CLOIU llllllllllUH"!lllllllllllllllll!IIIIIHIHH’lllllllllllll 301565 9240 LIBRARY Michigan State 1 Unlversity This is to certify that the thesis entitled Landlords and Tenant's Contract Preferences for Leasing Farmland in the North Central United States presented by Brian J. Paterson has been accepted towards fulfillment of the requirements for Masters degree in Agrlcnltnral Economics LQ/[Qyém’w Mag r rofessor Date 9/12/96 0-7639 MS U is an Affirmative Action/Equal Opportunity Institution PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES rotum on or baton date duo. DATE DUE DATE DUE DATE DUE l l L_J IIL_II l H. mm: MSU I. An Affirmative ActlonlEqual Opportunity lnctltwon LANDLORDS AND TENANTS’ CONTRACT PREFERENCES FOR LEASING FARMLAND IN THE NORTH CENTRAL UNITED STATES BY Brian J. Paterson A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Agricultural Economics 1996 ABSTRACT LANDLORDS AND TENANTS’ CONTRACT PREFERENCES FOR LEASING FARMLAND IN THE NORTH CENTRAL UNITED STATES BY Brian J. Paterson This thesis contributed in two ways toward the efforts to explain the coexistence of cash rent and share contracts. The first contribution is a literature review which provides a background of existing leasing studies. The second contribution is to gather data on landlord and tenant leasing behavior across the North Central Region of the United States (NCR) which will help future researchers to better understand the leasing market. Agricultural Extension Agents were interviewed in a telephone survey over the NCR. The questionnaire collected two kind of data: 1) quantitative data on characteristics of the local leasing markets across the NCR and 2) qualitative data on landlords and tenants’ leasing behavior and contract choice preferences. This study identifies many factors that influence landlord and tenant leasing behavior. This information will be useful for future research in designing and testing a contract choice model. Furthermore, this study finds relationships in participants contract preference are important and should be explored in future models of contract choice. To my wife, Monica iii ACKNOWLEDGMENTS This thesis would have not been possible without the assistance of the staff in the Graduate School of the Department of Agricultural Economics. 1 thank my guidance committee that included: Dr. Lindon Robison, Dr. Steve Hanson, Dr. A. Allan Schmid and Dr. Jack Meyer who gave me important and useful comments on the final draft of the thesis. I am especially thankful to my major professor Dr. Lindon Robison, who gave me outstanding comments in the development of this thesis. His patience, friendship and teaching have been invaluable. I thank Dr. Steve Hanson for also helping me finishing this research with his comments and patience. I would like to thank a number of other people who contributed to this achievement: Dr. Lester Manderscheid, Eric Wittenberg, Marcelo Siles, Sherrie Loader and Pedro Gil. I would like to thank my parents Brian and Gloria, and my grandmother Irene Lutz for teaching me all these years. I thank my brothers Bruce and Kevin, my sister in law Juliana, and Shelly my brother’s fiance for listening and trying to help when I was in need. Also, I thank my parents in law who have trusted in my effort until the end. Finally, I thank my wife Monica, who has given me all her love, support and understanding even when we were physically apart and I thank God for giving me the opportunity to learn and achieve a goal. iv TABLE OF CONTENTS LIST OF TABLES ........................................... viii LIST OF FIGURES ............................................ x CHAPTER 1 INTRODUCTION .................................... 1 1.1. Why cash rent and share contracts coexist? .................... 1 1.2 Understanding contract preference ......................... 2 1.3. Description of efforts to reach objectives ..................... 2 1.4. Organization of the study ............................... 4 CHAPTER 2 LITERATURE REVIEW ................................ 6 2.1. General overview .................................... 6 2.2. The share contract: an alternative to the cash rent contract? .......... 7 2.2.1. Traditional contract choice model .................... 7 2.2.2. Input sharing contract choice model ................... 8 2.2.3. Joint profit maximizing models of contract choice ........... 8 2.3. Factors that influence contract choice ........................ 9 2.3.1. Including risk in contract choice models ................ 10 2.3.2. Including transaction cost in contract choice models ........ 11 2.3.3. Including tenant and landlord management skill in contract choice models ........................... 13 2.3.4. Including the landlord’s off farm income opportuni- ties in contract choice models ...................... 15 2.3.5. Including relationships in contract choice models .......... 17 2.4. Summary ........................................ 18 CHAPTER 3 METHODOLOGY ................................... 3.1. Introduction to the survey .............................. 3.2. The design of the questionnaire and its implemetuation ........... 3.3 Description of the survey population ....................... 3.4 Sampling process ................................... 3.5. Survey implementation and response ...................... 3.6. Characteristics of respondents and non-respondents .............. 3.7. Geographical representation of the sample .................... 3.8. Organization of the factor groupings ....................... 3.9. Summary ........................................ CHAPTER 4 ANALYSIS OF THE LEASING MARKET IN THE NCR .......... 4.1. Introduction ...................................... 4.2. Leasing characteristics of extension regions of the NCR ........... 4.2.1. Crops grown on leased land in extension regions of the NCR .................................. 4.2.2. Percentage of farmland leased in extension . regions of NCR ............................... 4.2.3. The percentage of leased acres that are cash leased in extensions regions of the NCR ............... 4.2.4. Cash rent of leased land in a cash rent contract in extension regions of the NCR .................... 4.2.5. Inth and output shares of share contracts in the extension regions of the NCR ...................... 4.3. Similarities or differences of leasing characteristics of extension regions in the NCR .................................. 4.4. Summary ........................................ CHAPTER 5 ANALYSIS OF RELEVANT FACTORS ..................... 5.1. Introduction ...................................... 5.2. Major factors influencing the landlord to lease his or her property .................................. 5.3. Factors influencing landlords who lease to lease in a cash rent or share contract .......................... 5.3.1. Factors that influence landlords who lease to prefer a cash rent contract ............................. 5.3.2. Factors that influence landlords who lease to prefer a share contract ............................... 20 2 1 21 22 24 26 29 30 33 36 36 39 49 53 55 57 58 63 65 vii 5.4. Factors influencing tenants who lease to lease in a cash rent or share contract ............................. 68 5.4.1. Factors that influence tenants who lease to prefer a cash rent contract ............................. 69 5.4.2. Factors that influence the tenant into a share arrangement ................................. 71 5.5. How tenants and landlords who share lease determine inth and output shares ................................... 74 5.6. Summary ........................................ 78 CHAPTER 6 CONCLUSION ..................................... 79 6.1 The problem ...................................... 79 6.2 What was done to solve the problem? ...................... 79 6.3 Summary of findings ................................. 80 6.3.1. Literature review .............................. 80 6.3.2. Methods of research ............................ 81 6.3.3. Characteristics of leasing markets in the NCR ............ 81 6.3.4. Factors identified that influence leasing behavior .......... 83 6.4. Implications of this study on future research ................... 87 Appendix A: Questionnaire ....................................... 88 Appendix B: Leasing characteristics of each extension region in the NCR .......... 93 Appendix C: Factors reported by the respondents with less than 15 percent frecuency to influence landlord and tenant contract choice ............. 96 List of References ............................................. 97 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 4.1 Table 5.1 Table 5.2 Table 5.3 Table 5.4 LIST OF TABLES Number of AE agents asked to participate in the study (by extension area and state) ............................... Number of AE agents asked to participate and who responded by state ......................................... Number of agents who responded according to their extension area and average number of counties covered by responding agent . . . . Number of counties covered by the responding agents extension areas compared with the total number of counties per state ......... Factors influencing the landlords’ decision to lease .............. Factors influencing landlords and tenants who lease to prefer a cash rent or share contract ............................ Factors determining landlord and tenant input/output shares in a share contract .................................. The terms of the most common share contracts: crops tenants grow; landlord’s output share; landlord’s input arrangement( share of seed, fertilizer,and chemicals); and the number of extension regions in each state with the same most common share contracts ............... The frequency respondents reported a factor influences landlords decision to lease his or her property ................. The frequency respondents reported a factor influences landlords who lease to lease in a cash rent contract .............. The frequency respondents reported a factor influences landlords to lease in a share contract ....................... The frequency respondents reported a factor influences tenants to lease in a cash rent contract ...................... viii 24 26 28 29 31 50 59 63 66 69 Table 5.6 Table 5.5 ix The frequency respondents reported a factor influences tenants to lease in a share contract ........................ 72 The frequency respondents reported a factor influences how landlords and tenants who share lease determine inth and output shares .......................................... 75 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 LIST OF FIGURES Major crops grown in the Extension Regions of the NCR .......... Percentage of farmland leased in the Extension Regions of the NCR . . . Percentage of farmland leased in a cash rent contract in the Extension Regions of the NCR ........................... Cash rent levels that landlords receive in cash rent contracts in Extension Regions of the NCR ........................... 38 41 44 47 CHAPTER] INTRODUCTION 1.1. Economists have struggled over the years to explain why cash rent and share contracts coexist in the lease market. Some landlords lease farmland to tenants in exchange for cash. Other landlords lease farmland to tenants in exchange for a share of the output. Economists have proposed many theories to explain why landlords and tenants prefer one contract to the other. However, economists have not developed a consensus why the participants have different contract preferences. Some of the theories that have attempted to explain the different contract preferences are discussed in the literature review in chapter two. Some economists believe they can explain the coexistence of cash rent and share contracts if more detailed data on leasing behavior and local leasing markets were collected. More data is needed to explain: a) why landlords and tenants decide to lease in a cash rent or share contracts, b) lack of data that explains how landlords and tenants determine the temts of input and output shares in a share contract, c) limited data explaining why landowners decide to lease and d) how do leasing practices vary across geographical areas. 1.2. Collecting and reporting data on leasing behavior in a broad geographical area is one of the goals of this thesis. The analysis of the thesis intends to be the first of a series of studies which will aid to develop a more generally accepted theory that explains contract preferences. The following two objectives are pursued in this study. First, the study reviews past theories of leasing behavior to show the diversity of theories in leasing behavior literature. Generally, this review shows that there is no consensus among economists to explain leasing behavior. Second, this study collects primary data on landlords and tenants leasing behavior. This data explains four types of leasing behavior: 1) why landowners decide to lease, 2) why landlords who lease prefer a cash rent or share contract, 3) why tenants who lease prefer a cash rent or share contract, and 4) how landlords and tenants who lease in a share contract determine input and output shares. Data on the local leasing characteristics in each respondent’s area was also collected. 1.3. A literature review was completed to provide a general background to understand leasing bdiavior. The literature review discussed the views of many agricultural economists and economists on landlord and tenant contract preferences. Economists propose many different models to explain why cash rent and share contracts coexist, but they do not agree on one model to explain tenant and landlord contract preferences. 3 A telephone survey was done in the 12 states of the North Central Regions of the United Smes (NCR) to gather information on leasing behavior. The agricultural agents within the extemion regions in each state were contacted. Agricultural agents were contacted because they were considered the most qualified source of information on leasing practices and leasing behavior. The NCR was the area the agricultural agents were selected from because of the areas high leasing activity and diversity of leasing practices. The questionnaire for the interview used close and open-ended questions. Close ended quantitative questions collected information about the respondents local lease market characteristics. The characteristics that the respondents reported about their local lease market are: 1) the type of crops grown on leased land; 2) the percentages of farmland that landlords lease; 3) the percentages of leased farmland that landlords lease in a cash rent contract; 4) the percentages of leased farmland that landlords lease in a share contract; 5) the average cash rent landlords receive leasing in a cash rent contract, 6) the most common input and output shares landlords and tenants agree in a share contract. Open ended qualitative questions collected information on landlord and tenant leasing behavior in the respondent’s extension region. The information on leasing behavior that respondents reported for their extension is: 1) why landlords lease, 2) why landlords who lease prefer a cash rent or share contract, 3) why tenants who lease prefer a cash rent or share contract, and 4) how landlord and tenant who lease in a share contract determine the input and output shares. The data was organized into in the following manner. Quantitative information on leasing characteristics was categorized into high, medium and low percentiles. Categories of leasing characteristics were shown in color coded maps. Each map showed how some leasing chaacteristics varied across the North Central United States. Data on the terms of share 4 contracts found across the North Central United States were presented in a table because of the great diversity of the data. The qualitative data that the respondents reported on leasing behavior was organized into categories based on similar economic reasons of explaining. Separate tables were created for each qualitative question on leasing behavior. Each table shows the frequency each category was reported to influence leasing behavior in each state of the North Central United States. The survey data was limited in the following ways. First, the information about the leasing behavior was not directly taken from the landlords’ and tenants’ own perceptions because agricultural extension agents were selected to be the survey population instead of landlords and tenants. Second, the survey collected qualitative data that explain leasing behavior. Respondents only reported reasons why landlords and tenants displayed a certain type of leasing behavior, since the survey is only a first step towards collecting primary data about leasing behavior. Therefore, the probability of a type of leasing behavior occurring for a category reported to affect leasing behavior was not able to be reached with this type of data. Second, the survey collected aggregae daa on leasing characteristics in each area. Therefore, the variability of the data within an tea is unknown. In spite of these limitations, this data has identified many influences of the participant’s leasing behavior that will give future researcher a better understanding of why cash rents and share contracts coexists in the NCR. 1.4. W The remainder of this study is organized into five chapters. Chapter II describes the literature on leasing behavior. The first section of Chapter II presents past theories on why cash rent and share contracts coexist. Economists in the past have questioned whether the cash rent 5 and share contracts could offer the tenant and landlord equal benefits in each contract. These ecommists also debate whether the tenant’s use of inputs and production of outputs is the same in each contract. The second section of Chapter 11 reviews current studies on contract choice. In current studies, the focus is on the different influences that affect each participant’s decision to choose between the cash rent and share contract. Chapter III explains the questionnaire design and survey method used to collect data on landlord and tenant leasing behavior. The first and second sections of Chapter III discuss the design and implementation of the questionnaire and a description of the characteristics of the survey population. The third section of Chapter III explains the sampling process, rates of response, characteristics of respondents and non-respondents, and the geographic area included in this study from those surveyed. The fourth section of Chapter III explains how the qualitative data collected in the survey was organized and describes each category reported to affect the participants leasing behavior. Chapter IV describes the leasing characteristics of extension regions in the North Central United States using color-coded maps. Chapter V shows the frequency the respondents reported a category to explain each of the four types of leasing behavior in their region. Again, the four