are shown in Figure 12.

For the

period 1932 through 1942, the estimated direction of change was opposite from the actual change which occurred for two years, 1936 and 1937*

However, during the war

period and the few available years since the war, the estimates have not been a satisfactory guide to actual changes.

For the years 1948 and 1949, the estimates

have called for increases while the actual numbers have been sharply downward#

Both sheep numbers and lambs

83

Percent of Previous Year 115 110

105 100

Actual

1932

1935

Figure 12.

1950

Estimated Compared With Actual Changes in Humber of Lambs on Feed January 1, U.S., 1932-1949.*

* For data and relationships see Appendix C, Table 8.

84

saved in the spring have been down sharply each year since 1942*

Whether this method of estimation will be valid in

the future, probably cannot be ascertained until the sharp downward trend in sheep numbers is arrested and numbers tend to stabilize, Factors Associated with Changes in Numbers of Lambs on Feed in Different Areas As pointed out, lamb feeding operations are carried on throughout a considerable area and under many different conditions.

Some of the above factors were studied in

relation to changes in numbers on feed in the East North Central States, in the West North Central States and in the area outside these two regions (Table 24). When considered on a regional basis, the various factors studied generally had a low degree of association with regional changes in numbers.

Though about two-thirds

of the changes in total XT. S. numbers on feed could be explained by a combination of these factors, it could not be assumed that the same factors were equally valid for different areas

20/

In studying the East North Central region, the margin considered together with corn production was studied in relation to the changes in number of lambs on feed. This combination was associated with 38 percent of the variation; corn production explained none of the net variability after the effect of margins was eliminated.

85

Table 24*

Percent of Variation in Number of Lambs on Feed January 1 in Different Regions Associated with Variation in Several Factors, 1932-1942*

Region and factors considered

Percent of variation associated with factor

East North Central States Ü* S* lambs saved previous spring Actual margin between October feeder and March good-choice lamb prices, Chicago Corn production in region previous year West North Central States U. S. lambs saved previous spring Western lambs saved previous spring Actual margin between October feeder and March good-choice lamb prices, Chicago Corn production in region previous year Range conditions previous October Other than North Central States Western lambs saved previous spring Actual margin between October feeder and March good-choice lamb prices, Chicago Range conditions previous October *

0 38* 17 6 0 4 3 0 27 1 0

Only this figure is high enough to be statistically significant*

Summary of Findings for Lambs on Feed It appeared that satisfactory explanations of changes in number of lambs on feed in the United States were much more complex than those for either cattle on feed or sows farrowed.

Slightly more than two-thirds of the total

variability in U. S. lambs on feed from 1932 to 1942 could be explained by considering the number of lambs

86

saved in the U. S. the previous spring, a measure of the margin in the feeding operation of the previous year, and the size of the corn crop of the previous year.

Of these

factors, the number of lambs saved was the more important• It was evident that possible explanations for changes on a regional basis were much more complex.

In one area

margins were more important ; in another, the number of lambs saved was more Important.

What appeared to be an

adequate and logical explanation for changes in U. S* numbers, was not equally satisfactory on a regional basis. Satisfactory estimates using these three factors were not secured during either the war period or the post war period.

This fact casts some doubt over the validity

of this method of estimation for future use.

37

CHANGES IN THE NUMBER OF HENS AND PULLETS ON FARMS

Because of the relatively short time required to activate a decision to change, chicken numbers could be quite responsive to short time changes of pertinent prices and other factors. Each year the farmer is faced with the decision of whether to increase or decrease his laying flock.

The decision he makes is reflected through changes

in the number of hens and pullets on farms the following January 1. Most of the original factors and conditions influ­ encing the decision to increase or decrease numbers must be present during the winter months, since the majority of the orders for chicks to be used as laying flock replacements are placed in the spring*

Of course, con­

ditions may develop as the year progresses which will affect the culling and marketing program of the farmer. These practices will influence the final number of hens and pullets retained from the chicks purchased and which will be on hand the next January.

However, the basic

decisions must be made before the chicks are purchased in the spring. Factors Associated with Changes in U. S. Numbers of Hens and Pullets on Farms January I. The months of December, January and February were considered as the critical months for factors which

88

affected the number of hens and pullets on farms next Jan,uary#^i/

The indexes of variability for many of the

possibly important factors during this period varied considerably (Table 25).

The variation in hen and pullet

numbers was considerably less than that of the various kinds of livestock*

The feed ratios and uncorrected feed

prices showed the most variability from year to year• Corrected egg and chicken prices had substantially the same amount of variation as the uncorrected series. Table 25.

Indexes of Variability of Different Factors Associated with Changes of U. S. Numbers of Hens and Pullets on Farms January 1, 1926-42.

Factor considered*

Index of variability

Hens and pullets on farms, Jan. 1 Egg price corrected** Chicken price, corrected** Poultry ration price, corrected** Egg price, uncorrected Chicken price, uncorrected Poultry ration price, uncorrected Egg-feed ratio Chicken-feed ratio

5 16 19 13 17 18 24 21 29

,

Ÿ

**

A w

z-N -we

z-e a



O

T ’Na

a

m m

+• Vi

/* \1 1 /'w lrt

Li"*A

k t %**t 1 they were associated with 56 percent of the variability in numbers.

