FARMLAND mama AS A MEANs’» i? i _ if: iii":{'5533-5? OF RESOURc'EiszTRfiL-IN g ; U. 35 LAND'BASED AGRICULTURE - I Dissertation for the Degree of Ph; D. MECHEGAN STATE UNEVERSlTY BRUCE BYSONG JOHNSON 1974 llWlllllellfljllellillflHflljfllllfljifllflll {a LXI-j: 11.33.... L111?” MM “(g ‘ V /, ’1 3..“ . m.“ K unnsasuns 1 Beoxamo mam 11 LIBRARY BINDERS ABSTRACT FARMAND LEASING AS A MEANS OF RESOURCE CONTROL IN U. S. LAND-BASED AGRICULTURE By Bruce Bysong Johnson Structural changes of considerable magnitude continue to occur within the U. S. farming sector. Key dimensions of change are the process of farm consolidation and growth and the rising capital and credit intensity of agricultural production. The separation of farmland ownership and use through rental is believed to be an influential parameter of the physical, financial, and managerial organization of this sector. This study was launched to analyze (l) the farmland rental process, (2) the institutional framework through which it functions, am (3) the interrelationships of this process with current structural trends. Based on data from the 1969 Census of Agriculture, about 38 percent of all farmland is rented. Since most of this land is rented from nonoperator landlords, this process must be regarded as an important source of capital input. Moreover, analysis of tenure by acreage size and economic class revealed a heavier emphasis on farmland leasing among the larger farm operations . The largest one—fifth of the operating units (in acres) account for about three- fourths of the rented farmland. No significant difference in Bruce Bysong Johnson reliance on leasing vex; observed, however, among the various forms of financial organization. The tenancy patterns observed confirm that farmland rental is highly interrelated.with the structural adjustments occurring over the last few decades. Mbre specifically, farmland rental has taken on a different dimension. Where once tenancy was considered a temporary rung on the tenure ladder to eventual full ownership, leasing is predaninantly viewed today as an effective and frequently a permanent tool to achieving use rights to an.adequate—size land base. In fact, where capital and credit limitations have prohibited land purchase, rental has been the Operator's sole means of acreage size expansion. This is particularly evident in the landabased enterprises such as cash-grain farming. But even.where no financial constraints to buying farmland exist, farm operators may prefer rental over purchase for economic reasons; i.e., based on an internal rate of return analysis of farmland investment alternatives over the relevant range of mortgage interest rates, net rents, and Opportunity costs, rental is economically preferable unless rather substantial appreciation of farmdand values is expected. Despite the magnitude and importance of farmland leasing, findings of a case study of selected Corn Belt rental markets support the hypothesis that the rental market process is low keyed and infbrmal in nature with little visible competition. The study fOund the market area to be quite localized with participants usually knowing each other before entering the market. A significant Proportion of the leases were family arrangements. Information networks were largely through informal channels. Custom was also Bruce Bysong Johnson found to be an important factor. As a result, respondents indicated a low incidence of active competition—eboth at the time of initial rental and at the periodic renewal. What emerges, then, is a rather paradoxical situation in.which short—term, unwritten lease contracts are the rule, yet slow turnover rates and stable tenancy patterns prevail. For the farm Operator who has successfully rented farmland, such a.market framework appears to be advantageous. The tenant generally can feel that so long as there is reasonable cooperation between himself and his landlord, he can be assured of a continuing agreement. Frequently it is only upon sale of the property or title transfer that the tenant's position is in JeOpardy; and even the severity of resource loss due to such an event can.be reduced considerably by multiple-unit leasing, which is characteristic of today's situation. As fOr farm consolidation and growth process, this analysis supported the hypothesis that the availability of farmland to rent is influential. This was analyzed by incorporating probability factors for (l) renting land previously rented and (2) renting land not previously rented into a simulation growth model of a Corn Belt cash—grain farm. At probability levels representative of findings in the market case study, the effect was significant enough to reduce the ranking of rental strategy over Some of the other growth strategies. It is concluded that rental can.be the most accessible option of farm acreage size expansion for some farm Operators, but certainly not for the farm.p0pulation as a whole. Availability of land to rent is the crucial factor. Bruce Bysong Johnson Land rent theory suggests several reasons why leasing prevents maximunlresource efficiency. Yet empirical evidence to support this theory is meager and inconclusive. Findings of this study suggest that this is due in part to the failure of static theory to account for dynamic adjustments, such as the realization of size and scale economies of acreage expansion via rental. Also, the assumptions underlying much of the land rent theory no longer reflect conditions as observed in this analysis——most notable being the dominance of part-owner leasing, multiple-unit leasing, and a.market setting conducive to strong and.mutually beneficial landlord-tenant relation? ships. It is concluded there is little basis to support the theoretical proposition of resource inefficiency arising from tenancy. While the present rental process facilitates resource efficiency, other criteria must be considered also. Flexibility of adjustment is hampered by custom, thereby reducing provisions for progress. Due to market imperfections there exists much inequality of access to rental land. The problem of fragmentation of viable operating units in intergenerational transfer is often aggravated by the present rental process. Then, also, environmental considerations as well as recent shifts in food and energy supplies place added pressure on this man-land institution. Because of these factors, the fUture holds increasing challenge for the policy maker in resolving land tenure conflicts. FWEWEAND LEASING AS A MEANS OF RESOURCE CONTROL IN U. S. LANDéBASED AGRICULTURE By Bruce Bysong Johnson A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the. degree of IDCIOR OF PHILOSOPHY Department of Agricultural Economics 1974 ACKNOWLEDGMENTS The author expresses sincere appreciation to his major professor and thesis advisor, Dr. Larry Connor, for his helpful guidance and encouragement in this educational experience. As a very capable professional and as a warm and perceptive person, Dr. Connor was quite instrumental in making these years stimulating and rewarding. Gratitude is also expressed to Dr. Larry Libby, Dr. Allen Schmid, and Dr. Nfllton.Steinmueller for their guidance and cooperation. Each made unique contributions to my learning process and to this thesis, as did many other members of the Department of Agricultural Economics. I appreciated the input and encouragement of many individuals in Economic Research Service and the opportunity which this Agency provided. A special thanks goes to Mrs. Linda Marciniak who patiently and persistently typed this manuscript as well as countless tables. My poor penmanship and spelling never changed her friendly way, and I anlgraterl for her. Finally, my heart goes out to my family: to my parents for their support and encouragement; to my children, Jill, Jeff, and Joel for their loving devotion; to my "very special" wife, Judy, who radiates faith and assurance, vitality and purpose, gentleness and love; and to all my brothers and sisters in the Body of Christ who 11 have loved us and prayed for us. This time, this place, and these relationships have all been part of God's plan, and to God be the glory! iii TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES CHAPTER I . INTRODUCTION N N o N O SNNNWNNNNNNNNNH 0 WWW NNNNN HI—‘H O N 0 CHAPTER CHAPTERI 2.1 .2.2 I WLAJUOWUU O U'IJI‘UONH WWWWWWWWNH O O I O The Problem Setting The Problem Research Objectives Study Design and Format II. FARMLAND 'I'ENURE PATTERNS IN THE UNITED STATES Farmland Tenure Patterns—All Farms The Rented Portion l . 2 Part-Owner Dominance 3 Nonoperator Land Ownership Tenure Patterns of Economic Classes I - V Farms Characteristics by Tenure of Operator Tenancy Patterns by Age of Farm Operator Tenancy Patterns by Acreage Size of Farm Tenancy Patterns by Economic Class of Farm Concentration of Land Ownership and Rental Degree of Concentration by Age of Operator Degree of Concentration by Acreage Size Class Degree of Concentration by Economic Class Chapter Summary II. THE FARIVLAND RENTAL MARKET—A CASE STUDY 1 2 3 u .5 Tenancy Patterns of Cash Grain Farms .1 2 3 Survey Design and Execution The Market Participants The Tenants The Landlords The Market Process The Land Rented The Leasing Arrangement The Formality of Eases Land Tracts Prior to Rental The Flow of Information iv Table of Contents (Continued) Page 3.3.6 Competition at Time of Rental 61 3.3.7 Negotiation at Lease Renewal 62 3.3.8 Competition at Lease Renewal 64 3.3.9 Expectations of the Future 65 3.4 Land Rental and Farm.Adjustment 69 3.4.1 Land Use and Acquisition 69 3.4.2 Land Rental and Asset Control 75 3.5 Chapter Summary 75 CHAPTER IV. LAND RENT THEORX——RELEVANCE AND IRRELEVANCE 79 4.1 Land Rent Theory Reviewed 79 4.1.1 Resource Use Intensity in the Short Run 81 4.1.2 Resource Use Intensity in the Long Run 83 4.1.3 Resource Allocation Among Competing Enterprises 84 4.1.4 Tenure Uncertainty and Time Relationships in Leasing 86 4.2 A Review of Past Empirical Research Testing Rent Theory 87 4.2.1 Intensity of Resource Use 88 4.2.2 Lease Types and Enterprise Combinations 89 4.2.3 Resource Efficiency in the Long Run 89 4.2.4 Overview of Empirical Testing of Leasing Theory 91 4.3 Reasons for Deviation of Findings from.Theory 91 4.3.1 Leasing Under Pressures for Farm Expansion 91 4.3.2 Internal Inconsistency in Leasing Theory 95 4.3.3 Assumptions Behind the Theory 102 4.4 Chapter Summary 104 CHAPTER V} THE FARMLAND RENTAL—STRUCTURAL CHANGE INTERFACE-SPECIFIC ASPECTS 105 5.1 Rental Land Availability and Firm.Gr0wth 105 5.1.1 Probability Analysis of Renting Farmland 105 5.1.2 Rental Land Availability in the Firm.GrOwth Process-HA Model 113 5.1.3 Analysis of Findings 118 5.2 Mbltiple—Unit Leasing and Uncertainty 122 5.2.1 A Framework fer Analysis 123 5.2.2 The Findings 124 5.2.3 The Implications 127 5.3 The Decision to Rent or Buy 128 5.3.1 The Present WOrth Analysis Framework 130 5.3.2 A Decision Matrix 132 5.4 Famflarxi Rental and Business Organization in the Farming Sector 137 5.5 Chapter Summary 143 Table of Contents (Continued) CHAPTER VI. SUMMARY, CONCLUSIONS, AND IMPLICATIONS 6.1 Summary and Conclusions 6.2 Implications 6.2.1 Land Tenure in the Fature 6.2.2 Entry and Exit 6.2.3 Organizational Impact and Income Distribution 6.2.4 Environmental Issues and the Quality of Life 6.2.5 Shortages in Today's Setting 6.2.6 The Perspective of the Policy Maker APPENDIX BIBLIOGRAPHY 147 147 153 154 157 158 159 162 166 168 189 Number 2.1 2.2 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11 LIST OF TABLES value of farmland rented from nonoperator landlords as compared with farm mortgage debt outstanding of farm operators by farm production regions, 1970 . . . . . . . . . . . . Days reported worked off farm by tenure of operator, 48 states, 1969 . . . . . . . . . . . Number of farm.operators interviewed, average acreage operated, owned, and rented; and percent of farmland rented, selected areas, 1971 . . . . Percentage of farm operators interviewed and prOportion of farmland rented by acreage size class, selected areas, 1971 . . . . . . . . . . Percentage of farm operators interviewed and average rate of tenancy by gross receipts from farm.marketings in 1970, selected areas, 1971 . Percentage of farm operators interviewed and average rate of tenancy by number of years farmed, S€1€Ct€d was, 1971 o o o o o o o o o o o o o 0 Occupation of landlords, selected areas, 1971 . Residence of landlords, selected areas, 1971 . . Length of time tenant has rented the property, selected areas, 1971 . . . . . . . . . . . . . . Type of lease used, selected areas, 1971 . . . . Percentage of written leases by selected characteristics, selected areas, 1971 . . . . . . . Reason why land became available fOr rent, selected areaS,197l.o....o............. Source of market information, selected areas, 1971 . vii 14 19 43 44 45 46 48 49 51 53 55 58 59 Number 3.12 . 3.13 . 3.14 . 3.15 . 3.16 . 3.17 . 3.18 . 3.19 . 5.1 . 5.2 . 5.3 . 5.4 . List of Tables (cont'd) Incidence of discussion and negotiation between the tenant and the landlord at lease renewal, selected areas, 1971 . . . . . . . . . . . . . . Tenants' opinion of ability to rent tract in the future, selected areas, 1971 . . . . . . . . . . . Tenants' desire to rent tract in the future, selected fleas ’ 1971 l O O O O I O O O O O O O O 0 Land base characteristics of part owners and tenants, selected areas, 1971 . . . . . ...... Method of acquisition of owned land and incidence of previous rental, selected areas, 1971 . . . . . Tenure characteristics of farms expanding in acreage size over last five years, selected areas, 1971 O O O O I O I O O O O O O I O I O O O O O O 0 Farm operators' intentions for land rental in the future, selected areas, 1971 . . . . . . . . . . . Average value of real estate and total production asset value and relative importance of rental land value to total by selected characteristics of tenant and part-owner farms, selected areas, 1971 Estimation of rental acreage available annually based on effective market radius, percent of tenancy, and annual turnover rate of rental property . . . . . . . . . . . . . . . . . . . . . Annual probability of farmland being available fer rent, by rate of tenancy, annual turnover rate, effective market radius, and size of tract . . . . Growth of accumulated net worth and crop acres fer various probability levels of renting land not previously rented (PRLNPR) and of renting land previously rented (PRLPR) . . . . . . . . . . . . Annual probability of losing various land incre— ments on a hypothetical 480—acre rented farm under different leasing combinations . . . . . . . . viii 63 67 68 71 72 73 74 76 107 110 120 125 Pleas}: 5.5 . 5.6 . 5.7 . 5.8 . 5.9 . 5.10 . A.l . A.2 . List of Tables (cont'd) Annual internal rate of return on investment under selected rates of land value appreciation, mortgage interest rates, and downpayment levels . . Annual internal rate of return on investment under selected rates of land value appreciation, mortgage interest rates, and downpayment levels . . Percent of: farm numbers, land in farms, and market value of land and buildings of economic classes I - V'farms, by farm.production regions, 1969 O O O I O I O O O O O I O O O O O O O 0 O O O 0 Average farm.size and average market value of land and buildings per farm, for economic classes I - V farms, by farm production region, 1969 . . . . . . . Percent of farm numbers and percent of land in farms by type of organization and by tenure for econanic classes I - V farms by farm production region, 1969 . . . . . . . . . . . . . . . . . . . . Percent of land in farms rented by type of farm organization for economic classes I -'V farms, ’48 States, 1969 o o o o o o o o o o o o o o o o o 0 Appendix Tables Farmland rented: acreage, percent of all land rented, percent of rented portion rented by part owners, and percent of rented portion rented from nonoperator landlords, 48 states, 1969 . . . . . . . Total value of farm.real estate, value of rented portion and percent of total, and value of portion rented from nonfarm landlords and percent of total, 48 states, 1969 . . . . . . . . . . . . . . . Page 133 135 140 141 142 144 168 169 Number A.3 . A.4 . A.5 . A.6 . A.7 . A.8 . A.9 . A010 0 A.11 . A.12 . A.13 . A.14 . List of Tables (cont'd) Percent of: Farm numbers, land in farms, and market value of land and buildings for econonic classes I -'V farms, by tenure, 48 states, 1969 . . Average farm size and average market value of land and buildings per farm for economic classes I —'V farms, by tenure, 48 states, 1969 . . . . . . Average per farm.value of agricultural products sold and distribution of total receipts for economic classes I - V farms, by tenure, by farm production regions, 1969 . . . . . . . . . . . Tenure characteristics by economic class for economic classes, by farm production regions, 1969 . Percent distributions of farm.numbers, land in farms, and total market value of land and buildings by age of operator for economic classes I —'V farms, by farm production regions, 1969 . . . Average acreage size of farm and average market value of land and buildings by age of operator for economic classes I -'V farms, by farm production regions, 1969 . . . . . . . . . . . . . . . . . . . Tenure characteristics by age of operator fer economic classes I -'V farms, by farm production region ’ 19 69 O O O O O O O O O O O O O O O O O O O 0 Percent of land in farms rented by age of operator for economic classes I - V farms, 48 states, 1969 . Percent of distribution of land in farms by acreage size class of economic classes I —'V farms, by farm.production.region, 1969 . . . . . . . . . . . . Average market value of farmland and buildings per farm by acreage size class of economic classes I —'V farms by farm.production region, 1969 . . . . Percent of land in farms rented by acreage size class of economic classes I -‘V farms, by farm production region, 1969 . . . . . . . . . . . - Land in farms by economic class and distribution of land.among economic classes, 48 states . . . . . . . X Page 170 171 172 173 174 175 176 177 178 179 180 181 List of Tables (cont'd) Number Page A.15 . . . Average acreage size and average market value of land and buildings, by economic class, 48 states . . 182 A.16 . . . Percent of land in farms rented by economic class, by farm.production regions, 1969 . . . . . . . . . . 183 A.17 . . . Number of farms and land in.farms for economic classes I - V cash grain farms, by selected states and farm production regions, 1969 . . . . . . 184 A.18 . . . Average acreage size and average market value of land and buildings per farm.f0r economic classes I - V cash grain farms, by selected states and farm.production regions, 1969 . . . . . . . . . . . 185 A.19 . . . Percent of farmland rented of land in farms for economic classes I -'V cash grain farms, by selected states and farm.production regions, 1969 . 186 A.20 . . . Coefficients of concentration of land in economic classes I -'V farms, 48 states, 1969 . . . . . . . . 187 A.2l . . . Percent of: All land owned and all land rented by economic class, by farm production regions, 1969 . . 188 xi LIST OF FIGURES Number 3282 2.1 . . . Tenure characteristics by economic class of farm, ’48 States, 1969 o o o o o o o o o o o o O o o o o o 18 2.2 . . . Tenure characteristics by age Of operator, 48 States, 1969 o o o o o o o o o o o o o o o o o o o o 22 2.3 . . . Average acreage of owned and rented land in farms by age of Operator, 48 states, 1969 . . . . . . . . 23 2.4 . . . Production possibilities and values relating to money income and ownership with welfare maximiza— tion 0 C O O C O O O C C O O O C C C I O O C O C O O 2)4 2.5 . . . Tenure characteristics by type of farm, 48 states, 1969 C O O C O O C C O O O O O O O O O C C O O O C O 29 2.6 . . . Lorenz Curve and Gini Ratio . . . . . . . . . . . . 32 2.7 . . . Concentration of farmland owned and rented . . . . . 34 3.1 . . . Michigan Study Area . . . . . . . . . . . . . . . . 41 3.2 . . . Illinois Study Area . . . . . . . . . . . . . . . . 41 4.1 . . . Share lease model with cost sharing . . . . . . . . 82 4.2 . . . Production possibilities with different rental shares between competing enterprises . . . . . . . . 85 4.3 . . . Production possibilities fOr part-owner Operations . 86 4.4 . . . Longarun adjustments Of firm size . . . . . . . . . 92 4.5 . . . Shareleasing with one tenant . . . . . . . . . . . 97 4.6 . . . Share leasing with.multiple tenants . . . . . . . . 98 4.7 . . . Maximization of firm efficiency under share tenancy WithWtCOStSWj—rlgoooooooo0.000000 99 5.1 . . . Year—end decision flow chart . . . . . . . . . . . . 117 xii CHAPTER I INTRODUCTION ". . . and remember the land is mine so you may not sell it permanently. You are merely my tenants and share croppers." —Leviticus 25:23 Instructions of the Lord to Moses on Mount Sinai 1.1 The Problem Setting The U. S. farming sector has been and continues to be in a rapid process of change. While there are many dimensions, key structural trerfis are (l) the process of farm consolidation and growth and (2) the rising capital and credit intensity Of agricultural production .1 Farm mmbers have steadily fallen from 6.1 million farms in 1940 to 2.9 million farms in 197 0. Average farm size has more than doubled over this period as smaller units ceased Operation and were incorporated into larger farming Operations . In addition to this dranatic reduction in aggregate numbers , resource control and agricultural production are now concentrated within the larger operating units . More than half Of all production of farm marketings 1In this study the word, structure, will refer to the organiza- tion, ownership, and control Of agricultural production units . Included in this concept are such factors as farm size and numbers, capital and land tenure characteristics, managerial control, exit and entry Opportunities, firm growth, an). information flow. 2 in 1969 took place on the 223,000 largest farms (farms grossing more than $40,000 annlally [531.1 Technological advancement is one Of the primary factors underlying this adjustment . Maintaining or expanding farm incane through capital-labor substitution and the capturing Of size economies have encouraged the expansion of Operating units . Obviously, not all farm operators can or do take the expansion route. Sane accept lower returns to their resources than the opportunity costs and do not alter their production unit . Some leave farming entirely, while other Operators adjust through supple— mental Off-farm employment . Nevertheless , in the major crop-producing regions , technological developnent has encouraged substantial farm consolidation, and with it, changes in the ownership ard use patterns Of farmlani. Increasing capital requirements within the farming sector have accompanied the farm consolidation process. As stated by a group of researchers studying the financial structure of U. S. agriculture, We have been evolving to a capital-intensive farming where decisions are shared by many components of the agricultural industry. Capital requirements have increased so that internal savings are a completely inadequate source of funds for nany types Of farming. [52] The obvious manifestation Of this has been expanded credit use. Total U. S. farm debt rose from $24.8 billion on January 1, 1960 to $58.1 billion on January 1, 1970 [51]. Based on research by Dr. John R. Brake, Michigan State University arrl Dr. Enamel Melichar, lBracketed numbers refer to items in the bibliography. 3 Federal Reserve System, projections of future credit needs range from $120 billion tO $136 billion by 1980 [8]. In addition to the expanded role Of credit in corrmercial agadculture, there has also developed among producers, a greater interest in alternative ways to meeting expanding land and capital needs. Equipment leasing, hiring Of custom services, and vertical coordination and integration schemes have become more common in recent years. Hewever, in terms of dollar value, the primary alterna- tive to resource ownership continues to be farmland rental. There is evidence to suggest there is growing separation of use rights or control Of farmland and ownership. The proportion of all farmland acreage being rented has increased slightly from about 33 percent in 1949 to 38 percent in 1969. Mere importantly, however, it appears the composition of tenancy has changed. This is reflected in the trend in farm tenure toward part ownership. In 1949 part— owner farms accounted fOr about 37 percent of all land in farms and 45 percent of all land rented. By 1969, over half of the nation's farmland was in the part-owner Operations and about two—thirds of the rented acreage.1 1.2 The Problem The separation Of farmland ownership and use through rental is believed to be an influential parameter Of the physical, financial, lPrecise comparisons are not possible between the 1969 Census Of .Agriculture estimates and statistics from earlier Census years due to changes in tenure definition and classification in the 1969 Census. 4 ani managerial organization of the U. S. farming sector. This is particularly true of those farms in the crop-oriented subsector which is Often referred to as land-based agriculture. Furthermore, projections and predictions of economically viable-sized farm units in the future suggest land rental will play an increasing role in organizing those units with asset values approaching 1/4 to 1/2 million dollars [41, 4]. Despite a significant (and signs of an expanding) role in present ani emerging structure, the land rental process and the institutions through which it functions have largely been taken as given by the researcher and the policymaker. A comprehensive investigation is called for. In discussing aspects of firm growth and agricultural adjustments, Hottel and Martin noted the increasing need to study such factors: With fewer, larger, and more productive farms, externalities between producing units involving problems Of land market values, technological progress, resource acquisition, resource use, termre and structural production, and marketing problems will become more important in the agricultural production industry . There is a void in knowledge and economic theory regarding these important areas, particularly as these questions relate to firm growth and farm adjustments. [26 p. 10]. While obviously not the only influential parameter of structural change, the land rental process is certainly an important one, not only in the firm context but also in broader implications concerning the farming sector itself. In light Of this, this study was launched to analyze (l) the farmland rental process, (2) the institutional framework through which it functions, and (3) the interrelationships of this process with current structural trerds. l. 3 Research Obj ectives 1. Describe farmland tenure patterns in the U. S. and identify factors affecting the level of rental activity. 2. Analyze the characteristics of the rental market process using a case study approach . 3. Review and appraise theoretical models pertaining to land leasing. 4. Identify the interrelationship of farmland rental with present and emerging structural organizational trends of U. S . land- based agriculture. 5. Appraise the farmland rental process and the interrelationship with structural trends using selected conduct and performance criteria . 1. 4 Study» Design and Format Domestic lard tenure research of any empirical nature has generally been concentrated at the two extremes—either the specific firm level, or the aggregate level. The former is so detailed that generalizations to a broader base are precluded. The latter lumps such heterogeneous elements that it , too , cannot provide generaliza- tions of any significant degree Of explanable worth. The initial step of this study is therefore a comprehensive investigation of land tenure patterns across the country. This not only provides meaningful scope to the study, but it also is an empiri- cal base for more detailed analysis of the land rental-structural change relationship. Secondary data, primarily from the 1969 Census of Agriculture, is used in this phase. Analysis of these arri related data are presented in Chapter II. The actual rental process itself is believed to directly influence the characteristics of farmland leasing in U. S. agriculture. Thus, the secorri phase of this study is an analysis of selected rental markets, identifying what individuals actually do and why in relation to land use. Survey technique and analysis Of findings are presented in Chapter III. Several theoretical models which relate to the issues under study are outlined and discussed in Chapter IV. Past empirical effort to test various aspects of leasing theory is reviewed, and reasons for deviation of the theoretical models from real-world conditions are presented. The relationship of land rental and structural change is two way. Chapter V centers on the impact Of farmlard rental on structural trends. One important facet is the use of land leasing in farm acreage expansion. More specifically, the question of availability of rental land is a common real-world constraint that can directly influence the process of firm growth. By modifying a previously developed growth simulation model to include probability factors of land availability, this question and its relevance to Objectives of firm growth is studied. Also related to this is analysis of the practice Of multiple—unit leasing and the impact of this on the risk and uncertainty Of the land base. A third aspect to be considered is the interrelationship Of the rental market with the title transfer market . While there are several ramifications , the micro-economic question of "buying versus renting" is a significant portion of the relationship. This specific question will be studied under varying conditions usirg a present worth analysis framework. Chapter V concludes with a discussion of land tenure patterns under various forms Of firm organization. Chapter VI summarizes the study and draws the major conclusions. Implications of the farmland rental process concerning various economic arrl social objectives are also developed using a framework of selected conduct am performance criteria. CHAPTER II FARMLAND TENURE PATTERNS IN THE UNITED STATES In studying the interrelationship of farmland rental and structural change, it is necessary to have a general understanding Of farmland tenure patterns, both past and present. This chapter describes and analyzes the nature Of the man-land relationship throughout the country using secondary data from the Census of Agriculture. Emphasis is placed primarily on the aspects Of control- 1 Part 1 deals with land tenure relationships ling farm real estate. of all farms over time and identifies the participants. Part 2 is a more refined analysis of current tenure patterns Of Census Economic Classes I - V farms. Part 3 centers on the concentration Of the land PGSOUI’CG . 2.1 Farmland Ternlre Patterns—All Farms The high productivity and abundance of U. S. agriculture can be traced in large part to its rich resource endowment. In 1969, U. S. land in farms totalled 1.06 billion acres, a slight decline from five years earlier due to shifting use into urban and other 1In this study, control of farmland refers to access to decision-making prerogatives over the land resource such as rights of Occupancy and use. Excluded from this concept are claims on income derarri which arise solely out Of ownership. For a more detailed discussion of these attributes of tenure rights see [40, p.3]. 9 nonagricultural uses.1 This land base is distributed (unevenly) among approximately 2.7 million farm units ranging from tobacco and truck farms of a few acres in size to wheat farms and cattle ranches of several thousand acres. This heterogeneous nature of farms and farming enterprises greatly reduces the usability of any empirical data at the aggregate level. Thus, the analysis to follow not only considers various characteristics but also reduces the geographical perspective to state and regional levels where possible. 2.1.1 The Rented Portion The distribution of the total farmland acreage among states and farm production regions is presented in Appendix Table 1. While the rented portion cannot be taken directly from the Census state volumes, it can.be estimated from published data in the fellowing manner: (1) the rented portion of part-owner farms at the state level is available in the Census for economic classes I -'V farms only; this same ratio is assumed fer the other economic classes of farms also; (2) all land rented by part owners and tenants is assumed to be Operated by them and not subleased.2 Based on this estimation procedure, about 38 percent of all land in farms is rented. The 1Due to the specialized nature of their land resources and agricultural enterprises, Alaska and Hawaii are not included in this analysis. 2While these assumptions were not tested empirically, the proportion of total acreage affected by the assumptions is minimal. For example, expanding the rented ratio for classes I — V'part—owner farms to all part—owner farms is, in effect, using actual data from 96 percent of the total land area to estimate for the remaining 4 percent. Likewise, the question of subleasing is minor since land rented out by part owners is less than 3 percent of the total land acreage in part-owner farms, most Of which is probably land owned by part owners. 10 proportion rented ranges from about 20 percent in the Northeast and Appalachian states to over 40 percent in the Corn Belt, Plains states, and proportions Of the Mountain and Pacific regions. Due to a definitional change in the land tenure classification in the 1969 Census, a precise comparison with earlier years is limited.1 However, the proportion Of farmland rented does appear to have been increasing slightly over the last twenty years. In 1950, 33 percent Of all land in farms was rented [40, p. 35]. Prior to that time the prOportion Of farmland rented.had.gradually fallen from a previous high of 45 percent in 1935, the midst of the depression. As indicated in Appendix Table l, the relative importance of land leasing varies widely geographically. Several factors have been hypothesized as being contributors to this variation. In the Corn Belt states, relatively high land values and the resulting large investment requirement, it is believed, encourage land rental as an alternative to owner Operatorship. Then, too, the cash grain type of agriculture which predominates in the Corn Belt has a short planning horizon.with fixed investments of secondary importance. In this setting, Dovring argues the relative instability of short-term tenancy proves tolerable [15, p. 1266]. Higher rates of land rented are also prevalent in many Western states where the agricultural enterprises are quite different. Much 1The primary change in the 1969 Census was the dropping of the "Manager" category from.the tenure classification. Because this concept was believed to be no longer descriptive of a distinct type of farm management, farms that would have qualified as managed in the prior Census definition were distributed among full owners, part owners, and tenants according to the reported ownership of the land in the 1969 Census. ll of the land is being rented for the more extensive type land uses such as summer-fallow wheat production and livestock grazing.1 Here, the factor of availability may be the primary force on the rate of tenancy. That is, where Operating units must be considerably larger than the typical size Of ownership unit, then the process of accumulating the land resource base may require reliance on rental as well as purchase. In short, the rate of tenancy may be directly influenced by the size Of acreage operation. Throughout the Northeast , Appalachian, and Southeast regions , relatively lower proportions Of farmland is rented. This may be due in part to (1) generally smaller farm units (in terms of acres) which are frequently dependent primarily on dairy or livestock feeding enterprises and (2) the greater reliance on Off-farm income sources. Directly and indirectly these factors can reduce the relative importance of the land base to the present and ongoing income and wealth position of the Operator. 2.1.2 Part-Owner Dominance Throughout the country, the major share of land rented is being rented by part owners (operators who Operate land they own as well as land rented from others). As shown in Appendix Table l, in only two states (Illinois and Iowa) do full tenants operate a larger portion. The fact that two out of every three acres of rented farmland is now operated by part owners is the result of a long—run trend 1Government—owned grazing land is not included in the Census measure 0 12 away from full tenancy. In 1940, the proportion was just reversed with the part-owner group accounting for less than a third of the rented acreage. Since that time, however, the role of tenancy has changed; i.e. , in the pre—World War II years tenancy was still predominantly a rung in the traditional "tenure ladder" concept in which an Operator would rent a farm until such time that he could purchase it. But with the significant technological advancements of the last three decades and the accompanying trend towards larger, more specialized farms, the role of farmland rental has shifted towards acquiring the additional land base. Capital limitations as well as limited availa- bility of land to purchase has encouraged farm size expansion via rental. Many Operators who were once classified as full owners have chosen this route and have consequently been reclassified as part owners.l As size expansion has progressed, tracts that were once whole farms operated by full owners or full tenants have been consolidated into larger units, thus contributing further to the increasing predominance of part ownership . SO long as pressures to exparri farm size continue, this characteristic Of farmland rental will likely become more pronounced. And with it a further separation of resource ownership and control. 