types of leasing behavior the respondents reported information on are: l)why landlords decide to lease, 2) why landlords who lease prefer a cash rent or share contract, 3) why tenants who lease prefer a cash rent or share contract, and 3) how tenants and landlords who share lease determine input and output shares. Chapter V1 is a summary. CHAPTERZ LITERATURE REVIEW 2.1. W Economists have conducted many studies attempting to explain why cash rent contracts and share contracts coexist in the farmland leasing market. So far no generally accepted explanation has been found though many interesting ones have been proposed. This chapter will review the contract choice literature that attempts to explain existing lease arrangements. This chapter consists of two main sections. The first section explains earlier theories that question whether share contracts can offer tenants and landlords the same benefits as the cash rent contract. The second section discusses factors that influence the landlord and tenant’s contract preference. The last section is a summary. In describing the contract theories, many terms are used that may be difficult to understand. To help simplify the reading of this chapter, terms used in contract choice literature will be defined. The term “cash rent contract” defines a contract between the tenant and landowner in which the tenant pays the landlord a fixed dollar amount per acre as rent to use the land in one year’s agricultural production. The term ”cash rent“ defines the fixed dollar amount per acre paid in the cash rent contract. The term ”share contract” defines a contract between the tenant and landowner in which the tenant gives the landlord an agreed percentage of the crops produced as annual rent. The term "landlord’s output share” will define the proportion of the 7 crops produced that the tenant gives to the landlord as rent. The term ”tenant’s output share” will define the proportion of the crops produced that the tenant has left after paying the landlord’s output share. The term ”landlord input share" will represent the proportion of input cost the landlord contributes toward crop production on leased land. The term “tenant input share“ defines the proportion of inputs the tenant contributes toward crop production on leased land when the landlord shares input costs. In the past, economists have debated the question of whether or not a share contract can offer the same benefits as a cash rent contract. This section discusses economists’ views on the share contract’s ability to induce the participants to use the same inputs and produce the same outputs as would used under a cash rent contract. This section also shows economists’ views on whether tenants and landlords receive their same respective income in each contract. In early contract choice models, economists described the tenant as one who maximized profits by his choice of inputs. In a share contract, the tenant receives less than his full marginal value product. The model predicted the tenant would maximize his income using a lower amount of inputs and produce a lower output level in a share contract than he would in a cash rem contract. The landlord in the traditional model is assumed only to receive a cash rent or output share but hm no influence over the input use level. Thus, according to the early models, cash rent contracts resulted in higher input use and greater outputs than would share lease contracts. 8 Because of me theoretical benefits of cash leasing, the prevalence of share leases remained a question. Shickle (1941), Heady (1947) and Isawi (1982) criticized the traditional theory for failing to accoum for landlord sharing variable input costs. These economists suggested that sharing inputs and outputs would induce the tenant to apply the same input level as in a cash lease. Adams and Rask (1968) showed that this arrangement would, of course, increase the tenant’s profits above a traditional share contract. Whether or not the landlord’s profit position was increased compared with a traditional share contract, would depend on the increase in output resulting from increased inputs. While these economists suggested equal inputs and outputs are achieved in the input sharing share contract and the cash rent contract, the question of which contract me tenant and landlord would prefer remained unexplained. Chueng (1968) examined contract choices and found conditions that maximized the tennis and ladlerd’s income. Chueng explained that the tenant and landlord must receive their same respective incomes in both cash rent and share contract, if the contracts are to be equally agreeable for both participants. Chueng argued that three conditions are required to give the participams equal incomes in both contracts. First, the landlord contracts the tenant to apply the same amount of inputs in both contracts. Therefore, the landlord receives the same income in each contract since the same output is produced. Second, the tenant must receive a share of 9 output that allows him to receive his opportunity cost. Therefore, assuming labor is the only input, the landlord’s output share must equal the total value product of labor less the total factor com of labor that is the tenant’s Opportunity income divided by the total value product of labor. Third, the landlord must restrict how much land the tenant farms. Therefore, the tenant must apply all his labor on the landlord’s land to receive his opportunity cost. Chueng, therefore, showed that in a competitive market, cash and share lemes could be arranged to provide the same benefits. Thus, both types of contracts could coexist. He failed to explain, however, how to choose between the contracts. 2.3. MW Chueng showed that equal inputs, outputs, and participant incomes can occur in both contracts. Therefore, little question now exists if both contracts can offer the participants the same benefits. However, still little theoretical basis exists for why the tenant and landlord would prefer the cash rent contract to the share contract. Therefore, economists now search for an explanuion of why one contract or the other is preferred. Current contract choice theory now seeks factors that will create differences in incomes depending on the contract choice. These differences lead some landlords and tenants to prefer a cash rent contract and others to prefer a share contract. Economists have proposed to explain the team! and landlord’s contract choice decision using many factors: risk, tenant’s opportunistic behavior, management ability, transaction costs, and a landlord’s off farm income. Further, the participants lease land of different quality in areas of different climates. This section explains models that consider the influence of these different factors. 10 2-3-1. W Sutinen (1975), and Hiebert (1978), suggests risk is important in determining contract choice. The main difference between the Sutinen and Hiebert models is that Hiebert’s model assumes the tenant chooses the input level while Sutinen’s model assumes the landlord chooses the input level. These economists argue that the landlord and tenant may not receive the same utility of income in the cash rent and share contract because each contract offers a different potential distribution of income. If the participants’ expected incomes are respectively the same in each contract, then, the participants jointly choose the contract commensurate with each participant’s level of absolute risk aversion. The tenant and landlord prefer a share contract when both have a positive level of absolute risk aversion. The tenant and landlord prefer a cash rent contract when the landlord has positive level of absolute risk aversion and the tenant has no risk aversion. Tenants and landlords prefer a fixed wage contract when the landlord has a neutral level of absolute risk aversion and the tenant has a positive level of absolute risk aversion. The tenant and landlord preferred comm choice is undefined when both participants are risk neutral (Robison and Barry, 1987). The effect of risk on the efficiency of fixed rent and share arrangements has also been examined. Robison and Barry (1987) note that the landlord’s input solution may be greater, equal to or less than that wanted by the tenant. The difference between the landlord’s and tenant’s desired input solutions depends on whether the rate of per unit loss of the landlord’s land value is decreasing or increasing from the tenant extracting the services of land. Therefore, the efficiency question is incompletely resolved, even with risk in the analysis. The transaction cost model is the most widely accepted theory of contract choice. Chueng (1969), Johnson and Meckling (1976), Roumasset and Uy (1980), Datta, O’Hara and Nugent (1986), and Allen and Lueck (1992) have all incorporated transaction costs in their models to explain landlord and tenant contract preference. Transaction cost theorists argue that there are transaction costs in the leasing market. Transaction cost theorist state that the tenant can choose input levels that only maximize his income and not the landlord and tenant joint income. The tenant maximizes only his income because the landlord cannot perfectly monitor the tenants input levels. Transaction cost theorists argue the tenants choice of input level would maximize both his individual income and the landlords and tenants joint income without transaction costs. Yet transaction cost theorist state that because