These closer associations appeared because

feed prices were the more important of the two factors in the ratio. Though the greatest amount of variation could be explained with the combination of December-February ration prices, chicken prices, and egg prices (59 percent), for all practical purposes, the simpler combination of chicken and ration prices could be used in explaining substantially the same amount of variation in numbers (56 percent). This latter combination of factors resulted in estimates which were excellent indicators of the direction and fair indicators of the amount of change which actually occurred the following January. Both the combinations of egg prices and poultry ration prices and of chicken prices and poultry ration prices

103

explained a very high amount of the variation in volume of commercial hatchery operations from February through June (73 percent and 82 percent respectively). Since both the combination of egg and ration prices and of chicken and ration prices were significantly related to hatchings and to numbers the following January, it was not safe to conclude that farmers considered chicken prices more than egg prices in determining their future operations.

Studies covering more limited areas

support an assumption that the relative importance of these factors in influencing the farmers* plans differ from area to area ♦35./

25/

In order to further consider this general area of poultry responses, attention should be called to a study on the response of U. S. turkey numbers which was made by Don Paarlberg and D . J . Watson ("Factors Affecting the Price of Turkeys", Purdue Agricultural Experiment Station Bulletin 536, page 27). It was found that 56 percent of the variation in U, S. turkey numbers could be accounted for by the changes in the October-January average turkey-feed ratio. When the ratio increased 10 percent, the production of turkeys the following year increased 3 percent. Also, Morris White, Department of Agricultural Economics, Purdue University, in an unpublished study ("Factors Affecting the Price and Production of Broilers") found that 41 percent of the variation In chick placements in the Delmarva area from one quarter of the year to the next was accounted for by fluctu­ ations of the broiler-feed ratio the preceding quarter. When the broiler-feed ratio rose 10 percent, chick placements (seasonally adjusted) the following quarter increased 13 percent•

104

CHANGES IN THE LEVEL OF U. S. EGG STORAGE HOLDINGS^/

Because of the seasonal nature of egg production, there is a considerable volume which moves into storage during part of the year.

Eggs generally start moving

into storage with the increase in egg production in early spring*

Storage holdings usually reach their maximum

level in early August. From August until March the eggs move out of storage and into consumption channels. The volume of this storage operation varies consid­ erably from year to year.22/

The index of variability

for May 1 storage holdings, which were taken as a measure of the early into-storage movement was 24; the index of variability of August 1 storage holdings, which were taken as a measure of the total storage operation, was !?• Both the actual volume of storage and the volume of storage relative to the volume of egg production are important considerations.

However, changes in actual

storage volume and in volume relative to the egg pro­ duction moved up and down together.

Variations in actual

26/ It is recognized that this particular section does not fit into the pattern of a study of the response of production. However, in many of our agricultural commodities the extent of yearly ihto-storage and outof-storage movements are believed to have considerable effect on prices. If this is so, an indication of the extent of future storage operations could be of real value to the price analyst. Perhaps this section rep­ resents an exploration into another broad field of responses which should receive further study* 2?/ Egg storage holdings in this analysis include both shell and frozen egg stocks.

105

volume of May 1 storage holdings were associated with 94 percent of the variation of May 1 holdings relative to the March and April egg production.

Variations in the actual

volume of August 1 storage holdings were associated with 92 percent of the variation of August 1 holdings relative to the March through July egg production.

In other words,

actual storage volume and storage volume relative to pro­ duction tend to move up and down together.

Because of

this extremely close relationship, the following analysis considered only changes in the actual volume of storage * Factors Associated with Changes in the Volume of May 1 and August 1 Egg Storage Holdings Many factors were studied in order to ascertain their relationships to changes in both the early and late seasonal storage holdings as measured by May 1 and August 1 stocks.

These factors are shown in Table 32»

The number of hens and pullets on farms was used as a measure of the level of production for the forthcoming season.

(For the period 1926-1942, changes in January 1

numbers were associated with about 53 percent of the changes in the total egg production of that year.)

Changes

in these numbers were associated with over half of the total variability in August 1 storage holdings but with considerably less of the variability in May 1 holdings.

106

Table 32♦

Percent of Variation in May 1 and August 1 Storage Holdings Associated with Several Factors, 1925-1942,

Factor considered

Percent of variability associated with factors May 1 storage holdings

August 1 storage holdings

Number of hens and pullets on farms January 1

22*

53*

Cents per dozen spread between April-May-June and OctoberNovember-December farm prices of eggs preceding year, uncorrected**

14

27*

Cents per dozen spread between Chicago October future and U. S. farm prices on March 15

32*

39*

* **

Significant at the 95 percent or better probability level. When this spread was corrected for changes in the price level the degree of association was much less. The spread between the price during the principal

into-storage period, April through June, and the principal out-of-storage period, October through December, was taken as a measure of the relative profitableness of the storage operations of the preceding year.

