Rental spreads for share versus cash leases in Ilinois

Rental Spreads for Share versusCash Leases in IllinoisPeter J. Barry, Cesar L. Escalante, and LeeAnn E. Moss

Abstract

This study utilizes an expected utilityframework to conceptualize the risk-adjusted valuation of cash versus shareleases for farmers and landowners. Farm-level data then are used to empiricallyestimate the rental spread between theseleases in Illinois, and to econometricallyevaluate how these spreads are related torisks and other farm characteristics. Theresults indicate that non-risk factors likelyare the primary determinants of themagnitude and sign of the rental spread. In particular, high cash rent may be abidding strategy to control additionalleased acreage and thus expand farm size.

Key words: cash leasing, farmland control,risk, share leasing

Peter J. Barry is a professor of agricultural finance,Department of Agricultural and Consumer Economics,the University of Illinois at Urbana-Champaign;Cesar L. Escalante is an assistant professor in theDepartment of Agricultural and Applied Economics,the University of Georgia; and LeeAnn E. Moss is anassistant professor, Department of Agricultural,Environmental, and Development Economics, The OhioState University.

The long-standing practice of share leasingfor farmland, especially in Midwestern U.S.agriculture, is increasingly giving way tocash leasing and to combinations of cashand share leasing (Reiss; Barry, Moss,Sotomayer, and Escalante; Barry). According to the 2001 AgriculturalEconomics and Land Ownership Survey,cash payments instead of, or in additionto, crop shares characterized about 59%of farmland leases in Illinois during 1999,up from 37% in 1988 [U.S. Department ofAgriculture/National AgriculturalStatistics Service (USDA/NASS)].

The drivers of change primarily involverisk, income, managerial control(especially when multiple landownersare involved), and land value issuesfacing farmers, landowners, andprofessional farm managers who representthe landowners (Sotomayor, Ellinger, andBarry). These changes may stronglyinfluence the risk and financial positionsof the respective leasing parties.

Compared to fixed cash leases, shareleases offer farmers the opportunity toallocate yield risks and perhapsmanagement responsibilities tolandowners in the same proportion thatcrops and operating costs are shared. Atthe same time, however, the allocation ofreturns in the relationship would need tocompensate the landowner for theseinputs. The possible existence of a riskpremium in leasing arrangements iscomparable to the long-standing search forrisk premia in equity and commoditymarkets (Kocherlakota; Williams).

Other studies (e.g., Dasgupta, Knight, andLove; Cheung; Allen and Leuck) conclude

150 Rental Spreads for Share versus Cash Leases in Illinois

risk is of secondary importance in leasingarrangements relative to transactions costsand property rights. Little if any empiricalevidence is available, however, about thepotential spread between rent levels oncash versus share leases. The availabilityof such information would assist inevaluating the equitable terms andincentive characteristics of leasingarrangements and elucidate the riskmanagement dimensions of share leases.

The goals of this study are to empiricallyestimate the rental spread between cashand share leases in Illinois and todetermine how these spreads are related torisks and other farm characteristics. Aconceptual framework demonstrating thekey relationships is established in the nextsection. Data from the Illinois FarmBusiness Farm Management (FBFM)Association are used in the empiricalanalysis. The estimated spreads representthe rent paid by farmers and received bylandowners on cash and share leases,although the available data confine theanalysis to the farmer’s side of thetransaction. The article concludes with adiscussion of the implications of thefindings.

Conceptual Framework

The theoretical basis for the valuation ofcrop share versus cash leases by farmersand landowners can be demonstrated byexpressing the expected utility fromleasing under each rental arrangement. The goal is to suggest key attributes fromeach party’s perspective that couldinfluence the properties of the rentalspread, and thus serve as the basis forempirical testing. The demonstrationcan be aided by utilizing the mean-variance approach in which utility ismodeled by the negative exponential U(n) = 1 ! e!28n, where n is the net returnfrom leased land and 8 is the degree ofrisk aversion (Meyer; Robison and Barry). As Freund has shown, under normality,the utility expression is equivalent tomaximizing