transaction cost exists, that the tenant will lower the landlord and tenant joint income when he maximizes his own individual income. Transaction cost theorists believe the tenant lowers joint income because at his chosen input level, the landlord’s loss of income is greater than the tenant’s gain or the tenants loss of individual income is less than the landlord’s gain. Therefore, joint income would increase if the tenant choose an input level to maximize joint income instead of only his own income. Transaction cost theorists argue that the tenant chooses an input level that allows joint income to be closer to its maximum level when there are less transaction costs. Therefore, these theorists argue that the participants will enter the contract that has the lowest transaction cost. Allen and Lueck (1992) developed one of the most current contract choice models that incorporues transaction cost. Allen and Lueck predict the tenant and landlord are more likely to prefer a share contract as the value of land increases. In contrast, Allen and Lueck predict the 12 tenant and landlord are more likely to prefer a cash rent contract as the cost of dividing output increases. Allen and Lueck explain their predictions based on the contract that has the highest tenam and landlord joint income alter the tenant chooses the input levels. Allen and Lueck argue that the land is filled with soil nutrients. The tenant pays for some of these nutrients. landlords absorb the full cost of replacing other nutrients. In both the cash rent and share contracts, tenants deplete the soil nutrients because they do not pay the full marginal cost of the land’s soil nutrients. The tenant receives the full marginal value product of these nutrients in a cash rent contract, but less than their full marginal value product in a share contract. Thus, the tenant maximizes his income by depleting a higher amount of soil nutrients in the cash rent than in the share contract. Also with this behavior, the tenant lowers joint income because the landlord’s cost of replacing these nutrients is higher than the tenant’s total benefit from depleting them. Allen and Lueck also argue that the tenant’s different incentives to apply labor in each contract influence the landlord and tenant’s joint income in each contract. Under a cash rent contract, the tenant applies an amount of labor that maximizes both his income and the joint income. In contrast, the tenant’s allocation of labor in a share contract maximizes his income but does not maximize the tenant and landlord’s joint income. The tenant applies less labor in the share contract because he receives less than his full marginal value product of labor. Thus, the joint income of the tenant and landlord in a share contract is lower because, at the tenants chosen allocation of labor, the tenant’s cost of applying additional labor is less than the landlord’s and tenam’s joint benefit from a higher labor input. Allen and Lueck also suggest the cost of dividing the output as an additional transaction cost in the share contract. Therefore, Allen and Lueck argue that the tenant and landlord prefer the contract that offers them the highest joint income. High quality land gives the tenant more incentive to 13 deplete the soil inputs than low quality land. Soil depletion is costly to the landlord. Therefore, the tenant and landlord are more likely to enter a share contract as land quality increases. Output division cost is only present in the share contract and not in the cash rent contract. Therefore, the tenant and landlord are more likely to enter a cash rent contract as the cost of output division Ely and Galpin (1919), Samuelson (1973), Roa (1977), Hallagen (1978), and Kloppenburg and Geisler (1985) have shown that tenants and landlords’ management skills or entrepreneurial abilities are important factors in influencing the contract choice. In Ely and Galpin’s agricultural ladder theory, the age of the farmers was considered correlated with his management skill and wealth. This theory dominated leasing literature between 1920 and 1950. The aging tenant was believed to move through five various stages of land tenure: 1) unpaid family laborer, 2) hired laborer, 3) share-cropper, 4) tenant under fixed rent and 5) landlord. Each stage was seen as a way to increase skills and assets on his way to becoming a full owner. However, the theory was more of a story than an actual explanation of land tenure. Only some tenants have upward mobility. Roa observed that tenant and landlord’s managerial abilities influences contract choice. Under uncertainty, the tenant and landlord must make management decisions based on subjective judgements or opinions rather than facts. Tenants are compensated for making good managerial decisions. Under certainty, no subjective judgement is needed. Roa argued high skilled tenants will cash rent when farming is highly uncertain, since the potential gain from good management decisions is high. In contrast, high skilled tenants’ enter a share contract in a certain farming 14 environment because his decision making is not rewarded. Hallagen (1978) noted that the landlord offers the tenant different contracts to gather informaion about the tenant’s entrepreneurial ability because information is asymmetrical. Hallagen assumes that continuous monitoring of the tenant’s behavior has a high cost. Thus, the landlord is unable to learn the tenant’s entrepreneurial ability until after harvest. Tenants and landlords enter cowacts that brings both of them the highest income based on their management ability. Landlords must provide entrepreneurial inputs when the tenant is unable to earn the market return, which means landlords have to pay supervision cost. In addition, the tenant’s entrepreneurial talents are not displayed unless compensated. Hallagen argues that high skilled tenant’s earn more than their off farm income in a cash rem contract. Tenants pay all production cost and a cash rent to the landlord in a cash rent contract. Tenants also provide the entrepreneurial input. High skilled tenant pay all expenditures in a cash rent contract and still earn more than their off farm income. The income of a highly skilled tenant above his off farm wage is the payment of providing the entrepreneurial input. The landlord only receives the cash rent but pays no supervision cost in a cash rent contract. The landlord also only receives the market return because he provides no entrepreneurial input. Hallagen also argues that medium skilled tenants earn more than their off farm income in a share contract. All tenants must give the landlord a share of output as annual rent for the land. The landlord will only accept this share if it allows a rent above the market return. A team! will only accept his share if he earns at least his off farm income. The medium skill tenant has some ennepreneurial skill. Yet the medium skill tenant lacks talent to decide all the management decisions in a cash rent contract and still earn his off farm income. The medium skilled tenant has enough skill to decide some management decisions without always needing supervision. Therefore, landlords must make some management decisions. The landlord earns 15 a return higher than the market return for providing some entrepreneurial input. The tenant also receives a higher income than off the farm for lowering the landlords supavision cost in a share contract than would be necessary in a fixed wage contract. Hallagen also suggests that low skilled tenants have no management skill and need supervision to earn their off farm income leasing land. In addition, the landlord must make management decisions and supervise low skilled tenants to earn at least the market return on his land. Low skilled tenants refuse to enter a cash rent or share contract because they are afraid of earning less than their off farm income. Landlords do not want low skilled tenants in a share or cash rent contract because the landlord fears not receiving the market return. Low skilled tenants emer a fixed wage contract to receive their opportunity cost. The landlord with high management skill enters a fixed wage contract because they provides the entrepreneurial input and are compensated for their managerial skill. These landlords are unable to earn the market rent in the cash rent or share contracts with these low skilled tenants. The landlord offers different contracts for a short term as a low cost method to gather information on the tenant’s entrepreneurial input. The tenant will not display higher managerial ability unless he is compensated. The landlord makes fewer management decisions and spends lowers supervision cost when the tenant has some entrepreneurial ability. Therefore, the landlord and tenant maximize incomes entering a contract that matches the tenant’s skill. Ip and Stahl (1978) explain that the Opportunity cost of the landlord is an important factor in considering contract choice. They state that a landlord has an opportunity cost associmed with each hour he supervises. A landlord loses his off farm income for each hour supervises the 16 tenam. Ip and Stahl state landlord spends more hours supervising the tenant in a fixed wage than a share contract, and he supervises the tenant more hours in a share contract than a cash rent contract. 