2.1.3 Nonoperator land Ownership In most states, over 80 percent of the rented acreage is owned by nonoperator landlords. Since active farmers tend to Operate all the 1It should also be noted that full tenants have also faced simi— lar motivations for acreage expansion such as excess labor and machinery capacity. And while many Of then have rented additional tracts, many others have purchased additional land, which has moved them into the part-owner tenure classification also. l3 lard they own, only a small portion of the rented land is rented from other farm Operators . This high incidence of nonoperator ownership must be considered an important source of capital input into the farming sector. Without this degree of input, past trends in farm consolidation and growth would undoubtedly have been slowed. In terms of dollar value, the total farmland asset contribution by nonoperator landlords is a third of the current market value Of farm real estate (Appendix Table 2). There is wide variation geographically, ranging from 13 percent in West Virginia to over 50 percent in Illinois. But while the relative importance varies widely, it is clear that the rental process provides a far greater service in the acquisition Of use rights to land than do the credit institutions. A measure Of the relative importance of farmland leasing versus real estate debt can be made after allocating total real estate debt outstanding between farm Operators and landlords. This allocation was done by USDA researchers for the total farm real estate debt in 1969 [50]. This aggregate estimate of the Operator and landlord shares was assumed to be consistent among all regions of the country. Thus, by using this ratio, regional estimates of farm mortgage debt were adjusted to represent the farm operator share only. When compared with the current market value of real estate rented from nonfarm landlords, the value Of the latter is about three times the value of farm mortgage debt outstanding held by farm Operators (Table 2.1) . Admittedly, the information in Table 2.1 is a crude measure. Due to land value appreciation, the dollar value Of real estate debt outstanding understates the current market value of real estate 14 controlled via the credit route. In part, this is offset by the fact that leasing arrangements frequently include access to nonland assets as well; i.e., a portion.of Operating capital under typical share— rent leasing, or livestock under livestock share leasing. But while the refinement of these estimates may be argued, the magnitude of the difference is believed to be significant. Table 2.1 value of farmland rented from.nonoperator landlords as compared with farm mortgage debt outstanding Of farm Operators by fanm production regions, 1970. Percent Of Total Value Total market Farm.mortgage value Of Rented from. debt outstandr Region farmland and non-Operator ing of farm buildings, landlords, Operators, March, 1970 1969 Jan. 1, 19703 Million Dollars Percent Percent NOrtheast . . . . 11,154 22.6 12.9 Lake States . . . 14,597 23.2 15.1 Corn Belt . . . . 49,600 41.3 9.0 Northern Plains . 22,778 39.7 8.6 Appalachian . . . 15,949 19.8 9.8 Southeast . . . . 13,583 17.9 11.8 Delta . . . . . . 10,972 33.1 12.2 Southern Plains . 27,384 37.4 7.7 MOuntain . . . . 17,443 34.2 12.1 Pacific . . . . . 23,593 36.1 15.5 48 States . . . 207,053 33.5 10.8 aTotal regional debt outstanding adjusted by applying Operator share of total aggregate debt as estimated in The Balance Sheet of the Farming Sector-l969. [50, p. 29]. 15 2.2 Tenure Patterns of Economic ClaSses I - V Farms Additional information on land tenure is available in the 1969 Census of Agriculture for economic classes I - V farms (farms with annual gross sales of $2,500 or more).:L Unlike prior Censuses, the 1969 Census provides tabulations Of the acreage owned and acreage rented by various characteristics of the Operator and the farming operation for economic classes I through V farms. Thus, additional insight can be gained concerning actual ownership and control of farmland and the degree of concentration. 2.2.1 Characteristics by Tenure of Operator Classification by tenure of operator is a crude form Of break— down due to the ambiguity of the part-owner category. A farm operator may own 1 percent or 99 percent of the land he Operates and still be considered a part owner. Yet this classification scheme provides a useful starting point for tenure analysis. About half Of all classes I - V farms are Operated by full owners, yet the prOportion of land Operated by this tenure group is less than 30 percent Of the total acreage (Appendix Table 3). In contrast, part-owner Operations represent about a third of the farm units but account for about 58 percent Of the lard base. There is substantial variation among states and regions, however. In the Northeast, Lake States, Appalachian, and portions Of the Southeast region, the full—owner class still accounts for the largest share of JWhile representing roughly two-thirds Of total farm numbers, classes I - V farms account for 86 percent Of all land in farms, 95 percent of farmland rented, and over 95 percent Of annual cash receipts from farm narketirgs. Consequently, the aralysis is not believed to be limited by the exclusion of the "other farms" categories. 16 the land base. It is in the Plains region and Western states, particularly where the dominance of part ownership is most evident, both in terms of acreage and real estate value, although to a somewhat less extent with the latter. Part-owner units are considerably larger than their full-owner counterparts throughout all regions (Appendix Table 4). The difference is most extrane in the Western states where the rature of the farming enterprises tend to differ with tenure. That is, part—owner operations will tend to be the more extensive land use operations, whereas full— owner farms will Often be smaller acreage, more intensively used units. Part owners on average control substantially greater real estate assets than either full owners or full tenants. In the West, the wide differential that was evident in average acreage size was reduced somewhat by lower valued land in part-owner units . However , in most other states, land in part-owner farms has a higher market value than full-owner land due to the greater percentage of cropland in these farms. For example, in the Corn Belt states, 81 percent of the part-owner acreage is cropland as compared with 72 percent of the full-owner acreage . The larger proportion of crOpland and, hence, higher average value of part-owner land again reflects variation in the relative importance of various farming enterprises among tenure classes. Part owners and tenants generally rely more heavily on crOp enterprises and therefore need a relatively higher quality land base. In contrast, full-owner operations frequently are specialized livestock units with the land base being either partially or totally replaced by purchased feed inputs . 17 Of the three tenure classes, part-owner units are also the largest in terms Of average annual gross farm receipts (Appendix Table 5). Full-tenant farms are second in.average size in most regions. Yet because Of their greater numbers, full-owner farms still account fOr the largest share of cash receipts in five Of the ten.regions. Looking at the tenure pattern by economic classes also indicates the larger average size Of part-owner units relative to full-owner and full-tenant farms. In 1969, 51 percent of class I farms (annual gross sales of $40,000 or more) were part-owner units, and 33 percent were operated by full owners (Appendix Table 6 and Figure 2.1). While in the class V category (annual gross sales of $2,500 to $4,999) only 18% of the farms are part-owner operations,and 69 percent are full-owner units. This pattern Of size variation.among the tenure classes would seem to suggest that part owners are generally the more aggressive farmers, while the fu11 owners represent a class that has been less successful in.adJusting to economic conditions [33, p. 1555]. Harris has suggested, in fact, that owner—operatorship is attained at the expense of economic-size units for many full owners [20 , p. 3]. Hewever, the greater tendency for full—owner farms to be smaller units does not necessarily mmply that full owners are failing to generate adequate annual income. A full owner receives all receipts from farm marketings, including the rent share which a tenant would incur as a cost. TherefOre, the full-owner operation can be smaller than a rented operation (in.terms of acres and cash receipts) and still yield a comparable annual net farm.income for the Operator. Another factor is that many full owners are Older operators who have 18 D Full Owners 9,975 60 Part miners 59% Tenants F ‘ 51% g 4 46% 0 no \ £3 3 36 37% - ' 6% 20 17% 8% 15% 7% 5% 3%. 0 $40,000 $20,000— $10,000- $5,000— $2,500- or more 39,999 19,999 9,999 4,999 Annual Gross Farm Receipts Figure 2.1 Tenure characteristics by economic class Of farm, 48 states, 1969. established financial security and are in the process of scaling down their Operations (see section 2.2.2) . Then, too, Off-farm employment can allow fuller utilization Of labor resources and, in turn, supple- ment farm earnings. Census data on days reported worked Off the farm show the incidence of Off-farm work to be fairly similar among all tenure groups; the percentage Of full owners, part owners, and tenants reporting days worked off farm were 44 percent, 40 percent, and 19 48 percent, respectively (Table 2.2). Yet the extent Of this employ- ment varies significantly .1 Nearly 60 percent of the full owners who reported Off-farm work were working Off the farm 200 days or more annually (essentially full time), as compared with less than 40 percent of the part owners and terants who reported any Off—farm employment . This relationship consistently appears in all regions Of the country. In effect, then, there does appear to be a higher dependence in the full-owner tenure group on Off-farm income sources . But whether or not this greater dependency in the aggregate is influenced more by economic necessity than by persoral choice remains unanswered. Table 2.2 Days reported worked Off farm by tenure Of operator, 48 states, 1969.a Number Of days Percent of all farm Operators reporting reported worked Off days worked off farm by tenure, 1969 farm annually Full Owners L Part Owners I Tenants . 0 O O O O O I Pacent . O O O O O C I l — 49 Days . . . . . . 8.0 14.8 15.2 50 " 99 Days 0 o o o o o 3.7 5.0 6.3 100 — 199 Days . . . . . . 6.5 6.0 7.6 200 Days or More . . . . . 25.6 14.6 18.6 Total 43.8 40.4 47.7 aSource: 1969 Census of Agriculture, economic classes I - V farms. v—v 1Statistically significant at 1% level of confidence using Chi Square Test Of Independence. 20 2.2.2 Tenancy Patterns gy Age Of Farm Operator Since single proprietorship is the primary organizational form within the U. S. farm sector, age of operator is a useful classifi- cation in studying tenure. The dynamics of land ownership and rental tie closely to the life cycle Of the farm Operator. Labor resources, income demand, financial position—these are factors which change over time for the individual Operator, and, hence, his relationship to land. In distributing farm numbers and land in farms into age classes, a skewed distribution pattern towards the Older age groups is preva- lent. The majority Of farm operators, 68 percent, are 45 years Of age or Older and Operate 68 percent Of all land in classes I - V farms (Appendix Table 7). This pattern is prevalent in all regions. On a per-farm basis, the pattern among age groups takes on a somewhat different characteristic. Farm Operators of 35 to 54 years Of age tend to be farming the largest acreage units (Appendix Table 8). This size distribution is consistent with the labor cycle Of most farm Operators; many atterrpt to increase farm size during the period Of time when family labor resources are maximum, and then gradually cut back as the Operator himself prefers to reduce his own labor output and as his family leaves the farm. Although other factors frequently override the labor resource influence, regional variations add support to this; i.e., most significant size variations are in those regions where land-intensive farm enterprises predominate. As for actual lard tenure changes over the lifespan of farm Operators , this study cannot give a catprehensive picture . To fully answer this question would require monitoring and analysis over time 21 of identified representative farms. However, some insight can be gained by Observing tenure characteristics over the age categories, bearing in mind that historical forces can and do distort inter-class comparisons. The general pattern is one Of a high proportion of full tenants in the youngest age class with a shift to a high proportion of full owners in the oldest age class Of farm.operators (Figure 2.2 and Appendix Table 9). 'The prOportion Of part owners reaches a maximum in those age brackets where farm.size is maximum, Which supports an earlier statement that part ownership is a companion trend of farm size expansion and consolidation. Using a more precise measure, the proportion Of farmland rented, similar significant differences exist among the age categories (Figure 2.3 and Appendix Table 10). Due to both a decrease in average acres rented and an increase in average acres owned, the proportion Of the Operated land base that is rented drops steadily from the youngest age class to the Oldest age class. Rented land is the major portion of land in farms fOr the youngest age group in all but two regions, being as high as 74 percent in the Corn Belt. For operators 65 years of age or Older, the rented portion accounts fOr a fifth or less Of Operated acreage throughout the Eastern half Of the country and a third or less throughout most western states. The tenure pattern over the age classes may partially reflect the influence of the traditional "tenure ladder" concept whereby a young operator begins farming by leasing land, and over time, builds up enough equity and credit to purchase an increasing share Of his land. In this respect, the "tenure ladder" notion still appears 22 to have some validity. What is debatable, however, is the question of ends to which this process is directed; i.e., is unencumbered land ownership still the primary end? 80 Full Owner 60 / .. g “0 / d E). " """"‘-- Part Owners (1) ‘s 0-: ‘0“ 4' \n~ 4’ '~‘~ 20 7. .II . \. Tenants \.N O L l n l n I V Less than 25-34 35—44 45-54 55-64 65 or 25 more Age Of Operator Figure 2.2 Tenure characteristics by age of Operator, 48 states, 1969. Heady has studied this particular issue using a theoretical framework [22]. He constructed a production.possibilities curve as in Figure 2.4 and considered utility maximization in the tradeoff between quantity Of land ownership and quantity of money income. Representing the individual or group preference system by the 23 Acres Rented 100 / o . . i /. Less than 25-34 35-44 45—54 55-64 65 or 25 more Age of Operator Figure 2 . 3 Average acreage Of owned and rented land in farms by age of Operator, 48 states, 1969. t conventional indifference curve, MB, Optimization is achieved at less than full ownership (point A). This occurs in that range Of the production possibilities relationship where land ownership is in competition with money income; i.e. , when the price of land services (rental) is sufficiently lower than (a) the price Of the resource through the ownership market and (b) the marginal value productivity Of the resources used in production. 24 M\' M g P‘—-_\ s .3 “ E” P2 \\~. B' E Pl (’6' \ i \ 8' \ \L' o w3 \«r2 w1 Quantity of Land Ownership Figure 2.4 Production possibilities and values relating to money income and owner- ship with welfare maximization. Over the last two decades it is likely that the production possibilities curve has been changing. For example, structural trends of increasing farm size and consolidation could alter this curve from PL to P'L' . When production efficiencies of size and scale are prevented due to an inadequate ownership unit and/ or a burdensome real estate debt, then relatively less lard ownership is preferred (OW2 versus 0W1) . Moreover, there is some reason to expect the indifference curve to have also been shifting. Nany financial needs once met by full ownership are now achieved, at least in part, by other institutions; for example , social security and investment 25 returns from nonfarm.sources have reduced the relative importance Of land ownership as a source Of economic security upon retirement. Then, too, the ever-increasing predominance Of sepanation Of ownership and use in an industrialized economy such as this may diminish any social norms advocating full owner—Operatorship in.the farming sector. Consequently, the indifference curve may logically be shifting from MB to MFB', thus contributing fUrther to a relative reduction of ownership at the Optimumh To conclude, then, the tenure relationships fOund across age groups cannot be primarily attributed to the goal of full ownership. It is hypothesized that changes in.both acreage size and capital requirements of viable units limits ownership potential of today's younger OperatorwmuchImore than.that experienced by their Older generation counterparts. Then, too, aside from historical changes, it appears that age Ofxoperator, is, in fact, a proxy fOr other factors which change with age and tend to increase the level Of ownership irrespective of such a goal. variation in Operator and family labor resources over time, and its impact on size of Operating unit has already been'mentioned.l Secondly, the acquisition of ownership through inheritance, gift, or purchase from a relative (intergenerational transfer) also contributes to a declining dependence on land rental in the later years of the life cycle. This is in 1Not only in the expansion stage but also in the contraction phase is the land and labor resource relationship under change. It is during this contraction phase that the Operator Of a landebased farming Operation will tend to reduce his rented acreage before selling Off or renting out land that he owns (thereby reducing labor require— ments relatively more than the average level of his farm income). 26 addition to a credit position.that usually improves with years Of operation. Thirdly, income demand, more specifically the change in the composition of short-run and long-run income potential changes with age. Short-run or annual earnings are more critical to the consumption patterns Of the younger fanm family, whereas the older generation farm family may be more interested in investment with long-run.income potential. Finally, the aspect of availability Of land to purchase is a factor which can delay ownership several years. In part, greater ownership in the older age classes may be simply due to the probability Of availability which increases with time. 2.2.3 Tenancy Patterns by Acreage Size of Farm A wide range Of farm acreage size exists due to (l) variation in quality of the land resource and (2) differing land resource demands among farming enterprises . So , even within relatively small geographic areas, farms of virtually all sizes exist. However, the allocation of land acreage among these size groups varies widely among regions (Appendix Table 11) . At the extremes are the Mountain ard Pacific regions where 92 percent and 80 percent respectively Of the total land base is in farming Operations of 1,000 acres or more. In contrast, about 75 percent Of the land base in the Northeast and Lake States is in farming Operations of less than 500 acres in size. The average values of real estate assets per farm are presented in Appendix Table 12. Here, too, the variability both among and within regions is clearly evident . It should be noted, however, that £93211 asset value per farm may not vary as greatly over these farm acreage classes . Even though real estate on average represents about 75 27 percent of total asset value, the composition of production resources, including livestock and machinery as well as real estate, can vary greatly by type and size of farm. FOr example, a unit in the Corn Belt with less than.50 acres may, in fact, be a feedlot with a total asset value of several hundred thousand dollars, whereas the land may constitute essentially all Of the production assets Of a 1,500 acre wheat farm.in.Kansas. As fOr tenancy, in all regions, the percentage of land rented increases steadily from the smallest units through the 500—999 acres size class (Appendix Table 13). Beyond this size, the proportion drops off somewhat in a number of areas, particularly in those regions where such Operations represent capital investments of upwards of a million dollars or more. Nevertheless. it appears that large—scale Operations are not synonymous with large holdings of land under the ownership of a single individual or business entity. Rather, these units rely heavily on rental, and therefOre generally constitute land ownership holdings Of at least two or more individuals. 2.2.4 Tenancngatterns by Economic Class Of Farm VOlume of annual gross receipts from farm.marketings is a common measuring tool Of farm size. The advantage of using this classification is that size variables can be analyzed in relation to a measure Of income potential.1 The Census of Agriculture uses this LThe ratio Of realized net income to gross receipts varies cone siderably across size classifications. For example, the ratios for class I - V farms based on estimates fOr 1970 in the Farm Income Situe ation, FIB-218, July 1971, were as follows: class I, 21 percent, class II, 33 percent, class III, 39 percent; class IV, 42 percent; and class 'V, 48 percent. Thus, gross receipts can be considered only a crude measure Of income potential. 28 system with the following classes: class I - $40,000 or more; class II, $20,000 - $39,999; class III, $10,000 - $19,999; class IV, $5,000 — $9,999; and class V, $2,500 - $4,999- The distribution of farmland among class I - V farms varies widely both among and within regions (Appendix Table 14) . Less than a third Of farmland is concentrated in class I farms throughout the East, Midwest, and Northern Plains, while such farms account for over a half Of all farmland in most Western states. Part Of this variation can be explained by the difference in average farm size (Appendix Table 15) . Class I farms are typically two to three times larger than class II farms throughout the West, while the size difference is much more moderate elsewhere. With real estate asset value usually averaging more than $200,000 per class I farm, the reliance on land rental for such farms is substantial. In the aggregate, 46 percent of the land in class I farms is rented (Appendix Table 16) . In contrast, 28 percent Of the land in class V farms is rented. While there is variation in degree, this general pattern is evident in all but a few states. 2.2.5 Terancy Patterns of Cash Grain Farms Included within the statistics of farms by economic class are all types of farming operations . Some farming operations require a lengthy planning horizon and so, by nature, discourage lard leasing, which traditiorally has been short term. In other farming enter- prises, such as cattle feeding, the land base is relatively unimportant and represents a small part of total investment (see tenure patterns by type Of farm in Figure 2.5) . The inclusion of these operations, 29 therefore, creates a downward bias in the relative importance of farmland leasing to land—based agriculture. Because of this, analysis was made Of one specific type of farm—cash-grain agriculture. Cash Grain Tobacco Cotton Other Field Crop Fruit and Nut Poultry Dairy Livestock Livestock Ranches General . . P. 0 20 40 60 80 100 Percent (Accumulated) Figure 2.5 Tenure characteristics by type Of farm, 48 states, 1969 . 30 As indicated in Appendix Table 17 the majority of cash-grain farms are located in the Corn Belt and Northern Plains states.l Sizable numbers of cash—grain operations are also present in the Lake States and Delta regions. The highest concentration of such farms is in Illinois where 53 percent of all farms are classified as cash— grain units and account for 60 percent of the land base. Asset value Of the real estate in cash grain farms will generally run much higher than the all-farm average due to land quality as well as land quantity factors (Appendix Table 18). Average per- farm values were found to be consistently above $300,000 for class I farms grossing $40,000 or more in sales annually. Even class II farms were found to be approaching $200,000 per farm in many states. Investment levels such as this usually negates any Opportunity fOr full ownership of the land base by the Operator, unless he is fortunate enough to have access to financial windfalls. This then.promotes greater reliance on land resource control via leasing. For the largest cash-grain farms, rented real estate represents the major share of land in farms in nearly every state (Appendix Table 19). Roughly 60 percent of the land is leased. Assuming this land is approximately equal in per-acre value to the owned share Of land, then one can say that about $180,000 Of the $300,000 current 31The 1969 Census Of Agriculture has detailed data on cash-grain farms in 29 states. While other cash grain farms exist in other states, the relative importance of this enterprise was not sufficient to merit detailed statistics in these states. 31 market real estate asset value is leased from others. In the average Corn Belt class I farm, over $255,000 of the real estate assets are controlled by lease. While the proportion of land rented drops in the smaller sales classes, the average for all the classes of cash—grain farms was still over 50 percent. Farmland rental must therefore be regarded as an integral part of the firancial structure and growth strategy of cash-grain farms . 2.3 Concentration Of Land Ownership and Rental The preceding aralysis indicates that the lard resource is distributed quite unevenly among farm operations , with an apparent concentration of farmland in the larger units . However, the existence Of owned ani rented portions distorts the distributioral picture, preventing a valid appraisal Of distributional impacts. A more refined measure Of concentration is needed. To accomplish this, the Gini ratio is used to study how unequally land ownership and land rental are distributed among the various classifications Of the farm population. This ratio is derived from the Lorenz curve which is a plotting of the cumulative proportion of units arranged in order from the smallest unit size to the largest on the horizontal axis against the cumulative percentage Of the aggregate land base on the vertical axis (Figure 2.6) . If the land were distributed equally among all operators , the Lorenz curve would be a diagonal line extending from the origin. In this case, the Gini ratio, which is the ratio Of the area between the curve and the diagonal and the total area under the diagonal, would be zero. In 32 contrast, if one member of the population had all the land (perfect inequality), the curve would be the bottom and right straight lines, and the Gini ratio would be one. Ordinarily, the degree of concentra— tion will fall between these two extremes, with a value near zero indicating near equality and a value approaching one showing concentration. 100% Gini Ratio Percent of Acreage 0% Percent of Farm.Numbers 100% Figure 2.6 Lorenz Curve and Gini Ratio. 2.3.1' Degpee of Concentration by Age of Operator NEasures of concentration indicate there is virtually no concentration of the land resource by age Of operator. The Gini ratio fOr the aggregate Of all land in farms was .045, or near perfect 33 equality. Gini esttmates of regional distributions of land in farms were consistently below .060. In other words, the total.farmland base is distributed across age groups in nearly equal proportions to farm numbers. It was noted earlier that the proportion of land rented is highest among the youngest age class and decreases steadily across the other age groups. This would suggest some concentration of the rented land among younger farm.operators and consequently some concen— tration Of the land owned by farm.Operators among the older age groups. But separate Gini ratios fOr rented and owned land across age classes indicate the degree Of concentration is insignificant. For the 48-state aggregate the ratio fOr rented land was .128, and the ratio fOr land owned by farm Operators was .093.1 2.3.2 Degree of Concentration.by Acreage Size Class Based on distributions by acreage size Of farming Operation, a relatively high measure of concentration is found in the aggregate. Based on the 12-element classification.by acreage size Of farm, the Gini ratio fOr all land in farms fOr the 48 states is .67 (Appendix Table 20). When plotted, the accumulated percentage distribution shows that about 70 percent of all land in farms is in the largest one-fifth Of the Operating units (Figure 2.7). In contrast, the lThe higher Gini ratios fOr both the owned and rented breakdown than for the all-land average is due to the fact that rental land distributions is skewed somewhat toward the younger age classes, while the distribution of land owned is slightly skewed towards the Older age classes. The net effect then is fOr the combined farmland base to be more equally distributed across age groups. 34 smallest one—half of the farm units account for less than 10 percent of the total land base. 100 Q) 5%? 33 0 <1: a4 O s o O t (1.. 20 40 60 80 100 Percent of farms g, 100 a, 100 g 80 g) 80 . Rented Land O < 2 a, 60 Q4 60 0 o m s g 20 g 20 9* O o. 0 20 40 60 80 100 Percent of farms Percent Of farms. Figure 2.7 Concentration of farmland owned and rented. On a dollar value basis, a.much lower level of concentration is measured at the aggregate level. This is an indication that large acreage Operations generally are comprised of lower quality land than the smaller fann units. This is particularly prevalent in the Western states. Noteworthy is the fact that rented farmland is more concentrated in the larger acreage farms than is the farmland owned by Operators . In the aggregate, the Gini ratio for rented land is .72 as compared with .60 for land owned. In other words, three out of every four 35 acres Of rented land is Operated by the largest one—fifth Of the farms. This indicates that farmland rental is no longer just a temporary step for the beginning Operator, but is a key means Of resource control for the large, established commercial farm operation. State and region estimates of concentration generally reveal a similar pattern of relatively greater concentration of rented land than owned land. However, the _l_e_v_e_l_s_ Of concentration vary greatly. Lowest concentrations Of both land owned and land rented are located in the Lake States and Corn Belt regions, where the nature of the farming enterprises as well as the typical size Of Operation are relatively more homogeneous than elsewhere . Highest concentration levels are mostly in the Mountain and Pacific regions. On a state basis , California and Florida have the highest degree of concentration of farmland acreage; for all land in farms, the Gini ratios in these states are .85 and .81 respectively. The largest one-fifth Of the farming Operations in these two states account for about 9 out Of every 10 acres of farmland. In terms Of concentration Of farm real estate wealth, the data suggest the commercial farming sector is still one of a small land- holder type of agricultural Using the Gini ratio for dollar value as the initial measure of wealth concentration, it is generally fairly low. Moreover, even this ratio overstates the actual degree Of J‘I'he inclusion of only economic classes I - V farms in the ana- lysis reduces the level of concentration that would be evident for the total farm population. However, the omission of other farms is not believed to reduce the relevance Of this analysis Of concentration, since such farms are typically marginal in nature and frequently are nonagricultural activities. SO the inclusion of only economic classes I -- V farms, it is believed, more accurately defines the population Of the commercial farming sector. 36 concentration due to the aspect of land rental; i.e., while Operating units exist which are comprised of huge amounts of real estate wealth, the ownership of that wealth is frequently distributed over several land owners. Consequently, wealth in farm real estate generally does not show high degrees Of concentration, even though control Of use rights to this asset is quite unevenly distributed in many parts of the country. 2.3.3 Degree of Concentration by Economic Class About two-thirds Of the total rented land base of farms with sales of $2,500 or more is Operated by class I and II farms (Appendix Table 21). This ranges from 49 percent in the Appalachian.region to 75 percent in the Pacific region. Based on this distribution by economic class, the Gini ratio fOr rented land at the 48-state level is .44. Land owned by farm.Operators is less concentrated with a Gini ratio of .33. The levels of concentration by economic class are considerably lower than those fOr the acreage size classification since gross income is not necessarily correlated with the acreage base of the operation. Economic class I farms include all types Of’farming operations-—including those types in which the land base is a relae tively insignificant part of the total asset investment. 2.4 Chapterfimmmmmz Based on the 1969 Census Of Agriculture, about 38 percent Of all faumflamd.in the United States is rented. Nearly 90 percent of the rented land is owned by nonoperator landlords. Thus, land leasing 37 must be considered an important source Of external firancing for the farmirg sector. Following a long-run trend away from full tenancy, the major share is being rented by part-owner Operators , who typically Operate much larger units than either full terants or full owners. Over half of economic class I farms ($40,000 or more annual gross sales) were found to be part-owner units, whereas most smaller farms were full- owner Operations. Tenancy patterns vary substantially over the distribution of economic class I - V farms by age Of Operator. Most Operators in the youngest age class are full terants while those in the Oldest age class are generally full owners. Due not only to an increase in acres owned, but also to a decrease in acres rented in later years, the percent of farmland rented drops significantly from 65 percent in the youngest age class down to 27 percent in the oldest age group. This does not necessarily reflect the traditional concept of climbing the tenure ladder towards eventual full ownership , but rather the influence of historical changes in ability to purchase, as well as factors for which age of Operator is a proxy. Reliance on farmland rental increases with increasing acreage size of the farming Operation. Consequently, control of farmland via rental is more concentrated than the distribution of farmland owned by Operators. The fact that three out of every four acres of rented land is Operated by the largest one—fifth Of the farms suggests that rental is no longer a terrporary step for the beginning Operator, but is a key means Of resource control for the larger, established commercial farm Operation. 38 The importance of land rented varies widely by type Of farming enterprise. Leasing is extremely important to cash—grain farming which is concentrated in the Corn Belt and Northern Plains states. Because the land resource is typically valued in excess Of $200,000 per farm on the larger cash—grain units, more than half Of acreage is leased. CHAPTER III THE FARMLAND RENTAL MARKET PROCESS—-A CASE STUDY In addressing a symposium on land economic research, Kelso stated that one shortcoming of such research is the apparent lack Of emphasis on the human process-what people do and why in relation to land use and property relations [31, p. 38]. Early in the conceptualization of this study, it was concluded that such has been true Of tenure research, and that the rental market process particularly held key infOrmation into a more thorough understanding of the farmland rental-structural change relationship. Mere specifically, the fellowing was hypothesized: (l) the rental.market is highly personal with little Opportunity fOr competitive bidding and (2) due tO the short-term nature of the rental contract , the rental route provides the primary means of farm consolidation and growth. To test these hypotheses, a case study investigation of two selected rental markets was conducted [29]. 