(1) E[U(n)] ' E(n) & 82F2

n ,

where, in this case, E(n) and are theF2n

expected return and variance, respectively,from leasing.1

Let the farmer’s expected net income (n)(returns to labor, capital, andmanagement) under either cash or shareleasing be the expected value of production ( minus land rent, operating costs (oc),y )and transaction or agency costs (ac, as) forthe two leasing options (Barry et al.):

(2) n ' y & psy & (1& p)r & p(1& s)oc

& (1& p)oc & pas & (1& p)ac ,

where p = 1.0 for a share lease, andp = 0.0 for a cash lease; s is the landlord’sshare; and r is the fixed cash rent. Transaction costs and agency costs areclosely related, and as such will bereferred to as agency costs.

Under risk, are the expectedn and F2n

value and variance of net income, and yand are the expectation and variance ofF2

ythe value of farm production—the farmer’sprimary sources of risk. In a share lease,the variance of the farmer’s net income isreduced in proportion to the share rent,yielding net income variance of:2

(3) F2n ' (1& s)2F2

y .

Substituting (2) and (3) into (1), thefarmer’s expected utility condition undershare leasing is specified as:

(4) E[U(n)] ' (1& s)( y & oc) & as

&8f

2(1& s)2F2

y .

1 While the assumption of normality is forexpositional purposes, numerous studies havedemonstrated the conditions underlying the use ofthe mean-variance model (e.g., Meyer; Robison andMyers; Tsiang ). 2 Refer to footnote 2 of Barry, Moss, Sotomayor, andEscalante for a derivation.

Agricultural Finance Review, Fall 2002 Barry, Escalante, and Moss 151

For cash leasing, the variance of thefarmer’s net returns is written as:

(5) F2n ' F

2y .

Substituting (2) and (5) into (1) for cashleasing, the farmer’s expected utility isdenoted by:

(6) E[U(n)] ' y & r & oc & ac &8f

2F2

y .

The level of cash rent that yields thefarmer equal expected utility between ashare lease and a cash lease is found bysetting equations (4) and (6) equal to eachother and solving for r :

(7) r ' s( y & oc) % as& ac&8f

2F2

y [s(2 & s)].

The desired rental spread then is thedifference between the share rent and theexpected utility-equivalent cash rent:

(8) s( y & oc) & r ' ac& as%8f

2F2

y [s(2 & s)].

Inspection of (8) reveals that the rentalspread may directly reflect the farmer’slevel of risk aversion, the variability of cropreturns, the magnitude of the shares, andthe levels of agency costs. From thefarmer’s viewpoint, higher levels of riskaversion are associated with higher rentalspreads, and thus lower bids on cash rentsrelative to existing share rents. Less risk-averse farmers will offer higher bids oncash leases relative to share leases. Greater variability of returns on farmlandis associated with greater rental spreads,and thus lower bids on cash rents relativeto existing share rents. Similarly, a largerpositive (negative) difference between theagency costs on cash versus share leaseswould increase (decrease) the rentalspread.

Therefore, farmers who perceive lessvariability in returns, achieve lower thanaverage anticipated variability due to otherrisk management practices, or whoexperience higher agency costs on shareleasing would bid higher cash rentsrelative to expected share rents.

Similar expressions can be derived for thelandowner. His/her expected net incomefrom the leasing alternatives is representedby:

(9) n ' (1& p)(r) % p(sy ) & p(s)(oc) & pas

& (1& p)ac .

The landowner’s expected utility fromshare leasing is

(10) E[U(n)] ' s( y & oc) & as&8l

2s2F2

y ,

and from cash leasing is

(11) E[U(n)] ' r & ac ,

where 8l is the landowner’s level of riskaversion. Equating (10) and (11), andsolving for the rental spread yields:

(12) s( y & oc) & r ' as& ac%8l

2s2F2

y .

Differences in preferred spreads betweenthe farmer and landowner can bereconciled in a “market clearing” sense byjointly considering equations (8) and (12)and adding the market-clearing condition:

(13) SPf ' SPl ,

where for the farmer ( f )SP ' s( y & oc) & rand the landowner (l ).

Treating the share level (s) as the pricinginstrument, and assuming for simplicitythat as = ac, will lead to:

(14) s '28f

8l% 8f.