Changes in this spread

were significantly related to the storage holdings in August but not with the early holdings in May.

The changes

in actual price spread were more closely related to changes in storage holdings than were changes in the corrected price spread.

This was probably due to the relatively

107

fixed nature of the costs of storage over a short length of time. The spread in prices between the March quotations of October future eggs and the March farm price was used as a measure of the outlook for the coming storage season* This factor was more closely associated with changes in the May 1 storage holdings than were either of the other factors*

About one-third of the variability of May

holdings and almost 40 percent of the variations of August holdings were associated with this factor* Various combinations of factors were studied in relation to both May 1 and August 1 holdings (Table 33). In all cases., considerably more of the variability of the August 1 holdings could be accounted for than the vari­ ability of the May 1 holdings.

The three factors giving

a measure of the egg production, profitability of past storage operations, and probable profitability of present storage operations explained nearly three-fourths of the changes in the August 1 holdings, and about two-fifths of the changes in May 1 holdings* By using these combinations of factors, estimates could be made in early April which in the past had been associated with 42 percent of the variability in May 1 holdings and 73 percent of the August 1 holdings.

After

January 1, by the use of hens on farms and Into-storage and out-of-storage price spreads of the previous year,

108

Table 33.

Percent of Variation in May 1 and August 1 Storage Holdings Associated with Different Combinations of Factors, 1925-1942.

Combinations of factors

Percent of variability associated with combination May 1 storage holdings

August 1 storage holdings

Hens and pullets on farms January 1 and intostorage, out-of-storage price spreads of previous year

28

64*

Hens and pullets on farms January 1 and margin between October future and XJ. S. farm price in March

39*

68*

Into-storage and out-of storage price spreads of previous year and margin between October future and U. S. farm price in March

36*

50*

Hens and pullets on farms January 1; into-storage and out-of-storage price spread of previous year, and margin between October future and U. S. farm price in March

42*

73*

*

Significant at the 95 percent or better probability level,

estimates could be calculated which in the past have been associated with 64 percent of the variability of August 1 holdings.5^/ 2#/ In making the January estimate, an increase of 10 per­ cent in hens and pullets resulted in 21.1 percent increase in August 1 holdings ; an increase of 10 percent in the spread resulted in a 1.8 percent increase in holdings.

109

Table 34.

Net Relationships of Various Factors to Changes in the Volume of Egg Storage Holdings, 1925-42*.

Factor

Percent of net variation explained by each factor**

Percent increase in storage holdings with a 10 percent increase in factor**

May 1 Holdings Hens and pullets on farms, January 1

9

12.1

Cents per dozen spread between April-June and 0ctober-December farm prices of previous year

5

1.2

Cents per dozen margin between Chicago future and XJ. S. farm price on March 15

19

2.1

Hens and pullets on farms, January 1

46

17.6

Cents per dozen spread between April-June and 0ctoberDecember farm prices of previous year

16

1.4

Cents per dozen margin between Chicago October future and U. S. farm price on March 15 25

1.3

August 1 Holdings

*

These factors considered together explained 42 percent of the variation in May 1 holdings and 73 percent of the variation in August 1 holdings. ** After eliminating the effect of the other two factors.

110

The relative importance of the three factors used in explaining the variation in storage holdings varied considerably (Table 34)*

After eliminating the effect

of the other factors, the margin between future and actual prices during March of the storage season explained the greatest amount of the net variability in May storage holdings; the price spread of the storage operation of the previous year explained the least.

Evidently, the out­

look for the current season was one of the most important factors influencing the level of early storage operations. The number of hens and pullets on farms January 1 explained the greatest amount of the net variability of August holdings ; the price spread of the storage operation of the previous year explained the least.

From this, it

would appear that though the outlook for profit in the storage operation may be primarily important in determ­ ining early operations, the level of production(as indi­ cated by the number of hens and pullets) is most impor­ tant in influencing the total amount which finally goes into storage. The estimates of changes in both May 1 and August 1 holdings which were made from these factors were compared with the actual changes which occurred from 1925 through 1948 (Figures 15 and 16).

These estimates were correct

as to the direction of change of May 1 holdings in 18 of the 24 years.

Since this combination of factors explained

Ill

Percent of

Previous Year 160 Actual 140 120 100 BO

1930 Figure 15*

1950

1935

Estimated Compared With Actual Changes in Storage Stocks of Eggs on May 1, U.S., 1925-1943,*

* For data and relationships see Appendix C, Table 11.

percent of Previous Year Estimated

UO 120 100 BO

1930 Figure 16.

1935

1950

Estimated Compared With Actual Changea in Storage Stocks of Eggs on August 1, 0.8*, 1925-1948.*

* For data and relationshipe see Appendix C, Table 11.

112

only 42 percent of the total variability it was only a fair guide to the actual magnitude of changes in early storage. The estimates of August 1 holdings were an excellent guide to the direction of change, being correct 21 of the 24 years.