1p and Stahl assume the tenant shirks to increase his income. Therefore, a landlord incremes rental income for each hour he supervises because he lowers tenant labor shirking. In addition, 1p and Stahl also assume the landlord has a comtant off farm wage and his increase in rental income from supervising decreases when he supervises additional hours. Therefore, lp and Stahl argue that the landlord chooses the contract that maximizes his rental income and his off farm income. 1p and Stahl suggest that a landlord with a high off farm income prefers a cash rent contract to maximize the total of his rental and off farm income. The landlord with a high off farm income increases his total income by spending all his time working off the farm and leaving the tenant to farm unsupervised in a cash rent contract. This landlord increases his total income inacashrentcontractbecausehis gain from working each houroffthefarm is greaterthanthe increase in rental income he would receive per hour supervising the tenant in a share or fixed wage contract. lp and Stahl argue that a landlord with a medium off farm income prefers a share contract to maximize his total income. This landlord with a medium off farm income supervises for the hours when his gain in rental income from lowering tenant shirking is higher than his per hour off farm income. This landlord with a medium off farm income works hours off the farm when his gain from supervising per hour is less than his offfarm income per hour. Lastly, 1p and Stahl argue that a landlord with a low off farm income prefers a fixed wage contract to maximize his total income. This landlord receives a higher income per hour supervising the tenant than he could earn per hour working off the farm for all his available labor hours. Many studies have shown the importance of relationships on terms of trade. Sen (1977), Siles (1992), and Robison and Hanson (1995) show how relationships influence labor incentives, credit, and risk aversion. Sen’s (1977) study of China showed that commitment enhancing rewards can increase work motivation and production performance instead of an increased wage or bonus. Siles (1992) showed the effect of relationships on the credit market. His study showed that bankers are more likely to lend to farmers they have a close relationship, or they will lend to farmers they have a close relation at a lower interest rate. Robison and Hanson (1995) showed the effect relationships have on decisions with catastmphic risk consequences. Their study concluded that individuals’ decisions to accept the possibility of a catastrophic risk, the event of a large loss, are influenced by relationships. Economists have also shown a high incidence of leasing between relatives. Ely and Galpin (1919), Boehlje (1973), Bratton and Berkwitz (1976), and Carlston and Dillman (1983) all have reported many cases of related individuals leasing. Carlston and Dillman (1983) observed tenants were related to 50 percent of the absentee landlords and 60 percent of the local landlords in Western Washington and Northern Idaho. Further, 72 percent of the absentee landlords atained land ownership from a relative. In addition, Carlston and Dillman observed farmers make small land and machinery investments when they plan to sell their farms to non relatives. In contrast, farmers make large land and machinery investments when they plan to transfer ownership to their children. Further, tenants depleted the land less or used stronger erosion control techniques when they were related to the landlord than when they were not related. Ely and Galpin concluded the primary motivation of landlords to lease was to transfer the 18 land as inheritance to relatives. Ely and Galpin also argue regions with older retired farmers have more leasing than areas new to farming with younger landlords. Regions with older landlords lease more than regions with younger farmers because leasing is used to transfer ownership to relatives. Therefore, regions with farmers will lease less because younger farmers me not ready to transfer ownership. These studies on related individuals leasing suggests relationships also play a role in the leasing market. However, landlord and tenant relationships have not been incorporated into leasing or contract choice models. Gwilliams (1993) was one of the only contract choice models to have incorporated relationships. Gwilliams argued that landlords and tenants had a higher tendency to share lease when they had a close rather than a distant relationship. Furthermore, the subject matters of these relationship studies are important considerations in current contract choice models. Each participant’s level of risk aversion, a tenant’s incentive to apply inputs , and a landlord’s return for helping finance the tenant’s production, are all important issues considered in the participant’s choice of a contract. Therefore, insight into how relationships affect contract choice may be found by examining how relationships affect terms of trade on subjects important to contract choice literature. 2.4. 8mm Economists have developed many interesting models of contract choice. In early models, economists questioned if share contracts were inferior because the tenant applies fewer inputs and produces fewer outputs. In latter models, economists view that the tenant and landlord would have equal incomes, use the same amount of inputs, and produce the same level of output in bod: the cash rent and share contracts. However, why one contract was preferred to the other was not 19 explained. Economists now search for factors that influence the tenant and landlord to prefer one contract to another. In current models, economists have included, risk aversion, land quality, output division costs, the tenant’s management skill, and the landlord’s opportunity cost as a factor that affects contract choice. In addition, relationship studies have shown that relationships may play a role in contract choice. However, relationships have not yet been included in contract choice models. Therefore, the last section of this chapter displayed findings of studies on relationships in the leasing market and related studies on subjects important to contract choice literature. CHAPTER3 METHODOLOGY 3-1- W Economists have presented many different and sometimes conflicting theories of leasing behavior. To comribute to existing leasing studies, this research will investigate the current lease market for farmland and identify factors that influence the participants leasing behavior. This information is intended to aid in future development of a contract choice model that is consistent with empirical data. This chapter explains the questionnaire design and survey method used to collect data on farmland leasing behavior. The first section describes the questionnaire. The second section describes the survey population. The second section also explains why the survey population used was chosen. The third section explains the sampling process, the respondents rate of response, characteristics of respondents and non-respondents, and the geographical area included in this study. The fourth section explains how the qualitative data collected in the survey was organized into factor categories. The fourth section also describes each of the category the respondent’s reported influenced their lease decisions including: why landlord’s decide to lease; why landlords who lease prefer a cash rent or share contract; why tenants who lease prefer a cash rent or share connect; and how tenants and landlords who lease in a share contract determine input and output shares. The last section is a summary. 20 The survey objectives call for finding out both quantitative data on current characteristics of the leasing market and qualitative information on factors that relate to more complex leasing issues. Therefore, the design of the questionnaire must get both qualitative and quantitative data. A telephone interview was used to collect data because of its ability to explain better and interpret the survey to the respondents. The questionnaire and the phone script were written for a 10-15 minute survey. A pre-survey of Michigan county agents provided feed back on the questionnaire and interview process. This feedback was used to revise the questionnaire and phone script. The final questionnaire collected quantitative data on: a) the percentage of leased farmland; b) percentages of leased farmland that is cash rented or share leased; c) levels of cash reds: and d) landlord and tenant’s input and output shares in a share contract. The interviewer used open-ended questions to gather qualitative information on: a) factors that influence the landlords’ decision to lease; b) factors that influence landlords who lease to prefer either cash rent or a share contract; c) factors that influence tenants who lease to prefer either a cash rent or a share contract; and d) factors that influence how tenants and landlords who share lease determine input and output shares. The questionnaire used in the survey is included in Appendix A. 3.3 W The geographic area covered in the survey was chosen to be large enough to differentiate between general factors that affect leasing practices and local anomalies. The geographic region selected for the survey with the required variability was the North Central Region of the United 22 States (NCR). This area includes the highest amount of leased farmland and the greatest number of landlords and tenants in the United States according to the 1987 US. Census. The NCR, according to the USDA Extension Designation includes 12 states: North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, Indiana, Michigan and Ohio. The survey population most qualified to respond to our survey was determined to be the agricultural extension agents in the NCR. Therefore, the survey population was selected from the agricultural extension agents listed in the Extension Department Directories of the NCR. Postcards explaining the objective of the survey and a notice that the agent would be contacted by phone were then mailed to the agents included in the sample. 