Substituting (14) for s in (8) and (12) yieldsthe following reduced form for the farmer’sand landowner’s equations:

(15) SPf ' ac& as %8f

2F2

y28f 8l

8f % 8l

2

and

SPl ' as& ac%8l

2F2

y28f

8f % 8l

2

.


The risk premium portions are the samefor these reduced-form equations:

282

f 8l F2y

8l % 8f2

.

The relative positions of the farmer andlandowner in the lease determination thendepend on their preferred spreads, giventhe variables in equations (8) and (12).

Suppose, for example, the risk-aversionlevels are bounded by the values observedby Babcock, Choi, and Feinerman for agamble (risky rent per acre) of $100 withequally spaced intervals within theboundaries, yielding 8 values of 0.00020,0.01553, 0.03087, and 0.04620. Further,assume the standard deviation is $30,agency costs on cash and share leases areequal, and rental shares are 1/2 each. The preferred rental spreads are given inTable 1 for the respective combinations ofrisk aversion.

For a risk-aversion level of 8f = 8l = 0.03087,the utility-equalizing spread for the farmeris given as

SPf '0.03087

2(30)2[0.5(2&0.5)]'10.42,

and for the landowner, using (12), is

SPl '0.03087

2(30)2(0.5)2' 3.47.

In this case, the farmer is willing to pay arental spread of $10.42 (or a utilityequivalent cash rent of $89.58 = $100 –$10.42), but the landowner requires aspread of only $3.47 to carry the risk fromsharing leasing (a utility equivalent cashrent of $96.53). They would thereforeselect a share lease.

In contrast, a cash lease would be selectedwhen 8l = 0.03087 and 8f = 0.00020,yielding spreads of $0.07 and $3.47 forthe farmer and landowner, respectively,with the level of cash determined bybargaining. Other lease selections areevident in Table 1, with share leases

predominating in this example given the1/2 shares and the particular levels of riskaversion.

A similar selection process would occur ifthe cash rent levels were marketdetermined based perhaps on anaggregation of reservation spreads forfarmers and landowners. A market rentfalling within the range of the spreadwould then determine lease selection,similar to the process above. Alternatively,a market rent outside the spread rangemight negate the contract unless agencycosts or other factors were offsetting.

Empirical Analysis

The empirical analysis first determinesmeasures of the rental spreads for Illinoisgrain farms, and then utilizes multipleregression to test how positive andnegative spreads are influenced bymeasures or proxies of the variables inequation (8) and by other structuralcharacteristics.

Farm-level data for 1995 through 1998from the Illinois FBFM Association areused in the analysis. Revisions in 1994 tothe FBFM accounting and reporting formatto emphasize the compilation and reportingof operator data rather than whole-farmdata now allow direct measurement of peracre cash rents and share rents paid byfarmers to landlords. These rentalpayment measurements were notidentifiable prior to 1995. Inconsistenciesover time, however, in the balance sheetcertifications of individual FBFM operatordata in multiple-operator farms (i.e.,partnerships) require the use of single-operator farms only in the econometricportion of the study’s analysis. Thisspecification reduced the number of farmobservations by about 20 per year.

The data are reported by FBFM in terms ofeach farm’s tillable acres and the “operatoracres,” thus reflecting whatever sharinglevels (1/2S1/2, 2/3S1/3) are employed inthe operator’s lease contracts.


Table 1. Preferred Rental Spreads for Alternative Risk-Aversion Levels, with Standard Deviation of $30, Expected Income of $100, and 1/2SSSS1/2 Share Lease

Farmer Risk Aversion ( 8888f)

Landowner Risk 0.00020 0.01553 0.03087 0.04620

Aversion ( 8888l) SPf SPl SPf SPl SPf SPl SPf SPl

0.00020 0.07 0.02 5.24 0.02 10.42 0.02 15.59 1.75

0.01553 0.07 1.75 5.24 1.75 10.42 1.75 15.59 1.75

0.03087 0.07 3.47 5.24 3.47 10.42 3.47 15.59 3.47

0.04620 0.07 5.20 5.24 5.20 10.42 5.20 15.59 5.20

For example, two acres leased under a1/2S1/2 crop share lease are equivalent toone operator acre. The per acre values ofshare rent, including governmentpayments and variable costs attributed asshare rent to the landlord, are determinedby calculating the difference between thelandlord’s share of crop returns andvariable costs per share leased acre.3,4

Cash rent per acre is calculated bydividing a farm’s total cash rent paid bythe number of cash rented acres.