Through the greater part of the period they

also were an excellent guide to the amount of change. During the years since 1945 when price conditions were considerably disturbed, the actual changes in holdings were generally greater than the estimated changes. Summary of Findings for Egg Storage Operations Through the use of factors measuring future egg production, past storage operation experiences, and present storage operation outlook, 42 percent of the variability of May 1 egg storage holdings and 73 percent of the variability of the August storage holdings could be explained.

These factors provide a tool of estimate

of only limited use for the May 1 storage levels, but they do provide a very sharp estimating tool for the peak period of August.

By the use of only the measures

of future egg production and the past storage operation experiences, both of which are available in January, 64 percent of the variability of August storage levels can be explained. When the factors are used in combination, the margin

113

between October future prices and IT. 8. farm prices in March was associated with the greatest amount of net variability of May storage holdings.

The number of hens

and pullets on farms January 1 was associated with the greatest amount of the net variability of August 1 storage holdings. It would seem that the relation between the current price and the future price of eggs is one of the most important factors influencing early storage levels. However, the amount of eggs available is the most Important single factor in influencing the volume of eggs that finally move into storage for the entire season.

114

GENERAL SUMMARY CONCLUSIONS AND APPLICATIONS

Summary of Crop Responses In the analysis of the different crops there was evidence to substantiate the hypothesis that farmers as a group do or intend to respond to changing relative crop prices by changing the acreage planted. However, the amount of variation in either intended acreage or harvested acreage which could be explained by price changes was in many instances quite small (Table 35)* In some of the truck and special crops over one-half of the variation in acreage could be explained.

Only about

one-fourth of the variation in wheat acreage or intended corn acreage could be explained. It is not to be concluded from this, that more of the variation in acreage is not explainable. However, it is evident that the acreage response is not a simple supply curve of price and acreage which represents a high degree of relationship to actual data is not possible (Appendix C). One of the complicating factors in this type of analysis is that of ascertaining the appropriate time lag between the price and the acreage response.

In many

of the truck crops, changes in the price received the preceding year were the most important in influencing acreage while prices of earlier years appeared to have

115

Table 35.

Summary of the Significant Relationships and Response of Acreage of Various Crops to Various Price Factors* Most important factors explain­ ing acreage change

Crop

Cabbage Cantaloup Green Peas Onions Snap beans Tomatoes Watermelons Strawberries Potatoes

Spring wheat

Fall wheat Corn (intentions) Oats * **

Percent of acreage variation explained

Price preceding season Price one and two preceding seasons None found Price preceding season None found None found Price preceding year Price one, two, and three preced­ ing years December price two preceding years; August price preceding year uuly-Sept. price preceding year; March price at planting time Average acre value same and preceding year Nov.-Jan. price two years pre­ ceding None found

Percent change in acreage with 10 per­ cent increase in factor**

54

2.9

51

3.5, 2.5



-----

27 ———

1.9 — --

23

2.1

52

1.5, 2.9, 2.9

57

0.65, 0.78

28

-2.0, 4.3

29

1.9, 2.4

25 ——

0.7 ———

-----

All prices are corrected for some measure of the price level. When two or more factors are involved, net effect is given in the order of the factors mentioned; other­ wise the gross effect is given.

116

little effect.

For the acreages of strawberries, potatoes,

and the field crops studied, prices for at least two years previous were more important in explaining changes.

In

other words, though most of the crops studied could be planted and harvested within one year or season, other factors prevented or modified a swift response to changing price. The acreage of some of the crops studied— oats, snap beans, green peas, and tomatoes— showed no significant relationship to the price factors used„

It does not

necessarily follow from these findings that some of our crops are not responsive to some price or some other measurable factor. Many complicating factors could be present.

For example, in the situation of rapidly

expanding crops, such as soybeans, the methods of analysis here used is not adequate since the trends are too pro­ nounced.

In the case of many new crops or drastically

changing technological situations, the price-cost struc­ ture is probably far out of balance.

Adequate short-

time supply analysis cannot be made under such conditions, since the pressure to bring the production cost-price structure into balance is overwhelming.

This may well

be the situation under which many of our fresh market crops were grown during the period of analysis. Another reason for the lack of apparent response in such crops as oats (and possibly barley, rye and others)

117

is the nature of the farm organizational patterns under which they are grown.

Oats, in the corn belt, is largely

a rotation crop and the changes in the extent of the acreage is closely tied to changes in other crops. Data on rye acreage are difficult to analyze because of its widespread use as a cover crop.

The response of acres

for grain and for cover uses, and the changes in decision once it is seeded are extremely difficult to measure. The amount of acreage response to a given amount of price change varied considerably among the various crops (Table 35)•

Cabbage acreage, which increased 2*9 percent

with a 10 percent increase in corrected price the preceding year, was the most responsive of the crops studied.

Canta­

loup , watermelon and onion acreage all changed about 2 per­ cent for each 10 percent increase in the preceding season’s corrected price.

Strawberry acreage was quite responsive

to changes in the corrected price two and three years pre­ ceding.

Potato acreage responded less than 1 percent to

a 10 percent increase in either the preceding August price or the December price two years preceding.