3.1 SurveygDesign and Execution Due to the spacial dimension Of the land resource, the rental market, is by nature, localized. Therefore, the investigation took a case study approach. The major Objectives Of the study were: (1) to identify characteristics Of participants in selected land rental markets, (2) to analyze the farmland rental process in terms Of 39 40 infOrmation flow, type, and extent Of competition, landlord-tenant bargaining, and security of tenancy, and (3) to identify the inter- relationship of rental with size and organizational adjustments of the firms. Two study areas were selected to be representative of the Corn Belt, the region, as noted in the previous chapter, where the relative role Of farmland leasing appears most important. One area was in IMichigan. The other was in Illinois. The Michigan area consisted of a five—township block in southern Lenawee County (Figure 3.1). Forming the state's south-central border, this area is characterized by highly productive farmland. Cash-grain production is the primary agricultural enterprise, although some dairying and special crOp production exists. Approximately 35 percent of the farmland in this county is rented. The second area was a fourbtownship block in Champaign County, Illinois (Figure 3.2). The area, located in east central Illinois, is Often referred to as the "heart of the Black Prairie". Heavy loam soil with almost flat terrain and moderate rainfall make this area one of the most productive cash-grain regions Of the world. An exceptionally high rate Of tenancy is present-over 70 percent of the land is tenant operated. County ASCS records provided a name list Of farm.operators within the areas who rented all or part Of their land. Since parti- cipation.rates in the feed grains program.are over 90 percent in'both areas, the name list was fairly complete and current. A random sample Of these Operations was personally contacted and interviewed during the 41 Lenawee County Blissfi 1d Palmyra Madisowl; '1' FairfieldF (— -Ogden ’ Figure 3.1 Michigan Study Area. Champaign County A / // Illinois D - \ i Figure 3.2 Illinois Study Area. 42 summer of 1971. In total, 63 Operators in Michigan and 60 operators in Illinois were interviewed. Information collected included 1) characteristics Of the Opera— tion and the Operators, 2) characteristics of the rented lard, and 3) the nature of the landlord-terant relationship in the rental process. Because many tenants lease from more than one landlord, parts 2 and 3 were directed at each rental unit; and about 300 separate rental arrangements are included in the aralysis . 3.2 The Market Participants 3.2.1 The Tenants The Operator interviewed was farming an average Of 435 acres . Of this, 112 acres were owned or being purchased and the remaining 323 acres were rented (Table 3.1). In total 74 percent of the lam was being rented. The tenancy rate of these Operations (the prOpor— tion of farmland rented) was considerably higher in Illinois, 86 percent, as corpared with 61 percent in Michigan. Twenty-five of the 60 Illinois Operators interviewed (42 percent) were full terants corpared with eight Of the 60 Michigan Operators (13 percent). Being a random sample, the survey covered a wide ranging acreage size distribution Of Operating units (Table 3.2). The proportion of farmland rented increased somewhat with acreage size Of operation, as was found to exist in the rational tenure data (Appendix Table 13). However, in this case, variation in terancy was not found to be significant . l lBased on Chi Square Test of Independence at the 5 percent level Of Significance. ‘43 Table 3 .1 Number of farm Operators interviewed, average acreage Operated, owned, arnd rented;and percent of farmland rented, selected areas, 1971. 7 —Farm 7 3 Proportion of operators Average Acreage I farmland Areas interviewed Operated Owned [ Rented I rented Number Acres Acres Acres Percent Michigan 63 400 157 243 61 Illinois ._69_ 51.2. as igé at Total 123 435 112 323 74 Another measure of farm size, annual goss receipts from farm marketings, was used to classify Operators within the sample to observe variation in terancy rates . More than half of the Operators reported receipts Of $40,000 or more the previous year, and thus would be classified as economic class I farms (Table 3.3). The proportion Of farmland rented was not found to vary significantly among the economic classes. As noted earlier in the discussion Of U. S. tenure patterns, the inclusion of various livestock Operations, yielding high gross receipts but requiring a relatively small land base, tend to distort the tenancy picture across economic classes. Recognizing this, a classification was also made for the crop portion only of goss receipts; and here a significant relationship did emerge in Illinois, with terancy increasirg with volume of sales. In the previous chapter, it was noted that rate of tenancy and age of operator vary indirectly with the proportion of farmland rented, droppirg as the Operator ages. Correlated with this, it would be expected that rate of tenancy would vary inversely with number Of years farmed. This relationship did, in fact, exist among the 44 OOH OOH OOH mo. Hm... Om MHI 8 ml ones to 2:. we mm mm mm mm OH mom I OOm mg. mH mm mH Om HH mm: ... omm He mm me am we . em mam n com so mH es mH mm mm motor OON I- cog mama outcome not come poo comm out onto notched educate ounces , Ogden ounces . Emirate .HO 23988 2mg.“ .HO muoogooo Endgame .HO whopgoo cOHpmpooO .HO coflfiooonm .HO patched 53980.5 .HO psooumm cOHPHOOOLm mo patched ouHm omeopg Hooch. neon H 2H g3: atone. HRH .usono cocooHon £88 on? mwmouom mo Ooucop fig.“ .HO oOHpAOoQHo Oct enraged.“ 938.8% fine.“ no owmpcoopom m.m oHomm. 45 Table 3.3 Percentage Of farm Operators interviewed and average rate Of terancy by goss receipts from farm marketings in 1970, selected areas, 1971. ’ Areas Michigan Illinois Percent Average Percent Average Arnmal gross of rate Of Of rate of sales (1970) Operators tenancy Operators tenancy Percent Percent Percent Percent Total Receipts Less than $10,000 7 57 2 80 $10,000 - $19,999 21 67 14 79 $20,000 - $39,999 26 59 27 81 $40,000 or more i 60 _5_7_ 89 100 100 Cmps Only Less than $10,000 12 59 3 73 $10,000 - $19,999 26 62 20 70 $20,000 - $39,999 37 62 23 90 $40,000 or more _2_§ 60 ___‘_5_4 89 100 100 survey respondents, with higher tenancy rates observed among those farm Operators who had farmed less than 10 years arnd the lower rates found among farmers who had far-med 30 years or more (Table 3.4). i This was particularly evident in Illinois. Off-farm erployment is an important income source to today's farmers. In this survey half the respondents in each study area reported income from Off-farm erployment Of themselves or another member of their household. When asked what proportion of their household income was from off-farm enployment in 1970, it was evident that heavier reliance was placed on this in Michigan. In Michign, 46 Table 3.4 Percentage of farm Operators interviewed and average rate of terancy by rumber of years farmed, selected areas, 1971. Areas Michigan Illirnois Percent Average Percent Average of rate Of Of rate of Years farmed . Operators terancy Operators terancy Percent Percent Percent Percent Less than 10 years 2 100 12 94 10 - 19 years 21 72 23 91 20 - 29 years 41 59 42 87 30 years or more _3_6_ 65 __2_3_ 72 100 100 28 percent reported less than 30 percent; 44 percent reported between 30 and 69 percent; and 28 percent reported 70 percent or more from Off-farm exployment. In contrast, 64 percent of those in Illinois who reported such income said it accounted for less than 30 percent Of total income, with the remainder irflicatirg from 30 to 69 percent of total household income. This is consistent with county data obtained from the 1969 Ceraus Of Agriculture. A total of 69 percent Of all farm Operators in Lenawee County, Michigan reported working Off the farm, with 50 percent worldrg off the farm 200 days or more (essentially full-time employment) .1 In Champaign County, Illinois, 51 percent reported working off the farm, with 16 percent working 200 days or more. J‘I'he relatively high dependency on off-farm enployment in Michigan is due in part to the nature Of the state's econonw. The high incidence of industrial plants results in very good Off-farm work Opportunities as well as higher average daily wage rates than the rational average. See [55, pp. 52-53]. 47 As would be expected, size Of farm Operation was found to be inversely related to Off-farm employment. In this study, the value Of farm production assets Operated by farmers with no off-farm enployment averaged $341,000 while those reporting 70 percent or more of total household income coming from Off-farm erployment Operated production assets valued at $80,000 per farm Operation. 3.2.2 The Landlords Some irndication of landlord craracteristics was gained from questions directed to the terants. Since terants usually were renting from two or more landlords, information was collected for approximately 280 landlords. Nearly four out Of every ten landlords (38 percent) were related to their tenants in some manner.1 This ranged from 29 percent in Michigan to 43 percent in Illinois. The incidence of family arrange- ments indicates the importance Of leasing in intergenerational transfer and in inheritance arrangements. Ard as will be discussed in the following section, the famnily arrangement has implications on the conpetitive aspects of the rental process. Landlords in general had a strong orientation to farming (Table 3.5). Retired farmers and widows Of farmers were the primary goups.2 lAn aggregate measure Of the relative importance of family tenancy arrargememts was gained from the 1965 Sample Survey of Agriculture (a supplementary survey for the 1964 Census of Agriculture) . The survey found one out of three farm operators renting farmland in 1965 leased some land from a relative. 2More than 90 percent or the landlords were individuals with the remainder being primarily estates . 48 Table 3.5 Occupation of landlords, selected areas, 1971. I Areas Occupation of larrllord [ Michigan Illinois Percent Percent Retired farmer 146 26 Widow of farmer 30 37 Active farmer 3 . 5 Nonfarm business l2 l2 Retired nonfarmer 5 11 Other” _fl _9_ 100 100 *Includes salaried and professional people. The proposition that a significant amount of land is rented from absentee landlords was disputed somewhat by the survey findings. More than two-thirds of the Michigan landlords lived on the property, while in Illinois, more than half of the landlords lived in a nearby town (Table 3.6). In total, only 10 percent of the Michign landlords and 15 percent of the Illinois landlords could be classified as absentee landlords (living out of the county or state). Earlier it was noted that farmland investment by nonoperator landlords is an important source of capital for the farming sector. In this respect, nonfar'm ownership is similar to stockholder invest- mert in business corporations . However, this data on landlord characteristics irdicates one cannot identify the nonoperator landlord as being synorwmous with the "Wall Street" type of investor. If not retired farmers themselves, the majority of landlords are either members of farm families or closely associated with agriculture through the small rural community enviromlent in which they live. So, while “9 the financial aspects of land leasing may parallel equity financing, the interrelationship of the resource owner and the resource user differs greatly—the landlord-tenant relationship being much more personal and informal. Table 3.6 Residence of landlords, selected areas, 1971. Residence of 1 Areas the mm | Michigan 1 Illinois 6 Percent * Percent On the property 66 20 Nearby farm 8 13 Nearby town 16 52 (ht-of-county 2 5 Out-of-state __§ __lg 100 100 3.3 The Parket Process The characteristics of the market participants give partial insight into the land rental market . However, the key element is the actual negotiation itself. It is the activity which ultimately influences, and is influenced by, the structural changes which take place . 3.3.1 The Lard Rented The continual expansion of the size of operating units beyond the typical ownership unit has promoted multiple leasing (tenants leasirg from more than one landlord). In this survey, resporrients in both Michign and Illinois rented, on average, from three separate larrilords. Because each arrangement is unique, a series of questions was directed at the tenant pertaining to each of his rental arrangements . 50 The average size of tract rented was 120 acres. The units tended to be smaller in Michigan, 97 acres, than in Illinois, 1141 acres . This variation mainly reflects the difference in ownership patterns between the two areas .1 Typically, the tenancy arrangements had existed for a consider— able length of time. In Michigan, the same tenant had operated the rental unit for an average of 11 years. In Illinois, the leasing arrangemts had extended to an average of 114 years. About one-third of the leases had been in effect five years or less (Table 3.7) . Roughly one in six leases had existed for 20 years or more. The length of tenure agreements seems paradoxical since most lease arrangements are made from year to year. Apparently tenure arrangements tend to be fairly stable over time, even though there is a very low incidence of long-term lease contracts. Nine out of every ten leases in this survey were for one year. One might raise the question why one—year leases are the rule when tenancies generally run much longer. Aside from the importance of custom, short—term arrangements have specific advantages for both parties. The tenant can maintain greater flexibility in adjusting the size of his Operation (however, if he is plagued by insecurity of tenure, then a short-term lease can reduce his managerial freedom). For the landlord, a short-term lease provides a means of managerial JThe modal size of ownership unit was 110 acres in the Michigan area and 80 acres in the Illinois area. 51 Table 3.7 Length of time tenant has rented the property, selected areas, 1971. Areas Number of Michigan ' Illinois years farmed 21:22:: or. Percent 131-13222: Of Percent ' Number Percent Number Percent 1 year 8 6 8 5 2 years 16 ll 5 3 3 years 8 6 11 7 1; years 6 5 3 5 years 15 11 ll 7 6-7 years 7 5 l3 8 8-9 years 10 7 9 6 10-14 years 32 23 27 18 15-19 years 25 18 26 17 20-24 years 2 l 22 14 25-29 years 5 3 l2 8 30 or more years __5 _3 _6_ _4 142 100 155 100 52 control over possible undesirable farming practices by the tenant, as well as allowing greater short—run freedom to sell the property.l The length of the tenure agreements suggest that the rental turnover rate may be considerably lower than what might be implied by the typical length of a lease contract. In this study, an average of 8 percent of the existing leases in the Michigan area and 5 percent of the leases in the Illinois area had gone into effect in each of the three previous years . These, of course, are crude approximations of turnover rates, not only because of limited sample size but also because the inherent assumptions of l) uniform size of rental tracts and 2) no termiration of contracts arranged in this previous three- year period. Nevertheless , when compared with the average annual turnover rate for all farmland via title transfer of about 3 percent per year, there is no basis of support to the hypothesis that the rental route plays a greater role in farm consolidation and growth than title transfer due to the more rapid turnover of rental contracts . 3.3.2 The Le&sing Arrangement The type of lease used varied widely between the two areas (Table 3.8) . In Illinois, virtually all were crop-share leases. Variable expenses were generally shared in the same proportion as the crop. A very insignificant mmber were cash leases. In Michigan, the incidence of crop-share and cash leasing was roughly equal. 1A8. noted by Cheung, landlords exercise managerial control not only by the option of changing terants via the short—term contract but also be selling the property [9, p. 28]. 53 Table 3.8 Type of lease used, selected areas, 1971. Areas Michigan Illinois Number Number Type of of of lease leases Percent leases Percent Number Percent Numb er Percent Cash 70 48 5 3 Crop share 76 52 21:3 __9__7_ 146 100 158 100 There is some evidence that interest in cash leasing is increasing in many regions where crop-share arrangements had previously dominated [44, p. 7]. The cash farm facilitates a bidding process where demand is active. Then, too, tenants may see the cash lease as rendering greater managerial freedom; this becomes of increasing importance as maragerial s0phistication and the incidence of multiple5 unit leasing expands. Landlords may prefer to cash rent because of the assurance of a fixed income from the property. Despite these advantages to cash leasing, the share-rent lease predominates throughout most of the Corn Belt . This study did not document an explicit explaration for this . But from informal conversations with survey respondents, several possible reasons emerged. First, some tenants were fearful of cash arrangements because (1) the tenant must assume the full risk of price ard yield variation, (2) competitive advantage may arise to the larger operators under cash leasing, and (3) long-run security of terancy may be diminished. 54 Tenants are also aware of another advantage of share leasing over cash leasing. Under the typical share arrangements, the tenant not only gains control of the land asset under deferred payments but also half of the major non-labor variable inputs. In many areas in this amount may represent $20 to $30 per acre. To terants having inadequate operating capital or credit, sharing of the costs of putting in the crop is an important economic consideration. landlords, too, may be reluctant to enter into a cash arrange— ment. Part of this reluctance may stem from no appreciable gain seen in switching from share to cash. For example, throughout much of the Corn Belt, crop yields are stable enough to assure landlords a fairly stable rental return under share arrangements . Also, where rental customs have become so routine that landlords play an insignificant role in the managerial process, the landlord sees little gain in switching to a management-free cash lease. Finally, one cannot ignore institutional inertia. landlords may be reluctant to break from custom, especially if doing so may create ill-will within the community. 3.3.3 The Formality of Leases The majority of leases in the study were verbal agreements—- roughly two-thirds of the leases were oral (Table 3.9) .1 Written arrangements were used more frequently on larger tracts; so in terms 1Frequently, respondents said they had originally formed written leasing arrangements, but had not formally renewed these leases over time. However, according to tenure law in most states, the lease has renewed itself. Where nothing is said, both parties are governed by the agreements of the origiral lease consistent with the new Eituationéfnd the terms of the lease are then from "year to year". 5, p. 12 . 55 Table 3.9 Percentage of written leases by selected characteristics, selected areas, 1971. T Percent written leases in area Selected Michigan Illinois characteristics [Number 1 Acres?F Numberfi . AcresT ' Percent 5 Percent Percent Percent @222. Cash 54 66 4O 45 Crop share 17 20 27 37 Length of lease 1 year 27 36 24 32 Mbre than 1 year 85 79 100 100 Number of years rented Less than 5 years 51 50 24 43 5— 9 years an 51 15 22 10—19 years 23 30 28 42 20 years or more 17 21 42 39 Relationship with landlord Unrelated 34 41 31 43 Related 28 36 21 25 *Refers to percent of'acreage under written contract. For example, 66 percent of the land acreage that is cash rented in.Michigan is under written contract. 56 of acreage, a larger percentage of the land rented was under a written lease. Cash leases were more frequently written agreements than crop-share leases. The latter fbrm.has become institutionalized to the extent that margin for disagreement has narrowed. In contrast, cash leasing represents more of an outright purchase of use rights, and therefore both parties may tend to prefer a.more formal arrangement. It is difficult to determine if the emergence of a highly technical, commercialized agriculture has promoted greater formality of leases. In Michigan, some evidence of this is a higher proportion of the more recent leases being written. In Illinois, where crop—share leasing has dominated, no such trend is evident. In fact, the highest proportion of written arrangements was observed among tracts rented for 20 years or more. A lower proportion of written leases occurred where the landlord was a relative. When the tenant and landlord are related, mutual trust would likely be greater. In fact, several of the tenants interviewed said the mere suggestion of a written contract by one party in a family relationship may offend the other party. No significant variation in the proportion of written leases was observed.among other characteristics of the landlords such as occupation or residence. The length of lease had a positive influence on the fbrmality of the ageement . Of those contracts set up for more than one year, 90 percent were written leases. 57 3.3.4 Land'Iracts Prior to Rental About half Of the land rented had previously been operated by other tenants; the remainder had been.farmed by the owners and thus primarily represented land moving into tenancy for the first time. There was considerable variation between the areas. In Michigan, 68 percent Of the acreage had been Operated by the owner as compared to 28 percent in.Illinois. The high percentage Of the land in first- term.tenancy reveals the more general increase in.rented land in south central Michigan. Mach Of this increase has taken place during the last decade [12]. Farm.consolidation frequently accompanied rental. Of the acreage rented by the survey respondents, 55 percent had previously comprised complete farm units. Most of these tracts when rented, fbrmed portions of larger units. In most instances, the land had become available to rent because of the previous Operator (either owner or tenant) quitting farming (Table 3.10). This correlates directly with the high inci- dence of landlords who are retired farmers or widows of farms. Only 10 percent Of the tracts in.Michigan and 15 percent in Illinois came on the market as a result of the landlord terminating the previous lease. Of the tracts which had previously been rented, about two— thirds Of the leases had been terminated by the tenant as a result of his quitting farming, scaling down, or substituting other land. For 35 percent of these tracts in Michigan and 32 percent of the tracts in Illinois, the previous lease had been terminated by the landlord. 58 This suggests the permanence of leasing arrangements is more dependent on the decisions of tenants than on landlords. Table 3.10 Reason why land became available for rent, selected areas, 1971. Reason why Areas land became available for rent J Michigan Illinois Percent Percent Previous Operator - Quit farming 79 62 Scaled down Operation 6 13 Took other land 5 8 landlord terminated lease 10 15 Other __1_ ___2_ 100 100 3.3.5 The Flow Of Information An important aspect of any market is the flow of information among the potential participants . Respondents were asked how they had learned the land was available for rent. In about 75 percent of the cases they replied either "directly from the landlord" or "from a family member" (Table 3.11) . Community knowledge was the source of information only about 10 percent Of the time. Of course, when the tenant was related to the landlord, the initial knowledge was almost exclusively gained from the landlord or some other family member. But even when no family relationship existed, about 60 percent Of the tenants indicated that the landlord himself or a family member had told them the land was available to rent. In these situations, comunity knowledge still played a rather minor role—in only 20 percent of non-family terancies in Michigan and 11 percent in Illinois had information been obtained in this manner. 59 Table 3.11 Source Of market information, selected areas, 1971. How tenant learned ' ' ‘ Areas ' ' land was available for rent I Michigan. . Illinois ‘ Percent Percent Directly from landlord 61 21 Agent for landlord 3 7 Family member 12 52 Neighbor 5 7 COmmunity knowledge 14 7 Went to lardlord 3 6 Other __2_ __6_ 100 ' lOO The rather persoral commlnication linkages suggest the dis- semination of market information largely takes place after the fact. This was further substantiated by the response to the question, "Were other Operators aware Of the land being available to rent?" In both Michigan and Illinois, less than half the tenants replied "yes"-42 percent and 47 percent, respectively. In approximately equal propor— tions, the rerainder replied "no" or "uncertain". Although the awareness tended to be greater in nonfamily relationships, still in only half the cases did tenants know of others who were aware the land was available. When terants responded "no" or "uncertain", they were then asked if the landlord made an effort to inform others .1 Nearly all said the landlord had not—97 percent in Michigan and 90 percent in Illinois. JThere were, undoubtedly, frequent instances where other Operators had been aware even though the landlord rad not deliberately tried to inform others . 60 In light Of the relative importance of land rental, this frag- mentation Of market information seems somewhat paradoxical. Of course, the high incidence of family relationships means the market interact ion is frequently bypassed . However, even in nonfamily relationships , there was seldom widespread knowledge of the land being available. There are two possible reasons for this. First, the landlord may have no incentive to advertise if he intends to rent on a typical crop- share arrangement.1 Under this condition, the profitability to the landlord depends on attributes of the tenant and his Operation, such as his equipment, size Of Operation, managerial ability, and other personal qualities such as honesty. These characteristics are generally appraised from close persoral contact over the course of time. Consequently, the landlord may prefer to rent to an Operator who he know personally, not only as a favor, but also because he has evaluated the potential tenant on traits which normally do not surface in a more competitive market exchange between strangers . Although the lardlord ' 5 economic welfare is not as dependent on theSe traits when he is cash renting, there even appears to be some reluctance by the cash-rent landlord to advertise his land . Numerous tenants indicated that landlords in the neighborhood had contacted them about renting land even though they could have easily received equal or even higher cash rents by renting to outsiders . A second possible reason for landlord preference for inter- personal arrangements stems from noneconomic motives. Friendship and goodwill are regarded highly in the small rural community atmosphere. lIf he intends to cash rent, then he may be more interested in actively advertising. 61 As a result, landlords may be reluctant to rent their land in a corpetitive market exchange for fear of ill—will created among the unsuccessful bidders . 3.3.6 Corpetition at Time of Rental With the information flow being what it is, competition in the land rental market takes on a more subtle form than might be expected. Outright corpetition in terms Of price and nonprice bidding was found to be the exception rather than the rule. If the respondents indicated that other Operators had been aware of the land being available when they initially rented it, they were asked if these individuals were interested in renting the tract. Their answers varied greatly between the study areas indicating, in part, the difference in the demand for rental land. In Michigan, respondents said 36 percent Of those farm Operators} aware of the upcoming transfer were interested, 24 percent were not interested and, in the remaining cases, the respondent was uncertain of their interest. In contrast, Illinois respondents said 71 percent of these individuals were definitely interested in renting the land and only 8 percent were not interested. Despite the interest of others which the respondents were aware of (and, undoubtedly, some which they did not know of) actual competi- tion was infrequent. Terants encountered active competition in 8 percent of the cases from one or more Operators. In half Of these instances, managerial reputation was involved in the bidding. Bidding on cash rental rates was reported infrequently. In the remainder, there was no special bidding other than one or more other operators asking for the land . 62 The nature of the information flow and competition implies the beginning Operator may have extreme difficulty in renting farmland . Unless he is fortunate enough to bring family influence to bear, he will be carpeting at a relative disadvantage with the established Operator on two counts. First, he may be less likely to be aware Of farmland available to rent . Second, without an established reputa— tion of being an efficient farm manager, this individual would be less likely to be selected so long as other interested parties have such a reputation. Thus, the relatively greater reliance on land rental by younger farm Operators as noted earlier may tell only part of the story. It is also possible that the incidence Of unsuccessful applicants for rental land is much higher among younger potential farm operators . 3.3.7 Negotiation at Lease Renewal The periodic renewal of short—term leases can be as important as the initial market process. Not only does it involve terant- 1andlord interaction, but it also provides a situation in which poten- tial corpetition can arise. Despite the potential , however, the survey found the lease renewal process to be insignificant. In two out Of three instances, terants discussed nothing with their landlords (Table 3.12) . When discussion had taken place, it most Often involved farming practices and not factors pertaining to the actual leasing arrangements. Landlord-t enant interaction occurred more frequently among ‘ nonfamily contracts than among family tenancies—for the two areas combined, 37 percent as corpared to 28 percent. Discussion also 63 Table 3.12 Incidence Of discussion and negotiation between the tenant arri the landlord at lease renewal, selected areas, 1971. Factors ' ' ' ' ' Areas discussed and ' Michigan T Illinois I Total negotiated at Dis— Nego— Dis- Nego— Dis- Nego— lease renewal cussed tiated cussed tiated cussed L tiated Percent Percent Percent Percent Percent Percent Nothing 68 86 64 89 66 88 Type of lease 2 2 l l l 1 Cash rates or crop shares 7 7 l l 4 4 Share expenses -— - 2 -— 1 — Farming practices l4 14 29 6 23 6 Property improvement 2 — 3 3 2 1 Two or more 01' above _.7_ _: .2: .1: __3. .2: 100 100 100 100 100 100 deperrled on who the tenant dealt with; that is, when the landlord's business affairs were handled by an agent or when an administrator was responsible for an estate, discussion with the terant generally took place . A sharper measure Of interaction was gained from asking terants what actually was negotiated . They revealed that frequently the discussion had primarily been for the purpose of inforrming the landlord and was not done in the spirit of negotiation. This was particularly true Of farming practices. The rather slight evidence Of negotiation implies that the landlord plays a very minor maragerial role in the joint farm enterprise. A number Of terants replied, "My landlord leaves it all up to me." 64 The fact that tenants have this wide discretion in the operation Of the farm unit gives them more flexibility in the coordination of their total Operation. This is especially important in multiple-leasing operations . There are several possible explarations for the lack Of land- lord decision making. In family rental relationships a strong element of trust usually prevails. Likewise, mutual confidence may Often be present in other arrangements as well, and continues to grow between landlord and tenant over the years . Then, too, some landlords are not familiar enough with the operating unit, the farm programs , or modern farming techniques to enter into the management decision making; and they follow the suggestions of their tenant .1 The lack of negotiation may also arise from the tenant's reluctance to suggest alterations in the arrangement . Where derand for rental land is keen, the terant may feel he is in no bargaining position to modify the rental agree— ment. He may also hesitate for fear of creating ill will in the business relationship . 3.3.8 Corpetition at Lease Renewal Those terants who had renewed their leases were asked if they knew of other Operators who were interested in renting the particular tract. In Michigan, nine out Of every ten terants replied they knew Of none. Seven of ten respondents in Illinois were not aware of other lln this situation, the landlord is not necessarily relinquishing control to the tenant but rather shifting his managerial influence to a different phase; i.e., instead Of actively participating in the orgoing management , the landlord may practice greater discretion in his initial selection of a terant. 65 operators' interest . When they knew of interest , however, they generally replied that several were interested; but only a few terants reported actual competition with bidding for the property:L The Opportunity for a third party to dissolve the landlord- tenant agreement is somewhat limited. Even in cash arrangements, a higher cash Offer may not be sufficient. It appears conflicts Of interest within the landlord-tenant relationship must exist before outside Offers will be considered. Time is also a factor. As one respondent replied, "Potential competition is greater during the first year or two Of the agreement; and the longer the contract exists, the less the opportunity for others to colpete." 3.3.9 Expectations Of the Future The uncertainty Of terancy has commonly been considered a drawback to long-run decision making. Moreover, the increasing size and sophistication of today's commercial farming operation has placed even greater emprasis on the long-term planning horizon. Thus far, it has been implied from the length Of rental agree- ments and from the greater occurrence of tenant termiration as corpared to landlord termination that rental arrangements tend to be 1In many cases , the tenant may never know of the inquiries directed to the landlord. Yet, the fact that the landlord does not inform the terant about these outside interests in itself suggests corpetition was not present . 66 secure.1 Also, the lack of competition at lease renewal suggests relatively permanent contracts even though most leases are from year to year. Yet does the terant, in fact, feel secure? Or more speci- fically, is the element of tenure uncertainty great enough to significantly discount the future, and to alter long-run economic planting? The survey attempted to answer these questions in part by asking a series of questions pertaining to the future rental of each tract. Tenants were first asked if they had discussed long-range plans (five years or more) with the landlord . Long-run plans had been discussed for only 7 percent of the leases in Michigan and 20 percent of those in Illinois.2 Despite the absence of discussion, tenants responded that the majority Of tracts could continue to be rented indefinitely or at least until the land was sold (Table 3.13) In only a small percentage Of cases did tenants specify a specific length of time. Substantial differences in responses occurred between the areas with a considerably higher level Of certainty being observed in Michigan. Greater demand for farmland in Illinois relative to Michigan may be one explanation; due to more detand, there may be a greater chance that a tenant in Illinois will lose the tract when a charge Of ownership takes place. J'While the survey indicated stability and high levels Of securi- ty Of temire, it should be noted that the sample consists Of sue—cessful terants only. Little or no evidence exists about the incidence of tenants who have lost rental land, or about individuals who were unsuccessful in finding land to rent. 2The somewhat higher incidence of long-range planning in Illinois may be due to (1) the higher proportion of family relationships and ( 2) the greater scarcity of farmland available to rent in Illinois, which may encourage terants to be more concerned about future terancy. 67 Table 3.13 Tenants' opinion Of ability to rent tract in the future, selected areas, 1971. Lergth of time tenant will I ' ‘ Areas be able to rent tract J _ Michigan ‘ . [ Illinois ' Percent Percent Indefinitely 73 ”1 Until land is sold 12 52 Less than 10 years 9 1 Don't know ___6_ __6 100 100 Uncertainty of termre when influenced by ownership transfer depends on the turnover rate of ownership . National estimates show that about 3 percent Of the farmland is transferred each year [49 , p. 28]. Hence, ownership to a typical tract Of land would trans fer on average about once every 23 years . However, from the tenant's standpoint, it is more relevant to consider the age and health of the lardlord and the likelihood of an estate settlement than agregate estimates Of turnover. Many terants are faced with a high risk of losing the property in the near future (one to five years) unless they are in a position to purchase the property or make an agreement with the heirs , should they decide to maintain ownership . 1 Counteracting the long-run uncertainty of tenure is multiple- unit leasing. The greater the number Of rental units (and, therefore 1Occasionally a landlord will specify in his will that the present tenant would be allowed to continue renting after estate set- tlement. In other cases, heirs who are unfamiliar with farming or the community may prefer to keep the present tenant. 68 landlords), the lower the magnitude of loss when a particular landlord terminates the lease. Diversification via leasing from several landlords simultaneously can be as relevant to the stability of land resource control as is a balanced portfolio tO the investor who wants to minimize risk. In order to compare expectations with aspirations, respondents were also asked how long they would like to rent the prOperty (Table 3.14) . Most hoped to rent the land indefinitely, particularly in Illinois where demand for such land is keen. Only a small propor- tion of operators hoped to rent the property only until they had the opportunity and firancial ability to purchase the tract. This further supports the conclusion that the primary role of farmland leasing is no longer one of a temporary step towards eventual full ownership but is instead a means to acquiring the necessary land base. Table 3.14 Terants' desire to rent tract in the future, selected areas, 1971. Length of time tenant would I Areas desire to rent tract I Michigan L Illinois Percent Percent Indefinitely 67 86 Until can buy the tract 16 11 Less than 15 years 15 1 Don't know 2 ___2 100 100 69 3.4 Lard Rental and Farm Adjustment Aggregate tenure patterns indicate that farmland rental plays an increasing role in structural change as the disparity between size of ownership unit and Operating unit increases . Yet cross-sectional analysis of aggregate data cannot document the dynamics of firms over time. TO accorplish this, a corprehensive time series aralysis of specific firms is necessary to understand how rental interacts specifically with changes in the farm firms. Consequently, a series of questions was directed at survey respondents concerning land acquisition and use patterns, and the characteristics of asset control. 