The calculated share rent is then comparedto the farm’s average cash rent paid on

cash leased acres to determine the rentalspread. If the share and cash rentsaveraged $121.43 and $115 per acres,respectively, then the rental spread wouldbe $6.43 per acre, or 5.59% of the cashrent value (see footnote 4).

The descriptive and econometric analysesemploy two different measurementapproaches to determine the rentalspreads. In the descriptive portion, therental spread is measured as thedifference between the mean share rentand the mean cash rent for all balancesheet-certified, single-operator FBFMfarms for the 1995S1998 period. Thesefarms totaled 1,598, 1,805, 1,879,and 1,914 for 1995 through 1998,respectively.

The spread measurement approach in theregression analysis is based on thosefarms that utilize both types of leases (255farms). Constraining the data in this latterfashion implies a clearer opportunity forthe farmer to choose between the leasingarrangements, and may reflect moreaccurately and realistically the influence ofthe independent variables on the rentalspread.

Further adjustments in measuring spreadsin the descriptive case reflect the differentarrangements in the sharing of operatingcosts. Previous surveys and studies(Bullen; Reiss; Reiss and Koenig) indicateconsistent sharing of the costs of fertilizer,pesticides, seed, and other crop expensesbetween farmers and landlords in Illinois.

3 Under share rental arrangements in Illinois,government payments generally are shared betweenthe operator and the landlord in the same proportionthat crops are shared. 4 To illustrate the share rent calculations, consider afarm with 1,000 tillable acres, 700 “operator acres,”60% of total acres under crop share leases, 20% undercash leases, and 20% owned by the operator. In thiscase, the 700 operator acres less the 400 acres ownedand cash rented leaves the need for 300 more operatoracres and implies that the remaining 600 share rentedacres must be on a 1/2S1/2 lease. The operator’s cropreturns and expenses are $250,000 and $80,000,respectively. The ratio of operator acres to total acresis 0.70 = 700/1,000. Crop returns for the entire farmthen are $357,143 = $250,000/0.70. The value of thelandlord’s share is the difference between the farmand operator crop returns, or $107,143 = $357,143 –$250,000. Similarly, crop expenses for the entire farmare $114,286 = $80,000/0.70, and the landlord’s shareof crop expenses is $34,286 = $114,286 – $80,000. The net value of the share rent paid to the landlord isthe difference between his/her values of crop returnsand expenses, or $72,857 = $107,143 – $34,286. Thenet value of share rent per acre is $72,857 divided by600 share leased acres. The result is a share rent peracre of $121.43 = $72,857/600.


Inconsistencies arise, however, in the costsharing of drying, storing, and insuringcrops. Sharing of these costs occurs insome cases and not in others, but neithercondition is observable in the FBFM data. Accordingly, the rental spreads aremeasured with and without the sharing ofthese latter expenses.

To ensure that cash rent payments are notunduly influenced by family and personalrelationships between the leasing parties,the cash rent values are constrained toexceed $10 per acre.5 Rental levels belowthis amount are excluded from theanalysis. Finally, the regressions are runfor the data set as a whole, and for thethree classes of farms that differ materiallyfrom each other in terms of soilproductivity.

Descriptive Results

Table 2 reports the per acre averages ofcash rents, share rents, and rental spreadsfor the 1995S1998 period for each of threefarm classes: (a) North and Central Illinoisgrain farms with high soil ratings (86 to100), (b) North and Central Illinois grainfarms with low soil ratings (below 86), and(c) Southern Illinois grain farms.6 Thesethree classes distinguish among farms thatdiffer in soil productivity and potentialyield variability, with Southern Illinoisfarms having the lowest soil quality andhighest yield variability (Barry, Escalante,and Bard). Moreover, the Southern Illinoisregion is characterized by the 1/3S2/3

share lease, while the 50S50 share leasepredominates in North and Central Illinois.