In this

sense, potato acreage response was the most inelastic of any of the truck or special crops reported on in this study. The wheat acreage-price relationships were more complex.

Fall wheat acreage showed a positive net

relationship to the acre value for both the preceding

118

harvest period and the preceding year.

Spring wheat

acreage had a positive net relationship to changes in the March price but a net negative relationship to changes in the preceding harvest period price, though both were positive in their gross effects.

Intended corn acreage

increased less than 1 percent with an increase of 10 per­ cent in corrected price two years preceding. Only a part of the acreage changes could be explained by the studied price changes, and only a part of the total production of a given crop is determined by the acreage planted.

Therefore, it cannot safely be concluded that

year to year changes in total production of individual crops are responsive to price.

Considerable work has

been done which points out that increased yearly pro­ duction decreases price and that decreased production increases price•

This study, however, did not find that

changes in the price this year were an accurate guide to changes in production next year. Summary of Livestock and Poultry Responses In studying the response in numbers of livestock and poultry, it became more evident that the interrelationships of various factors were very complex.

The hypothesis that

there is a simple effect of price on supply could not be substantiated.

Both prices and other factors were used to

explain changes in numbers (Table 36).

119

Table 36*

Summary of the Significant Relationships and Response of Various Livestock and Poultry to Various Factors*

Commodity considered

Cattle on feed, January 1 Spring sow farrowings jpall sow far­ rowings Lambs on feed, January 1 Hens and pullets on farms, January 1 *

Most important factors explaining change

Percent of variation in numbers explained

Corn production Sept.-Nov. corn price; Sept Nov. hog price Spring sow farrow­ ings; March-May hog prices Lambs saved, Oct.March price margin; and corn production Prices of chickens, eggs and poultry ration

Percent change in numbers with 10 percent increase in factor**

66

4.0

75

—4•4 > 2.2

52

6.9, 5♦5

68

1.2, 0.3, 0.8

59

1.1, 0.5, -1.6

All prices, except lamb margins were corrected for some measure of the price level. When two or more factors are involved, net effect is given in order of the factor mentioned ; otherwise the gross effect is given* Corn production was the most important factor in

explaining the variation in cattle feeding operations. Corn prices were the most important factor in explaining the variation in spring sow farrowing while hog prices were of lesser importance.

In explaining the changes that

occurred in fall farrowings, the changes in numbers of sows farrowed in the spring were most important while hog prices were of lesser importance.

The principal factor in

explaining the variation in lamb feeding operations was the number of lambs saved; price margins and corn

120

production were of secondary importance.

In explaining

the changes in numbers of hens and pullets on farms, chicken prices and poultry ration prices were most important while egg prices were of lesser importance. Change

in the size of the corn crop, measured either

in its actual amount or through the effect of the amount on price, was a fundamental factor in explaining changes in livestock and poultry numbers.

This close relationship

of corn supplies and numbers is quite logical since a large proportion of crop production, especially corn, is marketed through livestock and poultry. A large corn crop with the consequent lower relative corn prices set off a chain of decisions which tended to increase the number of cattle put on feed, increase the number of sows farrowed the following spring and fall, increase the number of lambs put on feed, and through its effect on poultry ration prices, increase the number of hens and pullets. Other factors eliminated, a 10 percent increase in corn production resulted in a 4.2 percent increase in cattle on feed'and a 0.3 percent increase in lambs on feed the following January.

A 10 percent decrease in relative corn

price resulted in a 4.4 percent increase in sows farrowed in the spring.

The increase in spring farrowings in turn

tended to be associated with an increase in fall farrowings. A 10 percent decrease in poultry ration prices, which were significantly associated with corn prices, tended to result in a 1.6 percent increase in the number of hens and pullets

121

on farms the following January. The amount of the variability of the numbers of livestock and poultry which could be explained by a small group of selected factors was in all cases quite large. These factors could be used as fairly sharp tools for estimating changes in numbers a considerable length of time in advance. The differences between the estimated and actual changes in numbers were studied simultaneously for cattle on feed, sows farrowed in the spring and in the fall, lambs on feed and hens and pullets on farms.

This was

done to ascertain whether there was a general pattern of differences between the estimated and the actual changes. If like errors occurred simultaneously, it would be prob­ able that some other general factor was involved through­ out .

In the period prior to the war, considerable error

in estimation was made for one or more of the products in almost every year.

However, there was no general pattern

of error which might be attributed to some over-all factor such as changing price levels, psychology, etc. During the early years of the war, 1939 to 1942, most estimates of changes were low compared to the actual changes which took place.

During this period much of the

corn which was in government storage was utilized to encourage the expansion of livestock production.

This, of

course, allowed a greater response in livestock production

122

than would have otherwise been possible.

In 1944, the

estimated changes were considerably above those which actually occurred♦

This may have been due to the exhaus­

tion of storage stocks and the fear that the livestock enterprise was over-expanded in relation to the feed supply•

During the later war years and in the immediate

post war period actual changes fluctuated through much wider limits than the estimated changes. Much of this was probably due to the system of price controls and its subsequent relaxation which reduced the usefulness of past price relationships as a guide for the allocation of pro­ duction resources. Some General Conclusions 1.