3.4 MW Each agricultural extension (AE) agent is responsible for extension activities within his extension area. The size of an AB agent’s extension area varies across the NCR states. Each state contains between four and nine extension regions. An extension region includes between 13 and 23 counties. Sometimes extension regions are organized into two to four districts, although infrequently districts may overlap into two or three extension regions. A district contains between five and 15 counties. Extension regions may also consist of five to 10 county clusters. Clusters contain between two to four counties. The survey population consisted of four types of AE agents: 1) county agents who are responsible for the extension activities of one county; 2) cluster agents who are responsible for the extension activities in a county cluster; 3) district agents who are responsible for the extension activities in a district; and d) regional agents who are responsible for the extension activities in the region. 23 Since each state contains extension regions, the extension region is the unit of observation. To understand the leasing conditions of each region, different numbers of AE agents were contacted in each region because the size of an AB agent’s extension area varied across the NCR. Each AE agent explained in the interview the leasing conditions in their entire extension area. Fewer agricultural agents were sampled in a region when the extension area of an AB agent was large because of fewer AE agents to sample. Only a few district agents or one regional agent is found in an extension region. Therefore, all of the district and regional AE agents were included in the sample to make sure all extension regions in the NCR were included in the study. Many cluster or county agents are found in an extension region. Therefore, a target number of 20 responses per state were established when a state had only county or cluster agents in order adequately to represent each region in the research. Table 3.1 shows the total number of AB agents in each state of the NCR asked to participate in the study and the respective extension area of each AE agent asked to participate. 24 I‘leSJ Weffluentsaekedteparticipate inthesttdyasyextuimarealll state) _ timer of agents by extension area State Agents in Comty agent Cluster agent District agent Regional agent swle 1 comty 2% comties Illinois 6 0 0 0 6 Michigan 7 O 0 2 5 North Dakota ' 29 as 1 o o ltimesota 31 31 0 0 0 Nebraska 32 22 10 0 0 Kansas 37 27 8 1 1 loan 1.8 36 0 12 0 South Dakota 54 44 6 2 2 Hisconsin 54 S1 3 0 0 Indians 55 SS 0 0 0 “lie 59 55 I. 0 0 Itissouri 25 Na Na his his total 1.37 31.9 32 17 16 _— L As shown in table 3.1, 426 AB agents in 69 extension regions of the NCR were asked to participate in the study. The number of agents sampled in each state was inversely related to the size of the agent’s extension area. The agents with the most counties in their extension area, Illinois and Michigan, had the lowest number of agents asked to be in the study. In contrast, the agents in Indiana, Ohio and Wisconsin, with the fewest number of counties in their extension areas had the highest number of agents who were asked to participate in the study. The extension areas of the AB agents who were asked to participate in Missouri were not listed in the state’s extension directory. 3.5. MW AB agents were contacted and interviewed over a 4-week period. The respondents were asked to participate at the time of the phone-call or to reschedule a more convenient time. An 25 agent who completed the interview was counted as a response. The agent’s responses were recorded on the questionnaire sheet during each interview. As mentioned previously, each state extension department is organized differently. Usually, a district or regional agent was called upon often to be interviewed because fewer agents are in an extension region. In contrasts, county or cluster agents were called upon a maximum of two or three times, then a different agent was contacted because many AB agents are in the extermion region. Consequently, regions with few AB agents had a higher response rate than regiom with many counties or cluster agents. When only districts or regional agents were found in the regions of a state, a 100% response rate was attempted to ensure the region was represented in the study. When many counties or cluster agents were available in the region of a state, a target number of 20 responses per state were established to ensure the region is represented in the survey. However, no specific response rate was targeted. Therefore, a new county or cluster agent was included in the sample to save time and phone costs when these AB agents were not available after two or three call- backs. Table 3.2 displays the number of AB agents who were asked to participate and the number of AB agents who responded in the NCR. 26 ‘lble 3.2 tier of E gusts asked to participate uni lilo W is] state — — State litter of Miner of Response rate agents asked agents the responded lllinois 6 6 100% Michigan 7 7 100% Morth Dakota 29 18 62% Mimsota 31 17 55% Mebraska 32 20 63% Kansas 37 23 62% ions 68 23 68% South Dakota 56 23 63% Uiscortsin 56 17 31% Indiana 55 20 36% (lilo S9 23 39% Missouri 25 16 56% Total 637 211 68% As shown in the table, a total of 211 agricultural agents responded out of 437 agents asked to participate in the study representing a 48 percent response rate. Illinois and Michigan, the states with the lowest number of agents asked to participate, had the highest response rates of 100 percent. The states with the highest number of agents in each extension region had the lowest response rates such as Ohio (39 percent), Indiana (34 percent) and Wisconsin (32 percent). The agents responded for their entire extension area. Therefore, the quality of response may vary because agents responded for areas of different sizes. Usually, the regional agents were very experienced and many had conducted their own studies of local leasing practices and rental rates. These agents had little trouble responding for their extension region though some regions comained as many as 23 counties. However, the variation remains unknown within an extension region because the respondent only gave one average response for the entire region. 27 The district agents were very experienced and had little trouble responding for their extension district. Most of these agents were farm specialists. These district agents were very familiar with the local leasing practices, rental rates, and the input costs and farming practices in their extension area. Since the unit of observation is an extension region, the responses of district agents within an extension region were averaged to generate regional results for the analysis. Although, similar to the regional agents, the variation of the agents response within an extmsion district is unknown. The county and cluster agents were also very familiar with the local leasing practices and rental rates in their county or counties. Since the unit of observation is an extension region, the responses of county and cluster agents within an extension region were averaged to generate regional results for the analysis. Therefore, the reliability of these averages to the true mean is unknown since only a few counties or cluster agents responded per region. Table 3.3 shows the number of counties the AB agents described in their responses for the survey, the average number of counties described per responding AB agent, and the types of AB agent responding in each state of the NCR. 28 Tfile 3.3 Ides- of gents also responded accordion to their extetuim area all aver-us radar of comties covered is] Wit. went _ timer of each type of agent State W of Average I”? of comties radar of responding described comties 099"“ Cotnty Cluster District Regional bY described agents agents agents agents respondents per respondent lllinois 102 17 6 0 0 D 6 Michign 86 12 7 0 D 2 5 Morth Dakota 19 1 18 17 1 0 0 Mlmeeota 17 1 17 17 D D D Mebraska 31 2 20 16 6 0 0 Kansas 62 3 23 16 7 1 1 love 86 6 23 13 D 10 0 South Dakota 25 1 23 19 2 D 2 Misconsin S3 3 17 16 3 0 0 lndiana 20 1 20 20 O D 0 mio 26 1 23 21 2 D 0 Missouri 61 6 16 2 11 1 0 Total 586 3 211 151 32 16 16 The two hundred eleven agents completing the survey included: 151 county agents, 32 cluster agents, 14 district agents, and 14 regional agents. These agents described leasing conditions in 584 counties of the NCR. The average number of counties described per AB agent in the NCR was three counties. The average number of counties per agent varied considerably among states because of the different types of agents. The respondent’s average extension area ranged from a low of one county per agent in Ohio, Indiana, South Dakota, Minnesota, and North Dakota to a high of 17 counties per agent in Illinois. The states with small average extension areas per agent were composed of mainly county agents, while the states with large extension areas per agents consisted of districts or regional agents. The two hundred twenty six AB agents not responding to the survey included: 200 county agents, 11 cluster agents, and 4 district agents. The types of the eleven AB agents in Missouri were unknown because of limitations in the states extension directory. Non-respondents were typically county or cluster agents although a few district and regional agents failed to respond. 