The unadjusted rental spreads average$3.39, $2.25, and !$2.63 per acre for thehighest to lowest soil quality classes,respectively (Table 2).7 The averageadjusted rental spreads, reflecting thenon-sharing of drying, storage, and cropinsurance costs, are reduced to !$9.55,!$8.71, and !$8.65 per acre, respectively.

As indicated by the coefficients of variation(Table 2), the rental spreads varysubstantially from year to year, reflectinglarge swings in farm income which wouldaffect the values of share rent. The yearsfrom 1995S1997 were considered strongnet farm income years in Illinois, while1998 was a comparatively low income year(Illinois FBFM). Accordingly, the annualaverage unadjusted share lease premiumsfor North and Central Illinois/high soilquality farms were $8.64, $32, $8.90, and!$35.98 for the 1995 through 1998 years,respectively.

Regression Analysis

Ordinary least squares regressiontechniques are employed to explore theinfluence of several key variables on therental spreads for those FBFM farmsengaging concurrently in both cash andshare leasing.8 Most of these variablesarise directly from those in equation (8),while others relate specifically to key riskfactors and control practices that havebeen suggested as important to farmers. The general form of the regression model isexpressed as follows: 5 The $10 figure is subjectively determined based on

discussions with FBFM staff. 6 Each farm participating in the FBFM systemreceives a soil productivity rating. The rating is anaverage index representing the inherent productivityof all tillable land on the farm. Individual soil typesin Illinois are assigned an index, for a base level ofmanagement, ranging downward from 100. Theseindices, compiled for hundreds of soil types in Illinois,are calculated by relating estimated crop yields foreach soil type to benchmark average yields for nine ofthe more productive soils in the state. Compared toother regions of the United States, land quality inIllinois is relatively homogeneous, although significantvariations occur within regions of the state.

7 Statistical tests show that all means except theunadjusted premium for the South are significantlydifferent from zero at the 95% level, and among thepairings of regional means, only the pairs ofunadjusted premiums between the North Central/Highand South and between the North Central/Low andSouth differed significantly. 8 A binomial logistic version of the model, where thelogit variable is based on the “event” under which thefarm experiences a positive rental spread, generatedsimilar econometric results.


Table 2. Descriptive Results for Rental Values for Three Illinois Grain Farm Classes, 1995SSSS1998 ($/acre)

North & Central Illinois(High Soil Rating)

North & Central Illinois(Low Soil Rating) Southern Illinois

Description Mean S.D. C.V. Mean S.D. C.V. Mean S.D. C.V.

Cash rent 125.05 4.40 0.04 107.33 3.21 0.03 76.41 1.78 0.02

Unadjusted share rent 128.44 27.52 0.21 109.59 18.58 0.17 73.78 19.41 0.26

Adjusted share rent 115.50 25.66 0.22 98.63 19.19 0.19 67.76 19.53 0.29

Unadjusted share lease rental spread 3.39 28.44 8.39 2.25 19.85 8.82 !2.63 18.67 !7.10

Adjusted rental spread !9.55 26.64 !2.79 !8.71 17.56 !2.02 !8.65 18.87 !2.18

Notes: S.D. is standard deviation; C.V. is coefficient of variation.

RSi ' $0 % jK

k'1$k Xk,i % gi ,

where RSi is the ratio of rental spreads tocash rent, X1SX4 are variables arisingdirectly from the conceptual model, X5SX6

are financial variables, and X7SX9 are riskcontrol practices. Specifically, X1 isincome variability, X2 is the farmer’s age(a risk-aversion proxy), X3 is cash rent peracre, and X4 is the cash-share acres ratio(a proxy for agency costs). Variables X5

and X6 represent net worth and the debt-to-asset ratio, respectively. Risk controlpractices included in the model are soilrating (X7), machinery investment per acre(X8), and insurance expense per acre (X9).

Mean values calculated over the four-yearsample period are used for the dependentvariable and the explanatory variables,except for the income risk variable. Plausible, anticipated relationshipsbetween the rental spreads and therespective variables are considered in thenext section.