3.4.1 land Use and Acquisition Multiple unit Operations are the rule rather than the exception in today ' s lard—based agriculture . Generally, the farming Operation is not located on one continuous block of land. In this study, about four out of every five Operations (81 percent) involved nonadj Oining lard units. Those units which were complete blocks were generally smaller Operations , averaging 288 acres , than the discontinuous Opera- tions, which average 470 acres . Little difference in the proportion of land rented was observed between the block and the discontinuous units . It is commonly believed that the growing tenure class of part owners reveals an increasing tendency for farm Operators to own a headquarters unit while leasing additional land for expansion purposes . Such an arrangement supposedly gives the Operator two distinct advantages: (1) ownership of a headquarters unit gives greater security and managerial flexibility than under full tenancy 7O ard (2) larger size and greater production efficiency than otherwise possible unier full ownership. In this study, however, part owners did not necessarily own their headquarters unit. While 95 percent Of the part owners interviewed in Michigan owned the headquarters unit, only 52 percent of the part owners in Illinois owned this unit. This variation can be explained in part by the differences in agri— cultural enterprises existing between the areas. The Michigan area, while relying most heavily on cash grain crops, does have some dairy and livestock feeding enterprises. When such enterprises exist, the facilities of an Operator '3 headquarters are more important . Thus , he may prefer to own this unit to adjust his physical plant tO meet the needs of his livestock enterprise(s) . In contrast, agriculture in the Illinois area is almost exclusively cash-grain farrming. With the exception Of machinery storage and possibly gain storage, operators may not place special interest on the headquarters unit. An additioral possible explanation for the variation between the areas is the higher incidence Of family arrangements in Illinois. In these instances, a tenant would be less hesitant to make building improve— ments or any other modification Of the headquarters unit . Because Of the family relationship, security may be as great as that under owner Operatorship. Part owners in the Michigan area on average owned 42 percent of their total Operated acreage while in Illinois the owned portion was less—22 percent (Table 3.15) . This land which Operators held title to had generally not been acquired in a single unit. Rather, acquisi- tion usually rad taken place in increments over time. The units averaged 80 acres in size. Acquisition by the present Operators had 71 been an average of 14 years previously in Michigan and 12 years before in Illinois . Table 3.15 Land base characteristics Of part owners and tenants, selected areas, 1971. L Areas Acreage size characteristics by tenure | Nflchigan Illinois Average Average acreage acreage Part owners-— Acres Operated 428 486 Acres owned 178 108 Full tenants—- Acres operated 229 407 The method of acquisition Of owned land differed significantly between study areas. In Michigan about two-thirds Of the land had been purchased from a nonrelative with the remainder largely purchased from a relative (Table 3.16). In Illinois the frequency Of relative purchases and inheritances was much higher. Much of the land acquired had previously been rented. The proportion was somewhat higher in Illinois than in Michigan, reflecting the greater tendency for land rental to be used in.the intergenerational transition. Half Of the respondents reported a change in acreage size Of their loperating'unit over the previous five years. The generalization that larger farms comprise the expanding sector Of farming industry was txorne out in part by the variation in gross sales among farms increasing, remaining the same, and increasing in acreage size. Over tlxree-fOurths of those expanding Operations reported gross sales 72 volumes of $40,000 or more in 1970. In contrast, only 32 percent of the farms retraining constant in size and 22 percent of those decreasing in size reported sales of $40 ,000 or more. Table 3.16 Method of acquisition of owned land and incidence of previous rental, selected areas, 1971. Method of acquisition and I Areas incidence of previous rental J Michigan [ Illinois Percenta Percenta How acquired-— Nonrelative purchase 65 42 Relative purchase 28 39 Inheritance 4 19 Gift 1 _ Other __2_ .1: Total 100 100 Previously rented—- Yes 39 5“ No _a .45. Total 100 100 aPercentage based on numbers of tracts. In terms of acreage, the farms which had expanded in size were larger than the all-farm average, 585 acres as compared to 435 acres (Table 3.17). The rate of terancy was essentially the same. The percent increase in acreage average was 14 percent over the five-year period. The ekpansion process was most heavily dependent on land rental. In Michigan, three out of every five acres added were rented, while in Illinois, more than three out of every four acres added were rented. This parallels findings of an aggregate measure of farm size adjustments provided by the 1966- Pesticide and General Farm Survey 73 conducted by Economic Research Service, USDA. In this national survey, a.representative sample of farm operators was asked about changes in acreage Operated between 1964 and 1966. When expansion occurred, land rental was the primary means of acreage expansion. Over two acres of additional land was rented for each acre of additional land purchased. Table 3.17 Tenure characteristics of farms expanding in acreage size over last five years, selected areas, 1971. [ Areas Subject I Michigan I Illinois Total Average acreage in 1971: Owned 230 77 165 Rented 327 545 420 Operated 557 622 585 Average acreage in 1966: Owned 167 38 111 Rented 231 411 308 Operated 398 449 419 Average acreage added: Owned 63 39 5LI Rented 96 134 112 Operated 159 173 166 Percent increase in total acreage: 14 14 14 Percent rental land of total added acreage: 60 77 67 Analysis of aggregate tenure patterns by age of operator in the previous chapter seem to suggest that reliance on leasing in.acreage expansion will tend to dimdnish over the life of the operator. That is, as his financial position builds up over time, the operator will more frequently purchase rather than lease additional land. This 74 survey however, fOund no evidence to support this generalization. Using number of years farmed as a rough proxy fOr financial well being, the study found operators who had farmed for 30 years or’more were relying as heavily on leasing fOr expansion purposes as were their younger cohorts. The relative importance of land rental was also evident in the future intentions of respondents. About 90 percent intended to continue renting land for at least five years (Table 3.18). Those who did not were usually nearing retirement age and were considering quitting farming or scaling down their operations . Table 3.18 Farm operators' intentions for land rental in the future, selected areas, 1971. Intentions fOr land I Areas r rental in the fUture I Nflchigan Illinois I Total Percent Percent 7 Percent Continue renting? Yes 85 93 89 No 10 5 8 Don't know __Ji __33 __43 100 100 100 .Expand rental acreage? Yes 33 “5 39 No 55 52 53 Don't know ._;g __43 __j: 100 100 100 When asked if they intended to rent more land within the next five years, 39 percent replied "yes". A somewhat higher percentage intended to expand their rental acreage in Illinois than in Michigan. IRespondents frequently commented they would expand i§_rental land 75 became available. This was particularly noticeable in Illinois, where nearly all respondents reported available rental land to be hard to find. Apparently, the scarcity of rental property is a.maJor constraint on farm expansion. And this limitation frequently overrides the operator's intentions fOr acreage expansion. 3.4.2 Land Rental and Asset Control When asked to estimate the current market value of all their production assets (real estate and nonreal estate) survey respondents reported a substantial portion to be rented real estate (Table 3.19). In terms of current market value, the rented portion accounted fOr an average of 75 percent of the total production asset value. Production assets averaged over $300,000 per farm, Both the degree of rental and level of asset value per farm correspond closely to aggregate data on cash-grain farms. variation in the proportion of rental asset value among the various farm.size classifications was not significant. SimilarLy, rx>definite pattern was evident between the proportion of rented asset value and volume of gross sales. Apparently, a relatively high reliance on rental is prevalent in these study areas, regardless of acreage size and dollar volume of the operation. 3.5 Chapter Summagy Assuming the markets studied are generally representative of rental market institutions within the North Central States the evidence would support the hypothesis that such.markets are highly personal with little opportunity for competitive bidding. The market area was feund to be quite localized with participants generally 76 695.8038 3 CE» 339 .8329» .8er g Edema and £833: .oumumo Home E menace: gonna 5301693 gar mm 8 SN 2m 8 we mom 8N mm mm EH 0: 88 .8 cm 8 we elm 2m mm mm mam mom .3 mm 8H 9: 8.8 fl 8 Rm mom 8 3 Rm «.8 we 2. 9% gm SIS we no 93 m3 5 am 2... mm: a b n b S 55 33 lease was, 8 8 m8 :8 .1. me :2 MS om mm 2.: 93 +8062 me 8 mmm ma 8 8 93 03 em me com omm ommamuoooa: me 8. 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EST» 2.58 Home o3m> mime, 130» down Epsom Epsom mwmhw>< mwmho>< ooucom ooozox Rape: omega Epsom ocucom ego: awake: made 28:: 28,202 . .Hema ammosm oopooamm mange gonzolppmo use oomoop mo moapmeOpoMmeo empooamm mo Hence 0» moam> ooma ampeop mo woodpeooefl o>HpmHom new osam> ommmm cofiposeoeo Hence new coopmm Home mo osam> owmem>¢ mH.m canoe 77 knowing each other before entering the market. A significant propor— tion of the leases were family arrangements. Information networks are largely through infOrmal channels with general awareness of availa- bility frequently occurring after the fact. Moreover, custom and inherent need fOr social acceptability play important roles. As a result, respondents indicated a low incidence of active competitione- both at the time of initial rental and at the periodic renewal. Even in the Michigan study area where approximately half of the leases were cash agreements, active competition was minor. What emerges, then, is a rather paradoxical situation in which short-term lease contracts are the rule, yet slow turnover rates and stable tenancy patterns prevail. For the operator who has successfully rented farmland, such a market framework appears to be advantageous. For, as noted by Krausz and.Reiss, a highly competitive rental market could greatly increase tenure uncertainty [32, p. 1375]. The tenant generally can feel that so long as there is reasonable cooperation between.himself and his landlord, he can be assured of a continuing agreement. Frequently, it is only upon sale of the property or title transfer that the tenant's position is in Jeopardy; and even this can be bypassed in part by multiple—unit leasing which is characteristic of today's situation. Accompanying this low-keyed market interaction is a.management Iorocess which tends to be heavily weighted to the tenant. USually, 1:he landlord plays a passive role in ongoing:management—-especially 1f the agreement has functioned for several years , or the lardlord is eelderly and not familiar'with present farming technology. Lease Irenewal, then, is usually automatic with negotiation being little more 78 than the tenant informing the landlord of his cropping intentions . This is particularly beneficial to the tenant who is controlling a land resource investment of a quarter million dollars or more largely through leasirg from a number of separate landlords. Managerial coordination is critical if the most efficient operation of the total unit is to be realized. And this would be most difficult if each landlord demanded a more positive namgerial role . It should also be noted that the landlord is not necessarily relinquishing his managerial influence. Rather, he may be transferring it fran ongoing Iranagement responsibilities to the initial selection of a tenant capable of mu responsibility. Thus, the informal and nonccmpetitive nature of the rental market can create a climate of mutual trust and responsibility that can be of benefit to both paties. As to the hypothesis that farmland rental is the primary means for farm consolidation and growth due to the short-term nature of the rental contract, this case study presents conflicting evidence. Respondents in this survey had relied heavily on rental for expansion purposes. Three out of five acres in Michigan and over three out of four of the acres in Illinois which had been added during the previous five years were rented. And a substantial portion of such tracts had previously been farmed as complete farm units; thus, consolidation frequently had accompanied expansion. But to appraise the role of rental in the aggregate requires investigation of the total farm population and not Just that element which has successfully rented farmland. In this perspective, the rate of rental land turnover gives partial insight into the potential reliance on rental relative to farmland purchase. Based on this sample of leases, the turnover rate 79 of rental property is likely less than 10 percent per year and possibly as low as 5 percent . So the difference between this rate of the rental acreage and an average of 3 percent turnover of farmland title for the total farmland base may not be significant.l In short, it appears that rental is the most accessable option of farm acreage size expansion for some farm operators, but certainly not for the farm population as a whole. Availability of land to rent is the crucial factor. 1In addition to the flow aspects, the stock aspect of the rental land resource must also be considered; i.e., since the proportion of all farmland rented varies from less than 20 percent to over 50 percent in states where land-based fanning is important, the relative influence of rental on the farm consolidation and growth process will Vary accordingly. CHAPTER IV LAND RENT THEORY—~RELEVANCE AND IRRELEVANCE An extensive body of land rent theory has been developed over time. As true of all theories, it is an attempt to construct simpli- fying frameworks by which complexities of reality can be reduced to meaningfirl relationships. This chapter reviews these traditional constructs and evaluates them in terms of applicability to present land tenure conditions within the farm sector. Part I outlines basic land rent theory. Part II reviews past empirical effort to test such theory, and Part III presents factors believed relevant to explaining observed deviations between theory and reality. 4.1 Land Rent Theory Reviewed The earliest economists expressed concern over the effects of leasing. Adam Smith condemned share rents because the landlord benefits from capital outlays of the tenant without contributing toward these investments. Mill and Marshall continued the study of share renting and the inherent problem of discouraging improvements [38, 36]. More recently, Schickele evaluated various tenure systems on the basis of efficiency criteria of (1) marginal revenue equal marginal costs and (2) all factors of production yield equimarginal returns [45]. He emphasized the inherent deviation from the optimum of various leasing methods due to separation of control or decision making and 79a 80 the different perspectives of the landlord and tenant concerning durable and nondurable factors. Schickele also erployed marginal analysis to share renting to clarify the resource inefficiency dilemma noted by earlier writers. A decade later Heady merged and expanded the major ideas of land rent theory that had been developed [21]. It is this effort which serves as the primary basis for the discussion to follow. Heady initially develops criteria for evaluating leasing systems which center on efficiency and equity. Assuming private ownership, competition, and an Operating pricing and exchange system, Heady says a perfect leasing system must therefore result in (l) the most efficient organization of resources on the farm firm relative to consumer derand as expressed in market prices and (2) an equitable division of products among the owners of the various resources employed in production. In the term, equitable, Heady is referring to the condition where return to any of the resource owners is based on the marginal value productivity of the resources that the owner contributes. This standard is directly related to efficiency, in that if a resource owner receives either more or less than the marginal value product of his resources he will be motivated to use them in ways that reduce the 81 efficiency of the firm. Consequently, erphasis is placed on efficiency since the equity will necessarily follow;L Having defined the concept of efficiency, Heady then identifies various ways in which leasing can distort the attainment of this end. 4.1.1 Resource Use Intensity in‘the Short Run The short run is defined as the period in which there is no opportunity for the tenant or landlord to alter the agreement . In this time frame, the participants' preferences can be in conflict. This is illustrated by Adams' and Rask's share lease model in Figure 4.1 [1]. Assuming a 50—50 output share lease without cost sharirg, line AQ represents the marginal value product (MVP) to the 3 firm for the variable factor X1, holding land and all other factors constant. Line BC represents the firm's marginal factor cost (MF‘C) for the variable input . The profit maximizing owner—operator would produce where MVP = MRC or at the Q2 level of input.2 This represents the optimum output level of the firm. lEfficiency takes on the same conditions then of the equilibrium conditions of the profit maximizing firm—namely, the attainment of: (l) factor-product relationships and cost structures must be retained over time consistent with short-run technological conditions. The scale of the firm must be one which defines maximum return; (2) marginal value productivity of substitute resources must be equated, and factor—factor relationships must not be distorted; (3) product combination will equate marginal returns on the last unit of resources employed for each product at a given point in time; (4) product combinations must be such that marginal value products are equated over time (discounted) for all resource units; (5) economic activity must not increase uncertainty above that normally existing in the market. 2The cash rent tenant would also prefer to operate at this level since he would appropriate all production the same as the owner- Operator . 82 A +3 8. a m MVP 73’ D 2MVP EB‘ G c l/2MFC ‘g ii I’ll-L. D4 NED U Q1 92 93 Level of variable Input xl/x2 . . . x3 Figure 4.1 Share lease model with cost sharing. For the 50—50 share tenant however, line DQ is perceived by him 3 as his MVP schedule. Thus, he would wish to produce at the Q1 level where his own MVP = MFC. At this level inefficiency is introduced into the firm.since MVP is twice as large as MFC. The landlord in this situation would take an entirely different perspective. Since the IMFC of the variable input is zero to him, he would desire production at the Q output level (as equally inefficient in the firm context as 3 the tenant's preference). Thus, conflict between.1andlord and tenant exists; and it is only by chance that the bargaining power of each 'would be balanced so as to arrive at the most efficient level of ‘production, Q2. I To resolve the share rent discrepancy, Heady says that the cost ‘of variable factors (where land is fixed) must be divided between the 83 landlord and tenant in proportions paralleling the division of the product [21, p. 600].1 This is illustrated in Figure 4.1 by line HM. Given this, the share tenant's MVP would intersect the new MFC line at point K; and optimum resource use would be attained. 14.1.2 Resource Use Intensity in the LoniRun A corollary misallocation of resources occurs in the long run which can also be illustrated by the model in Figure 4.1. In brief, tenants having essentially zero marginal factor costs with respect to the resource land, would want to farm extensively using the maximum amount of land (Q3 in Figure 4.1 if the variable was referring to the land resource). In contrast, the cash rent tenant faces an incremen- tal cost with each land unit and would choose to operate more inten- sively on a smaller sized operation, operating at Q2, the optimum resource combination. For the landlord with a share lease, his desire would be for the tenant to farm only Q1 units of land, thereby equalizing his MFC and MVP of the land resource. As with the short- Iun condition, the long—run imperfections can be remedied with sharing provisions of the inputs. But the process is more complex since the resources of both the landlord and the tenant are variable. Heady notes perfection can be brought about only if both parties own some of each category of resource, the proportion depending on the share of product received by each. "Thus , perfect share leases would almost always require complete partnership arrangements." [21, p. 601]. lJust what are considered variable factors and what are considered fixed factors remains a critical issue. Elefson notes that researchers have arbitrarily assigned inputs to these categories without explicitly recognizing this fact [16, p. 134‘]. 84 4.1.3 Resource Allocation Among Competing Enterprises Farm firms are frequently comprised of more than one major enterprise. Moreover, the major share of rental land is operated by part owners. Theory suggests that these situations can lead to re— source misallocation. More specifically, variation in the tenant's marginal value product between different crop enterprises or between his owned land and rented land will introduce inefficiency. First, enterprise combinations under differing share leases. Consider a situation in which two major crop enterprises are produced, at 50—50 shares and Y Y and Y2, with Y and a 1/3 to 2/3 share 1 1 2 agreement. The production possibility curve AB in Figure 4.2 shows the various combinations of the two products which can be produced. Based on the price relationships of the products, the optimum combi— nation is at the intersection of price line, ab, and production possibilities curve, AB, or point C. However, the tenant's production possibility curve is DE. And because of differing lease shares, its shape differs from the firm's curve. When the price line is applied to the tenant's curve, the resource combination varies; and when transferred to the firm context, production would take place at point F, or less than maximum efficiency. The remedy for this imperfection is for rental shares of each enterprise to be equal. In so doing both tenant and landlord preferences will not deviate from the optimum enterprise combination. In a somewhat similar vein, resource misallocation can arise in partownership where the tenant is allocating resources among land acreage owned as well as land rented. To illustrate this, production possibilities between the owned and the rented portions are a.ralyzed 85 Output of Y1 U Output of Y 2 Figure 4.2 Production possibilities with different rental shares between competing enterprises. as in Figure 4.3. Again, assuming part-owner and landlord resources are fixed in quantity, the production possibilities for the firm can be represented by AB in Figure 4.3. Likewise, the combiration providing greatest returns would be point C, the intersection of the production possibility curve and the product price line, ab. But the part owner's production possibilities curve is AD, since he re— ceives only half of the product from the rental acreage . Thus , the part owner can produce relatively more with his labor and capital resources if he uses more of these inputs on his owned acreage. However, the combination of resources which give the part owner highest returns (point B on the total production possibility curve) is not optimum from the standpoint of the firm. 86 a A g \ . . a ---+- -- C i . . O l O I 5 I J: | ' i . . 8 o ! I D B Output from Rental Land Figure 4.3 Production possibilities for part—owner operations. As with the inherent problem of differing shares between enterprises, the equal sharing of resource inputs between tenant and landlord will prevent this distortion of the opportunity curve. When this is done, return per dollar of resources invested by the tenant will have the same value productivity as a dollar of resources applied to his own land [21, p. 611]. 4.1.4 Tenure Uncertainty and Time Relationships in Leasng Because of the short-term nature of lease contracts, there is a tendency among tenants to contribute only those inputs whose benefits will accrue within the period covered by the lease. Theory suggests this leads to inefficiency, since the enterprises and resources with quick returns will be chosen even though other 87 (enterprises and other uses of resources could provide larger profits :in the long run [16, p. 24]. Resource inefficiency due to tenure uncertainty can occur in all types of leases, cash and share leases alike. Special jprovisions to increase security of tenure such as lengthening lease contracts or compensating unexhausted tenant inputs can reduce this defect. However, these actions do not entirely eliminate uncertainty, since it is highly unlikely that such efforts are perfect substitutes for something so complex and immeasurable as tenant uncertainty of the future. 4.2 A Review of Past Empirical Research Testing Rent Theogy Rent theory generally indicates that deviation from optimum resource allocation can take place due to certain features of lease agreements. Unless special provisions to eliminate these elements exist, empirical tests should reveal resource inefficiency under various leasing conditions. However, E1efSon notes there are two aspects to be recognized in such testing [16, pp. 30-33]. First, when there is motivation to depart from efficiency, the motivations of the tenant and the landlord are frequently counteracting. For example, when the tenant wants to farm extensively so that the marginal product of land is zero, the landlord is motivated to encourage the tenant to farm so intensively that the marginal product of tenant's resources are zero. Thus, to the extent that bargaining power is distributed evenly between the participants, the degree of ineffi- ciency fbund in any empirical test would be reduced. A second 88 aaspect to consider is the fact that motivations exogenous to the Ilease contract can result in distortions in optimum.resource use. ZIn other words, any relationship fOund in the empirical test must toe critically evaluated to see if inefficiency did, in fact, arise toecause of the lease itself. Bearing these potential limitations :in mind, specific empirical efforts can.be studied. 4.2.1 Intensity of Resource Use In.what is now considered a pioneering effort in testing leasing theory, Heady and Kehrberg tested the hypothesis that cash :rent farms are operated more intensively than share rent operations (assuming the tenant dominates decision making) [24]. Survey :results of their study gave g9_supporting evidence to this hypothesis. ‘Mhile the researchers fOund cash tenants to be farming somewhat more intensively than their crop-share counterparts, the authors note that variation appears to be due largely to variation in capital and equity positions among the tenure groups and not because of the lease type [24, p. 664]. Related to this, these researchers also looked at a specific input use (fertilizer) with and without cost sharing. Here, too, the survey evidence was less than significant. ElefSon has summarized the findings of this particular study by saying, "There is a strong suggestion that the desire to utilize fertilizer leads to cost sharing arrangements and that causation does not run in the opposite direction." [16, p. 43]. the~sophisticated techniques have also been used to test for the above relationships. Using Cobb-Douglas analysis, Nfiller fitted 89 equations to cross sectional data to compare resource efficiency under various tenure groups [39]. In looking at three tenure classes, (1) full owners, (2) livestock-share renters, and (3) crop—share cash :renters, Miller concluded: ". . . differences between tenure classes in the average deviations of actual costs of productive services from the minimum.costs attainable, that is, in the overall inefficiencies, are not significant in a probability sense." [39, pp. 4 and 5]. 4.2.2 Lease Types and Entepprise Combinations Several attempts have been made to test the hypothesis that enterprise selection as well as level of input use will vary among tenure groups. Cormack found relatively few significant differences with respect to the dependent variables betweeen the various groups [11]. He stated: It appeared that other variables were more powerful in affecting enterprise selection and the level of variable inputs than were those suggested by the hypotheses. . . . Enterprise selection may be more a function of long-run considerations, facilities available, price relationships, custom, or location rather than those which were hypothesized. [11, pp. 82-83]. In their earlier study, Heady and Kehrberg also discounted the mdnor cropping variation they observed between cash and share rented farms by suggesting it was due to exogenous factors such as capital and managerial differences. 4.2.3 Resource Efficiency in the Long Run The Heady-Kehrberg study also looked specifically at the (D 93 4.) U) 0 O 0 Figure 4.4 Long-run adjustment of firm size. It follows, then, that the validity of such an argument rests on whether or not economies of size do exist over the relevant size range of commercial farm firms. A number of studies of farm size economies have been made of various types of farm operations. Van Arsdall and Elder analyzed various sized cash—grain and corn farms in Illinois and found that on J'Primarily this is prevented by capital rationing of either external or interral types. 93 a one—man farmtwith four row equipment, a gross income of about $20,000 is needed to break even [54, p. 52]. Further, they found that average costs drop rapidly as annual gross income increased to $58,000. Expansion beyond this level for one-man units resulted in diseconomies. This particular study also found the efficiently- operated one—man unit could essentially compete quite effectively with the much larger units; in short the one—man unit could capture essentially all the size economies as his two-, three—, or six-man counterpart. The relevance of this particular study to significance of farmland rental can be seen by recalling the tenure patterns of cash grain farms in the Corn Belt in 1969. For example, the average class III Corn Belt cash-grain farm.(gross sales of $10,000 - $19,999 per year) was 275 acres in 1969 of which 152 acres were rented. By contrast, the average class I farm (gross sales of $40,000 or more annually) was 711 acres of which 493 acres were rented. In essence, nearly 80 percent of the size difference is rented land. This would suggest that expansion via rental does lead to achieving significant size economies fOr cash-grain operations. In two separate but similar studies of cash-grain.farms in Iowa, cost per unit of product was found to decline dramatically with increasing acreage size [28, 25]. Using synthetic budgeting techniques, average costs for all types of one—man and two—man farm organizations considered declined as acreage size increased from 160 acres to 320 acres. And fOr those operations where labor and machinery was less constrained, average costs continued to decrease to a size of 640 acres. 94 Other studies Of size—efficiency relationships on various types of farms have found technical economies to exist across the range where most of the farm population exists. However, as Madden notes, findings of synthetic firm analysis such as these must be interpreted with care since these studies typically ignore many financial factors and dynamic growth considerations facing actual firms [35, p. 95]. Thus, factors influencing economies as well as dis— economies do not enter into the analysis. In other words, the synthetic firm.may not be representative of an actual element of farm firms. The alternative empirical approach used in studies Of economies of size is Cobb-Douglas analysis of actual farm data. In contrast to the synthetic firm.method, this type of analysis measures the aggregate influence of all factors. But because such elements are not standardized according to level and combination in the data used, the Cobb-Douglas analysis invariably concludes no significant size economies exist. Hence, findings using this approach must also be interpreted with caution. Nonetheless, given the limitation of this empirical research, it is reasonable to conclude that efficiency gains from size expansion are significant. And where capital or credit constraints prevent size adjustment, farmland rental can facilitate increased resource effi- ciency even though the lease itself may partially negate the gains.1 This is illustrated in Figure 4.4. Size expansion via land purchase 1The situation is synonymous with a highly concentrated industry in which substantial size and scale economies are captured by the existence of a few large firms. Despite the distortion of resource efficiency due to an.imperfect oligopolistic market, higher levels of resource efficiency result than possible with many undersized, competitive firms. 95 may not be possible, and the firm must therefore remain at SACl. By renting farmland, however, the firm.can expand to a more efficient size, SAC And while the rental contract may introduce some 2. inefficiency , SAC2', greater resource efficiency in terms of lower cost per unit of production still results, 0P2 versus OPl In.brief, because of dynamic pressures to expand farm.size, farmland rental can play an expanding role in increasing efficiency, even though static rent theory suggests otherwise. 4.3.2 Internal Inconsistency in Leasing Theory Theory has been developed to argue that the main distortion of efficiency in leasing arises in the share-rent agreement. Theorists have proceeded to argue that variable costs must be shared in the same proportion as output in order to eliminate inefficiency. Yet, in reality, share leasing is still being used extensively without the cost-share provision. This has led to reconsideration of the theoretical framework. Johnson has noted that two important problems relating to the share contract have not been considered adequately by the theorist: (l) the issue of how the tenant determines the amount of land to rent (instead of soley the allocation of resources on a given farm) and (2) the type of adjustments that landlords and tenants make in their .mutual relations to make crop—share tenancy function reasonably well [30, pp. 114-115]. Johnson suggests the tenant considers the value of the marginal product of his labor in non-farm alternatives or in farming under a cash lease. Therefbre, the landlord cannot coerce the prospective tenant to farm so intensively as to drive the MVP 96 of his labor input to zero. In similar fashion, the landlord always has the option of renting for cash independent of output . "This , " says Johnson, "presumably represents the minimmm aggregate amount of rent that he will accept for the farm." [30, p. 117]. Given these bargaining positions, Johnson then says mutual agreement can be achieved via three routes, one of which is the classical suggestion of sharing expenses of variable inputs. A second is employment of detailed leased contracts . The third, and what Johnson considers the most important element , is the inherent restraint within the short-term lease . Because of the short-term lease, both landlord and tenant can terminate the lease contract should returns to their inputs fall below opportunity costs. Consequently, while disadvantages to short-term leasing exist , it does create a condition within which the crop-share lease results in reasonably efficient utilization of land. More recently, Cheung has incorporated similar considerations into the theoretical framework and concludes the traditional share tenancy model is inconsistent with the underlying assumptions of perfect competition in the leasing market [9]. His analysis is based on the premise of wealth maximization subject to the constraints of private property rights in a free market with zero cost of contracting. Cheung proceeds to modify the traditional framework by assuming a constant supply of land belonging to the landlord, Q1 in Figure 4.5. The MVP of tenant labor is represented by AB; and assumirg 50—50 share leasing, line CD would be tenant returns, or what Cheung calls "marginal contract rent . " Tenant returns to labor would therefore be area ABCD and landlord returns would be CDQlO. 