29 In contrast, more regional or district agents responded because a 100 percent response rate was targeted since so few of these agents are in an extension region. The extension region is the unit of observation. The number of agents reporting in an extension region varied with the agent’s extension area. In table 3.4, column 1 shows the number of extension regions in each state of the NCR. Column 2 shows the number of regions in each state described in full or part by a responding agent or agents. Column 3 shows the percentage of regions in each state that agents described in the study. Column 4 describes the total number of counties in each state. Column 5 shows the number of counties in each state that respondents described leasing conditions. Column 6 shows the percentage of counties in each state described by the respondents in the study. Tble 3.6 liter of courties covered by the reaporaiim agents extenion areas ewes-ed uith the total radar of cotnties per state State mr of litter of Percentage Total Miner of cotnties Percentage of regions regions of regions matter of covered by cotnties covered by per state included covered comties responding agent responding agent illinois 6 6 100% 102 102 100% Michigan 6 6 100% 86 86 100% Morth Dakota 6 6 100% 56 19 35% Mimesota 6 5 83% 89 17 19% Mebraska 5 5 100% 93 31 33% (“as 5 5 100% 105 62 59% ioua 9 9 100% 99 86 87% South Dakota 6 6 100% 67 25 37% Hisconsin 6 6 100% 68 S3 78% lndiana 5 5 100% 92 20 22% this 5 5 100% 88 26 27% Missouri 8 8 100% 115 61 53% Total 69 68 99% 1056 586 55% 30 The agents described leasing conditions in 584 of the 1056 counties in the NCR that represented 55% of the counties in the NCR. In addition, the respondents described extension areas in 68 of the 69 extension regions of the NCR. Only the region in Northern Minnesota was not represented in the survey because it did not have any agricultural agents. This is presumably from the low agricultural production in the region. The percentage of counties covered by the agents’ responses varied from a low of 19 percent in Minnesota to a high of 11%) percent in Michigan and Illinois. 3.8. QraanlntinnnLLhelactnLamuninss The survey collected quantitative and qualitative data of the lease market in the NCR. Quantitative data collected from each agent within an extension region was averaged to provide a single figure for the region. However, the qualitative data needed to be grouped into major categories to report the results. First, the qualitative responses were recorded exactly as reported by the respondents. Then, the responses were grouped into categories with similar characteristics. Finally, the factors with similar economic interpretations were grouped. Table 3.5 describes the factor categories that influence the landowner decision to lease. 31 Table 3.5 Factors influencing the landlords’ decision to lease Factor Interpretation 1. Landowners’ age 2. Landowners’ farming experience or distance from farm 3. Landowners’ motivation to purchase farmland for an investment 4. Landowners’ off-farm income opportunities 5. Landowners’ cost structure 6. Landowners’ motivation to purchase farmland for a hobby or recreation Landowners tend to lease more often as they grow older. Older landowners lease because of health problems, loss of spouse, or a desire to retire. Landowners tend to lease more often as they have less experience or live further away from their farm. Inexperienced landowners lease because they do not have the skills or equipment to farm. Landowners who purchase land as investments often have no desire to farm. More investors purchase farmland to lease as the return from leasing and selling farmland increases compared with other investments. Landowners tend to lease more often as they have better off farm opportunities. These landowners may be experienced or inexperienced. However, experienced landowners must have a higher off farm opportunity cost to induce them to lease since they earn a higher farming income. Experienced landowners tend to lease more ofien as their cost of farming increases. Landowners who have small land bases or older equipment often lease because they have high cost per acre and low farming incomes. Landowners who purchase land for a hobby or recreation are more likely to lease as their benefits from farming or recreation decrease or the available rent in the area increases. 32 Table 3.6 describes the factors influencing landlords and tenants who lease to prefer a cash rentor a share contract. Table 3.6 Factors influencing landlords and tenants’ who lease to prefer a cash rent or share contract Factor Interpretation 1. Landlords’ and tenant’s farming experience Landlords are more likely to prefer a cash rent contract as they or their tenants have less farming experience. Tenants are more likely to prefer a cash rent contract as they have more farming experience. Landlords and tenants prefer a share contract as they have less farming experience. 2. A landlord’s and a tenant’s level of Landlords with high risk aversion tend to cash absolute risk aversion and expected lease more often as their level of positive risk income variance 3. Landlords’ and tenant’s financial security 6. Relationship between the landlord and tenant 7. Land quality aversion or expectation of income variance increases. Tenants with high risk aversion tend to share lease more often as their level of positive risk aversion or expectation of income variance increases. In the opposite case, landlords and tenants prefer the other contract. Landlords are more likely to prefer a cash rent contract as they are less financially secure. Tenants are more likely to prefer a share contract as they are less financially secure. Landlords prefer a share contract as they are more financially secure, and more financially secure prefer a cash rent contract. Landlords and tenants tend to lease more often in a share contract when they have a close relationship. Landlords and tenant tend to lease more often in a cash rent contract When they have a distant relationship. Land quality influences the tenants and landlords choice of a contract. However, the effect land quality has on the participants contract preference varies over areas. 33 The factors that influence how landlords and tenants who share lease determine input and etuput shares are shown in table 3.7 along with a brief interpretation of each factor. This 3.7 Factors deteninim landlord ltd tan-it inst/output shares in a share attract Factor interpretation 1. Landlord and tenant contributions of Landlord and tenants agree to output shares based on inputs the value of the inputs each contributes toward prediction. The landlord receives a higher output share as the value of his land increases comared with the tenants equipment and labor cost. The split of the other variable imut costs (seed, fertilizer and agrochenicals) is usually based at the output share. 2. Tradition Landlord and tenants agree to imut and output shares consistent with local tradition. These imut and output shares are based on past rules of I“ that have evolved from historical farming practices, productivity levels, and input cost. 3. Land productivity Landlord and tenants agree to output shares based on the land's past prochsctivity levels. The landlord receives a higher output share as the average of his past yields increases. 6. Fixed imut and output shares with Landlord and tenants agree to fixed imut and output side arrange-ants shares but the share contract is altered by side arrangements. The landlord receives more beneficial side arramenents as more tenants comets for the land. Side arrangements include atoning the yard, mending fences, and privilege rents. A more detailed explanation of each factor and the frequencies each factor was reported in each state will be described in Chapter 5. 3.9. 