Model Relationships

Greater income variability, measured bythe coefficient of variation of the farmer’snet income over the 1995S1998 period,could be associated with a larger rentalspread reflecting the risk-reducingattribute of share leases. The farmer’s agecould serve as a proxy for the level of risk

aversion, where older ages are associatedwith lower spreads.

Table 3 suggests the inclusion of the levelof cash rent as an explanatory variable inthe model. Mean values of theindependent variables for spread classesranging from !$50 per acre to above $50per acre are reported. One feature is theinverse relationship between the rentalspreads and the mean cash rents. Apparently, a willingness to pay a highcash rent is a dominant factor affecting therental spreads. Thus, the level of cashrent is included as one of the independentvariables.9

While no direct measures of agency costsare available, the cash-share acres ratiocould reflect the relative agency costs ofthe two lease types (e.g., lower agencycosts on cash leases are associated with ahigher cash-share ratio and a lower rentalspread). Alternatively, greater reliance oncash relative to share leases could increasethe rental spread, reflecting the greaterrisk exposure of cash leasing for thefarmer.

Several authors have investigated the roleof net worth and the debt-to-asset ratio onthe choice between cash and share leases

9 Based on results of a correlation analysis, the cashrent variable and the dependent variable are onlyabout 30% correlated, thus avoiding the possibility ofsimultaneity bias.


Table 3. Mean Values of Explanatory Variables Categorized by Unadjusted Rental Spreads, 1995SSSS1998

Rental SpreadNo. ofFarms

Size(tillableacres)

SoilRating

Age(years)

NetWorth

($)

Debt-to-Asset Ratio

Below !$50 10 1,413 77 49 780,892 0.2951

!$49 to !$25 31 905 76 49 541,437 0.4387

!$24 to $0 95 832 77 47 457,289 0.4367

$1 to $25 68 864 78 48 592,433 0.3126

$26 to $50 44 812 83 49 713,540 0.3689

Over $50 7 1,049 89 44 935,601 0.3102

Total Farms 255

(Sotomayor, Ellinger, and Barry; Bierlen,Parsch, and Dixon), although their effecton rental spreads remains an empiricallyunanswered question. Greater net worthcould have an ambiguous relationship tothe rental spread. On the one hand,greater net worth could indicate a greaterfinancial capacity to pay a higher rentalspread. Conversely, greater net worthcould reflect an expanded risk-carryingcapacity, thereby supporting a lowerspread.

Higher debt-to-asset ratios could alsohave ambiguous relationships. Theaccompanying increases in financialrisk would help to explain largerspreads, thus reflecting the riskreduction in the sharing arrangement. Alternatively, greater leverage maysupport a farmer’s quest for businessgrowth and a tendency to make higherbids on cash leases to control additionalacreage.

Soil productivity may also have anambiguous relationship with the rentalspread. More productive soils providegreater income-sharing potential,especially in North and Central Illinoiswhere share leasing has been moreextensive than cash leasing (Lattz,Cagley, and Raab). Or, more productivesoils may be viewed as risk reducing,allowing lower rental spreads (Barry,Escalante, and Bard).

Finally, investments in greater machinerycapacity by farmers could indicate agreater response capacity to productionrisks, suggesting a linkage to lower rentalspreads. Alternatively, this investmentcould provide an incentive to bid a highercash rent in order to spread fixedmachinery costs over a larger acreage. Therisk-reducing effects of crop insurance andother forms of insurance could reduce theneed for share leasing, thereby reducingthe rental spread.

Econometric Results

The econometric results are reported inTables 4 and 5 for all farms, regional andsoil quality categorizations, and forunadjusted and adjusted rental premiums. The results are largely consistent withsome of the potential relationships amongthe mean values suggested in Table 2.10

The most uniform results across all farmsand farm classes are the negative andhighly significant relationship of the levelof cash rent to the rental spread, and thepositive and significant relationshipbetween soil productivity and the spread. Rental spreads consequently tend to belower when cash rents are high and onmore productive soils.