50 long as the 97 Product per Unit of Labor 0 Q1 Tenant Labor per Unit of land Figure 4.5 Share leasing with one tenant. tenant's income is as big) or higher than his alternative earnings, the tenant will continue to farm. He will use all the land available to him on the farm as long as marginal productivity of the land is greater than zero (other inputs held constant) [9, p. 17]. For the landlord, his returns are maximized if he can increase his rental share (marginal contract curve) until the tenant's income from farming just equals his alternative earnings. However, in the assumed carpetitive state, the landlord has yet another variable which can be adjusted to maximize wealth—the amount of land leased to any one tenant. That is, a landlord will not allow one man to operate all the land he owns if parceling his lard to several terants will result in a higier total rent. This is illustrated in Figure 4.6 where the 98 land owned by a landlord is parceled and leased to four separate terants. As the number of tenants increases, the marginal value product of the landlord's property increases relative to a single tenant operation. 0 Q1 Figure 4 .6 Share leasing with multiple tenants . For the terant, the situation is somewhat similar. He will prefer to parcel out his own labor resource among a number of land- lords so long as total earnings increase. Moreover, because of the terant's non-farm labor earnings options, the landlord will need to decrease his share of output as size of unit declines. This decrease in landlord share will obviously lead to a lower rent received from each tenant, and if the land size per tenant continues decreasing, the rental percentage will eventually become so low that total rent from land will decline [9, p. 19]. 99 The conclusion, then, is that in reaching a mutually agreeable contract, the landlord and tenant must agree to three conditions: (1) the share rate, (2) the amount of land the landlord will contribute, 81d (3) the amount of labor a tenant will supply [7, p. 531]. Together, these conditions assure maximization of firm returns without the cost sharing provision so long as viable alternatives exist for each participant . This is more clearly illustrated in Figure 4.7 which is merely an expanded version of Figure 4.1. As previously stated, the MVP of tenant labor is represented by AQu, and the MVP received by Product Labor Tenant Labor Figure 4.7 Maximization of firm efficiency under share tenancy without cost sharing. 100 tenants under 50-50 share leasing is shown by DQL'. Line BC, which before represented MFC of the variable input now refers specifically to terant labor or alternative earning capacity. According to traditional theory, equilibrium will occur at point E, with OQl of labor input. This, of course, is an inefficient level of input since MFC temre labor < MVP tenant labor. But now, assuming that OQ2 inputs of labor are agreed upon, the following can be observed: (1) the landlord's share of the total product is area DAGH, which is greater than before (DAEF); and (2) the tenant's share (area ODI—IQZ) is still greater than his alternative earnings, since BDF is larger than FGH. This also means that total landlord rent DAG~I is smaller than the return under owner operatorship or a fixed cash lease, area BAG. To observe what will happen in this situation requires the interjection of average value product of tenant labor, IJ , and the .corresporxiing average tenant receipt of KL . Given these , landlords could stipulate the terants work up to Q where average 3 tenure receipts equal income from his alternative earnings. ' But with the tenant input pushed to DO the landlord would 3, receive rent equal to area BAG less GNN, an amount smaller than possible under owner Operatorship or fixed cash rent leasirg. Therefore, in order to maximize his return subject to tenant costs, the landlord would raise his share of output to r*, line PQu, which in turn lowers average tenant returns to RS. 0Q2 of tenant labor is used resulting in: (1) landlord return equal to that under owner operatorship, and (2) tenant return equal to that of his earnirgs alternative . 101 Given homogeneous factors of production, landlords will choose among carpeting tenants who offer rental shares as high as r*, while corpetition among landowners implies the share rates will not go any higher [9, p. 54]. Thus, Q2 at r* share rate represents a market equilibrium where the MVP of tenant labor equals MFC for the tenant . Simultaneously, the MVP of the firm equals its MFC. Therefore, resources are allocated efficiently. While revealing the inconsistency of the traditional model given the assumption of a corpetitive state, Cheung's model is not itself free from criticism. A primary reservation, of which Cheung is the first to acknowledge, is the assumption of zero transaction costs [9, p. 55]. In reality, parceling irputs among several dif- ferent landlords involves some costs including the cost of contractirg as well as transportation expenses. Inclusion of these costs in the analysis would distort the equilibrium level from the point of maximum efficiency. A second aspect to consider is the flexibility of landlords; i.e. , is it ptwsically feasible for most landlords to parcelize their property? If this is not possible, the landlord does rot have as viable an economic alternative from which to gain bargaining strength. The third and perhaps most important aspect of Cheung's model to critically consider is the type of competition and the degree to which it exists in leasing activity. For example, how feasible is the landlord option to alter share rates when custom prevails? Are the market information channels adequate for colpetitive bidding? Of markets surveyed in this study, there did not appear to be the types of conditions assumed in the model. 102 Nonetheless, the case studies do reveal (l) a tacit form of competition among tenants, (2) the parceling nature in the form of multiple-unit leasing, (3) the ready alternative of off-farm employ- ment for most tenants, and (4) the prevalence of short—term leases and the inherent opportunity for landlord control. All these elements are conducive to a landlord-tenant relationship in which both parties can bargain from strength, and resource efficiency ultimately results. To conclude, the Cheung model incorporates the corpetitive elements into the share-rent framework ard reveals that resource inefficiency is not inherent within this lease type. It follows, then, that the cost-share provision of variable inputs is not in itself a perfect remedy. Rather, it is entirely possible for share— rent leasing without cost sharing to lead to maximum resource efficiency. Whether or not this is attained is contingent upon the same variable influential in all tenure forms—the competitive nature of the market . 4.3.3 Assumptions Behind the Theory In addition to [dynamic versus static conditions and internal inconsistencies within share-rent theory, the assumptions underlying the theoretical frameworks must also be considered in determining why leasing theory has little supportive evidence. The present predominance of leasing by part owners is considera- bly different than when the body of leasing theory was being formulated. It is reasonable to assure that today's part owner renting farmland for expansion purposes reacts much differently than the full tenant of a few generations ago who viewed rental simply as 103 a step in the tenure ladder. For example, because most rental land today is Operated as part of larger operations, the risk and uncertain- ty of the farming Operation are not tied as directly to the specific lease. With less uncertainty of loss, the tenant operates from a larger planning horizon. This suggests greater managerial efficiency as well as greater social and community stability in high tenancy areas than once believed possible. The prevalence of multiple-unit leasing—leasing from more than one landlord—is another factor which traditional theory has not accounted for. As will be demonstrated in the following chapter, the uncertainty of short-term terancy is substantially reduced by such a practice, specifically with respect to the size of the total lard base. Finally, the rental market introduces deviations into the underlyirg assurptions of traditional leasing theory. The highly personal nature of the rental market found in this study appears to be quite a contrast to a primary assurption of individual profit maximization. A sizable portion of rental agreements are family agreements and therefore noneconomic factors frequently override the profit-maximizing individual incentive . But more importantly, the leasirg agreement usually involves a personal relationship (family or ronfamily) between the participants which strengthens with time. And even though the landlord frequently is quite passive in the management decision making, the established relationship is such that it is more of a partnership. In this context, both participants act from the starripoint of welfare of the firm. Mutual trust am 104 responsibility encourages efficient resource allocation irrespective of the theoretical imperfections of the lease contract.1 4.4 Chapter Summary Leasing theory in general concludes there is inefficient allocation of resources when land is operated under tenancy. Yet erpirical evidence to support this theory is meager and inconclusive . Partial explanation for this lack of support lies in the inherent inability of static theory to represent a dynamic setting. Secondly, there are internal inconsistencies within the theoretical framework of share renting which appear to negate the validity of the framework. Finally, certain assumptions cannot be considered realistic in light of structural charges and the findings of this study concernirg the market process . 1Even though some leases do rot evolve around such a relation- ship, the fact this is the norm means that custom forces efficient resource allocation on the total rental population. CHAPI'ERV THE FARMLAND RENTAL-STRUCTURAL CHANGE INTERFACE—- SPECIFIC ASPECTS The preceding chapters have identified a number of interrela- tionships between farmland rental and current structural trends . In this chapter, four specific aspects of this interface are analyzed in depth. Included are (l) the impact of rental land availability on the process of firm growth; (2) the effect of multiple—unit leasing on tenure uncertainty; (3) the economies of buying versus renting farmlarxi; a.rd (’4) land tenure unier various forms of business organization. 5.1 Rental Land Availability and Finn Growth 5.1.1 ProbabilitLAnalysis of Renting Farmland In discussing conditions for growth of farm business firms, Bailey states that one of the five necessary coalitions is that added resources are procurable [2]. Other researchers have referred specifically to the availability of the land resource as being critical to the g-owth process of the firm ['48]. Yet in most studies of firm growth, these availability aspects have not been empirically considered; i.e. , a perfectly elastic supply of land to either purctase or rent has been assumed. 105 106 Finiings of this study would suggest , however, that this assumption may be unrealistic, with respect to the availability of rental land. The observed stability of leasing arrangements and the distortions of the market itself seem to imply that farm operators or prospective Operators cannot and do not look to the rental market as being a ready source of land. Availability at any given point in time may be highly uncertain. The probability of farmland being available to rent is dependent on several factors . Amng these are (l) the proportion of all farmland rented within the area, (2) turnover rate of rental land, (3) effective narket radius considered by the potential tenant , (ll) particular land ownership patterns, and (5) the relative ease of information flow and degree of open competition. Because of the canplexity created by these factors, a specific probability is very evasive am hypothetical. However, probability analyses based on varying levels of each of these factors can be illustrative. To begin such an analysis requires the rather straightforward estimtion of total rental acreage available annually using various tenancy and turnover rates (Table 5.1). Three tenancy rates were used, 35 percent, 50 percent, and 65 percent. The low rate approxi- mates the terancy rate in the Michigan study area, while the high rate is similar to the rate of tenancy in the Illinois area (nationally, the 35 percent rate is most representative). Turnover rates of 2, 5, and 10 percent were then applied to each of these tenancy levels to arrive at the annual acreage of rental land changing hands . ‘ These .3588 gasps B 3:8 8358 no SSEEEBN 3:5 $5 68980.8 8 2:8 $8 22 H38 23 ac ES.“ ao «mascoflma B» b dag.“ on 8 c238 3 8.8. "SH H88 on» 603833: no 3335.." Lona 107 mmoama a OH Hmoam I o mane u m 8902' a 30; . mVSmam alums imam u m . w: n m $0.2 . S m/ r m8; - c / Ron . m H862 IBmNSoém TI 838 3? 2 . gm .. mvmmofi Alluomwozxa «III 938 «is a So.~ . m mm .. m an: n S own; a S Ema . m mama; lam 8m . m 08.: Alamm 8:; u m mmm u m :36 a o 0:; u 2 m2; u mv gag Ill Em mam u m mom: Allumm MS; u m mmm .. m 39.0 n S / mom .. S / Mam; . m eagle Illnomfomwéma 1' «:88 2? m mm: u m 96.0 ‘Iuomwomoafl flu 988 3? m mm; a m 8H u m 28.: u 2 \ MS u S mmm.m a m mmofi: lumm a u m 9.... 4|an am. a m RH .. m mom: a 0 MR. u o :3 n m 9: n m 39m n o / me: n 2 SW; n mvafldm Tuomemm£a 0| 388 22 m 8m a m we; AIIISm ~36 All SEE 3?. N am n m om - m mmm.m . 2 man u 2 Sm; - m :mmfim 1|me :2 u m mama“ Alumm Sm u m om .. N SQM u 0 H2 u o :8; .. m 2.9% 5' «mm 3 - mVSmJ All. umw mom a m om u m 29m u 0 V 02 n 0 mm; .. m Rdmm 4| Sm menaom Tn! 888 mg: m om - mv m8; 4| «8 o8.~ 8H8.“ ode H o a m cm . N 9;; u o \ E u S mmm . m i n m 3983 3.0.83 3% 03m ling A5 wwwoaom Bozo.“ mommmfiow madman Iago A: 3388 03:8 mmwmonom n38.“ 0.328 mum.» 35m u H.309 poo—Ame wwmopom mum.» Epsom a H.309 pastas amazon ago 9388”.” Econ pm>o 0388.3” 22.52 1:55. g 1.53. pzmopmo .mSHump umxpme m>apommmm so comma zaflmsoom maanHm>m mwmopom Hanson no soapmefipmm H.m manna m.zphmmoaa Hanson mo moan pm>ooh59 Hmzccm now «magnum» mo 108 turnover percentages were based on the distribution of tracts by number of years rented (refer to Table 3.7).1 The annual rental acreage available varies considerably. For example, a prospective tenant looking for rental land within a two-mile radius of his base, where 35 percent of the land is tenant operated, with a turnover of 5 percent per year, would be able to bid on about 1&0 acres in any given year. In contrast, a potential renter living in an area of 50 percent tenancy with 5 percent turnover who is willing to rent within a fiveamile radius may compete fer any of approximately 1,260 acres annually. While these estimations may represent the total market movement, the individual operator still cannot appraise the potential availap bility of’the land he needs. To accomplish this, two additional steps are needed. First, the implied assumption of incremental flow of rental acreages must be dropped. The land resource is a lumpy input, typically transferring in increments of NO, 80, and 160 acres or divisable fractions thereof (as determined by the rectangular survey). Second, it trust also be recognized that demani for rental land tends to be categorized in terms of size; that is, a potential renter may be looldng for a particular-sized tract. This is especially cannon where denand is for farm enlargement purposes, which accounts fer the maqor portion of demand. lAssuning a constant net volume of total rental property, the distribution of tracts by years rented suggested an average turnover rate of 5 to 6 percent. There were instances when as high as 11 percent and as low as 3 percent of the total tracts were rented in am! year. Consequently, the 2 percent and 10 percent turnover rates were adopted to illustrate the extremes . 109 The annual probability of a particular-sized unit being available is dependent to a large extent upon the land ownership patterns. More specifically, it is dependent on the percentages of land area in each particular size unit. An example will clarify this. Return again to the situation of a 35 percent tenancy rate with a 5 percent turnover rate, and a potential tenant looking within a two-mile radius of his base. Assume he is looking for an 80-acre tract to rent. Since the total annual acreage turnover is 1111 acres, there is a mirrum potential of 1.76 80—acre tracts available annually (llll ~3- 80). However, this assumes that all land is divided into 80—acre ownership units . In reality, only a portion of the land is in 80-acre units; thus, a second adjustment is needed to arrive at a probability. If 142 percent of the land is in 80—acre tracts, then the minim potential (1.76) trust be adjusted (1.76 x .12 = .714). 80, less than one 80-acre tract per year becomes available within a two-mile radius; or one 80-acre tract comes up for rent in about three out of four years. i This same technique has been used on other tract sizes for other various conditions to arrive at the array of probabilities in Table 5.2. Probability analysis such as this illustrates the relationship of time and distance to the expected availability. In short, a trade—off exists. For example, if an operator wants to rent an additional 80 acres within a one-mile proximity of his headquarters, 110 Table 5.2 Annual probability of farmland being available fer rent, by rate of tenancy, annual turnover rate, effective market radius, and size of tract.a ‘35% farmland rented 65% farmland rented Annual turnover Annual turnover Effective market rates rates radius and 7 size of tract 2 5 . 10 2 5 10 . . No. of tracts available ...... l mile~market radius ‘“0 acres .08 .19 .39 .1“ .36 .72 80 acres .07 .18 .37 .1“ .3“ .69 120 acres .02 .0“ .09 .03 .08 .16 160 acres .02 .05 .09 .03 .09 .17 2 mile market radius “0 acres .31 .78 1.56 .58 1.““ 2.89 80 acres .30 .7“ l.“9 .55 1.38 2.76 120 acres .07 .18 .35 .13 .33 .66 160 acres .08 .19 .37 .1“ .3“ .69 5'mdle'market radius “0 acres 1.9“ “.8“ 9.68 3.59 8.99 17.97 80 acres 1.85 “.62 9.2“ 3.“3 8.58 17.15 120 acres .““ 1.01 2.20 .82 2.0“ “.08 160 acres .“6 1.16 2.31 .86 2.15 “.29 10 mile market radius “0 acres 7.7“ 19.36 38.73 1“.38 35.96 71.92 80 acres 7.39 18.“8 36.97 13.72 3“.33 68.65 120 acres 1.76 “.“0 8.80 3.27 8.17 16.35 160 acres 1.85 “.62 9.3“ 3.“3 8.58 17.16 8Based on analysis of size of ownership units in the two study areas, the land area was estimated to be allocated among ownership units as fellows: and 160 acres, 21%. “0 acres, 22%; 80 acres, “2%; 120 acres, 15%; 111 he may need to wait several years for a tract to become available.1 If timeliness is more important, then an operator may choose to expand his effective market radius . (The probability factor increases at a rate equal to the square of the market radius). larger operators particularly may not heavily discount the increasing radius of their land base. In many instances, they are more interested in the location of a potential tract with respect to another tract they are already renting, rather than from the headquarters unit; their nobility reduces the importance of operating from a base unit . And while some knowledge of the physical qualities and needs of the tract may be sacrificed, they more readily gain their necessary land base. Moreover, they may also gain some degree of production stability by geographic dispersion. Thus far, the probability analysis has assumed perfect knowledge and open carpetition. In reality, the rental market has been found to be highly personal and informal in nature with very restricted flow of information. This study found in less than half the cases that others were aware of the land being available to rent . In effect, the estimated annual probabilities could be halved. It would also be realistic to assume that market knowledge is a decreasirg flinction of distance; the farther the potential renter is from the rental tract; i.e. , the less his opportunity to become aware of its availa- bility. Thus, any adjustment for imperfect information flow would 1Besides the locational advantages and lower transportation costs of farming land within close proximity, operators may also place higher value on land close by beCause of their familiarity with soil fertility, past land use, and need for special farming practices. 112 increasingly discount the probabilities attached to distance of market radius. Several implications can be drawn from.this model of rental land availability. First, despite the short-term tendencies of rental contracts, the potential supply of rental land available is limited at a given point in time. Unlike the title transfer market, where "one can always buy farmdand-if he's willing to pay fer it," the rental market offers little opportunity fer such bidding (especially if crop—share leasing prevails). Highly inelastic supply means that someone looking for farmland to rent may be constrained by the availability. Moreover, market imperfections reduce aggregate supply considerably. Thus, even if a potential tenant looks fer land over a wide area, his decisions will still be predicated on the relative chance of finding land to rent. For the operator hoping to expand his acreage base, this uncertainty of availability may motivate him to choose another means of land asset control such as mortgage or low equity financing. But if such alternatives do not exist, the growth sequence of his farming operation will conform.closely to the supply of land to rent. To the beginning farmer, access to rental property may be especially limited. Unless he has special options arising from kinship or personal friendship, he may have difficulty in competing with farm.operators whose managerial reputations are already established. Quality of the land available is yet another parameter to consider. A realistic assumption is that tracts of poorer quality or tracts owned by uncooperative landlords may experience a higher 113 turnover rate than average . Thus , land being offered for rent may carry a somewhat higher risk for the prospective terant. 5.1.2 Rental Land Availability 'in'the Firm Growth Process—A Model A rnmmber of firm growth studies have determined that farmland rental can be the optimum strategy for reaching the growth objectives unier limited equity arri credit coalitions. For example, a study by Martin and Plaxico of the rolling plains of Oklahoma and Texas found land rental was preferable to purchase in maximizing net worth over time [37]. In maximizing cash return objectives, Bostwick found growth by renting optimal due to the greater investment leverage of this strategy over equity alternatives [6] . When maximizing net worth, Bostwick's growth model also indicated rental was preferable in the early stages of the growth cycle in order to increase scale of resource use. For similar reasons, a simulation growth model of Corn Belt farms developed by Lins identified the rental strateg' as achieving higher net worth when consumption and minimum size of purchase or rental were both high [3“]. Findings of this study and others concerning the relatively greater reliance on rental in farm expansion would support the results of these growth models . Yet these models do not consider that rental land may not be available. Likewise, the empirical supporting evidence refers only to the successful expansion operator who is only a sub—group of a larger population of Operators who may have wished to expand their acreage; i.e. , the data does not indicate the degree of constraint on the successfill and unsuccessful expansion operator alike due to unavailability. 11“ Consequently, the following hypothesis was proposed: The availability of rental land significantly influences the desirability of farmland leasing in attaining firm growth objectives. In other words, the supply of rental land available at any given point in time follows essentially a random geographic pattern:L This sporatic nature of land availability can override the commonly considered financial constraints on firm growth; and in turn, alter the relative advantage of leasing over other strategies. To test this hypothesis, a previously developed growth simulation model was modified to account for various levels of rental land availability.2 The model selected was one developed by Lins that was initially designed to examine alternative land investment strategies common to Midwest cash grain farms [3“]. Evaluation included consideration of the relative merits of each strategy in achieving specific goals . This particular model was chosen for two reasons . First, the data was representative of the geographic area and type of farming in which the lard resource is crucial to growth and rental is a 1Inherent: within this statement is the assumption of inelastic supply of rental land. Hence, supply will not respond significantly to price (rent) charges, and availability is predicated on chance. The case study of selected rental markets indicates the market is persoral in nature with very limited price competition. So, the assumption above appears realistic. 2Similar probability conditions were not assigned to the purchase market, even though it too may demonstrate sporatic availability. However, the purchase market appears to offer more opportunity for bidding on land, thus bringing into the market land that might not otherwise be available. Then, too, rental is most critical in the early stages of the growth process when firancial constraints prevent purchase; therefore, the availability of the rental land is the more crucial of the two markets . For theSe reasons , analysis of the effects of availability are limited to rental land only . 115 comonly used alternative to ownership. Secondly, the model could be easily modified to include a random probability factor for finding land to rent in any given year.1 The mecranics of this model are a beginning base unit farm of 185 owned tillable acres [3“, p. 6 and 7]. It was believed this was representative of a well-established unit in the Midwest which could be supported independently of off-farm income and capable of growth. Production coefficients were developed for a cropping pattern of two-thirds corn and one—third soybeans. Total assets at the beginning of the lS—year growth period are valued at $135,000 with debts of $59,600 leaving a beginning net worth of $75,“00. Land values are assumed to be appreciating 3 percent per year. Farmland is assumed to be rented for cash at 5.75 percent of land value. The effects on the growth of this base firm were analyzed for five different land investment strategies: (1) fixed land investment; (2) conventional mortgge contract, with no refinancing; (3) convent ioral mortgage 2 with refinancing; (“) land contract; and (5) cash rent. In addition 11h essence, this simulation model is nothing more than a series of financial budgets for a hypothetical farm firm. These annual budgets are linked together over a period of time in order to corpare the performance of various growth strategies over a probability array of rental land availability. The advantages of simulation over basic farm budgeting is (1) speed of data processing and (2) reduction of human error in hand calculation. 2While referring to cash rent only, this strategy is assumed to be representative of all leasing arrargements , includirg the dominant crop—share arrargement . While operators may incur somewhat lower rent under cash leases than under share arrangements , the difference could be viewed as what the tenants' discount cash leases because they are assuming a relatively greater amount of the uncertainty . Thus , rental changes should be consistent among all lease types; and growth, as measured by accumulated net worth, should not be altered appreciably by lease type. 116 to the average conditions described, the model considered the influence of other factors such as interest rate on debt; percent equity on debt, size of purchased or rented land unit, and operator goals. The rental strategy consisted of a year-end decision to rent or not to rent based on available cash at the start of each production period (see decision flow process in Figure 5.1). Mere specifically, cash and nonfarm asset value has to be equal to or greater than oneéhalf the rental fee on the particularhsized rental unit(s) under question'befbre rental is allowed. A penalty element is included fer a reduction of rented acres below the level of the previous year; this reflects depreciation of unused machinery that may occur if the number of crop acres rented fluctuates from year to year. Adjustments in machinery investment are then made as appropriate with external financing if cash is inadequate. The availability element of rental land was built into the model at two different levels: (1) the probability of renting land previously rented (PRLPR), and (2) the probability of renting land not previously rented (PRLNPR). The latter is what is typically influential in the growth process. However, the former needs to be considered also since, as previously noted, land is generally leased on a one-year or yearhto—year arrangement, and therefbre the growth process can.be subject to the periodic decision of the landlord. . A random probability scheme was devised to interject various prObability levels of availability at the two levels. The procedure was as fellows: using a table of random.numbers, a number between 0 a.rd 9 was selected at random and assigned to each of the 15 years in 1(No) Is New Land Available to Rent? 117 éb (No)! Is Land fir ‘1: , l """""+r::sh Rent Strategy I Available? (Yes) UK. Rent One Unit of Land and Adjust Cash and Other Necessary Variables (Yes) 14’ eviously Rented ] l 7 Cash and Nonfanm ' of Land? ‘ «- (N0) Assets 1/2 Rental (No) Cost of One Unit Is Land Rented Great Enough to Amount to that Rented Last Year? Sell Corn Inventory at Reduced Price to Obtain Cash Needed? (Yes) - ‘i’ _ Is machinery I (No) Adequate? Purchase Machinery Using , Machinery Credit if Cash is Inadequate 1 (Yes) ‘I’- Narketing Routine Figure 5.1 Year-end decision flow chart. 1:5» [60 to Production and I 118 the planning horizon. A separate random combination was assigned to each rental tract, recognizing that even though two or more tracts may have the same probability of being available, it does not necessarily follow that such tracts would be available in the same year. Various levels of probability of renting could then be assigned based on the random number arrays. For example, suppose one assigned a “0 percent chance of renting land which had not previously been rented and a 90 percent chance of renting land which had previously been rented. Then, new renting would be allowed in those years assigned a number of 0 through 3; and renting of land which had previously been rented would be allowed in all years assigned a number of 0 through 8. 5.1.3 Analysis of Findings Runs for the 15-year growth period using the land rental strategy were made for the following levels of availability: probability of renting land not previously rented of .20, .“0, .60, arrl .80; arri probability of renting lard previously rented of .80, .90, arri 1.00. The ranges of probabilities chosen were based on the survey firrlings of this study; i.e. , the probability of renting land not previously rented appeared to cover the whole range with respon- dents in Illinois frequently commenting available rental lard was virtually nonexistent , while some Michigan operators could rent all they wanted . As for land now rented by the operators , such arrange- ments showed much stability; thus, a range of relatively h1g1 probabilities was assigned to the maintenance of existing leases. Combining these two elements of rental lard availability yielded 12 different probability combinations to use in analysis . 119 Accumulated net worth and acreage operated Over the lS—year period were compared for each of the 12 levels of probability (Table 5.3). When availability is no problem (probabilities = 1.00), accumulated net worth after the lS—year period is $2“7,600 with a total of 6“0 acres of land eventually being rented. On an.annual basis, the growth rate of net worth averages “.7 percent. As probabilities of availability of rental land decrease, growth of net worth declined steadily also.l At the lowest probability levels, PRLPR = .80 and PRLNPR = .20, net worth totalled $223,900 after 15 years, or 10 percent less than under conditions of unlimited availa- bility. Growth rate is reduced to 3.6 percent annually. The relative importance of each of the two availability factors is somewhat evident in the pattern Of accumulated net worth under various probability combinations. When there is no chance of losing land already rented (PRLPR = 1.00), and a probability of renting land of .20, final net worth falls to $232,700. When a prObability element Of renting land previously rented Of .80 is added, total net worth falls to $223,900. In other words, about 30 percent of the total reduction could be attributed to the risk of losing land already being rented, and the rerainder is due to the risk of finding other land to rent. The prObability of renting land not previously rented influences vthe eventual size of the Operating unit. As shown in.Table 5.3, the 1Inusing probability analysis of this nature, it is necessary to interpret empirical estimates cautiously. That is, the values for net worth derived in Table 5.3 represent a particular set of random . numbers. It is highly unlikely that these same values could result fromtdifferent randomtdraw. However, the values derived on average should approximate the same levels. 120 .33 $0.. 60.. Jam: .93 .33 Conan 9.3.83 02.2.: 3.533%: .< 338 Jason 595 :20 «as; .3 5.8.5 o... 2.0.532: 9:... mo 33 cote—23m ¢ .00» Zea mo 55238:. Lou .395 .3332: 52. 3 v9.33. 33:230.... sons... 5:. 3.» c. 3.8- 8 on 3 was»: a... 33... none: .83.. v5.82“. 366 no. we 33 8.5.33 5:. 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".2. 88 ..~.. 8 8.2. 8. 2.2 .8 28. 8. a... 8. e8. 8. ”.8. 8. .8. 8. 2.2 8... .. ~..2 8 no: 8. .8. o.~ 2... 8. ~..2 8 .8. 8. .8. .8 0.8. 8. n8. 8. 8.2. 8. ~.2. 8. 28. 8. 8.8. 8. 2 8.8. 8 8.8. 8. 8.8. 8. 2.2 8. 8.8. 8 28. .8 8.8. 8...... 8.. 8...... 8. 8.8. 8. .8. 8. .8. 8. 0.8. 8. a 8.8. 8 8.... e.~ .8. 8. 2... o.~ 8..... 8 8.8. 8. .82 8. 3... 8. ~.n.. 8. ...2 8. .82 8. 8.8.. 8. .82 8. e 8.8. 8. ~82 8. 8.8. 8. 8.8. 8. .82 8. 8.... 8. 8.8. 8. ..~.. 8. 8.8. 8. ~.n.. 8. 2... 8. 8.... 8. a... 8. . 8.2. o .8. 8 28. 8 .8. 8 22. 8 ...~. 8. 8.8. 8 8.8. 8. 8.2. o 8.8. 8. .8. 8. 28. .8 ...2 8. . ..... o .8. o.~ 8.2. 8. 28. .8 ..... e .8. o.~ 8.2. 8. 28. oz ..... o ..8. o.~ 22. 8. 28. .8 8.8. .8 m 28. a n8. 8. 2.2 8 e... 8. 28. e .8. 8. 2.2 8 n... .8 28. o .8. 8. 2.2 8 Q... o.~ ~.~.. o... . .8 o 8.8. 8. 8.8 8 28 8 .8 a 8:8. 8. 28 8 28 8 .8 o 8.8. 8. 28 8 8.8 8 2.2 8. n .8 o .8 e a... 8 a... 8 .8 o .8 o 8..... 8 8..... 8 .8 o .8 o 2.... 8 2... 8 28 8. ~ 8.8 a 8.8 e 8.8 e 8.8 e 8.8 o 8.8 o 28 o 8.8 o 8.8 e 8.8 o 8.8 e 8.8 o 8.8 e . 88.. e8. 88.. 82. 82. 8.. 88. 82. 82. e8; 82. 8.. 88.. 5.3.. 3...... 5.53 «20¢ 5...... 38¢ 5.5: 3.82 5...... «98¢ 5...... 38¢ 5.6: 38¢ 5.53 «95¢ 5.83 «20¢ 5.3.. mtu¢ 5...! «95¢ 5.83 3.2 5.03 «9:!— 8: .2. .3. 82 .2. a... so. 8.. 8.. e... e... 8.. e... 8. .82.... 8. .83.: 8. .83.: 8. .82.: 8. .85.: 8. .858 8. .85.... 8. .858 8. .85... 8. .83.... 8. .85.... 8. .82.... 82.85.... to. 8. .. «as... 8. . 8e: 8. . 8..: 8. . 8:8 8. . as: 8. . as... 8. . .58 8. . 8..... 8.. . an... 8.. .. 8..: 8.. . 5:8 8.. . 8..... 8.. . 8..: o. Ammqmmv 8888 39686.3 oqma wofiooom .Ho pom End/3mg ooocoa 3 2.086%. no: papa @8258 Mo meme/OH moHHHomoopo 2.3.8.. no.“ moped no.8 one 5.8... poo oopmfieSoom .HO .3398 m.m magma. 121 final size. of rented acreage drops from 6M0 acres to 320 acres as PRLNPR goes from 1.00 to .20 while holding PRLPR at 1.00... This, of course, would reduce the volume of cash receipts from the operation over time; and, in turn, reduce net worth buildup. What appears to be contributing even more to a lower accumulation of net worth is the erratic size of operating unit over time and the resulting over investment in machinery. When the acreage base of an operatim doubles in a few short years , only to contract as rapidly due to such unforeseen circumstances, serious reSource misallocations are likely.1 It was believed that the size increment of acreage change could significantly alter the impact of rental land availability on the growth process . Consequently, the previous assumption of rental tracts averaging 80 acres in size was altered to be 160 acres; and mns at the various probability conbinations were made. While the frequency of size adjustment declined over the 15—year period, the impact on size and total net worth at the end of the period did not vary significantly? Results of this model prior to the modification for rental land availability ranked the cash leasing strateg as number one in maximizing net worth under shorter planning horizons of five and ten 1To adjust to this situation the operator has two alternatives: (1) he could under-invest in equipment and custan hire in those years when his acreage is large, or (2) maintain an adequate machinery investment and do custom work himself when his acreage is down. Either option, however, may come at an economic cost . 2Based on Chi Square Test of Independence at the 5 percent level of significance. 