The short-time supply response of agricultural pro­

ducts studied was quite complex.

A simple price-acreage

or price-numbers relationship which would explain a large proportion of the variability was not found for any commodity studied^2/

Changes in the level of production—

or of intended production— evidently occurred within a framework of many interrelated factors. 29/

It was not

The study further strengthens the observations made by Henry Schultz. ("Statistical Laws of Demand and Supply", University of Chicago Press, Chicago, Ill­ inois, 1928, Preface). He pointed out that our market phenomena have become exceedingly complex. Economists, he observed, are beginning to perceive that prices form an interrelated and interconnected system and that to say that the quantity of a com­ modity demanded is a function only of its price and not of many other related prices is to adopt an over simplification.

123

possible to state with surety and accuracy that an increase in corn prices would result in an increased corn acreage or that an increase in steer prices would result in an increase in the number of steers on feed in the short run* Most of the work done in this study considered price and production responses on a national scale which necess­ arily included an infinitesimal series of small localized situations.

Within a limited area, if the agricultural

pattern and alternate opportunities could adequately be considered in the evaluation of the price data, it is possible that much closer relationships could be found. With the possible exception of the highly seasonal crops, such as the truck crops, the breaking of the total picture into smaller fragments has limited use.

In this age of

closely knit communication systems and rapid transportation facilities, the market for most of our commodities is on a broad scale.

To ascertain whether the individual

segments differ is a matter which may have a bearing on the optimum allocation of resources, but it adds little to the broad questions of supply response for the market area»J2/ 30/

Micro-economic analysis of this type is discussed by John M. Brewster and Howard L. Parsons, "Can Prices Allocate Resources in American Agriculture?” , Journal of Farm Economics, Volume XXVIII, November 1946• Brewster and Parsons point out that responses are different for different type farms. The question which is pertinent here, however, is how do farmers in the aggregate respond?

124

2,

Price alone is not an adequate indicator of the

changes in total crop production to follow.

Since a large

share of the changes in acreage cannot be explained by price, it follows that with the great number of unknown and uncontrollable factors involved,price is not an adequate indicator of total production volume to follow. Even if the farmer intended to respond to price changes, uncontrollable factors can change materially the actual response which takes place. 3•

Factors which influence the scale of short-time live­

stock and poultry production are complex.

In many cases,

the level of corn production— or the effect of the level on price— is of prime importance.

In instances where a

feed-ratio is of importance, there is considerable evidence to indicate that the price of feed is the more important element of the ratio.

In other instances the existing

level of production of the commodity is important— such as lambs saved in the spring or sows farrowed in the spring. In livestock and poultry responses there are many influ­ encing factors outside the control of the farmers. How­ ever, within an existing framework of feed supply and selected other factors, advance estimates of how the farmers in the aggregate will respond are possible. 4.

The short-time supply response of the various com­

modities studied was, in general, inelastic in nature. A given amount of fluctuation in the causal factors always

125

resulted In a markedly smaller amount of fluctuation in acreage or numbers* 5•

No part of this study denies that price may be the

dominant factor in the distribution of supplies already on hand--both as to the place and time they will move to the market.

Nor is the long-time effect of price on

supply denied.

Many studies have shown considerable

relationship between long-time trends in production of a commodity and the long-time trends in relative price. Until there is good evidence to the contrary, the most logical assumption is that farmers, given the time and opportunity, will apply the principle of substitution to their best advantage.

What the study does conclude is

that in the short run, price changes of a commodity are not an adequate indicator of future supply changes of the commodity. This study was predicated in the assumption that in the current economic fabric of uncertainty, the indicator of the future most commonly used by farmers in planning was the immediate past.

Some exploratory analysis denied

that the immediate past is an adequate indicator of the future.

For example, the amount of change in November-

Dee ember corn prices over the preceding year is not sig­ nificantly related to the amount of change in the November December corn prices of the following year (Appendix B). This would indicate that the farmer is not necessarily

126

working against his best interests by not changing his corn acreage in response to preceding prices.

To what

extent responses are tempered by the knowledge that changing conditions have always been the pattern is not known.

How production of individual products would

respond in an economy in which uncertainty was largely removed may be considerably different. 6.

The approach of this study has given results which for

many commodities are usable and, in some cases, quite com­ plete.

The results were of such nature to justify addi­

tional exploration into this problem of short-time response.

Some Possible Applications Several tools for farmers, trade personnel and economists which could be useful in production planning and outlook work were found.

Both the farmer producer

and market personnel are continually striving to antici­ pate future developments so as to better their positions. Whatever advance information can be made available should be of considerable importance. Assuming an economy of relatively free prices, some of the tools available for anticipating the future are as follows : 1.

Price-acreage relationships which accounted

for enough of the acreage variation to at least give an indication of the direction of change the following season were found for cabbage,

127

cantaloups, onions, and watermelons. As soon as the seasonal average price becomes available, which should be shortly after the marketing season, estimates of acreage change for the next year can be made» 2.