10 Diagnostic tests performed on the data sets forboth estimating equations establish the absence ofheteroskedasticity problems.


Table 3. Extended

Rental SpreadNo. ofFarms

MachineryInvestment/

Acre ($)

InsuranceExpense/Acre ($)

IncomeRisk(C.V.)

Cash Rent/Acre ($)

Cash-ShareAcresRatio

Below !$50 10 240.28 9.54 1.14 152.09 0.95

!$49 to !$25 31 241.57 10.20 2.70 116.09 1.03

!$24 to $0 95 269.31 10.00 2.01 110.43 1.19

$1 to $25 68 325.60 10.31 1.82 98.16 1.42

$26 to $50 44 307.28 11.20 0.60 97.10 1.29

Over $50 7 437.70 13.94 !19.57 88.87 0.94

Total Farms 255

In addition, net worth appears to bepositively related to the rental spreads forthe full data set and for the North Centralcases, but not for Southern Illinois. Thepositive relationship suggests a greaterfinancial capacity to pay a higher spread orless willingness to pay a high cash rent. Both age and income variability showsignificant negative relationships for thefull data set, but lose this significancewhen the three farm classes aredistinguished.

None of the other independent variablesyielded significant results, even though themean values reported in Table 2 for thespread intervals suggested a potentiallypositive relationship for machineryinvestment per acre. The R2 values areabove 0.40 for each equation, indicatingrelatively high explanatory capacity for apredominantly cross-sectional data set,yet leaving considerable degrees ofunexplained variability in the rentalspreads.

Discussion and Implications

The above descriptive and econometricresults suggest non-risk factors likely arethe primary determinants of themagnitude and sign of the rental spread. The trends toward higher cash rent levelson larger farms may indicate that highercash rent is a bidding strategy to control

additional leased acreage and perhaps toavoid management sharing with multiplelandlords (Barry, Sotomayor, and Moss). Expansion of farm size may be moreimportant than soil productivity innegotiating higher cash rents, due topotential size economies and underutilizedmachinery investments. Variablesassociated with income risk, financial risk(the debt-to-asset ratio), and insurance didnot yield consistent significant results.

These conditions suggest that manyfarmers engaged in cash leasing may bemissing an effective risk-reducingopportunity. Under a 1/2S1/2 crop sharelease, for example, the higher soilproductivity farmers in North and CentralIllinois can transfer half of their variabilityof net income [see equation (3)] to thelandowner relative to cash leasing, whileincreasing their rental expense, onaverage, by only 2.71%.11 Sizeablereductions in risk may thus occur relativeto modest reductions in expected returns.

In contrast, landowners must be willing toaccept these return levels on share leasesin exchange for carrying their shares of theincome variability. While landlord data areunavailable for this study, findings of othersurveys of farmers and professional farm

11 From Table 2, dividing the unadjusted share leasepremium by the cash rent level (i.e., 3.39/125.05)yields 0.0271.

Table 4. Econometric Results for Unadjusted Rental Spreads, 1995SSSS1998

All FarmsNorth & Central Illinois

(High Soil Rating)North & Central Illinois

(Low Soil Rating) Southern Illinois

Variable Coefficient Prob

> |t| Coefficient Prob



> |t|

Intercept !0.25598* 0.066 !0.82489 0.263 !0.00859 0.9710 !0.27845 0.589

Net Worth 0.00000011** 0.023 0.0000002** 0.034 0.0000002*** 0.0007 !0.0000003** 0.043

Age !0.00330* 0.052 !0.00264 0.413 !0.00248 0.2415 !0.00371 0.326

Income Risk !0.00212* 0.099 !0.00181 0.351 !0.00919 0.3021 !0.00143 0.564

Soil Rating 0.01506*** 0.000 0.02459*** 0.002 0.00114*** 0.0004 0.01405* 0.062

Size (tillable acres) 0.000005 0.912 0.000023 0.739 !0.00002 0.6742 0.00004 0.728

Debt-to-Asset Ratio !0.00081 0.992 0.07600 0.675 !0.03089 0.7274 !0.04717 0.811

Machinery Investment/Acre 0.00012 0.245 0.000041 0.813 0.00009 0.5289 0.00014 0.608