122 years. Under the more limited degrees of availability as presented in Table 5.3, total net worth under the rental strategy is reduced about 10 percent in the shorter time horizons as well as over the entire period. This reduced the ranking of the rental strategy to a third position behind a land contract strategy and the mortgage with refinancing route. No specific measure of impact on the growth objective of mimum cash returns was possible with this particular model. However, here too, the erratic pattern of annual income and periodic over-investment in machinery due to tenure uncertainty would suggest a significant decrease in maximizing this objective. Thus , from this analysis and given the assumptions and parameters of this particular sinulation model, the hypothesis that availability of rental land significantly alters the relative desirability of farmland rental in reaching growth objectives is supported. 5.2 Miltiple—Unit Leasing and Uncertainty’ Related to the firm growth issue is the question of the firm maintaining a viable-sized acreage base. Leasing interjects an element of uncertainty. Unless long-term leasing contracts exist, there is always the risk of losing the land unit because of the landlord's decision to sell or to change tenants. This, coupled with the lack of other available land to rent, can pose a serious uncertain- ty to the operator of a land-based operation. Moreover, this uncertainty becomes more critical as the increasing size am financial sophistication of the farm 1‘? inns demand longer planning horizons. But, with expanded farm size there. has also emerged serendipitously a particular characteristic of the farmland rental situation which, 123 it is hypothesized, effectively reduces tenure uncertainty—nultiple— unit leasing (renting parcels from several different landlords simultaneously). The operator who is renting from a number of independent lardlords, perhaps unwittingly, reduces tenure uncertainty with each additional rental agreement made. While the relative risk of termination remains unchanged on each parcel , the operator effectively reduces the probability of losing a substantial portion of his land base in any given year. In so doing his planning horizon can be longer; and, in turn, his long-run managerial decision making more efficient. In the case analysis of selected narkets in Michigan ard Illinois , operators interviewed were , on average , renting tracts of land from three different landlords . These finiings are likely to be representative of U. S. land-based agriculture in general, since the trend of an increasing gap between size of Operating unit and ownership unit appears to be widespread. 5.2.1 A Framework for Analysis To test this hypothesis, a representative farming operation was constructed with the following assumptions: (1) a HBO-acre farming operation with all the land being rented, and (2) the probability of the tenant operator losing any leashold is .10 (one year out of ten, the operator could expect to be unable to renew his lease due to the landlord ' s preference). Several different forms of rental arrangements are then considered, ranging fran a single lease for the entire 1180 acres to six separate leaseholds of 80 acres each. 1214 Annual probabilities of losing part or all of the rental property were then calculated using the binomial distribution fornula [18, p. 137]. This formula is: _ n-x n _n! F(X) - :qu — P) where X — n_x M n = Number of trials (number of separate leaseholds) x = Number of occurrences (number of leaseholds lost) P = Probability of occurrence (probability of losing leasehold = .10) . 5.2.2 The Finiings Table 5.14 illustrates the annual probabilities of losirg one or more tracts under various leasing combinations. In terms of incidence of loss the annual probabilities range from .100 for a single leasehold to .168 for the trultiple-unit operation having six leaseholds. This would appear to suggest that multiple-unit operations are at a disadvantage in terms of risk of resource availability. Arxi, indeed, if circumstances required that specific parcels comprising the total lard base be maintained, the single leasehold is preferable. However, generally the more important measure is the extent of loss incurred. It is this aspect which is the value of multiple-unit leasing. For example, while the six-unit operation faces a 117 percent chance of losing some land annually, it faces less than a 10 percent chance of losing more than a third of its total acreage in any given year. In contrast, the operation having Just three leaseholds faces a 27 percent chance of losirg morethan a third of its acreage annually. In another perspective, . the single leasehold unit faces a 10 percent chance of losing its entire acreage in any given year, 125 .Hoo. can» mmmqn .om. no cannon sz50fi>mnd poms» some wcfinzmn mo zudaanmbogn mnp_co vommmm 00H. oma. mom. mam. wmz. OOH. Ho. Hoo. moo. 5N0. Hoo. omH. mzo. mHo. cam. moo. Nam. :mm. Ammnom omsv vac: nommoa mamcam one Anode meson ozmv muaonwmmoa mumsmamm 039 Anomo women 8.8 @3238.” mpmnwdmm mouse Anomo manna omHv muaonmmmoa mumsmdmm nzpm some manna omv mafia: _Iomwoa mamnmamm me mpompu whoa no mco ,mmpqm om: meson oo: .mmpom, omm mason... 0mm women. cam moped own mmqu omH . menus om wCHUHonucma no coaumufiqmwno when..." .8 Eggnog Hanna a.mcofinm:«QEOo wcammoa ucwnwghao nuns: snag cannon mnemlom: Hwoaumnpodzn_m.co mucusmuosfl wand msoanw>.wcamoa mo mpHHHnmnona Hmszq¢ :.m manna 126 while the likelihood of this occurring urxier any of the other organizational patterns is one percent or less. While multiplehunit leasing clearly reduces risk in this hypothetical analysis, the validity of the underlying assumptions of constant probabilities for tracts across all organizational forms could be questioned. First, there is the issue of coordinating the total operation when dealing with several landlords . The possibility of conflicting interests is real if landlords enter actively into management, thereby suggestingan increasing probability of loss of each tract as more landlords are involved. However, evidence of this study suggests that landlords usually play a rather minor managerial role, so this is unlikely to be a significant factor. What is more likely to arise is the relatively greater motive of a tenant to please the landlord of the large leasehold and attempt to solidify their relationship and promote a more refined agreement. And, if renting his entire rented base from a single landlord, the tenant may be in better nanagerial position to satisfy the lardlord with special services—in effect reducing uncertainty by paying a hidden privilege rent [“5]. Thus, it my be possible that probability of lease termination does decline somewhat with ownership concentration of rented land. Nonetheless, this does not negate the fact that multiple-unit leasing does effectively reduce tenure uncertainty for the majority of operators, who must carbine parcels from several land— lords in order to gain access to an ecomnically viable land base. 127 5. 2 . 3 The Implications As to Just how these different probability levels can influence the economic structure of the farm firm, it is relevant to introduce the notion of a threshold level; i.e. , that degree of cutback in acreage base that would create serious financial difficulties . For example, suppose such a point in the NBC-acre hypothetical farm was a reduction to 2140 acres. In theory, such a point may be that level of output below which the firm's average revenue (also marginal revenue assuming a competitive market) falls short of average variable costs. In other words, it is not economically rational to continue operating even in the short run; and the firm would cease operation. However, the threshold point may be viewed somewhat differently by the farm operator. He may visualize such a point as that minimum net revenue necessary to allow adequate family consumption and to carry the debt obligations of the operation. Therefore , the operator would like to minimize this probability as much as possible because of the magnitude of implications.1 As shown in Table 5.1% , the operator with several independent rental parcels can essentially reduce the possibility of exceeding this threshold point to virtually zero while those with one or two leaseholds face a much higher risk of maintaining a minimum land base from year to year. Obviously not all tenure uncertainty is eliminated by multiple- unit leasing. Amt long-«run investment which a tenant may want to make J‘I'his is particularly true if replacement units are scarce and alternative income generating activities are not available. Both these conditions imply a longer duration to the situation. 128 regarding a particular tract of rental land is still subject to uncertainty. Likewise, the landlord, too, faces similar risk in any plans having longer ramifications than the length of the rental agreement. This aspect of uncertainty remains. Yet, where the main- tenance of a viable land base is the critical factor, multiple—unit leasing offers considerable advantage . Then, too, there is a corollary of this which is the concept of flexibility. Heady describes this as more nearly a method of preventing the sacrifice of large gains [21 , pp. 5214-29]. Flexibility allows for changing plans as time passes. Here, also, there is value in multiple—unit leasing, despite increased effort of coordination of the total operation. Basically, it not only frees the individual manager from constraining land debt, but also allows greater year-to- year opportunity to make incremental adjustments in the size of his land base.1 5.3 The Decision to Rent or Buy In the process of firm growth and farm consolidation, land purchase as well as rental takes place. Assuming farmlard is available to rent, which the previous analysis reveals is generally probabilistic, the rental route has several advantages . Rental offers the attractiveness of virtually no capital requirements while purchase can place substantial capital constraints on the operator. As a supplement or substitute to equity capital and credit , rental can ——v 1Land is a discrete resource. Marginal product theory suggests that the smaller the incremental unit of a discrete resource relative to the total quantity used by the firm, the closer the firm can come to achieving full utilization of that resource. 129 strengthen repayment capacity of the operation, and, depending on the type of lease, even increase risk bearing ability [141]. And, as noted in the previous section, the short-term nature of the rental contract allows greater flexibility of land resource adjustments over time to the Operator. On the other hand , the operator who rents faces an element of uncertainty concerning the availability of the rental parcel beyond the contract point, as well as potential managerial constraints. More importantly, the rental route bypasses the investment aspect, which in recent years has been attractive because of the combination of steady appreciation in land values and capital gains tax provisions.1 Other factors also influence the decision, including any intangible benefits of land ownership. At the heart of the rental versus purchase decision is the relationship of rent to market value. Over the last two decades, farmland values have moved upward briskly despite an apparent low rate of return. Nationally, net rents of farms rented for cash have fluctuated slightly between 3.5 percent and “.5 percent of market value [LB].2 While there are variations among regions and states, net rents generally fall below 5 percent of market value—an annual rate of return readily accessible in the most conservative and risk-free investment options . Given the opportunity costs and cost of mortgage credit, the historical average of farmland rents seems low. Hence, 1The inclusion of appreciation as collateral for further short— run am long—run credit needs is an additional incentive to choose ownership over rental. See [17 J. 2Net rents are reported gross rents less landlord expenditures for fire and wind insurance, maintenance, depreciation, and accidental damage on improvements, and real estate taxes. 130 the following was hypothesized: rename rental is economically preferable to farmland purchase as a means of attaining land use rights, unless substantial appreciation of both values and rents can be anticipated in the future. 5.3.1 The Present Worth Analysis Framework Being immobile ard serving as a spacial dimension for production, land reflects future income streams in terms of present value. Consequently, to test the above hypothesis, a present worth analysis of the relevant range of financing and potential returns is employed. The indeperdent variables of this analysis are: (1) expected land value appreciation, (2) mortgage interest rates, (3) downpayment levels, and (14) net rents. The assumptions are: 1. Since land is usually purchased over time, a 2S-year amortization period was chosen so as to minimize cash flow problems that could arise from much shorter repayment periods. 2. land is available for purchase and for rent at the same time. 3. Net rents of 2%, La, and 6% of current market value are assumed to be the relevant range of net rents. While it is based on reported cash rents, it is believed that market forces would adjust all types of leasing to similar average levels of returns. 14. Net rents are assumed to vary directly with land value appreciation. Recent findings suggest this is a valid assumption in regions haVing a stable agricultural base [H2]. 131 5. No difference in physical productivity exists between rented farmland and farmland owned by the operator; i.e. , rental contracts do not distort resource efficiency. The model is a modified income capitalization formula designed to determine the internal rate of return which will make the present value of the anticipated income stream.(net rents minus loan payments) and anticipated net sale proceeds (sale price at time of sale) equal to the downpayment [13]. In equation ferm: a C)(1 + g)t .- LP xvto=§=o t t +Vt°(l+g)n t (l + r) (l + r) Where: XV£O = downpayment (x is percent of purchase price). ab(l + g)t = annual net rent expected to change "g" percent per year, where a0 is the level of net rent at the end of year 1. Rents received at end of each year. LP = amortized loan payment. r = internal rate of return used to discount future net rents and sale proceeds. V£O(l + h)n= expected market value of the property at end of year n with expected annual percentage change, h. Initially, h = g which means a constant net rent to current market value ratio. Various combinations of (1) land value appreciation.rates (h), (2) net rents (ab), and (3) financing arrangements (LP, which varies with.mortgage interest rate and downpayment) were entered into the formula, which.was then solved for the internal rate of return (r). 132 These values were then arranged to comprise a form of decision matrix for the orderly appraisal Of the buy versus rent decision. 5. 3 . 2 A Decision Matrix Table 5.5 is an array of internal rates of return when annual net rent is assumed to be A percent of each year's current market value. For example, assume the purchase price of farmlard is $600 per acre and the potential investor calculated initial net rent Of $21! per acre. He could then turn to this table and by identifying the financing arrangements he would need and the appreciation expected, he could read off the internal rate of return on his investment . By comparing this rate with the opportunity cost he places on that investment, he would be able to rationally decide whether or not to buy, or in the case of the expansion-minded operator, to buy or rent . For instance, if this Operator could make a 10 percent downpayment with a 25—year mortgage at 9 percent interest; and he anticipates u percent anrnial appreciation Of land values and rents, the internal rate of return on investment is 7 percent.1 If 1It should be recognized that this return is prior to income tax. Because interest payments are a deductible allowance, the actual rate of return deperds on the individual investor '3 tax bracket . For example, if the investor above is in the 22 percent tax bracket, he is essentially paying only a 7 percent mortgage interest rate [.09 - .22(.O9)]. Thus, his expected internal rate of return would be higher. If he were in the nu percent tax bracket, he would be paying only 5% mortgage interest after tax deductions , thereby increasing expected return even more. Likewise, the deduction Of property tax from federal and state taxable income also increases the effective internal rate of return somewhat . These two deduction allowances , plus the capital gains tax provisions, combine to make the profitability Of farmland investment highly contingent upon the income position of the potential investor, with considerable financial advantage to those in the higher tax brackets. Thus, the tax aspects of the farmland investment must be an implicit variable in the analysis to follow. 10% Internal Rate or Return (Percen677- - - — - — — - — _ _ _ _ - 5% l 6% j 711;] 8% 1f 9% l l [”7 Annual Appreciation Ebcpected Over 25 Year Period 1, 1% j]? 2% 411 3% M mortgage interest rates, and downpayment levels.a Mortgage Interest rate and Downpayment Table 5.5 Annual internal rate of return on investment under selected rates of land value appreciation, H :rr-mo Lfi :rzm HHHHH ONSLDUD wwGDCDCO Ofib-ON \DWONK; O\:T (7‘le m5: mm @0000?! HNmm: OOmt- LP. TOOHN afiomzrxo mNr—ioo I I I I 10% Dowrpayment 20% Dowrpayment 30% Dowrpayment ”0% Downpayment 50% Dowrpayment 10! Mortgage interest 9% Mortgage interest 133 ONamw weep» QMVDONN :1” Lnanxo 00‘th OO\O\O\O\ H HHr-{HO (IDCOCOCDCI; ON-tr LOW \O\D\O\O\O ®N\OO\N manam SHNNW HNNMM mmmmm ri‘lC'DOt-Ir-i 7% Mortgage interest OUWNQF- I O O O 0 H0000 HHH oooxomn oxoooooooo ooooo NNNNN «)0qu :TLOLOUNLD 30‘«=1:I\:O NNmmn N\om0\:r oa octahooozop one .mopmo pmosoooH owmmpooe .o000000o0oom osam> 0:00 mo moons empooHom mono: poospmm>o0 so endows mo Open announce Hmzoo< 0.0 canoe 136 Given the steady rise in.farnfland values over the last two decades of nearly 6 percent per year, it would be reasonable to expect potential farmland investors to anticipate similar gains into the future. And, consequently, a general preference of purchase over rental would seem.likely among operators. The fact that such a trend towards owner—operatorship does not exist reflects the financial constraints facing operators. These constraints are manifested in essentially three ways. Financing fOr real estate purchase may simply be unavailable due to lending requirements of the institutions; i.e., a form of external capital rationing. v Then, also, the operator himself may place constraints upon purchase. As is true of’many operators who are becoming established, the use of available equity capital may yield much higher returns in short run uses such as fertilizer inputs. In effect, then, the operator'may face opportunity costs of 20 percent or more in the short run and may therefbre impose capital rationing upon.himself. Finally, the question of repayment capacity is a critical consideration to the lender as well as to the loan applicant. The fact that appreciation represents a very significant part of the returns to land ownership infers that it is a longeterm investment decision. As Hottel and Martin point out, "The key point to be made in such an analysis is that land ownership takes place because the entre— preneur is interested in returns from the standpoint of both a farm operator and a land owner." [26]. This is true because returns are not distributed evenly but rather are clustered at the end of the planning horizon.when capital gains are eventually realized. For 137 instance, in this analysis where the debt load was amortized over a 25-year period, annual interest and principal payments exceeded net rents during the first 15 to 20 years of the period depending upon downpayment levels , mortgage interest rates , and rents . Consequently, cash flow problems may arise because of purchase. For the younger operator already facing difficulty in maintaining an income flow adequate for meeting family consumption needs , land purchase would probably be prohibitive, even though profitability in the long run may be high. Of course there are some counteracting considerations which individuals must also weigh into the buy versus rent decision; as . noted earlier, there may be increased access to short-run and long-run credit via ownership and the inclusion of appreciated land values as collateral. In essence, this represents a benefit to appreciation before realization of capital gains at time of sale. Also, security of access to particular land units may be crucial to the efficient long—run organization of the firm and therefore require ownership . Nevertheless, it could be concluded that, in general, where both alternatives exist, rental is the economically preferable means to obtaining access to use of the land resource in the short run. Only when the decision maker is financially capable of considering long-run benefits of ownership, as realization of capital gains, is land purchase in canpetition with the rental option. 5.14‘ Far_'mland'Rental and BusinessOrganizationin'the WSector With increasing land and capital requirements of farm firms has come greater interest in more sophisticated forms of business 138 organization. Partnership and sub-chapter S corporations frequently can better facilitate financial and managerial needs of larger operations than possible under single proprietorships. Concern has been raised over the possible influence of such organizational ferms on farmland tenure patterns-amore specifically the potential accumulation of large ownership holdings. While the ramifications of such a trend (whether actual or potential) are not the issues at this Juncture, there are reasons to support the argument of ownership concentration. As noted, partnership or incorporation.may provide greater access to equity capital and credit than under single proprietorship. Secondly, the removal of a single generation planning horizon such as with a corporation would imply greater interest in land purchase from the standpoint of long-term investment. Thirdly, the potential fbr nonfarm investment is enhanced and with it greater emphasis on tax considerations of farmland investment. Finally, the very personal, infbrmal nature of the rental market suggested by the case study may result in the more sophisticated, impersonal type of organization being at a distinct disadvantage in competing for rental land. Based on these arguments it was hypothesized that rate of land tenancy differs significantly among organizational fOrms with lowest rates among farming corporations and highest among individual proprietorships. This hypothesis was tested using tenure data for economic classes I - V'farms in the 1969 Census of Agriculture. The predomdnant form of organization is the individual or 100013 proprietorship throughout all areas of the country. Over 70 perCent of all land in economic classes I -'V farms is under this 139 form of organization (Table 5.7). The proportion ranges from.6l per- cent in.the Mountain.region to 84 percent in the Lake States. The partnership ferm.controls the next largest portion of the total land base, generally accounting for 15 to 20 percent. Corporations account for only small amounts of farmland acreage throughout much of the country. The exceptions are the Southeast, Mountain, and Pacific regions where 13 percent, 21 percent, and 1“ percent, respectively, of the land is in incorporated units. On a state basis, the highest incidence of'farming corporations is found in Florida.where 33 percent of the farmland area is controlled under this organizational form. California runs second with corporations accounting for 15 percent of the land in farms. The greater importance of the corporate fonm in these areas can.be attributed in.part to the types of farming enterprises in which they are engaged. These operations typically involve enterprises demanding large land units as a comparison of average farm size suggests (Table 5.8). But are tenure patterns significantly different among the various ferms of business organization? A comparative analysis of farm numbers and land in farms by tenure for each organizational form reveals no evidence to support this (Table 5.9). At the aggregate level, no significant difference in tenure patterns is apparent for either the distribution of farm numbers or land in farms.1 On a rate of tenancy basis (proportion of land rented), differences do appear when the distinction is made between corporations of ten or fewer 1Based on Chi Square Test of Independence at the 5 percent level of Significance. 1140 .0m 00000.0. 00.003020 gm 003m .00300600w< .00 .00ng $3 "0903mm 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. 000000 00 0.0 0.00 0.00 0.00 m 0.0 0.00 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . . . 0000000 0.0 0.00 0.00 0.00 m 0.0 0.00 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . . 0000000: 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. 000000 00000000 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . . . . 00000 0.0 0.00 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . . 000000000 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . 00000000000 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 0. 000000 00000002 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m. . . . 0000 0000 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 0. . . 000000 0000 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 m 0.0 0.0 0.00 0.00 n. . . . 000000002 0 o o o o o o o Pcmoahmnw o s o o o o o m. 0 o o o o o o pcmgmm o o o o o o o o m. o o o o o o o pcmnvaHmnm o o o o o o o o” H0000000 m m N “0000000 00000000 m m m 0000000 0 .00000 0 0000 0 000000 n 0000000 0 :00000 n 0000 . 000000 . 0000000 0 .00000 H 0000 N 000000 H 10.820 00 0 0033 ”1.0020000 " .00 00 "3.0.0.020 00 0 0030.0 "0005.000 .00 00 ”$0020 00 ... 0.0.30.0 ”00:00.80 ” .00 0.0 H macawmm 0000 0002 u 00 00 n 0100000000 ”0000 0000 0 0o 00 . ".000>0000 ”0000 00o: 0 0o 00 u ”n000>0000 H 0000000000000 0 a. n 0000000098 . . . 000000009000 H H H .0000 0 0000 00 0000> .000 00000 00 a 0 00000 00 0000 00 0000000 M. 0000002 0000 00 0000«« m 0.0000 00:00w00 soapoooogo 050% an 005000 >.I H 0000000 ofieocooo mo meHUHHso one soda mo 0000> 000008 pow 00050“ CH coma .mhmoescngodu "no Homooom 0.m canoe .0m 0309 3005020 gm 003.0 503030090 .00 03050 300 60.980 lul 00050.0 000.000 000.000 000.00 0 000.0 Ema 000 000 u . 000000 00 000.0m0.m 000.mmm 000.00m 000.000 0 000.0 000.0 000.0 000 n . . . . . 00.00000 08.0000 000.000 000.000 00m.mm0 " 000.00 000.00 000.0 000.0 0 . . . . 000052 000.000.0 000.000 000.000 000.mm0 . 000.00 000.0 000.0 000 0 . 000000 00000000 000.000 000.m00 000.000 000.00 0 000.0 000.0 0mm 00m 0 . . . . . . 00000 000.mmm.m 000.000 000.0m0 000.00 0 mm0.0 00m.0 ~00 mmm " . . . . 000000000 000.000 000.000 000.00 000.00 m 000.0 000 000 000 u . . . 00000000000 80.00% 80.000 000.00 000.00 m 000.0 000.0 000.0 mi. 0 . 000000 00000002 000.000 000.000 000.00 000.00 m 000 000 0mm 0mm 0 0000 500 000.000 000.000 00m.00 000.00 m 000.0 000 000 0mm 0 . . . 000000 0000 000.000 000.000 000.000 000.3 m 000.0 000 00.0 000 u . . . . 000000.82 oooooooooOOOnHMoooooooonoH1 oooooooooonHU I H 0000000 00000000 pom .5000 000 0wcH00000 0:0 0:00 00 0:00> 000008 0w000>m new 0000 8000 0w000>< m.m 00009 l“22 Table 5.9 Percent of farm.numbers and percent of land in farms by type of organization and by tenure for economic classes I'— V farms by farm production region, 1969.a : . Percent of Land : Percent of Farm Nurber-sb = in Famsb : FUII’ : Part : = Full : Part : : Owners : Owners : Tenants = Owners : Owners : Tenants : . . . . . Percent . . . . . = ..... Percent . . . . . : . . Individual or Family Farm10rganization . . . . Northeast . . . . : 60.8 30.8 8.“ : 50.6 “2.“ 7.0 Lake States . . . : 62.3 29.0 8.6 : 50.0 “1.2 8.8 Corn Belt . . . . = 51.3 30.3 18.3 3 37.8 “2.9 19.3 Northern Plains . : 3“.2 “7.1 18.6 : 22.1 6“.“ 13.5 Appalachian . . . : 60.1 26.5 13.“ : 56.3 35.6 8.1 Southeast . . . . = 60.3 29.5 10.2 : “8.6 “3.8 7.6 Delta . . . . . . : 52.3 33.“ 1“.3 = 38.5 “7.7 13.8 Southern Plains . : “3.8 38.8 17.“ : 28.7 55.3 16.0 Mountain . . . . : “6.3 “1.5 12.2 = 18.6 72.8 8.6 Pacific . . . . . : 62.“ 26.5 11.2 = 25.“ 61.0 13.6 “8 States . : 52.“ 33.2* 1“.5* : 31.1 56.0’ 12T9’ ; O O O O O 0 O ..... Pmmmp O O 0 O O O O O O 0 0 Northeast . . . . : 50.3 39.2 10.5 = “0.1 51.6 8.3 Lake States . . . = 51.2 33.1 15.7 = 39.“ “7.0 13.6 corn Belt . . . . : 3“.9 33.5 31.7 : 25.3 “9.8 29.9 Northern Plains . : 28.0 “7.7 2“.3 = 17.7 65.1 17.2 Appalachian . . . : “8.8 31.9 19.3 = “5.7 “1.5 12.9 Southeast . . . . : 51.5 3“.0 1“.5 = “3.0 “6.3 10.7 Delta . . . . . . : 39.6 “0.0 20.“ : 29.“ 53.8 16.8 Southern Plains . = 35.6 “0.6 23.8 = 2“.6 51.0 2“.“ Mountain . . . . : 37.“ “6.5 16.0 = 16.0 73.9 10.1 Pacific . . . . . : 82.3 30.; 16.8 = 20.6 60.2 19.2 “8 States : .9 3 . 22.5 = 2“.0 58.1 17.9 g 0 0 O 0 I O O O O 0 O O Corfioratim O O O O O O O O O 0 Northeast . . . . = 55.“ 32.1 12.5 = 35.7 55.5 8.8 Lake States . . = 56.9 29.0 1“.1 = 37.“ “9.2 13.“ Corn Belt . . . 3 52.1 27.2 20.7 = “0.8 “2.3 16.9 Northern Plains 3 33.8 “5.8 20.“ i 13.5 73.0 13.5 Appalachian . . : “9.1 27.0 23.8 = 50.1 36.7 13.2 Southeast . . . . : 62.8 20.6 16.7 3 61.5 32.7 5.8 Delta . . . . . . : 38.3 33.“ 28.“ : 39.1 “0.8 20.1 Southern Plains . : “3.1 29.“ 27.5 : 22.2 59.7 18.1 Mountain . . . . : 3u.5 5“.3 11.2 : 8.5 81.0 10.5 Paaicic . . . . . : “6.8 32.9 20.3 : 20.“ 70.2 9.“ ;___ “8mams .:9fi8 33“ ’1&8’ =I&1 703 116 aSouroe: 1969 Census of Agriculture, State Sumnary Voiures, Table 2“. bPercentages may not add to 100.0 due to rounding. l“3 shareholders and those of more than ten shareholders. Yet even with this greater classification refinement, a consistent pattern is not evident (Table 5.10). For example, corporations of more than ten shareholders rent a high proportion of their land in a number of midwestern states. Frequently, these operations are involved in specialized crop enterprises and rent a large land base on long-term contract. In contrast, such corporations may, on average, rent very little of their total acreage in a neighboring state—-all depending on the nature of the specific enterprises involved. One must conclude, then, that this comparative analysis offers no empirical support to the hypothesis that tenure patterns are altered by organizational form. Mere specifically, there is no evidence to suggest a tendency towards land ownership among large—scale operations such as corporations with more than ten shareholders. In fact, these business entities:may be controlling a larger portion of their land resources via rental than the operation organized around an individual. It could be proposed that decisions regarding the use rights to land are more sensitive to the physical land needs of the enterprise than to the variation in financial flexibility among the various organizational forms. 5.5 Chapter Summary Farmland rental is an integral part of the process of farm consolidation and growth . Finn growth researchers have frequently advocated the rental route in attaining various growth objectives, particularly when capital and/or credit constraints exist. Yet in concentrating on the firms, research has tended to ignore the aggregate 1““ Table 5.10 Percent of land in farms rented by type of farm.organiza- tion for economic classes I -'V farms, “8 states, 1969.a Percent of Land in Farm Rented State and Corporation Region Individual Partner- 10 or fewer I More than 10! All Corpora- or family ship sgeholders shareholders tions . . . . ......... Percent .............. New . States 16.0 17.“ 15.3 13.5 1“.9 New York 19.1 22.1 28.6 1“.3 27.7 New Jersey 37.3 36.7 50.6 33.3 50.0 Permylvania 23.“ 27.2 29.1 25.0 28.3 Delaware “0.1 “3.6 3“.1 9.1 28.8 mtg/Land 35.“ “5.2 “2.9 30.“ “0.“ W 22.5 26.7 29.“ 19.3 27.9 Michign 25.3 36.5 32.6 13.3 30.7 Wisconsin 16.7 27.0 25.5 61.1 33.7 Minnesota 32.2 38.1 36.8 78.2 ““.“ LAKE STATES 26.2 3“.5 30.9 62.“ 36.9 Chic 37.6 5“.0 37.1 11.8 35.2 Iniiana “2.3 58.7 33.2 35.7 33.3 Illinois 55.3 63.“ 39.“ 7“.3 “6.0 Iowa “5.0 57.1 37.5 20.7 35.0 Masouri 28.9 “3.“ “3.5 26.9 “2.5 CORN BELT “2.5 55.5 38.9 “2.2 39.2 North Dakota 37.3 “2.6 “2.5 60.0 “3.0 South Dakota 37.8 38.0 29.8 15.0 29.“ Nebraska “5.“ “5.7 29.7 1“.0 27.“ Kansas 53.1 5“.Z 55.6 81.3 58.8 NOW PLAINS “3.9 “5.5 33.1 23.1 32.0 Virginia 23.0 29.2 27.8 39.3 29.5 West Virginia 17.2 21.0 27.5 25.0 27.3 North Carolina 31.6 36.1 28.3 10.“ 2“.9 1(thle 18.3 33.2 26.0 10.0 2“.1 'I_1e_nnessee 2“.8 3“.6 33.9 32.5 33.5 APPALACHIAN 23.8 33.0 28.“ 23.“ 27.5 South Carolina 30.0 29.9 25.“ 17.5 2“.3 Georgia 23.1 26.2 16.1 6.0 15.2 Florida 37.8 “3.8 22.3 7.2 16.8 Alabama 29.3 30.“ 29.1 10.3 26.7 W 29.3 32.2 22.0 7.5 17.5 Mississippi 31.8 38.7 “2.7 17.“ 39.8 Arlmnsas “2.0 53.3 “7.“ 35.1 “5.8 mater—1a 50.1 “9.7 an, 15. 3_2._7 DELTA “0.3 “7.0 ““.9 19.3 39.2 Oklahana. “3.“ “5.7 “5.6 25.0 “5.0 12129, as.“ 52.3 “5.3 19.8 438.1 mm PLADB “7.3 51.2 “5.3 19.9 38.5 antana 36.0 38.“ 33.3 36.8 33.5 Idaho 33.7 39.7 “0.0 ““.8 “0.3 Wyanirg “1.“ “1.7 “1.5 26.1 “0.“ Colorado 39.0 39.0 38.0 53.6 “0.2 New Bbxico “9.0 “1.0 ““.9 39.5 ““.0 Arizona 69.? 61.9 68.5 “9.5 61.“ Utah 36.2 39.2 30.9 17.5 30.0 Nevada 55.1 i“ 73.] 37.8 67.5 MAIN “2.2 “1.“ ““.6 “2.0 ““.2 Hashirgton “8.7 “9.8 60.2 72.5 60.6 Oregon 33.3 37.9 30.0 15.1 28.8 California 56.0 60.2 55.1 26.6 “6.5 PACIFIC “8.“ 53.1 “7.6 26.3 “3.3 “8 STATES “0.8 “5.7 “2.2 29.9 “0.1 8Source: 1969 Census of Ayiculture, State W Volumes, Table 2“. Calcu- latedassmdrgalllaxutrntismtedbypmtowmrsamltemntsisopemted and mt subleased. bNew Mend States include: Maine, New Whine, Verunnt, mssacmsetts, Rhode Island, am Connecticut. 1“5 dimensions of farmland leasing. One such aspect is the question of availability. Analysis using hypothetical models and case study findings on tenure stability revealed (1) that availability is probabilistic and (2) that at apparent rates of turnover, the limited availability of rental land can significantly alter the desirability of rental over other growth strategies. The analysis suggests that the probability of maintaining a rental contract from year to year is more critical to the growth process than is the availability of rental land for add-on purposes— reflecting resource misallocation of fluctuating operation size. Part of this problem of tenure uncertainty is buffered by the high incidence of multiple-th leasing. By leasing from several landlords sinniltaneously, the operator reduces the chance of losing a signifi- cant proportion of his acreage base in any given year. When availability is no problem, rental is preferable to purchase of farmland over a wide range of financial conditions and expectations. Present worth analysis using a representative decision framework indicates appreciation of “ percent or more per year generally mist be anticipated (virtually risk free) before purchase is economically preferable to rental. In other words, rental is the most economical means of attaining use rights to land in the short run. Only with consideration of profitable long-run investment aspects of land ownership is purchase a more desirable route. Despite the greater inherent motivations to consider these long-rm investment aspects , the farm corporation and other more sophisticated organizational forms do not show a tendency towards land ownership. No significant difference in tenancy patterns between 1“6 these types of business organizations and sole proprietorships was found. Apparently, the short-run advantage of land use control via rental is primry, regardless of the type of business organization. CHAPTERVI SUNMARY, CONCLUSIONS , AND D’IPLICATIONS 6.1 Sunmary and Conclusions Analysis of U. S. farmland tenure patterns indicates that rental is a widely used means of obtaining use rights to the land resource. Based on the 1969 Census of Agriculture, about 38 percent of all land in farms (in terms of both acreage and market value) is beirg rented. Since the bulk of this rented portion is leased from nonoperator landlords, leasing must be regarded as an important source of capital for the farming sector. Relative to estimated real estate debt outstanding held by farm operators, the capital input via farm- land leasing is roughly three times as great. Further insight beyond these aggregate means is gained by observing tenure patterns across various classifications of classes I - V farms. For example, classifications of farm firms by acreage size and by economic class both revealed a relatively heavier emphasis on farmland leasing among the larger farm units. On average, roughly four out of every nine acres of farmland in class I and II farms were rented while less than 30 percent was rented in class V farms. Units of 500 acres or more were leasing twice as mich of their land as those operations of 100. to 139 acres in size- In terms of concentration, the largest one—fifth of the operating units (in acres) account for about three-fourths of the rented farmland . No siglificant 1“7 l“8 variation in reliance on tenancy was observed among the various forms of financial organization. Hence, even though more sophisticated organization units may increase in incidence, it does not infer that less reliance on farmland leasing will follow. Wide variation in the relative importance of rental is also evident among age classes of operators, with younger farmers relying much more heavily on leasing than older farmers . While there are numerous variables influencing this pattern, the dramatic increase in dollar volume of the real estate needs of the current generation farm unit over its predecessor appears to be an important factor. The tenancy patterns that are observed, then, confirm that farmland rental is highly interrelated with the structural adjustments that have occurred over the last few decades. More specifically, farmland rental has taken on a different dimension . Where once tenancy was considered as a temporary rung on the tenure ladder to eventual full ownership, leasing is predominantly viewed today as an effective and frequently a permanent tool to achieving use rights to an adequate-sized land base. In fact, where capital and credit limitations have prohibited land purchase , rental has been the opera- tor's sole means of acreage size expansion. This is particularly true of land-based production such as cash-grain farming. But even when an operator is not financially constrained from buying farmland, he may still choose to rent, given the anticipated returns on investment he could expect . In fact , over the relevant range of mortgage interest rates, net rents, and opportunity costs, rental would be preferable unless rather substantial appreciation in farmland values is anticipated. l“9 Despite the magnitude of'farmfland leasing and its past and present role in the process of farm consolidation and growth, evidence of this study supports the hypothesis that the rental market process is low keyed and informal in nature with little visible competition. In part, this can be attributed to the significant number of family tenancies-—38 percent of those in this case study analysis.l Also, because of the inherent motivations of both landlords and tenants to make rental arrangements within their friendship circles, a price—competitive market is discouraged. Correlated with this is the existence of poorly developed market infOrmation channels, a rather slow adjustment to technological change as custom prevails, and very slow turnover rates of rental arrangements. So, even where motivations fOr price competition may arise, the market system offers little opportunity. The above is not to say the market is devoid of competition. Quite the contrary, an effective system of checks and balances appears to be operating which fOrms a type of tacit competition. Findings of this study indicate the landlord typically plays a very:minor managerial role, thus allowing the tenant considerable latitude in maraging his total operation. Moreover, renewal of short-term leases often is essentially risk free so long as land ownership is not transferred. Yet, landlord exploitation by the tenant is discouraged by (l) custom'within.the area and (2) the potential termination of a short-term.lease by the landlord. This, in addition to the personal relationship of the tenant and his landlord, results in a form of partnership in.which.maximum resource efficiency equilibrium is approached, even though active price competition does not exist. 