Estimates of the potato acreage can be

made as early as the preceding September by use of the December and August price relationships. These estimates for all practical purposes were as valid as the acreage intentions which are not available until the following March. 3.

By following the prices of the three

preceding seasons, a considerable proportion of the change in strawberry acreage can be anticipated » 4.

As soon as the size of the corn crop is

known, an estimate of considerable reliability can be made of the number of feeder cattle which will be on feed the following January. This knowledge should also sharpen the outlook predictions for the relative level of feeder cattle prices. 5.

Estimates of the number of sows farrowing

in the spring can be made early in December by the use of corn and hog prices.

This is prior

to the availability of the December pig crop

128

estimates.

An estimate of fall farrowings can

also be made prior to the June pig report. 6.

As soon as the July estimate of lambs

saved becomes available, these data along with the margin results of the past feeding season can be used in arriving at an estimate of the number of lambs on feed the following January. As soon as the size of corn crop becomes known, this estimate can be improved♦ 7.

As early as in March, a reliable estimate

of the number of hens and pullets on hand the next January can be made by the use of DecemberFebruary price relationships.

At this time a

highly reliable estimate of the bulk of com­ mercial hatchings for the year can be made. 8.

As early as in January, a reliable esti­

mate of the level of egg storage holdings the following August can be made. After March this estimate can be somewhat improved. The findings of this study could be of considerable value to the worker in the field of agricultural policy. More and more people, through government, are attempting to better the position of agriculture.

Some of these

attempts have taken the form of support prices and pro­ duction control.

The statistical findings of this study

concerning the supply-response relationships are those

129

which have existed within a system of relatively free prices.

They cannot be used with equal validity as

indicators of such responses within a system of forward or guaranteed prices.

However, some of the findings

which would be applicable to the various problems of policy are as follows: 1.

The short-time response of agricultural

production is not a simple process.

The

raising or lowering of the relative price of a commodity will not necessarily increase or de­ crease the production of that commodity in the short run.

The prices to which the acreage of

a certain commodity might respond may extend over a period of two or more years.

For example,

prices which are related to acreage next year may extend through this year and last year. Because of the many uncontrollable factors, the change of prices alone would not be an adequate measure to bring about changes in the production of a particular crop. 2.

Short-run production for livestock is

closely tied to many other factors besides price. In many instances the more important factors are those other than the price of the commodity itself.

Short-run livestock production is

closely inter-meshed with crop production. If it

130

were desired to decrease the farrowings of sows next spring, the increase of corn prices during September through November would be more impor­ tant than a decrease in relative hog prices* No part of the pricing and production mechanism can be adjusted or changed without affecting many commodities in many ways. Any action must be taken with these many ramifications in mind, or the desired results in one area may bring about undesired results in another. 3.

The significant relationships between

prices and production found in this study were positive in nature•

The assumption is often

made that farmers attempt to maintain incomes by increasing production in response to a falling price.

Considering the various phases

of production analyzed, there appears to be no basis for such an assumption.

APPENDIX A

APPENDIX A SOME EXPLORATORY ANALYSIS OF THE RESPONSE OF REGIONAL ACREAGE PLANTED TO VEGETABLES

It was recognized that because of the seasonal nature of production and the geographic extent of this country there is a series of marketings arriving through­ out the season*

Thus, U. S. annual acreages and seasonal

average prices could not represent any particular actual price-response situation.

Some exploration into the

response of regional acreages to seasonal prices was made to determine whether a significant response to price was being made which was hidden in the U, S. aggregate statistics (Table 1). Only in the cases of snap beans and tomatoes was a higher degree of correlation obtained on the regional basis than for the IT. S. as a whole. (For U. S. results see Table 2, page 15.)

In most instances, the price of

the preceding year was associated with more of the acre­ age variability than was the price of two years preceding It would seem logical to assume that if the prices being considered could be adjusted in such a manner so as to take account of the particular competing crops of the area under study, a closer relationship to acreage change could be found. A study of the changes in cantaloup acre age in Indiana lends weight to this assumption.

Much of

133

Appendix A

the Indiana cantaloup acreage is grown in competition with grain crops.

When the seasonal prices received were cor­

rected by the truck crop price index, a low degree of association was found.

When the prices were corrected by

the Indiana grain price index a high and significant assoc­ iation was found (Table 2)*

In other words, when prices

were high relative to the prices of crops which were alter­ native opportunities for the farmer, cantaloup acreage was increased » Table 1.

Percent of Variation in Regional Harvested Acreage of Selected Truck Crops Associated with Several Factors , 1927-1942.* Percent of variability associated with factor

factors Early Summer Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Winter Acreage; Price preceding year Price two years preceding Price preceding year and two years preceding Cantaloup Mid-Summer Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Early (Imperial Valley) Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Continued

4 2

10 2

30

7 1 14

2

134

Appendix A

Table 1.