5mm This research conducted a telephone interview to collect quantitative and qualitative data. A telephone survey was chosen because it allowed more detailed data to be collected than would be a mail survey. A telephone survey allows more complex qualitative data to be collected in a short length of time. The NCR was selected to be the area for the study. The NCR was selected because of its importance in agricultural production and the large amount and diversity 34 of leasing activity. AB agents were chosen for the study because of their knowledge of local leasing conditions and leasing behavior. The sampling method used both target response rates and a target number of responses because of the differences in state extension organizations. Response rates varied in relation to the targeted goal of either high response or a specific number of responses. The agents described local leasing conditions within 68 of the 69 extension regions and 55% of the counties in the NCR. The quantitative data was averaged per extension region to show regional results. Qualitative data was organized into factor categories based on the similarities of responses within in each factor category. A detailed description of each factor and the frequency each factor was listed for each state is reported in Chapter 5. CHAPTER4 DESCRIPTION OF THE LEASING MARKET IN THE NCR 4-1- Introduction This study collected data on tenant and landlord leasing behavior to help answer the question of why cash rent and share contracts coexist. Landlords and tenants contract preference partly depends on the terms of the cash rent and share contracts. Therefore, this study also collected data on the characteristics of the local leasing markets within which the tenant and landlord make their contract choice. In this chapter, the data about the leasing characteristics of the extension regions in the NCR is reported. The local leasing characteristics reported for the extension regions of the NCR are shown in color-coded maps or tables. This chapter is organized in two main sections. The first section of this chapter describes leasing characteristics found across the extension regions of the NCR. Discussed in section one: 1) the crops tenants grow; 2) the percentages of farmland that landlords lease; 3) the percentage of leased farmland that landlords lease in a cash rent contract; 4) the cash rent a landlords receives in a cash rent contract; 5) the input and output shares accepted by landlords and tenants in a share contract. The second section of this chapter examines the correlation between different leasing characteristics across the regions of the NCR. Section two also discusses: l) the correlation between cash rents and output shares; 2) the correlation between cash rents, output shares, and the percentage of farmland cash leased and; 3) the correlation between cash rents, output shares, 35 36 and the percentage of farmland leased. Each agent who responded to a telephone survey reported the characteristics of leasing markets found in his or her local extension area. In this chapter, the data about the leasing characteristics is reported by extension region because the number of agricultural extension (AB) agents are found in each extension and the number of AB region who responded in each extension region varies in the extension regions of the North Central Region (NCR). The data presented for each extension region is constructed in two ways. The data for each extension region is an average of all the responding AB agents’ responses within the extension region when the data collected is a numerical figure. In contrast, the data for each extension is the most frequently reported response of all the responding AB agents’ within an extension region when the response was a non quantitative response. The respondents reported that tenants grow different crops on leased farmland in extension regions of the NCR. The crops that tenants grow most often on leased farmland in the extension regions of the NCR are shown in Figure 4.1. Bach extension region was categorized by the types of crops that the tenant grows on leased land within the extension region. Bach extension region is categorized as: 1) an extension regions where tenants grow sugar beets (brown area); 2) an extension region where tenants grow corn, or soybeans (blue area); 3) an extension region where tenants grow wheat, barley, or sorghum (red area); and 4) an extension region where tenants grow hay (yellow area). 37 Extension regions that have more than one category of crops being grown most often on leased farmland within the extension region were given more than one color classification. In cases where the respondents failed to report crop type, the USDA’s agricultural statistics report (1994) was used to decide the crops most often grown in the extension region. 38 M02 05 mo Samoa song...“ ofi E :3on 380 3. Earn flooauomaw I he chafing vac hove“..— Jooém " asoahnu «as so 0 I Rubraiit to. :6»... s .2. w. . 39 Figure 4.1 shows that tenants in the extension regions of the corn belt states (Iowa, Illinois, and Indiana) grow corn and soy beans. Figure 4.1 also shows that tenants in some of the extension regions bordering the corn belt States (Missouri, Ohio, Nebraska, South Dakota, Minnesota, Michigan, and Wisconsin) also grow corn and soy beans. Tenants in the extension regions of the great plains state (North Dakota, South Dakota, Nebraska, and Kansas) most often grow wheat and either barley or sorghum. In addition, extension regions directly bordering the great plains states in Southern Missouri and Northwestern Minnesota also grow wheat. Extension regions in Southern Illinois next to extension regions of southern Missouri also grow wheat. Tenants in many extension regions of the lake states (Minnesota, Wisconsin, Michigan, and Ohio) often grow hay. Tenants in western South Dakota and eastern Missouri also grow hay though they are not in the lake states. Tenants in some extension regions grow more than one crop classification. Tenants in many extension regions of the lake states that border the corn belt grow corn, soybeans, and hay. Tenants in Southern Missouri and southern Illinois grow both wheat and corn. Finally, tenants in a few scattered extension regions of western Minnesota, western Nebraska, and Eastern Michigan grow sugar beets. The respondents reported the percentage of farmland acres that landlords lease in their extension region. The percentage of farmland acres that landlords lease in each extension region of the NCR is shown in Figure 4.2. Leased land includes all land leased for agricultural production such as dry land, pasture, irrigated, and any other agricultural land. 40 Each extension region was ranked from lowest to highest by the percentage of farmland acres that landowners lease in the extension region. Then each region was classified into one of three percentile groups: 1) an extension region that has high leasing activity, where landlords lease from 51% to 78% of the farmland acres (blue area); 2) an extension region that has medium leasing activity, where landlords lease 39% to 50% of the farmland acres; and 3) an extension region that has low leasing activity, where landlords lease 10% to 38% of the farmland acres (yellow area). The actual percentage of farmland leased in each extension region is shown in Appendix B. 41 MO Z 2t mo meomwom commeoim 2: E 833 vain—am mo owfiuooaom a... 2:»:— sxowmsxomc .53 l seaming sense I $3585.29: I . . In. . . . . I :s. 9.3:...5315 . . a w . u — 42 Figure 4.2 shows the percentages of farmland acres that landowners lease in the extension regions of the NCR. This figure shows that each of the three categories of extension regions’ leasing activity is found in a distinctive location of the NCR. Landlords lease the highest percentages of farmland in a block of extension regions starting in the south eastern corner of the great plains running north eastwardly through Iowa and southeastward through Illinois and Indiana in the Corn Belt. A few scattered extension regions in western Nebraska, Northern North Dakota, and the extension regions on the Ohio/ Michigan border also have high percentages of farmland acres leased. Landlords lease medium percentages of farmland in a band of extension regions running on the northern and souther edges of the extension regions that have high leasing activity. The northa'n band of medium leasing activity extension regions starts in the southwestern great Plains running northeastwardly into northern Iowa and southern Minnesota and then through extemion regions of southwestern Michigan, western Indiana, and eastern Ohio. The southern band of extension regions runs in a semicircular pattern through Missouri. A few medium leasing activity extension regions are also found in North Dakota and South Dakota directly south of high leasing activity regions. landlords lease low percentages of farmland in extension regions found throughout most of the lake states and in the extension regions of the central great Plains. A few low leasing activity regions are also found in the center of the semicircular pattern of medium leasing activity extemion regions in Missouri. The respondents reported the percentages of leased land that landlords lease in a cash rent contract or a share contract in their extension regions. The percentage of leased land that landlords cash lease in each region of the NCR are displayed in Figure 4.3. The percentage of leased land that is share leased in each region of the NCR is simply the residual fraction of the percentage of leased land that is cash leased. Bach extension region was ranked from lowest to highest by the percentage of leased acres that landowners lease in a cash rent contract in the extension region. Then each region was classified into one of three percentile groups: 1) an extension region that has a high proportion of cash rent contracts, where landlords lease 71% to 99% of the leased land acres in the extemion region in a cash rent contract (yellow area); 2) an extension region that has a medium proportion of cash rent contracts, where landlords lease 50% to 70% of the leased land acres in the extension region in a cash rent contract (red area); and 3) an extension region that has a low proportion of cash rent contracts, where landlords lease 12% to 49% of the leased land acres in the extension region in a cash rent contract(blue area). The actual percentage of leased farmland that is cash leased in each extension region is shown in Appendix B. M02 05 mo muomwom nommnowxm 65 E womb—So EB :23 a 5 women. vfiwafifl mo omfifioaom n6 enema “reassess“: I nxfitsoc 5:82 I Savanna son I ‘! a .> ‘,