150 For the farm Operator who has successfully rented land and has his desirable land base, the nature of the rental market process is quite beneficial in that tenure uncertainty is reduced substantially. Yet, the process of achieving that rented land base may have been much slower than desired. Then, too, his prospect of future acreage expansion may be highly uncertain due to the issue of rental land availability. Likewise, the potential farm operator may often find the accumulation of a land base via rental to be highly risky. In short, in moving from the firm perspective to the more aggregate concept of the market, the question of rental land, availability becomes crucial. A significant finding of this study was that the characteristic short-term lease contract does not necessarily create rapid turnover of rental land and thus a reduction in the problem of availability. Despite the fact that 90 percent of the leases studied were one-year arrangements, they had existed an average of 13 years. Crude measures of the turnover rate of rental land indicate that less than 10 percent may become available in any given year. Given this low rate of turnover, a potential tenant could expect rather limited opportunity to rent farmland within a reasonable operating radius . The question then is, does this limitation affect the farm consolidation and growth process significantly? This was analyzed by incorporat irg probability factors for (l) renting land previously rented and (2) renting land not previously rented into a simulation yowth model. Under the more limited degrees of availability, the amnial compound growth rate of accdmulated net worth was reduced about 151 one percentage point. This was significant enough to reduce the ranking of a cash rent growth strategy over some of the other growth strategies. To the extent that rental land is being used by larger farms, the findings above could suggest that the farm.consolidation and expansion.process has been constrained by the unavailability; i.e., the speed of growth has been governed by the availability of rented land. Respondents surveyed in this study would support this hypothesis, in that about “0 percent hoped to expand their rental acreage in the future "1:5" as numerous operators added, "I can find land to rent." However, there is also a counter argument to this in that lack of land to rent can encourage operators of smaller units to sell out and potential entrants to seeklmnukumlemployment. Thus, limdted.availability could also speed.up aggregate adjustment in farm size and numbers. For the established operator, the key issue of availability of rental land is maintaining the land base over his planning horizon. ‘Though leases exhibit high levels of stability, an.e1ement of tenure uncertainty lingers, simply from the possibility of ownership transfer. However, because of a particular aspect of leasing today, this uncertainty is being effectively reduced by multiple-unit leasing. By leasing land from several landlords, a tenant serendipitously reduces the risk of losing a substantial portion of his land base in any given year. In so doing, he can more efficiently manage his operation in the long run. This suggests that some credit institutions may need to reconsider their credit policies in the case of applicants with 152 sizable reliance on farmland rental. In essence, the enhancement of repayment capacity via leasing does not necessarily carry negative connotations with regards to risk and uncertainty, which previously demanded high equity levels of the loan applicant. Given (1) the magnitude of farmland leasing in U. S. land-based agriculture and (2) the low-keyed, imperfect nature of the rental market, the body of leasing theory would suggest there is serious misallocation of the land resource. For several reasons, the theory infers that deviation from maximum resource efficiency results when the firm moves from the optimum of owner-operatorship into tenancy. However, a review of empirical research efforts to test such theory reveals very little supporting evidence. In part, this can be explained by the failure of static theory to account for dynamic adjustments, such as the realization of size and scale economies of size expansion. There is also criticism of the share—rent portion of theory in that it is internally inconsistent with the urrierlying assumptions of perfect competition. The nature of the market process revealed by this study (i.e. , a form of tacit competition with strong bargaining positions of both tenant and landlord) would further support such a conclusion. Finally, the assumptions under- lying much of the theory no longer appear to reflect real—world coalitions—most notable being the dominance of part-owner leasing, multiple—unit leasing, and a market setting conducive to strong and mutually beneficial landlord-tenant relationships . Thus , it is concluded there is little basis to. support the theoretical proposition of resource inefficiency arising from tenancy. 153 6 . 2 Implications Inquiring into institutional relationships invariably becomes quite complex and multidimensional. This analysis is no exception. There are a number of social—economic implications arising from the findings of this study, which, while defying quantitative measurement, should not be ignored . In order to recognize and appraise the various implications requires that one first broaden the perspective of the analysis. In addition to efficient resource use, other objectives which are generally accepted by society as improving general welfare must also be considered. Then, too, the conduct and performance aspects of the rental market process need consideration along with the structural factors. Many objectives have been proposed to which the ideal lard tenure system is to be directed. Harris, however, has outlined several tenure objectives which essentially represent the thinking of many researchers [19, p. 7]. These are (l) efficient resource use, ( 2) stability of resource productivity, (3) equality of access to land by individuals, (“) provisions for progress, (5) improved equality of income, and (6) maintenance of the family farm. For this discussion, all but the sixth objective are considered; mainten- ance of the family farm is omitted simply because there is no concensus on the definition of the family farm. As to appraisal of the market process per se in terms of corduct and performance, Sosnick has advocated that conditions for effective competition be stated explicitly [“7]. He proceeds to list twenty-five flaws which can negate effective competition and therefore 15“ the socially desirable state of affairs. Ten of these conditions Sosnick regards as undesirable, both in themselves and in their effects. These are: (1) unsatisfactory products, (2) underuse or overuse of production plants, (3) inefficient exchange, (“) inefficient production, (5) bad externalities, (6) spoilation, (7) exploitation, (8) unfair tactics, (9) wasterl advertising, and (10) irrationality. Fifteen other criteria Sosnick considers undesirable only because of their effects. These are: (l) undue profits or losses, (2) inadequate research, (3) predation, (“) pre—emption, (5) tying arrangements, (6) resale price maintenance, (7) refusals to deal, (8) undesirable discrimination, (9) misallocation of risk, (10) undesirable col- laboration, (ll) undesirable mergers, (12) undesirable entry, (13) misinfbrmation, (1“) inefficient rules for trading, and (15) mdsregulationt Obviously, many of Sosnick's criteria are directed more at the large—scale, industrial market and do not apply to the farmland rental market process. Nevertheless, it is a comprehensive framework'by which to consider conduct and perfOrmance aspects and is therefbre used in this context. 6.2.1 Land Tenure in the Future Findings of this study indicate a direct relationship between acreage size of fanm firms and reliance on land leasing. At present, it appears the trend towards increased farm.size will continue. It follows that rental land may cOntinue to become more concentrated on larger operations. As to whether or not the magnitude of farmland rental will increase, the future is less certain. Increasing capital and credit 155 demands associated with larger units would seem to suggest the affirmative. But, as noted by Nelson, a number of customs and practices, as well as attitudes of farmers and the public, probably would need to be modified for renting to increase significantly in magnitude as a source of capital [“1, p. 1388]. Nevertheless, the conditions for a substantial modification of the land tenure system in terms of ownership as well as control of use rights appear to exist. For example, today many farm operators in the older age classes are accruing large capital gains on land which had been acquired twenty or thirty years earlier. The growth in the wealth position via appreciated land values has greatly improved their credit positions and thus has facilitated acreage expansion through purchase as well as rental. This is in sharp contrast with today's younger operator who faces a more difficult and costly task of purchasing farmland, particularly in the quantity necessary for an economically viable unit. This would confirm an earlier conclusion of greater permanence to the emphasis on land leasing by younger farmers today than that of earlier generations. If such is the case, the relative importance of inheritance and intergenerational family transfers to the next generation could decline. Then, too, any decline in the relative importance of land .investment as a long-term income source places greater demands on the annual income generating potential—~thus encouraging further expan— sion of farm.operation size. So, in effect, the tenure system could gradually shift towards increased ownership by the investment— oriented nonfarmer . 156 In terms of the general objectives, the present tenure system contributes to efficient resource use. Operation size can expand beyond the typical capital and credit constraints of full-owner operatorship and capture size economies. Likewise, the apparent stability of leasing arrangements is conducive to stability of resource productivity. There is some question, however, of the provisions fOr progress within the tenure process. While facilitating size economies and the inherent application of new technology, there is some evidence to suggest the contrary. A case in point. Landlords in Illinois have “traditionally paid a certain per bushel rate for the tenant to shell ' their share of the corn crop. With the introduction of field shelling, this cost has been incorporated into the tenant's costs. Leases have generally not been altered for this change, leaving the landlord with a windfall and the tenant with less incentive fOr adopting this technological improvement. In the Sosnick framework, this is essentially an example of inefficient exchange, in that standardization of leasing arrangements due to custom.reduces flexibility in adjusting to technological developments. Should landlord-tenant agriculture increase in magnitude, new flaws within.the market process could also develop. Absentee landlordism.could alter the personal infOrmal market relationship and require greater emphasis on legal means. In essence, even though imperfections previously promoted by custom would be reduced, the more formal market setting would place greater demands on such aspects as information networks and price competition. 157 6.2.2 Entry and Exit . The concentration of rental land on larger units raises the issue of accessability. Due to a number of market imperfections, there apparently is much inequality of access to rental land. The existence of tying arrangements in the fOrm of family tenancies discriminates against the nonrelative. The beginning or inexperienced operator who is considered a higherarisk also faces discrimination, since the market rates are often inflexible. Then, too, market misinfbrmation and inefficient rules for trading (little or no open bidding) reduce availability to varying degrees fOr all potential tenants, resulting in access at any point in time being largely by chance. The objective itself of equal access is deeply ingrained in the democratic and capitalistic nature of our society. Hence, deviation is considered undesirable from the standpoint of human rights as well as potential resource inefficiency. Yet, there is a positive aspect to inequality of access; i.e., a gate—keeping function of limiting potential entrants and thereby facilitating farm consolidation and eventually, more efficient organization of the sector. That inequality does injustice to the unsuccessful applicant could also be questioned, in that production practices and technology of today do not allow organization of units in sizes and numbers as those of a few generations ago. If such units were allowed by the market,:many would not be economically viable, and therefore yield insufficient income and returns to the individual's resources. Thus, from the standpoint of the individual's welfare as 158 well as the broader welfare considerations of society, the objective of equal access must be carefully weighed. 6.2.3 'Organizational Impact and Income Distribution Fbr two reasons, the farmland rental process tends to contribute to the objective of greater income equality. First, because of about one—third of the value of farmland being held by nonfarm operators, a substantial share of the returns (annual as well as capital gains on investment) earned in this sector are widely distributed to more than a million resource owners outside the sector. Mbreover, even though farm gross receipts are heavily concentrated among the larger units, these units rely more heavily on farmland rental, which further disperses economic returns. Secondly, the use of farmland rental in expansion purposes allows the individual proprietorship to remain competitive with industrial-type firms that have the advantage of greater capital reserves. This is particularly true within land-based enterprises. The result is the continuing dominance of U. S. agriculture by the individually held farm.firm even though per-farm capital and asset levels have far surpassed the cumulative capacity via individual owner operatorship. Ownership and control of farmland is further dispersed by the process of intergenerational transfer. And as the gap between ownership size and size of operatorship expands, fragmentation of Operating units becomes more extreme. But while contributing to greater dispersion of farm.income and wealth, such fragmentation of viable operating units can lead to inefficient resource use. In 159 Sosnick terms, this could be termed inefficient exchange. It appears that farmfland rental, with respect to this particular resource allocation.problem, is a.mixed blessing. In the case of family tenancies, rental frequently is providing a smooth ownership transition, and continuity of the operation bridges the intergenera- tional gap. But in nonfamily rental agreements, rental can magnify the fragmentation dilemma. Incorporation or the formation of two-generation partnerships are increasingly being employed to maintain a fanming operation, both in terms of owned and rented assets. However, where there is no personal incentive to do so, public policy may need to be considered. This could take the ferm of governmental encouragement of long-term lease contracts much like the European system [11!]. 6.2.1-1 Environmental Issues and the Quality of Life It is becoming increasingly apparent that serious problems are confronting virtually every thread of our social fabric. To consider the mture of the rental institution within the farm sector while ignoring the fact that it is part of a larger set of social—economic factors is folly. Two basic issues bear heavily on the social welfare implications of the farmland tenure system including the rental process. One is population patterns. Excessive population concentrations and decay of urban cores initially come to mind. Farm outmigration has contributed to these present urban ills . But there is also the more subtle but equally severe extreme of social decay in rural areas experienCing population loss [23] .‘ To the extent that rental has 160 facilitated farm consolidation, it has indirectly added to these undesirable states. It has also been detrimental to the rural areas in that income and wealth in varying degrees is transferred away from the economic base of the rural community to absentee landlords. Given these conditions, it is reasonable to at least raise the possibility of future public policy to attain more socially desirable population dispersion. Rural resettlement would be a logical portion. This could result in an altered view of farm size expansion from the now "unlimited" position to one of prohibiting units larger than the levels where major size economies are exhausted. Absentee landownership might also be discouraged under a comprehensive resettlement policy. A second major problem area is environmental constraints which appear to be increasing both in magnitude and complexity. Farmers already are experiencing environmental constraints in the production process and, undoubtedly, will experience more. Simultaneously, policy measures are being taken which atterpt to alter property rights so as to internalize various externalities. Private ownership of land, which once was considered to be virtually free of public influence, is now increasingly coming under public constraints [3, p. 28]. Increased public influence in private land ownership is becoming a "third party" so to speak, in the traditional landlord—tenant relationship. It is reasonable to foresee the rather personal, informal relationship of the present being no longer as functional under public pressure; these limitations may require more complex and legally documented rental relationships in the future. 161 In addition to reacting to these outside forces, it should not be forgotten that the farmland rental process, itself, represents a potential tool for implementing desirable changes in land use. A case in point. Society is becoming increasingly concerned about land in the rural—to—urban transition. Partly the problem stems from the economically and aesthetically undesirable aspects of leap—frog development. Also there is increasing pressure to maintain the inventory of higher-quality agricultural land—which is all to often threatened by urban sprawl . Thus , on two fronts there is interest in establishing green belt areas around urban areas . Various mechanisms for property taxation at agricultural value have been devised which indirectly help to preserve farmland and to discourage disorderly development. However, the success of such efforts is questionable, since high property taxes are only one factor leading to farm liquidation. Possibly equally significant is the fact that farm consolidation and enlargement is much more difficult in these areas due to inflated land prices. Consequently, commercial agricul- ture may largely move out of the urban periphery long before the land moves into the more intensive use. In short, there is a time lag in which farmland will revert to scrubland, and be economically useless and aesthetically unpleasing. A more viable farmland rental market in these transitional areas could do much to improve these conditions. Farmers in need of larger land acreages could then expand via rental instead of relocating in areas of lower—valued farmland . Moreover , in encouraging long- term leases of five— to ten-year terms, public policy could also con- tribute to a more gradual , orderly development process . 162 As land use conflicts intensify in the rural—urban interface, new policy tools must be forged to meet these problems. Most likely, these measures will fall between the one extreme of outright public ownership ani the other of nearly absolute private rights. The rental market process represents Just such a mechanism. 6.2.5‘ Shortages ‘in Today's Setting In a very pronounced way, U. S. commercial agriculture has found itself moving in recent months from the perennial dilemma of surplus to one of shortage. Rising world demand for U. S. farm commodities, due to both short-run and long-run effects, has driven up farm prices dramatically. Coupled with this has been a rapidly developing shortage of fossil fuels—the economic effects of which remain to be seen. In no small way do these recent developments affect farmland tenure. Yet, this new dimension contains both acting and counter- acting forces, leaving the outcome highly uncertain. Hence, only issues can be raised and relationships identified. First, the production side. A series of circumstances have contributed to the demand increase for U. S. farm commodities . Short . crops , new trade ageements , the dollar devaluation—these have been important short-run factors . However, experts also point out long- run aspects of rapid world population increases and rising living starflards (and associated eating habits) of numerous countries. While the short—run causes may change, it is generally believed that world demand is moving upward. For the U. S. farming sector, it follows that farm commodity price relationships have essentially moved 163 to a higher place, and will not return to levels of a few short years ago. In those basically agricultural areas of the country where farmland value still relates primarily to agricultural potential, higher commodity prices tend to encourage land values to increase accordingly. The 13 percent increase in the national index of farm real estate values from March 1, 1972 to March 1, 1973 would support this relationship. While this would be additional incentive among farm operators to purchase farmland from a long-t erm investment standpoint, a counteracting force is the declining ability of producers to achieve high equity levels in their necessary resource base. Given the increase in the proportion of farmland rented over the past twenty years, during which land values rose steadily, it appears the latter force (capital and credit constraints) is the dominant force. And any further rise in real estate values in the future may be accompanied by greater reliance among Operators on rental. On the input side, the impact of energy shortages on land tenure relationships can be studied in terms of input substitution. Historical data on agricultural production over the past thirty years iniicate two important substitution relationships [10, p. 6]. One has been the substitution of capital for labor. The other is the substitution of capital for land. The former, which refers to such substitution as mechanization techniques and fossil energy inputs, indirectly can bear on the land resource and the relationship with other inputs. In short, as noted in the introductory chapter, mechanization and other capital substitutes for labor have encouraged and often times necessitated expansion of farm unit size. The 16“ result has been heavy reliance on rental to expand the land base accordingly. The substitution of capital for land has been no less dramatic. Manufactured fertilizers and pesticides, irrigation, drainage, and improved seed varieties have all contributed to a sizable decrease in the land base necessary for producing a given level of output. Largely this has represented the substitution of one form of energy, fossil fuels, for another, solar energy which land represents. It appears now that shortages of fossil fuels will continue to be a long-term reality and with them the rippling of structural and land tenure adjustments. At the minimum, a slowdown of trends towards mechanization and other forms of capitalization is likely. Even if agriculture was considered a top priority sector of the economy in terms of energy allocation, the cost relationships could still dampen further substitution incentives. This does not neces- sarily mean that a return to a more land-based agriculture is in store for the future. As Connor notes, virgin farmland in the U. S. is essentially exhausted, while farmland continues to move out of production into nonfarm uses (10, p. 8]. Thus, such a trend would represent a cutback in total production—an unrealistic and undesirable outcome given the supply demand situation of U. S. and world food needs . Nevertheless , the price of energy in the form of land and labor inputs relative to capital inputs, which is essentially fossil fuels, will probably be altered dramatically. It is this which appears to hold significant implications .for future land tenure patterns . As the allocative process (either the market mechanism or policy mandate) creates a price increase in the scarce fossil fuels, 165 Ckmamd.for and prices of substitutes will also adjust upward accord- ingly-—including farmland. This will influence annual rents as well as market value. For reasons previously discussed, further price increases may well encourage greater reliance on farmland rental ani thus more aggessive competition in this market. It might also be proposed that the uncertainty which the energy crisis interjects into the longerun economic outlook may in turn reduce the relative weighting of long-run appreciation versus annual returns in the fonm of rents; in short, a higher rent—to-value ratio may develop over time. Specific adjustments may develop in share-rent arrangements. Operator labor, machinery, and fuel inputs have not normally been shared by the tenant and landlord. The tenant may be faced then with (1) significantly higher prices on the fuel inputs he contri- butes entirely and (2) greater need to apply labor inputs instead of purChased capital inputs (example: :more frequent cultivation versus pesticide application). As indicated in the theoretical framework presented on page 99 , these factors will enter into the bargaining process and could result in an increase in the relative share going to the tenant. Shortages of processed fertilizer and pesticides also suggest the necessary lengthening of the rental planning horizon; i.e., more reliance on crop rotations fer soil buildup and pest control would suggest the greater need fer long—tenm rental contracts than now necessary with.00ntinuous cropping specialization year after year. In summary, the present energy crisis suggests that technolo- gical inputs which are land and.labor substitutes may become too 166 expensive to allow the rate of capitalization of the sector to continue. In fact, given the resource availabilities, it may be that the present capital intensity of this sector has proceeded too far; i.e. , technological developments have not fully accounted for either real-world resource constraints or social externalities. Non-marginal change in resource allocation in agricultural production appears imminent. And this will take place in the face of rising world food needs. To the extent that the farmland rental process is flexible an! adaptable, it will contribute to the adjustment necessary 0 6.2.6 The Perspective of the Policy Maker . The man-to-land relationship ani the institutions through which it functions is a key variable within the social fabric of a country. The policy maker in his role as a representative of society cannot ignore it nor belittle it. This study reveals that the consequences of farmland rental, only one facet of the larger relationship, extends far beyond the landlord-tenant level of interaction. Leasing as a means of resource control is significantly integrated with the structural charges which have occurred within the commercial farming sector. Moreover, the implications in terms of conduct and performance exteni into the complex social welfare matrix. The present system is generally satisfactory. Yet, as the implications are drawn more heavily from the total context of social-economic welfare ard less from the more isolated standpoint of commercial agriculture, the future appears to hold an increasing .167 challenge to the policy maker in resolving land tenure conflicts. Comprehensive understanding and continual monitoring of the system will be necessary in order for proper adjustments to be made. Further research into the various tenure aspects will enhance the likelihood of institutional innovations with positive social benefits. APPENDIX 168 Table A.l Farmland rented: acreage, percent of all land rented, percent of rented portion rented by part owners, and percent of rented portion rented from nonoperator landlords, u8 states, 1969.a State ' Percent of Percent of rented and Land in Farm Percent of all land :53 {Swim $133,333,, Regim b rented Total L Rented Apart owners landlords 1,000' acres ......... Percent .......... New filglandc States 5,597 758 13.5 78.1 93.0 New York 10,1189 1,7511 17.3 76.6 90.8 New Jersey 1,036 3139 33.7 58.7 89.0 Pennsylvania 8,900 1.7112 19.6 63.8 87.3 Delaware 6711 252 37 . h 65. 5 98 . 6 Maryland 2,803 519 32.8 51.6 86.7 mm 29,159 5,771! 19. 8 Q7.“ 91 .5_ Michigan 11,903 2,588 21.7 76.2 88.3 Wisconsin 18,110 3,071! 17.0 57.9 71% 1: Minnesota 28,8135 8,981 31.1 62.9 89.3 TAKE SI‘ATES 58,858 1156143 214.9 6h 2 86.0 (1110 17,112 5,970 313.9 58.0 90.6 Indiana 17.573 7,223 141.1 61.0 90.5 Illinois 29,911! 16,255 59.3 l$7.6 91.1 Iowa 33.569 15.329 145.7 ‘43.6 88.1 Missouri 32,1418 8,998 27.8 63.5 816.5 CDRN BELT 130,586 53,775 81.2 52.1 89.0 North Dakota 133,118 16,953 39.3 67.1 91.3 South Dakota 135,581: 15,678 314.14 68.5 90.3 Nebraska 185,839 19,989 143.6 57.6 88.9 Kansas 149,391 25,695 52.0 68. 88.“ NOW PLAINS 183,927 78,315 182.6 6j.’4 89.5 Virginia 10,650 2,126 20.0 69.0 86.7 West Virginia 11,380 5131 12.5 72 2 90.1 North (hrolina 12,733 3,273 25.7 61 1 811.8 Kentch 15,968 2,791 17.2 53 8 79.1 Tennessee 15,057 3,065 20 . U 67 . 1 83 . 7 APPALACHIAN 58,799 11,786 20.0 62.9 83.7 South Carolina 6,992 1,70u 214.1: 75.1 89.6 Georgia 15,806 3,155 20.0 69.1 67.5 Florida 116,032 11,1168 29.6 67.6 79.9 SOJI‘HEASI‘ @1885 124269 211 .L 10 .3 78 . 8 Mississippi 16 ,MO 11 , 388 27 . l! 68 . u 83 . 7 Arkansas 15.691! 5,976 38.1 58.1 83.0 Louisinga 9,789 5232 113.2 63. 81.5 DELTA STATES 1$1,523 19,596 35.2 62.8 82.8 Gdaham 36,008 114,790 111.1 70.15 87.7 Texas 192,567 65,136 115.7 59.0 85.0 33W PLADB 178,575 79,926 “9.8 61.1 85.5 butane 62,918 21,638 314.15 78.5 92.7 Idaho 19,916 5,098 35.“ 70.3 90.“ Wyoming 353”? ”358 l‘0 5 75-“ 93 0 Colorado 36,697 13,937 38 O 716 2 87 11 New Mexico 136,792 18,28“ 39 1 77 7 95 1 Arizona 38,203 11,991 29 9 85 1 97 9 Utah 11,3114 3,973 35.1 90.6 93.7 Nevada 10,709 5,975 51.1 56.2 98.3 WAD: 256,526 99,201: 3px] 16.8 93.1: Wm 17,559 7,717 113.9 72.2 90.7 Or'egm 18,019 5,838 32.18 75.” 92." California 35.723 19.110 53.5 67.1 8L5 PACIFIC 71,301 32,665 185 . 8 69 . 8 88. 5 1:8 sums 1.059.689 397.913 37.5 65.8 88.6 8Source: 1969 Census of Ag'icultune, State Summary Volumes bDerived tron Census data with the assumptions that (1) the rented portion of part-owner farms at the state level is the same for all farms as it is for economic classes I - V farms, and (2) all land rented by part owners and tenants is operated by then and not subleased. cNew mgland States include: Maine, New Hampshire, Vermont, Massachusetts, mode Island, and Cmnecticut. 169 Table A.2 Total value of farm real estate, value of rented portion and percent of total, and value of portion rented from nonfarm landlords and percent of total, 148 states, 1969. 'ibtal ’Ibtal Total State mm mm fhrket and Value of Value of Percent of Value of Percent of Familand and Farmland and Total Value Fannlard and Total Value “351°" mildirgs aiil Rented Bindings Rented iron m, 1970‘1 normed Rented iron Naifam Nonfarm c landlords Landlords m Phillion Milli 92M ___Dollm ___Percent @1139. M New 33131:! States 9 1,803 3111 17.1! 293 16.3 New York 2.772 581 21.0 527 19.0 New Jersey 1,132 1103 35.6 358 31.6 Pemsylvania 3.319 801% 211.2 702 21.2 Balm 336 123 36.6 121 36.0 W 1.793 529 33.“ 519 28-9 m 11,151: 2,112}: 25 3 2,520 22.6 maxim 3.883 923 23. 815 21.0 Hiscmsin 11,201 8112 20.0 626 111.9 mmewts 6,512 2,189 33.5 1,951 30.0 was arm-3 19,597 3,909 21.1 3,392 23.2 Chic 6,819 2,589 9 2.3111 38.3 Indians 7,136 3,115 113 7 2,819 , 396 Illinois 18,6113 8,1335 57.6 7,685 52.5 m 13.733 6,397 '16.6 5,636 111.0 Missouri 7,269 2,370 32.6 2,003 27.6 com m 219,600 22,901 146.2 20,981: "1 1 North Dakota 11,005 1,598 39.5 1.1159 36 1 South Dakota 3,815 1,389 36.1: 1,251: 32 9 Nebraska 7,076 3,2171 175.8 2,881 to 7 Kmaas 7,8712 3,906 119.8 3,1153 km 0 mm PLAINS 22,778 10 L133 an. 5 9,097 39 7 Virginia 3 ,0u7 680 22. 3 589 19.3 west Virginia 8!: 114.3 76 12.9 North Carolina ".2911 1,265 29.8 1.073 25.3 Kmtueiq 11,0111 831 20.6 657 16 3 Maize “.028 910 23.6 761 18 9 gm 15.909 3.770 23.6 31% 19 8 South Carolina 1,827 '475 26.0 1:26 23.3 Georgia 3.701 7.5 20.1 503 13.6 Florida 5.31) 1,205 22.6 963 18.1 Alabana 2,725 6_66 218.13 51w 20.0 300nm 13,23 3,991 2.8 23436 17 9 Mississippi 3,7116 1.1314 30.3 9119 25 3 Arkmsas 11,081 1,803 “.2 1,1497 35 7 new 3mg»; 10,972 11,323 90.0 3.633 33 1 (Idaho!!! 6,21': 2,577 111.5 2,260 36 a Texas 21,170 9,381! “1.3 7.977 37 7 mm mum 27.38;: M1 83.7 10.237 37 '1 Mmtann 3.798 1,227 32.7 1.137 30.3 Idaho 2.5115 39.6 796 31.3 WM 1.885 531 36.7 14911 33.2 Colorado 3,1171 1.3114 37.9 1.1149 33.1 New Mexico 1,959 31! 37.5 698 22.6 Arizma 2.661: 1,213 105.5 1,187 .6 Utah 1. 333 32.0 312 30.0 Nevada 571 35.7 201 35.2 mm 17,1193 6,937 $9 5,971: 311.2 Hashimtm 3.930 1,950 36.9 1.315 335 Oregon 2 .707 802 29 . 6 7131 27 . n California MW 7,816 1111.1 5,967 3§.1 PACIFIC 23,593 9,728 111.2 8.523 3.1 1:8 arms 207.053 AL 39.2 @1102 33.5 ‘hsedmestinnteoofmwvumpmvmodinmmfimof Agriculture. Wumormwmmmmawmsumdimtummmm Value for the rented sham of put-owner land and buildings derived by asamim state pawns values of owned and muted lard are equal; thereform the percent of land acreagemtedcmbeusedasamtwthevaluebreakdomofomedandmted lamlinpart-omerf‘am. Since theabovedataisavailable for Eccnmic ClassesI-V farms only, value and total acreap mud of "otter fame" was assured to be a residual, with the value of rented land in this category auin derived usirg the proportim of acreage rented as a m. c Wmummmmtpemmmofmmtednmmmrmm landlords is identical. Guneqtmtly the percmt oflandacnnse mtednmrmm landlordsisusedtoestimtovalueattheStatelevelandthensimsdtomgions. W States incline: him, Now We, Venmt, ihssaohmetts, Rude Island, and Camticut. 170 Table A.3 Percent of: farm numbers, land in farms, and market value of Land and buildings for economic classes I - V farms, by tenure, 48 states, 1969.a [Percent of Farm Embers Percent of mgr: m Percent of 'notafldaTket b State and Farm Value of land and Bindings Region [REF 1 Part. I F1111 [ Part P1111 Part Owners Omers Tenants Owners Omers 'Degnts Owners Omers Tenants Percent ..... . Percent ..... . . . . Percent ..... New Englandc States 61.9 32.8 5.3 52.3 1414.3 3.14 135.8 119.0 5.2 New York 58.7 35.9 5.3 118.9 146.8 11.3 ‘42.7 149.5 7.8 New Jersey 57.3 28.11 111.3 38.5 115.7 15.7 35.8 115.14 18.8 Penmylvania 60.5 29.6 9.9 50.7 141.0 8.3 1114.1 163.14 12.11 Delaware 55.1 31.” 13.5 31.7 511.9 13.11 35.2 50.1 114.7 M13111 57.6 25.5 16.9 112.8 39.5 17.7 141.9 39.5 18.7 mm 59.6 31.6 8.8 118.6 1114.1 7.3 112.5 115.6 11.9 Michigan 59.8 311.0 6.2 ‘16.8 167.11 5.8 113.0 119.7 7.3 Wisconsin 68.5 23.7 7.7 60.2 32.1 7.7 53.9 36.11 9.7 Minnesota 511.9 32.1 12.9 111.5 116.3 12.2 39.0 136. 111.2 A.“ STATES 60.9 29.5 9.6 118.2 142.1 9.5 “'4-3 W.