Continued

Crops and factors Snap Beans Early Spring Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Early Summer Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding

^Percent of variability associated with factor

Tomatoes Early Spring Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Late Summer Acreage: Price preceding year Price two years preceding Price preceding year and two years preceding Watermelons Early Summer Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding Late Spring (Imperial Valley) Acreage : Price preceding year Price two years preceding Price preceding year and two years preceding * **

11 8 12 2 21 24

21 22 31**

21 4 23 1 11 12

The average price for the season concerned was used and corrected by the U. S. Index of Truck Crop Prices* Statistically significant at the 95 percent probability level*

135

Appendix A

Table 2*

Percent of Variation in Indiana Harvested Acreage of Cantaloup Associated with Various Factors, 1926— 1942.

Factor

Percent of variability associated with factor

Prices Corrected by the U, S* Truck Crop Price Index: iPrice preceding year Price two years preceding Price preceding year and two years preceding

13 15

Prices Corrected by the Indiana Grain Price Index: trice preceding year Price two years preceding Price preceding year and two years preceding

13 43

*

A statistically significant relationship*

18

56*

APPENDIX B

137

APPENDIX B THE RELATIONSHIP OF CHANGES IN PRICE ONE YEAR TO CHANGES IN PRICE THE NEXT YEAR

If it can be shown that farmers do not respond to any considerable extent to the prices which prevailed in pre­ vious periods, it does not necessarily follow that they are working against their own interests.

If the previous

price change was not an accurate indication of the future price situation, possibly farmers are wise in not per­ mitting it to influence their crop allocations.

It prob­

ably must be admitted that in an economic system of free and changing prices, the immediate past is the most accessible factor to use as an indicator of price behavior for the period ahead. The assumption that the amount of change in prices one year is a valid indicator of the amount of change in prices the following year— that is, if prices increased 10 percent this year, they will increase 10 percent next year— was tested for several commodities (Table 1).

With

one exception, no significant relationship was found between the changes of one year and those of the following year.

In the one instance in which a significant relation

was found, the relationship was a negative one.

138

Appendix B

Table 1*

Percent of Variation in Changes of Prices One Period Associated with Changes in Prices of the Same Period the Following Year for Various Commodities, 1926-1942.* Percent of variation of price changes associated with price changes the following year

Commodity prices Truck Crop Prices Seasonal average Seasonal average Seasonal average Seasonal average Seasonal average

cabbage prices cantaloup prices green pea prices tomato prices watermelon prices

— —

1 42 —— 19

Field Crop Prices Inovember^December corn prices July-September oats prices July-September wheat prices

9 4 ——

Livestock and Poultry Prices December-February chicken prices October feeder cattle prices (Chicago) December-February egg prices September-November hog prices March-May hog prices

22 9 14 6 8

*

All prices were corrected by an appropriate price index. The corrected data were then converted to percentages of the preceding year. Relationships were then obtained by studying the datum for one year in relation to the datum of the following year.

139

APPENDIX C

140

Appendix C

Table 1.

Indexes of Variability of Acreage of Selected Crops and Numbers of Livestock, U, S .*

Commodity

Index

Truck and Special Crops Cabbage Cantaloup Green Peas Onions Potatoes Snap Beans Strawberries Tomatoes Watermelons

16 9 15 15 8 10 12 11 12

Field Crops Wheat Spring Fall Corn Oats

8 12 9 7 11

Livestock and Poultry Cattle on feed Sow farrowings, total Spring Fall Lambs on feed Hens and pullets on farms

12 11 14 17 7 5

*

These indexes are coefficients of variability based on the standard deviation of the percentage that each year was of the preceding* The larger the index the greater the variability* Periods covered vary somewhat. For truck crops the period was 192? to 1942; for potatoes and strawberries, 1925 to 1942; for field crops, 1922 to 1942; for cattle, 1931 to 1947; for sows, 1925 to 1947; for lambs, 1932 to 1947; and for chickens, 1926 to 1942.

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VITA

Richard Louis Kohls:

Born April 19, 1921, in Kentland,

Newton County, Indiana.

Reared on a general farm there.

Was graduated from Kentland High school in May, 1939. Entered Purdue University in September, 1939.

Was

graduated with distinction in December, 1942, receiving a Bachelor of Science degree in agriculture. Ordered to active duty with the army in January, 1943. Served three years and eight months, eleven months of which were in the Ear Eastern Theatre of Operations, Philippine Islands.

Separated from active duty with the

rank of Captain, Military Intelligence in August, 1946. Entered the Graduate School, University of Missouri in August, 1946.

Was graduated in August,1947 with the

Master of Arts degree with a major in agricultural economics.

Thesis title:

Some Economics of the Hog

Industry in Missouri. Served on the staff of the University of Missouri as Assistant Instructor in agricultural economics from August, 1946 to August, 1947; promoted to Instructor in September, 1947. Joined the staff of Purdue University in June, 1948 as Instructor in agricultural economics.

Entered the

Graduate School of Purdue University in June, 1948 and was graduated with the Doctor of Philosophy degree in

June, 1950 with a major in agricultural economics and minors in economic theory and money and banking. title:

Thesis

The Response of Agricultural Production to Price

and Other Factors.