“ 11.31 0110 53.1 31.6 15.3 38.1 145.1 16.8 311.1 117.1 18.8 Indiana 51.3 33.18 15.3 33.9 118.6 17.5 30.1 50.5 19.3 Illinois 37.5 313.2 28.13 211.7 l$6.0 29.16 21.6 185.3 33.1 Iowa 186.2 27.8 25.9 311.14 39.3 26.3 31.5 140.2 28.3 Missouri 61.0 27.9 11.2 118.1 no. 11.2 111.0 113.9 15.1 (DEN EILT 148.9 30;] 20.14 35.6 113.1 21.3 29.8 1411.6 25.5 North Dakota 35.1 51.1 13.7 25.0 611.5 10.5 211.18 611.1 11.5 South Dakota 33.6 119.2 17.2 21.0 68.2 10.8 22.7 611.1 13.2 Nebraska 311.5 110.2 25.3 22.0 59.7 18.11 22.0 55.3 22.6 Kansas 31.5 169.8 18.7 17.1! 66.5 16.2 18.1 65.5 16.11 mm PLAINS 33.5 117.1 19.10 21.2 611.7 11!.2 21.2 61.8 16.9 Virginia 57.6 31.2 11.2 51.5 111.11 7.1 116.8 1111.3 8.9 West Virginia 69.7 25.6 18.7 61.2 311.3 14.3 56.9 6.; 6.1! North Carolina 116.8 31 n 21.8 145.0 2. 12.2 37.9 5. 16.5 Kentuclq 66.6 21 1 12.3 62.2 28.0 9.8 56.6 30.8 12.6 Tennessee 63.; 27.18 9.1 511.2 _37.6 8.2 143.14 181.6 10.0 APPALACHnN 58 5 27.3 111.2 514.2 36.7 9.2 117.6 110.2 12.2 South Carolina 145 2 8.5 16.11 112.2 51.3 6.6 38.0 53.5 8.5 Georgia 60 8 28.2 11.0 53.1 110.2 6.7 51.6 111.6 6.8 Florida 73 0 19.5 7.5 52.3 37.8 9.9 63.7 27.9 8.“ Alabama 6 33.5 9.9 45. 117. L2 “L0 168.8 8.2 301mm 59.14 29.7 10.9 5.6 153.6 7.8 53.5 49.5 L2 Mississippi 56.0 33.9 10.0 I10.6 '19.“ 10.0 36.6 51.0 12.18 We: 52.2 30.9 16.9 36.7 135.1 18.3 30.2 '17.0 22.8 Imisiana 180.2 39.8 20.1 £2 50.8 17.0 27.8 50.5 21.] IELTA STATES 50.; 311.1 15.18 37.0 148.1 15.0 j1.6 ’19.3 19.2 cannula 111.0 ‘13.9 15.1 26.2 61.7 12.1 25.7 61.0 13.3 Texas 113.7 36.6 19.7 28.2 2.8 19.0 29.0 51.5 19.” 301mm PLAINS 112.9 38.8 18.3 27.8 511.5 17.7 28.3 53.7 18.0 humane 36.18 52.0 11.7 15.8 76.6 7.7 21." 70.5 8.1 Idaho 53.9 311.3 11.8 29.6 61.1 911 3u.9 53.1: 11.7 Wyoming 36.6 139.6 13.8 8.8 82.7 8.10 16.11 711.16 9.2 Colorado 162.6 110.6 16.8 20.5 69.7 9.8 27.3 57.8 113.9 New Mexico 140.2 “6.5 13.3 15.1 711.9 10.0 22.3 65.9 11.8 Arizma 119.0 36.0 15.1 6.5 83.8 9.7 20.2 61.14 18.11 Utah 511.5 no.0 5.5 25.1 72.1 2.8 35.7 60.2 11.2 Nevada 69.1 23.14 7 ll 19.6 56.16 211.0 183.6 113.0 13.1! MAIN 1111.8 “2.5 12.7 16.1 ju.6 9.3 25.8 62.13 11.8 Wm 55.7 33.3 11.0 17.9 68.0 114.1 33.2 53.1 13.7 (h‘egm 60.3 31.11 8.3 30.1% 62.5 7.2 38.5 53.1 8.“ California 62.6 23.3 114.1 23.2 59. 17.8 37. M. 17.6 PACIFIC 60.6 27.1 12.3 23.8 61.9 111.3 37.0 l[7.0 16.0 “8 STATE 50.8 33.5 15.6 28.8 57.5 13.7 33.14 169.3 17.3 aSource, 1969 Census of Agriculture, State 3mm Volunes, Table 211. bPercentays may not add to 100.0 due to munding. °Neu 313mm States include: Me, New Hmpshue, Vemmt, Massachusetts, Rhode Island, and Connecticut. 171 Table 11.9 Average farm size and average market value of land and buildings per farm for economic classes I — V farms, by tenure, 98 states, 1969.a Market Value of [and and State and Avefimeime Buildings r Farm Region Full - —— A11 1 Part A11 Omar Odned Rented | Total 'Ilenant Farms Omar Owner 'Denantj Fams .......... Acres.......... ......¥1,00....... New Ward) States 202 230 92 322 153 238 57.1 115. 9 75. 5 77 . 1 New York 203 213 109 317 199 293 98.5 91.9 27.1 66.7 New Jersey 105 128 123 251 171 155 109.0 266.2 218.9 166.9 Permaylvania 198 152 93 295 198 177 50.9 101.5 86.9 69.2 Delaware 127 203 183 386 219 221 70.1 175.5 100.1 109.9 Mland 159 165 156 321 217 207 95.5 203.2 195.2 131.9 NORINEASI‘ 172 188 106 299 176 211 58.6 118.9 111.6 82.2 Michigan 162 165 129 289 192 207 99.0 99. 3 79. 7 68. 0 Wisconsin 182 185 95 280 208 207 38. o 79.0 60 . 6 98. 3 mm 229 235 193 928 279 297 98. 3 98 . 8 79 .7 67 .9 LAKE STATES 199 203 197 350 296 295 99.2 91.6 71.2 60.8 Ohio 150 190 157 297 229 209 59.5 126.2 109.0 89.8 Indiana 152 199 192 336 263 230 59.9 191.6 117.9 93.5 Illinois 187 159 222 381 293 283 79.9 189.0 162.1 138.8 Iowa 196 178 193 371 266 263 70.0 198.7 111.9 102.8 Missouri 297 230 227 957 319 313 97.8 111.9 J60 71.0 00101 @T 192 171 201 372 275 269 61.9 196.5 125.8 100.6 North Dakota 691 702 529 1,226 795 972 65.9 118.1 78.6 99.2 South Dakota 611 830 527 1,357 613 978 59.0 113.7 67.0 87.3 Nebraska 998 598 998 1,096 512 705 68.7 198.0 96.2 107.5 Kansas 381 913 511 929 597 692 62.0 192.5 99.7 108.2 NORIHEBN PLAINS 508 603 501 1,109 587 809 69.2 133.0 88.9 101.3 Virginia 228 200 138 338 162 255 59.9 109.6 58.5 73.7 West Virginia 305 289 189 968 318 397 39.7 69.7 65.6 98.6 North Carolina 190 108 90 198 81 195 39.0 67.0 36.5 98.2 Kentucky 177 197 109 251 151 190 92.3 72.7 51.2 99.8 'I‘ernessee 185 153 199 297 196 217 93.5 86.5 62.7 57.0 APPALACHIAN 182 198 116 269 127 196 99.2 80.1 96.8 59.9 South Carolina 279 222 176 398 120 299 63.6 105.2 39.9 75.6 Georgia 293 285 195 980 209 336 69.8 112.8 97.2 76.9 norm 959 539 687 1,226 835 633 195.9 320.2 299.8 223.8 Alabann 269 256 216 972 299 J3“ 98.9 92.9 52.7 63.8 30mm 323 299 260 559 271 386 91.0 131.9 119 101.0 Mississippi 316 337 299 636 932 936 68.5 157.7 129.7 109.9 Arkansas 267 299 313 557 913 381 60.9 158.8 191.0 109.9 Imisigxa 3_27 209 312 521 495 908 88.1 161.7 137.5 127.3 mm 3191335 297 265 308 573 395 906 68.9 159.3 137.9 110.2 qualms 393 928 938 866 995 616 65.2 199.7 92.3 109.2 lexas 696 718 838 1,556 1,090 1,078 100.0 212.1 198.2 150.5 301mm PLAINS 609 619 703 1,322 906 990 90.1 189.2 139.9 136.6 Mzntana 1,219 2,616 1,513 9,129 1,890 2,802 98.5 226.9 115.9 167.0 Idaho 357 658 999 1,157 515 650 77.1 185.2 118.9 119.0 Waning 1,038 9.370 2,819 7,189 2,629 9,303 82.5 277.9 122.8 189.7 Colorado 760 1,586 1,135 2,721 922 1,583 93.8 208.9 129.5 196.5 New Mexico 1,839 9,066 3,832 7,898 3,696 9,902 115.3 295.9 186.0 208.9 Arizona 539 3.172 6,219 9,391 2,596 9,032 182.5 756.5 539.9 992.8 Utah 521 1 ,191 899 2 .035 577 1 ,130 66.9 153.9 77 .9 102.1 Nevada 1.699 6.019 7.960 13.979 18.669 51802 198.? 579.1 567.1 315.2 WNTAIN 826 2,267 1,783 9,050 1,685 2,309 95.6 299.5 159.1 166.3 Washingtm 215 653 711 1,369 860 669 88.2 235.6 183.9 197.8 987 1,123 798 1,921 837 967 85.9 226.2 136.5 133.9 Califomia 239 591 1,003 1,599 798 6L0 173.2 555.9 360.6 288.7 PACIFIC 276 722 875 1,597 816 701 138.8 393.9 295.9 227.3 98 STATES 299 “IL 933 906 963 528 (3.9 151.9 119.5 103.3 8Source: 1969 Camus of Agriculture, State Suntan] Volunes, Table 29. WW Blgland States include: mine, New Harpshire, Vermont, masachusetts, Rhode Island, and Connecticut. 172 Table A.5 Average per farm.value of agricultural products sold and distribution of total receipts for economic classes I —'V farms, by tenure, by farm production regions, 1969.a 3 Average market value of all : Percent of total Region ';;agricultural products sold : market value ; Full :Part ' All fFull fPart : : owner 'owner ’Tenant farms owner 'owner 'Tenant E . . . . . $1,000 ..... . . Percentb . . . Northeast . . . . Q 29.0 38.7 27.9 29.9 99.9 92.2 8.3 Lake States . . . Q 15.2 26.1 19.1 18.8 99.3 90.9 9.8 Corn Belt . . . . Q 16.5 31.7 25.1 22.9 35.2 92.5 22.3 Northern Plains . Q 21.5 31.9 21.6 26.9 27.3 56.8 15.9 Appalachian . . . Q 11.9 20.0 13.2 19.3 98.8 38.2 13.0 Southeast . . . . Q 27.2 36.6 29.3 29.7 59.9 36.6 8.9 Delta . . . . . . Q 22.2 30.3 26.1 25.6 93.9 90.5 15.7 Southern Plains . Q 21.9 28.1 21.3 23.9 38.2 95.9 16.3 mountain . . . . Q 39.3 99.9 93.7 98.3 31.9 93.9 29.7 Pacific . . . . . Q 39.7 89.5 82.9 55.5 37.9 93.8 18.9 98 States . = 20.1 33.9 27.8 25.9 39.9 93.9 16.8 8Source: 1969 Census of Agriculture, State Summary Volumes, Table 29. bPercentages may not add to 100.0 due to rounding. 173 .3 Soon. .893, Dan Baum funded! as 888 $2 "gems e.na o.nfl a.mom a.ma a.mn m.am O m.ha m.wm a.mau a.ma m.m: Ni 00 so do o. 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H.m a.ma o.o>m m.» m.o~ m.mwm m.oa m.am m.~mw m.ma ~.~m m.mmm a.mm m.w~ a.mam «.ma m.ma o.m o.mm a.mm. m.» m.~= a.mzm m.m o.m= m.~am a.ma a.ma m.pmm =.om m.om m.mmm ~.ma a.ma m.m o.m~ a. wow ~.~H a.o= =.wam a.mH a.ma ~.wwm H.- 5.3: ~.mmm a.mm a.mm N.mmm o.co m.~H 3. «é méw v.3 Em 3mm EH 3m 9.9m ...: 19. ...sz 3m can 5mm 3.: 9w ~.m a.mH m.>~M o.m o.om o.~mw m.m ~.=m m.mmm a.ma w.mm m.amm m.m~ w.mm m.~am a.mm H.=~ m.o ~.:H Hump” ~.oa o.o~ a.mmm a.ma m.~m m.=mm 5.0H m.=m a.mam m.m~ m.om w.o:m ”.3: o.o~ E ...m a.mmm 0.3 3... «.3 3: 3m 3m 0.2 3H. sum 3: 9% $1 33 3: m.» ~.mH a.mhm a.ma H.om a.mmm F.5H =.~m a.mzm m.m~ m.~m m.mmm m.mm a.mm m.~mm s.om H.=H m.~ m.ma a.mmm a.= a.mm m.ohw m.o a.mm H.oom H.HH a.hm m.amm H.=~ a.mm a.mam =.m= m.m~ m.~ H.o~ a.hs. ~.m =.a~ ..m.mmm ~.m o.mm a.mmm H.HH a.~m m.amm a.mm m.~m a.mam m.mm ~.o~ ”can. 0 o o 0%: coamom soaposcopa Sham an nmEhmm >.| H mmmmwao vagacoom pom nonmammo mo mwm mp moapmfiumemumno madame m. ¢ manwe «.83 £2me 1377' Table A.10 Percent of land in farms rented by age of operator for economic classes I — V farms, #8 states, 1969.a State and Percent of Land in Fazmxs Rented Region as than 12:3 [25'3“135-‘1‘3[MS-EuJfi-flLfiormore .............. Percent............ New Wb States 39.3 28.3 17.9 16.0 13.2 8 9 New York 38.7 30.2 23.3 18.9 15.14 10.9 New Jersey 76.9 62.2 136.8 36.8 28.6 27.0 Pennsylvania 148.0 39.8 28.7 23.2 16.5 11.3 Delaware 185.5 56.1! 51:.5 36.1 28.8 27.1 ‘flggzlgpd 63.9 62.8 u8.u 36.5, 27.2 16.9, mm “5.2 11.8 28.0 22.5 17.“ 12.3 Michigan 511.9 115.3 32.0 214.6 20.9 11.7 Wiscmsin 118.8 35.2 22.2 16.2 11.0 7.0 Minnesota 611.6 53.6 39.7 31.1 21.5 15.1 IAKE START) 57.1 166.7 33.0 fij 18.3 11.8 0110 71.2 59.6 50.2 140.18 30.11 17.5 Indiana 76.“ 63.1% 53.0 145.5 313.9 20.3 Illinois 80.6 73.6 66.14 57.5 145.6 29.0 Idwa 78.7 68.5 56.1 135.2 32.0 17.8 Missouri 61.3 452.2 no.2 32:; 23.7 12.2 CORN BELT 714.2 611.7 516.3 ‘“4.9 33.3 184 North Dakota 66.8 61.5 186.1 35.3 27.3 18.7 South Dakota 68.7 57.5 115.6 36.1 27.6 21.7 Nebraska 71.7 65.1 56.3 “5.1 31.11 21.6 Kansas 79.3 J0.L 63.8 55.9 "3.8 33.2 NORI‘HEPN PLAINS 71.7 63.9 53.1 “3.6 33.2 211.8 Virginia “2.9 112.1 33.“ 26.9 19.1 11.4 West Virginia 30.0 3‘4.5 25.8 18.8 118.5 9.“ North Carolina 53.6 53.1 ‘‘25 33-6 214.2 11.9 Kmtuclq 136.5 39.1 29.0 21.7 16.2 7.3 Tennessee 116.2 “5.2 35.5 28.0 22.1 10. APPALACHIAN 146.5 1814.0 3U.5 27.0 19.9 10.0 South Carolina 36.8 145.1 39.2 31.9 23.11 12.1 Georgia 147.7 131.8 32.9 22.8 17.7 9.1 Florida 713.“ 139.8 38.7 30.“ 25.9 21.0 Alabama 51.5 115.5 35.3 31.9 26.0 118.0 SOUD‘IEAST 59.1 185.6 36.2 28.6 22.9 15.0 Mississippi 149 . 5 no . 9 132 . 5 31! . 6 28 . 2 17 . 0 Arkansas 66.9 63.8 53.0 143.1 36.0 21.1 Iouisiangr 75.0 67.2 59.5 146.9 181.8 26.2 ETA STA'EB 63.8 61.2 51.0 141.0 318.5 20.7 Oldahana 72.6 62.1 53.8 145.3 37.“ 25.9 'Dexas 22.0 616.7 59.7 “8.3 "5.1: 32.5 SQHHEIW PIADB 72.2 611.2 58.16 137.7 163.7 31.“ Montana ”7.9 "8.5 '43.1 36.7 29.8 23.2 Idaho 72.5 51.5 39.8 35.0 31.0 31.1 Wyarung 21.9 52.8 148.6 “3.5" 36.3 29.8 Colorado 166.5 50.3 147.6 140.3 314.3 25.7 New Mexico 57.9 515.6 50.2 168.0 ll7.8 35.0 Arizona 3&8 71.1% 6h.l 68.1% 62.6 61$.9 Utah 20.7 58.8 3K6 33.5 313.1 27.7 Nevada [2.9 36.8 75. MI. 57.” 31.9 DOMAIN 188.1 52.5 99.1 “2.7 38.6 32.5 Washington 69.6 69.2 55.5 52.7 151.9 31.8 Q‘egon 50.6 132.13 40.9 3&2 28.3 24.? California 72.2 66.13 65.0 57.0 50.5 “5.” PACIFIC 68.0 60.2 56.5 50.0 “3.2 38.18 as smmras 6u.6 58.1 u9.8 u1.7 3u.3 26.8 aSource: 1969 Census of Agricultm‘e, State Sun-nary Volumes, Table 25. Calcu- lated asstming all land that is rented by part dimers and tenants is operated and not subleased. bNew England States include: Maine, New Harpshire, Vemmt, mssacmsetts, Rhode Island, and Comecticut. 178 58me do 5.5 $30 $56.50..” 3 86 0.03 on com 90: a: mmwwufiopomo .om magma. wot-5H3? 535m 33m .93ng“? no 05:8 moofl "gown ad: dma a.ma mid dm m.m m.m N.N NJ. :.o do 0 . . . $995 w: 9mm 3?: w.» m.: m.o 0.4” NJ da m.o 0.0 dd 0 . . . . . 0523mm a.mm m6 3.: N.N :.o m.o m.o m.o N.o do do 0 . . . . a»; dam ~41” a.ma 5m :4 N...” n4 ~30 2.0 do do dmm a.mH o.mm oSH 5m Wm ozm dm o.N do 0.0 . 23a 52.58 . . . . . . 325 ...mm 5: 2.: 3: ~.m mam aim m.m am 04 HA . . . .pmmfipam . . . 53% . madman 593.32 0.0 do m.mH m.:m do mg. m.m m6 :.m m.m m.m do a.mm N.mm m.mm a.ma 04 mo 04 m.o m.o min m.m a.mm 3.0m m6 m.» m.m o.m w.m m.o m.o . . . . uHomEoo m.m m.m NSH 3.3m wd do dd” m6 dm mo m.o do . . . mongm 03mg m.~ km 3.: 9mm Nam ma dm 2 3.” m4 m4 fio . . . . 682.82 0 o o 0 O O O O 0 0 O o o o o o O o 0 o o O o pcgmnw 0 o o I o O o O O O O O O 0 0 O I O O O aged " mgow " meow " meow u aged u monod ” meow u mWHow " mohod u mvuom u $80.0 u meow £8 .8 " mam; " m8 " mm: " Rm " Sm ” a: u m2 “ mono» ” 818 u 91: u m .. H 83.8 ooo.~ "-80; a -Sm " -08 " 6mm “ no? u -9: u -03 u n u “ b 95mm 5 6:3 mo £683 «.83 €04..on 8.33608 Shaw .3 £58.“ > I H momma? odaosooo mo 330 Sam mwmoaow .3 gm 5 98H mo soapsoamumfio ucoohom ado magma“. 179 Ill .8 633. .855. gm 83m .gugog go 888 8% “856m... 93m o.m=~ H63 a.moa a.me 93 min mam: a.mm mom mdm mtnm . meadow. m: m.omH.H 2mm: m.mmm Hémm v.38 H.5H ~63 5.9: a.mmH p.02 a.mh Q13 . . . . . 3.33m 29. ~63 mama 3:: 3.8 3.5 oi. mam ...mm «.3 3.9. m.~m . . . . 8658. was ...mmm «53 fig TS m.mm do: a.mm 5mm mam 0.3 3: . 238 E838 mama a.mmm dam: a.mm 9% mdm 9m: 0.2m mam a.mm mam mg . . . . . . 8H8 :.emH.H a.mmm m.mma a.mm m.:m a.mm a.mz :.o= a.mm m.am :.nm a.mfl w . . . . unaccusom ma: 0.8m 93H Now 3.8 9% 9m: a.mm mam a.mw mam 92 . . . 525392 aim mama ”.9: 9m. 0.8 9% ...mm ~.mm a.mm mam 92 9d . 93m 523.82 mama 9mm: 3%. mama #8 ....i. a.mo mm? mam Tam wow 13 . . . . £3 58 «AR. «.mmm ....mi 5? 0mm 3.3 0.9 gm 3m m.mm Ham 3m . . . 633m 83 993; came 3.3 32 9: ...m» ...me mém Tom on? 33 mam . . . . pfimnfioz . . . . . . . . . . . . . . . . . . . . . . . o8.g . . . . . . . . . . . . . . . . . . . . . . . m mace no" .8 moms? 8.89 8.8.9 moped" mmpom” motes" 898 u 8.8.» " 8.8m u meow u ago... 0 .8 . u no 0. “mmmuoom"mmfiomwummmnomm"menomdmzuofiamToS ” 3.2. " 3.8 u 9.3 u n a H m 8&2 52.8.8 EVE... 6585.2 no SEC. mfiaFomega 1 wow? 60%.?“ 83360.8 :53 .3 mafia > I H 8330 35988 ...8 $30 $3 mommmpom .3 Emu Loo wwfioHHdo QB onHefiwm .Ho 63.9 33.8: mwmpoé mH.< 3nt 180 Table A. 13 Percent of land in farms rented by acreage size class of economic classes I — V farms, by farm production region, 1969.€11 State 9 Percent of Land in Farm Rentedb ' ard WTW‘oo-i 1 179 [“81 0-219 220-259 I 260-999J 500-999 1,000— 2,000 acres Mn Ecres acres acres acres acres icres 1,999 ac. or more ..... Percent New Mani States c 16.9 15.8 16.7 17.0 16.5 16.9 19.3 10.5 New York 13.9 19.3 16.9 17.9 20.7 29.9 23.5 28.3 New Jersey 26.5 29.2 92.5 92.9 95.9 98.9 52.8 38.1 Pennsylvania 18.9 21.1 29.2 29.7 26.9 27.2 33.0 20.9 Delaware 26.3 31.6 33.3 38.1 91.1 99.0 52.9 23.5 mm 23.5 29.6 30.1 33.7 39.9 95.1 98.9 99.2 mm 18.1 19.6 21.6 22.3 29.1 27.0 29.9 $2 Michigan 22. 9 17.5 21.6 22.9 31. 9 38.7 36. 9 ~ 39.6 wiscmsin 11.5 13.7 17.0 18.7 21. 5 25.9 27. 7 35.0 Mimeeota 15. 2 19.2 21.5 27.8 39. 7 90.7 93. 5 99.9 1.9103 smog: 15.2 16.7 19.6 23.8 30.3 37.9 90.3 95.6 Chio 22.6 27.0 a 39.1 39.6 98.8 55.6 51.7 96.7 Indiana 21.7 27.9 39.5 91.9 52.9 61.3 55.8 26.8 niinois 29. 9 90.9 95.3 53. 7 62.5 65.0 58.1 92. 2 Iowa 29. 2 39.6 38.9 95.1 52.8 59.1 97.1 36. 0 Missouri 15. 0 17.6 20.3 22. 2 30.2 90.2 91.3 35. 6 00m asur 22.8 90.9 35.2 91.9 50.9 J“. 2 98.5 36.9 North Dakota 95.8 32.3 36.0 30.6 31.9 35. 6 90.8 39.8 South Dakota 35.2 31.6 36.1 37.6 93.9 92. 7 37.9 33.8 Nebraska 35 9 38.1 93.1 97.1 51. 8 50. 3 96.5 37.6 Kansas 31. 9 29.3 38.2 37.5 96. 6 59.8 J77 55.7 Norman: PLAINS 39.3 33.6 39.8 91.3 95.6 96.1 96.1 90.5 Virginia 20.0 20.2 21.9 22.5 25.0 27.1 28.2 19.1 West Virginia 11.8 11.2 11.8 16.0 17.1 20.0 22.7 17.8 North Carouna 30.9 29.9 32.6 32.6 39.5 39.2 32.7 17.5 Kentucky 19.2 16.8 17.7 22.0 23. 8 28.2 31.8 26.1 Messee 16.9 18.7 20.2 21.5 26.1 33.7 91.1 39.3 APPALACHIAN 19.8 20.6 21.9 23.9 26.3 294 3_2.3 29.8 South Caronna 28.6 27.9 28.8 28.8 29.0 31.1 32.8 29.3 Georgia 22.3 21.9 23.1 23.3 29.8 26.0 25.5 17.1 Florida 17.9 16.7 19.1 17.6 22.2 25.1 30.2 35. 5 Alaban 25.8 29.9 27.0 30.9 31.3 33.2 2.9 25 7 __ mm 21.7 22.7 29.6 25.6 26.9 28.7 29.5 29.8 mssissippi 20.2 20.2 21.6 23. 9 28.6 39. 7 91.9 36.9 Arkansas 26.7 28.9 31.7 35. o 92.1 50. 5 52.5 99.0 Louisifl 3L] 39.9 95.9 95 9 52.] 58 9 53.2 38.9 DELTA SI‘A'IES 27.2 28.2 31.5 33. 9 90.0 97. 2 98.7 39.5 Gamma 28.1 29.8 31.3 32.7 90.2 96. 3 98.1 93.9 'Dexas 30.1 33.1 35.2 92. 3 99.0 50.1 50.2 98.7 301mm PLAINS 29.6 31.9 39.2 39.0 93.47 98.9 99.6 98.3 mm 2707 2305 3209 2900 3103 3309 3505 3603 Idaho 29.2 30.9 32.3 30.7 31.3 32.8 35.6 39.1 waning 29.2 30.8 36.8 35.8 29.5 36.2 39.9 91.8 Colorado 35.5 35.0 99.9 90.8 39.3 37.9 39.1 39.2 New Mexico 30.0 31.7 33.3 38.5 37.9 90.2 38.3 97.2 Arizona 31.8 28.6 33.3 31.8 90.8 91.3 50.0 67.2 Utah 22.9 23.1 29.2 23.1 22.9 22.0 26.1 38.1 Nevada 20.0 51.9 50.0 50.0 52.0 50.7 52.5 50.9 mm 29.0 31.0 39.9 33.9 39.0 35.5 37.0 93.9 Vhshirgtcn 22.0 20.5 25.3 29.7 39.1 96.9 53.9 59.6 Oregon 20.0 21.3 29.7 25.0 29.2 32.1 35. 5 39.7 Califmnia 31.9 35.5 39.8 39.2 95.8 50.2 51.9 59.6 PACIFIC 26.9 27.8 2.0 31.8 38.9 95.3 99.2 52.0 98 States 21.9 26.0 28.9 33.8 90.5 99.6 99.3 99.3 aSource: 1969 Census of Agriculture, State axillary Volumes, Table 26. Calculated assmnirg all land that is rented by part owners and tenants is operated art! not subleased. bUnits of less than 100 acres were excluded due to (1) wall percentage of land represented by these farms (2 percent in the We) and (2) the anbigiity of land leasing amng these size classes; i.e., m small units are leasing land and, in tum, subleasing. cNew England States include: Mme, New Harrpshire, Vennmt, Massacmsetts, Rhode Island, and Correctiout. 181 Table A.19 Land in farms by economic class and distribution of land among economic classes, 98 states, 1969.a g—ate and 1 ' Land in Fame I Percent Distribition or Land Classes goon [I I II T 1 IV I v I I T—IT—‘I—‘m—ILmifi—I—V— ........... 1,000Acm........ hment New and States 1,989 1,376 769 916 397 33.9 31.0 17.2 9.9 8.9 New York 2,337 2,878 1,678 808 671 27.9 39.9 20.0 9.7 8.0 New Jersey 91 193 102 82 86 97.1 22.0 11 6 9.9 9.8 Pamymhia 1,995 1,979 1,966 965 879 21.5 29.3 21.8 19.3 13.1 Deiam 316 110 80 67 99 50.8 17.7 12.9 10.8 7.9 Miami 867 570 351 330 256 36.1 23.7 15.8 13.7 10.6 mm 6,8_62 7,101 9,971 2,668 2,338 29.3 30.3 19.1 11.9 10.0 Michigan 1,719 2,096 1,968 1,779 1,587 18.8 22.9 21.5 19.9 17.9 Hiscmsin 2.393 9.737 9,779 2,588 1,997 15.0 29.7 30.0 16.2 9.1 mmesots 9,601 7.368 7.518 9,999 2,939 17.9 27.9 28.5 17.0 9.2 we 3191115 8,713 19,201 19,260 83856 5.973 16.9 27 6 27.7 17.2 10.6 0110 2,692 3,999 3.151 2,592 2,091 19.1 29.9 22.8 18.9 19.8 Indian g,989 9.193 3.320 2,309 1,690 25.7 27.1 21.9 19.9 10.9 minois .981 8,821 6,013 3,033 1,615 31.6 31.0 21.1 10.7 5.7 Iowa 1' .316 10,505 7,076 3,203 1,368 31.8 32.9 21.8 9.9 9.2 Hisscuri 9,908 6,011 6,920 5,191 9,2_6_0 18.1 22.2 23.7 20.3 15.7 com EEL'I‘ 301836 32.979 251980 16.573 10.979 2_6.3 28.1 22.1 19.1 9.9 North Dakota 6,085 12,991 19,065 5,932 1,852 15.1 30.8 39.8 19.7 9.6 South Dutota 12,109 12,608 9,697 3,769 1,957 30.6 31.9 29.9 9.5 3.7 Nebraska 17.762 12.115 9.069 9,095 1,668 39.8 _ 27.1 20.3 9.1 3.7 Kansas 19359 12,368 11,235 6,931 3,007 30.1 26.2 23. 13.6 6.9 mm PIADB 50,205 99,532 99,0115 20.177 7.989 29 2 28.8 25.6 11.7 9.6 Virginia 1,889 1,917 1,970 1,699 1,506 23 8 17.9 18.5 20.8 19.0 west Virginia 255 335 913 610 701 11 0 19 5 17.8 26 9 30.3 North carouna 2,907 1,990 1,912 1,769 1,519 25 2 20 3 20.0 18.5 15.9 Kentuclq 1.575 1.832 2,500 2,990 2,636 . 13.7 15.9 21.7 25.9 22.9 Tumssee 1,562 1,603 1,858 2,931 2,603 15.5 15. 18.5 29.2 25.9 APPALACHIAN 7,683 7,127 8,153 9,999 8,960 18 6 17.2 19.7 22 8 21 7 South Carolina 1.732 996 872 798 810 33 3 19.1 16.7 15 3 15 6 Georgia 9.615 2.557 1.995 1,837 1,691 36.5 20.2 15.8 19.5 13.0 norms 7.556 1,658 1,296 1,090 1,118 59.9 13.0 10.2 8.6 8.8 Alston 2.857 1.905 1.799 m9 1.733 g8.8 19. 17.6 16.9 17.5 summer 16,760 7,116 5&1 5,399 5.302 91.9 17.6 19.6 13.3 13.1 Mississippi 9,770 1,879 1,657 1,691 1,873 90.9 15.9 19.0 13.9 15.8 mites 5.290 2,190 1,813 1,772 1,823 90.8 17.1 19.1 13.8 19.2 Iouisisna 3.767 1.997 11.146 ,8_82 916 96 0 18.3 13.8 10 8 11 2 IELTA sum 13.777 5.599 9.51 3.295 9.612 91.9 1619 19.0 13.1 19 0 mm 8,179 6.557 7.131 5,822 9,163 25.7 20.6 22.9 18.3 13.1 'nexas 99 2 012 1 961.0 17.1 15,0 11.6 9-1_ 12 9 26 688 20 9 92.0 18.2 16.5 12.9 10.9 m“ 27.337 15.835 9,629 3,913 1,525 97.3 .9 ' 15,7 5,9 2,5 Idaho 6,153 2,871 2. 1,017 596 98.6 22.7 16.5 8.0 9.3 Hyanirg 19,995 5,953 3,312 1,999 682 69.6 17.7 10.7 9.8 2.2 0o1orado 15,188 7,288 5,990 3,269 2,099 95.0 21.6 17 6 9.7 6.2 New Mexico 22,723 6,195 9,370 2.585 1.971 60.1 16.3 11 6 6.8 5.2 “PM 11.935 2.108 1.537 1.139 932 66.7 12.3 9 0 6.6 5.9 Utah 9,986 1,690 1.370 860 609 52.9 17.8 19.9 9.0 6.9 we 5.909 899 1.129 321 922 69.3 9.2 12.3 9.3 10.0 MIMAIN 113,676 92,239 22.3é1 19,163 9,276 59.5 29.2 19.1 6.8 9.9 Hashingtm 6.751 3,599 2,399 1,139 735 96.3 29.7 16.1 7.8 .0 098801 8.933 3.913 2,179 1,117 792 59.9 20.8 13.3 6.8 2.8 0a1iromia 221632 9.592 3% 1.998; 1.907 66.5 13 3 9.0 5.6 5.6 $11710 3_8,316 11.559 7,599 9,159_ 3,939 58.9 17.8 11.7 6.9 5. 3 98 31mg 359.951 206,212 111.02 106,661 15,191 38.8 22.6 18.1 11.7 8.2 8Source: 1969 Gums of Moultun, State W Velma, m1: 2?. New England States include: “no, M W, Vemmt, Wu, Mode Islmd, and Cormticut. 182 Table A. 15 Average acreage size and average market value of land and buildings, by economic class, 98 states, 1969. a Averagefiket Value of land 2:33.13“ Ave Farm Size and mild Per Farm 1 II 1 III IV V v I T II I ' 11181; T—W_I'_V"" "' ......... Acres........ 71000 New land States 351 266 192 158 152 138.9 75.3 51.9 98.8 99.3 New York 912 279 205 153 139 155.9 61.9 99.8 38.9 90.5 New Jersey 299 150 105 89 79 290.9 168.9 119.8 107.1 99.9 Pennsylvania 300 202 163 135 118 160.5 77.9 59.0 95.9 90.3 Delaware 337 202 186 159 103 166.0 109.0 80.3 93.0 97.9 fl§311§pd 367 293, 186 193 100 236.3 193.1 119.3 90.9 70.1 NORTHEAST 353 290 182 192 123 173.1 81.2 59.0 53.6 99.0 Michigan 932 281 212 162 126 170.0 99.7 66.8 98.0 38.1 wisconsin 950 255 192 151 128 198.8 69.6 38.3 28.2 26.3 Minnesota 628 377 277 219 172 175 . 9 99 . S 60 . 7 91 . 0 29. 3 LAKE STATF$§ 529 311 233 181 199 165.9 82.3 52.5 38.1 31.3 Ohio 996 296 215 159 115 218.7 125.9 89.3 55.9 90.3 Indiana 516 330 222 196 109 239.7 136.6 86.7 53.7 37.2 Illinois 590 391 239 161 113 296.9 170.8 108.5 66.9 99.9 Iowa 922 301 221 155 111 187.9 117.1 80.6 53.6 37. 8 Missouri 7 8 961 330 235 175 219.2 113.6 71.5 95.8 33. 2 CORN EEDT 509 336 295 179 129 229.9 139.3 86.9 59.6 38.1 North Dakota 2,390 1,901 932 593 371 266.6 136.8 89.2 55.3 36.2 South Dakota 2,630 1,225 796 969 320 206.8 109.6 71.5 96.6 35.3 Nebraska 1,680 761 512 333 239 227.9 125.0 83.1 55.5 38.6 Kansas 1,807 993 631 ,385 233 276.7 197.1 97.3 61.6 90.9 mm PLAINS 1,956 1,028 693 930 270 293.0 129.9 85.0 56.1 38.7 Virgdnia 669 901 276 188 191 239.1 118.2 71.6 96.2 39.0 Nest Virginia 605 513 913 396 297 136.5 79.2 55.5 91.1 30.6 North Carolina 909 220 190 99 81 135.9 75.2 97.2 30.7 26.0 Kentucky 699 333 231 156 113 299.5 99.2 58.7 36.6 25.9 Tennessee 799 389 271 182 129 230.2 108.3 70.8 99.5 31.9 APPALACHIAN 567 315 216 153 118 190.7, 93.9 59.5 38.0 29.9 South Caro1ina 911 967 269 179 195 236.7 112.9 68.3 95.1 35.9 Georgia 702 362 282 227 185 163.3 83.3 69.1 98.3 91.7 Florida 1,865 636 388 290 200 717.9 169.1 119.5 79.3 77. 8 Alabama 769 907 4350 251 180 160.6 75.0 63.0 99.6 39. 3, SOUTHEAST 1,031 932 317 226 179 309.3 98.9 73.6 51.6 95.0 Mississippi 1,195 567 1136 276 186 393.3 130.3 88.0 55.1 37.7 Arkansas 808 389 391 266 191 268.0 106.3 85. 9 55.8 36.5 Louisiana 1,193 951 326 211 152 371.7 195.1 101.2 65.0 97.1 DEUTA STATES 1,010 951 366 256 180 3319.1 123.2 ,90.5 57.9 39.5 Oklahoma 2,195 970 662 908 257 339.9 179.7 112.9 70.3 96.0 Texas 9,927 1,932 896 523 311 983.1 212.6 199.3 90.8 60.8 SOUTHERN PLAINS 3,995 1,295 819 985 295 951.1 201.3 133.7 89.0 56.6 Montana 8,835 2,986 1,670 898 576 938.8 186.3 118.5 72.1 52.2 Idaho 1,952 675 928 252 170 317.2 139.9 81.7 59.6 91.3 Wyoming 13, 359 3.511 1,923 1,125 629 997.1 169.6 100.8 70.9 99.9 Colorado 3, 839 1,711 1,229 750 539 320.1 163.6 116.9 78.8 69.9 New Nexico 16,906 9,823 2,727 1,556 1,102 610.2 210.9 138.1 90.8 67.7 Arizona 7,178 3,927 2,690 1,797 1,196 900.2 261.6 202.0 128.1 106.9 Utah 9,909 1,258 733 939 288 281.8 121.5 86.9 58.7 97.1 Nevada 19,921 3,289 3,973 1,303, 3,093 673.9 217.2 270.8 196.5 196.6 mm 7,019 2,290 1,360 782w 585 996.3 168.0 111.6 13.2 58.6 washdngton 1,552 799 525 291 173 333.3 158.7 105.5 70.6 60.6 Oregon 2,921 1,102 669 317 199 332.9 152.2 97.9 67.6 57.0 California 1,518 591 331 196 161 675.1 223.0 199.5 119.2 99.6 PACIFIC 1,717 707 997 293, 170 561.5 190.6 128.0 ,,99.7 82.7 98 319158 1,603 625 932 273 190 296.8 126.1 83,3 55. 9 92,1,_ a Source: 1969 Cemsus of Ag'iculture, State Sammy Volums, Table 27. Econanic Class based on value of Agricultural products sold. Class I - 390, 000 and over, Class II - $20, 000 - $39. 999; Class III - $10, 000 - $9,999; Class Iv - $5,000 - $9, 999; and Class v- 82.5-0- $9. 999 bNew England States include: Main, New Haxrpshire, Vermont, Missacmsetts, Rhode Island, and Connecticut. 183 Table A. 16 Percent of land in farms rented by economic class, by farm production regions, 1969. a Rate and j A Percent of Land in Farms Rented Easier: E I II I TII 4 TV L V . . . ........ Percent ................... New and - States 18.3 18.6 19.9 9 9 8.6 M Ym'k 25.2 20.9 16.9 19.0 12.2 New Jersey 91.9 95.6 35.3 26.8 20.9 Pennsylvania 31.? 28.1 22.5 16.1 12.9 Delaware 93.9 91.8 91.2 28.9 22.9 mend 97.2 92.8 2.3 23.6 15.6 mm 29.7 25.0 20.6' 16.0 12.1 Michigan 33.9 32.5 27.5 23.6 17.1 Wisconsin 29.8 22. 7 16.9 11.2 8.6 Minnesota 93.6 39. 6 32.2 29.3 16.7 LAKE STATES 37.2 32.9 26.3 20.3 19.7 0110 51. 3 51. 2 91.9 31.9 20.2 Indiana 56. 6 55 9 93.6 29.9 18.7 Illinois 63.8 62. 6 52.8 91.2 29. 5 Iova 52. 5 52. 2 93.0 31.2 23. 3 9118801121 93.0 90.7 2.9 22.6 15. 8 (DEN EILT 59; 53.3 92.6 30.0 20.0 North Mots. 93.9 92.1 36.0 33.0 30.5 South Ibkota 36.1 38.7 38.9 36.3 31.8 Nebraska 90.9 99. 7 96.6 91.1 37.8 Kansas 56.0 56.5 59.0 96.9 39.3 1017119394 PLAINS 99.2 96.7 93.9 39.1 35.8 Virginia 32.7 29.8 25.0 19.6 13.3 West Virginia 25.9 23.3 18.9 16.1 13.7 North Carolina 36.1 91.0 35.6 25.7 17.9 Kentuclq 33- 9 31. 9 29. 9 16. 5 10. 6 Tennessee 99.5 36. 1 305 19. 8 19. 9 APPALACHIAN 36.2 39. 3 28.9 19.6 13.6 South Carolina 37.1 33. 3 29.1 22.7 16.0 Georgia 26.3 26. 8 29.6 18.3 13.0 Florida 28.7 33.6 91.9 33. 2 33.7 Alabama 3gg 35.1 31.3 29. 6 20.3 SQMIEAST 29.6 31.5 30.9 23.9 20.2 Mssissippi 91.6 38. 0 31.0 23. 3 19.9 Arkansas 53.5 50. 2 95.6 30. 5 22.3 Louisiaia 97.5 58. 9 50.9 92. 2 37.2 m SI‘A'I‘Ej. 97.7 98.9 91.5 30.1 29.3 atlaham 96.1 99.7 95.9 39.8 32.9 Texas 50.9 51.7 98.0 92.9 35.5 301mm PLAINS 50.3 51.2 97.3 92.0 39.8 Mmtana 35.8 36.9 36.3 39.2 32.5 Idaho 39.8 36.1 32.3 26.9 20.9 Waning 92.2 38.7 39.6 39.3 91.3 Colorado 39.5 39.9 39.8 37.9 39.6 New Mexico 96.1 97.8 97.9 95.8 95.9 Arizona 62.9 70.5 79.0 62.7 76.1 Utah 67.3 62.7 69 0 70.6 77. 6 M 93.6 65. 9 80. 9 76.5 89. 6 MAIN 99.2 9_2.5 99.0 9_2.7 98.8 Nashirgton 59.8 50.5 96.8 36.6 32.5 (regal 35.2 35.9 31.7 25.9 22.1 California 59.6 95.6 53.7 95.6 92.9 PACIFIC 53.1 99.1 95.2 37.7 35.9 98 STATES 96.1 99.8 90.9 33.8 28.2 21Source: 1969 Census of Agriculture, State anmary Volumes, Table 27. Calculated assming all land is rented by part owners and termts is operated and not subleased. bNew England States include: Maine, New Hanpshire, Vemmt, Massachusetts, Rhode Island, and Connecticut. 189 Table 9.17 Number of farms and land in farms fOr economic classes I - V cash grain farms, b‘ selected states and farm production regions, 1969. State and : Pam Hm : Lma in Duh Grain Pam ”51°“ :I— m :III :w :v : 'Ibtal :1 : II rm“ 1 Iv tv Trotal W. ..... ..... 1,000Acnes......... Nam . . . 299 979 6% 808 879 3,086E 306 227 171 199 102 250 mm . . . . 220 908 2.098 3.317 9.350 10.893; 175 385 565 596 558 2,279 mm . . . . 99 196 909 765 1.290 2.709? 89 83 108 150 179 609 Mascots . . . . .;_;_,053 3,929 59$ 6,508 9,926 22,891; 1,295 2,233 2,379 11529 905 8.366 Lion States . . .: 1.372 54028 8,888 10,590 10,516 36,399; 1.509 2,706 3,052 2,395 1,692 11,299 W 01.10 . . . . . . .: 828 2,663 9,615 6,933 7,537 22,076; 695 1,188 1.309 , 1.108 868 5,113 1mm- . . . . . .3 2.279 9,980 6.397 7,129 7,897 28,6122 1,609 2,097 1,795 1.196 871 7,513 1111mm. . . . . 6,990 19,900 15.191 11.083 7,593 55,157; 9,619 5.595 3.998 1.933 927 17,017 1m . . . . . . 2.592 7.579 9.630 7.973 9.801 32.575; 1.727 2.959 2,998 1.352 591 9.072 Nissan-1 . . . . .:41071 2.599 3.891 9,222 9,988 16,2715 1,160 1,590 _1,971 1,067 772 6.010 00m 8018 . . . 13.705 3,221:3_9,679 36,835 2,36 159,751; 9,750 13,379 10,916 6,656 9.029 99.725 North Dakota . . 1.279 swift—9.159 6,276 3:083 25,256r 3,016 7,900 8.150 3,612 1.158 23,336 South mu . . 339 1.290 2.073 1.980 1.529 7.156? 886 1.929 1.938 826 990 5.069 Ndamka . . . . 1.679 9,9[6 6.987 5.178 3,009 21,329 1,670 3,220 2.952 1,629 669 10,130 ma. . . . . . _1L7..21 4.667 7.765 7.568 5,836 27.557 5 3,902 5.169 5.591 3.391 1923 19.130 Norm Plain _45313 16,357 35,979 21,002 1.34.."_"7_ 81,298i 8,979 17,218 18,081 9,953 3,939 57,665 90091006010” 765 1,297 1,905 2,718 $8 10,2037 890 673 585 529 991 Lg: Southeast . . . 160 297 388 577 986 2,358? 263 217 193 163 190 ;,5_12_6_ 1916610017751 . . . 699 502 571 709 993 3.929; 1,183 379 266 189 163 2,175 mm... ..... 2.338 1.859 1.898 1.706 1.889 9.690% 2,992 1.003 682 372 298 5.297 1.00121“ . . . . .2 1,165 1,285 1,185 959 888 5,9773 1,529 689 381 182 122 2.893 0.1:... . . . . 9,152 3,696 3,659 3,369 4,170 18,5911; 5,699 #21066 4&9 738 533 10,365 09mm. . . . . 333 1.399 2.667 3.059 2.613 10.011 697 1,957 1,828 1.309 691 5.932 'Dexn . . . . . . 2,993 3,955 _3LB98 34907 3,593 17,296; L923 2,716 2,169 1,271 859 11.938 mpmiim 9.799 6.515 6,961 6,156 27,257: 5,570 9.173 3997 2580 1550 17870 A—‘ M hmtain . . . .:_1,919 3,667 9,595 3,052 2,038 19,721? 5,656 7.357 5.725 24379 1,070 22,182 Pacific. . . . 31.191 1.939 1.585 995 571 6.231% 3.779 3.155 1.791 569 210 9,999 k ‘'3 States. 9 . 3.31.397 69.630 93.258 $.35? 79.2.2 359390;”.3“ 51.165 “5.790 25.596 13.756 178.5“ aSaunas: 1969 Mu of'Ay'ieultm‘, State Sunni-y Volun, Table 29. 185 Table A.18 Average acreage size and average market value of land and buildings per farm for economic classes I - V cash grain farms, by selected states and farm production regions, 1969.a : ”3ng Size M; 9:01:59 Market Value of 5.20 and Building 951- Farm 51 . : II : III : IV : V : All I : II ° III : IV : V : All ;...........Ac1u.......... $1.000.......... Moment . . . .:h091 979 271 178 .127— 308 : 295.8 181.2 1150 86.1 56.0 102.9 Michigan . . . . 795 929 276 180 128 210: 336.9 177.9 105.9 69.1 95.6 61.3 Hisomsin . . . . 898 923 267 196 199 223 382.8 165.1 97.9 61.9 38.9 58.0 Mir-mots . . . . $1,182 570 370 296 189 366 302.2 193.6 90.9 57.5 37.2 80.6 Lake States . . .:fl 538 393 221 156 309 313.6 150.6 99.6 59.8 90.8 M Ohio . . . . . . 779 996 283 172 115 232 381.9 207.9 123.8 73.0 98.8 86.5 Indian . . . . . 705 921 273 168 110 262 390.0 183.2 115.5 67.6 93.1 101.3 1111:1010 . . . 665 389 261 179 122 309 399.3 207.8 128.1 79.5 51.5 155.0 Iowa . . . . 666 390 259 170 123 278: 310.5 179.5 108.9 68.0 96.8 119.0 Missouri . . . . 311081 593 378 253 172 369 391.0 189.0 106.9 67.5 92.7 98.2 Corn Belt . . . .:_7_1_11 915 275 181 125 289 368.9 199.2 _1_18.7 72.2 96.9 43% North Dakota . . .:2.358 1,359 890 576 376 929 : 290.0 197.9 90.5 59.9 38.5 99.9 South Mots . . 32.619 1.152 699 917 322 708 285.3 190.2 85.7 52.9 37.5 77.3 Nebraska . . . . 998 696 955 319 221 975 287.7 169.3 102.8 66.6 92.7 108.9 mas . . . . . $1,977 1,108 719 998 279 _699 2 361.7 188.0 116.2 79.9 97.8 107.7 710 950 293 709 i356 163.8 101.1 66.3 93.9 101.1 Northern Plains .71.T9O 1.053 _r Appalachian . . . 1,75; 590 307 195 138 310 1 392.2 160.9 88.2 53.0 36.3 79.6 Southeast . . . “gm 879 997 282 193 935 : 912.0 195.9 109.2 62.7 93.9 81.0 mssissippi . . . $1,823 755 966 260 169 635 7 571.2 197.3 112.5 62.9 37.3 169.0 Arkm . . . . €1,280 590 359 218 131 597 937.0 169.1 102.9 63.0 39.8 168.2 Louisima . . . . £1,118 532 18%... 91 138 528 £84 171.6 3139.1 63.1 95.0 158.5 Delta . . . . . €1,373 567 a 219 191 558:; 997.1 171.3 109.8 63.0 37.9 165.5 0km . . . . .:1.993 1.089 685 929 269 593 5 916.6 233.2 199.7 89.0 59.7 110.9 Tam . . . . . . $1,695 786 569 373 292 692 3 987.8 327.3 150.2 99.6 57.3 182.9 300mm Plains .:$ 870 619 399 252 656 980.7 228.9 198.0 91.9 56.2 156.1 Maintain . . . 33,986 2,006 1,260 778 525 1,507 3129.9 207.5 125.1 83.0 59.8 199.0 Pacific . . . . €311.62 1.627 14098 597 368 1,516i 596.0 260.6 156.6 98.1 66.9 290.2 98 Statu....§1.350 735 991 296 185 m3§$.2 187.0 113.3 70.5 95.6 118.1 aSource: 1969 Gem- of mealtime. State 3.“? Volume T018 29. 186 Table A.19 Percent of farmland rented of land in farms for economic classes I - V cash grain farmsé by selected states and farnlproduction.regions, 1969., State anti ‘—Peroent of Farmland Rented of Land in Parts gggion ‘I 5 II’ 4 111 4 IV . V’ . All :...........Percent.... . ...... Northeast . . . .f60.1 51.5 92.7 31.9 22.5 96.6 Michigan . . . . .§58.3 53.0 92.7 30.0 28.3 38.8 Wisconsin . . . . .350.0 91.0 32.9 19.3 13.9 27.2 Minnesota ..... Q51.7 99.8 93.3 39.9 29.5 ==92.6 Lake States . . .f52,9 50.0 92.8 32.3 29.6 91.0 Ohio . . . . . . .266.5 69.8 59.8 91.0 27.1 50.9 Indiana . ..... 369.1 65.3 53.0 37.8 25.8 59.3 Illinois . .272.8 69.9 59.3 98.8 36.0 69.0 Iowa . . . . . 66.3 63.7 53.2 38.5 30.8 55.5 Missouri . .262.7 59.5 50.8 90.9 29.0 50.7 Corn.Belt . . . .f69.9 6633 55.2 92.1 29.8 57.3 North Dakota .§51.0 98.3 91.3 37.0 32.3 93.7 South Dakota . 99.6 98.1 99.0 95.9 35.5 96.2 Nebraska ..... 259.1 60.6 55.9 99.9 99.9 56.0 Kansas . . . . . .f62.0 61.7 59.9 59.1 98.9 58.6 Northern Plains -§5§:0 59.6 99.8 96.0 91.9 51.0 Appalachian . . .360.8 59.1 50.8 39.6 25.1 97.6 Southeast . . . .297.9 35.5 38.9 30.7 22.6 36.2 Mississippi . . . .350.1 53.8 99.9 91.3 28.2 97.7 Arkansas . . . . .259.1 65.7 62.5 53.8 90.7 59.5 Louisiana . . . . {60.9 73.2 61.9 57.1 98.9 63.2 'Delta . . . . . .257.7 66.0 58.7 51.5 38.6 958.1 Oklahoma . . . . .358.1 59.2 56.5 52.0 95.2 55.0 Texas . . . . . . .§69.6 62.8 60.9 55.9 97.6 61.3 ___ Southern Plains .32339 61.6 58.9 53.7 96.5 59.2 Mountain . . . .290.9 95.5 99.5 91.0 38.9 93.1 Pacific . . . . .;57.9 56.9 <_3§2.1 97.0 39.0 55.13:]_‘ 98 States . . . .}58.3 57.1 51.0 93.8 35.2 52.3 8Source: 1969 Census of Agriculture, State Sumnary Volunes, Table 29. Calculated assuning all land that is rented by Part Owners and Tenants 13 Operated and not smleased. 187 Table A.2O Coefficients of concentration of land in economic classes I —‘V farms, 98 states, 1969.a 'Ibtal Real ' A11 [and All Land A11 Lard Ebtate Value State and Began Ownedb Rentedc in Farm in Farm England States d .99 .99 .95 .23 New York 36 .98 .39 .21 New Jersey .50 .66 .57 .95 Permsylvania .36 98 .91 25 Delaware .51 .66 .59 -52 95.11am .111 .61 .51 .99 pm .92 .51 .93 .28 Michlan .32 .53 .90 .31 Wisconsin .29 .99 .35 .27 Minnesota g9 51.38 go LAKE arms . 30 .59 .3L .30 Chic .27 .55 .91 .36 Indiana .26 .57 .92 .91 Illinois . 29 . 96 . 37 . 37 Iowa .23 .93 .39 .32 Missouri .319 .55 .92 .39 (BEN 132m .28 .50 .32 .36 North We .32 .39 .36 .29 South Dakota .55 . 51.5“ .39 Nebraska .56 .59 .55 -32 Kansas .39 .53 .98 .39 W FLARE .98 .50 .50 Lil Virginia .99 .55 .52 J45 West Virginia .93 .55 .96 .31 North Carolina .57 .55 .57 .91 Kentuclq . 90 . 58 . 97 . 39 2mm .93 .61 .5; .90 APPAIACHIAN 99 56 .52 ‘ll South Carolina .62 .60 .62 .99 Georgia .60 .58 .59 .98 Florida .77 .86 .81 .65 513m .60 .69 .62 .98 saw .66 .70 .68 .56 Mississippi . 59 . 66 . 58 . 57 Arkansas .50 .62 .55 .52 Louisiana .60 .63 .62 .55 DELTA arms .59 .63 .53 .59 Ckalatma .96 .56 .52 .91 Texas .65 J1 .69 .9_8 W m .61 .69 .66 .97 Itmtam .99 .51 .50 .26 Idarn .65 .73 .70 . 9 Waning .55 .58 .57 91 Colorado .62 .69 .69 36 New Mexico .61 .69 .63 .90 Arizma .73 .79 .77 .52 Utah 076 .83 I79 .38 Nevada LE .75 .75 .51 MAIN .65 .70 .63 91 habitual .63 .80 .79 .91 Oregcn .75 .81 .78 .92 Calii‘afl .78 .88 85 .57 gen-ac .76 .85 81 .50 98 3mg 30 .72 .67 .91 I"pennies tron data in the 1969 cams of Agricultme, State W Volume, Table 26. 'lhe data is tabulated into a 12-elelnent classification by acreage size of fun. Coefficients of mutation (Gini ratios) are bomded by ratios of 0 (pennant mlity) an 1 (perfect ineqmlity or 912109013). bullamalmdbyMIOpemtm. misistmuorlaruinmil-ounrmms. mmmimofpurt-omermu.uda—llmmtotluuomed utimtodmtbymlltamta. cAlllandwmtedby famopemtm-sisthemoflaniinmll-tanntmmand the rented portion of part-omer opemtims. dNew W States amine: thine, New l-Upshire, Venmt. masacnmetts, Rode Island, and Oumticut. 188 .mCHocdom op oso o.ooa on own no: ads mowmpcoonom cofiposoopa show an .mmmHo oasocooo an vopcom UCMH Ham Ucm Gonzo Gama Ham 9 .Nm oanwe amoezao> zmmsssm mumpm .mpSpHSOHLw¢ mo momcoo mood "oomsomm m.m H.HH o.wH a.mm N.Ha " s.oa a.ma a.ma m.Hm .a.mm m . nooaom ma .m.a H.m a.oa m.aa a.mo ”.m.a m.a a.ma a.mH a.mm m . . . . . oaaaooa m.a 0.0 H.3H a.ma m.am m 5.: m.e m.aH m.om m.mm m . . . . oaaaosoz m.s m.HH m.ma a.ma s.:: ” m.ma m.aa m.mH 0.5H m.mm m . ncfinam sponasom m.m m.m 0.:H a.ma a.ma m o.ma m.mH a.ma a.ra m.mm m . . . . . . meson a.m m.HH o.oH a.mfl a.ma m m.aH H.3H a.ma 3.5H H.0a m . . . . onsosaoom m.HH 3.5H m.Hm a.mm «.mm m a.mm 5.3m a.mH a.ma a.ma m . . . anaooaanaaa m.m m.mH m.mm a.mm m.wm " m.o m.ma a.mm a.mm m.mm m . noaoaa oamaoaoz m.a m.m o.Hm m.mm o.mm m H.3H m.mH a.mm m.mm :.Hm m . . . . oaom once a.m a.ma m.mm a.mm a.mm " N.MH m.mfi m.am a.mm 3.:H ” . . . noooom axon m.m m.~ a.ma a.mm m.am m a.HH a.ma a.ma a.mm a.mm m . . . . enaoaaaoz o o o a. a PCQO-Hmm o o o o o o o w o... o o o pcmoaHmm o o o o o o e u s. W >H M HHH M .HH. W H u .e. W. en. M. HHH W _HH_ W H m, sesame nwoucoe coma Ham no pcooaom u .nwoczo ocma Ham mo ucoonmm m a.mmma .mcoawom ”no seasons Hm.< ofiose BIBLIOGRAPHY [l] [2] [3] [9] [5] [6] [7] [8] [9] [10] BIBLIOGRAPHY _ Adams, Dale W., and Rask, Norman. "Economics of Cost-Share Leases in Less. Developed Countries." ' Arnerican Journal Of AgriCultural EcOnomics. Volume 50, No. 9. November, 1968. pp. 935—992. Bailey, W. R. "Necessary Conditions for Growth of Farm Business Firms." Agricultural Economics Research. Volume XIX, No. 1. January, 1967. pp. 1-6. Barlowe, Raleigh, and Libby, Lawrence. "Policy Choices Affecting Access to Farmland." Who Will Control U. S. Agriculture? North Central Regional Extension Publication 32. University of Illinois Special Publication 27. 1972. pp. 23-28. Benson, Richard A. A Comparative Analysis of Financing Reguirements of Selected Types of Farm Operations in the Eastern Corn Belt for 1980. Unpublished Ph.D. thesis. 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