Insurance Expense/Acre 0.00614 0.119 0.01021 0.118 !0.00171 0.7634 0.00410 0.710

Cash Rent/Acre !0.00838*** 0.000 !0.01196*** 0.000 !0.07390*** 0.0001 !0.00567*** 0.001

Cash-Share Acres Ratio !0.00209 0.806 !0.00849 0.483 !0.00415 0.7293 0.02194 0.456

R2 0.462 0.612 0.471 0.417

Prob > F 0.001 0.000 0.000 0.013

Note: Single, double, and triple asterisks (*) denote significance at the 10%, 5%, and 1% levels, respectively.

Table 5. Econometric Results for Adjusted Rental Spreads, 1995SSSS1998

All FarmsNorth & Central Illinois

(High Soil Rating)North & Central Illinois

(Low Soil Rating) Southern Illinois

Variable Coefficient Prob




> |t|

Intercept !0.29711** 0.024 !0.92612 0.186 !0.04730 0.825 !0.33380 0.489

Net Worth 0.0000001** 0.022 0.0000002** 0.038 0.0000002*** 0.000 !0.0000003** 0.028

Age !0.00317** 0.049 !0.00270 0.378 !0.00221 0.262 !0.00389 0.272

Income Risk !0.00156 0.200 !0.00095 0.605 !0.00770 0.353 !0.00114 0.623

Soil Rating 0.01378*** 0.000 0.02378*** 0.001 0.00979*** 0.001 0.01424** 0.044

Size (tillable acres) 0.0000096 0.815 0.00003 0.637 !0.00002 0.775 0.000028 0.814

Debt-to-Asset Ratio 0.01316 0.862 0.07974 0.643 !0.01883 0.819 !0.03161 0.864

Machinery Investment/Acre 0.0001 0.219 0.00004 0.790 0.00007 0.601 0.00019 0.464

Insurance Expense/Acre !0.00061 0.871 0.00482 0.434 !0.00720 0.174 !0.00694 0.502

Cash Rent/Acre !0.00746*** 0.000 !0.01090*** 0.000 !0.00643*** 0.000 !0.00492*** 0.001

Cash-Share Acres Ratio !0.00147 0.855 !0.00776 0.500 !0.00354 0.750 0.02388 0.386

R2 0.423 0.584 0.452 0.403

Prob > F 0.0001 0.000 0.000 0.018

Note: Single, double, and triple asterisks (*) denote significance at the 10%, 5%, and 1% levels, respectively.


managers identify avoidance of risk asa major determinant of landownerpreferences for cash leasing (Barry,Sotomayor, and Moss). Some landownersapparently prefer to shift to cash leasesrather than seek higher share levels.

At the same time, based on anecdotalevidence from professional managers,lenders, and farmers, landowners likelyare older, wealthier, and more diversified(especially between farm and nonfarminvestments), thus enhancing their risk-carrying capacities. The institutionalnature of some landowners (pensionfunds, banks, religious organizations,and insurance and trust companies) alsosuggests larger size, greater diversity, andexpanded risk-carrying capacities. Engaging professional managers to selectand monitor farm operators and to assistwith risk management, productiondecisions, and marketing alternatives mayfurther help to stabilize the landowner’sreturns.

These results could also reflect the effectsof possible inequities in share levels dueto rigidities in the traditional sharingarrangements (1/2S1/2 in North andCentral Illinois, and 1/3S2/3 in SouthernIllinois). The 50S50 crop share lease isan equal, yet not necessarily equitableapproach to allocating returns to farmersand landowners. It may overcompensatelandowners with low quality soil andundercompensate those with high qualitysoil. Such inequities could explain thenegative average rental spreads inSouthern Illinois.

Timing and liquidity issues may also arisein determining the preferences and rentalspreads for share and cash leases. Undershare leases, the landowner is obligated topay his or her share of variable costs. Under cash leases, the farmer must bearall of the operating expenses and oftenpay part of the cash rent in advance. Additionally, the landowner may require ahigher cash rent for late or split payments(e.g., half spring, half fall) to compensatefor the time value of money.

Rental spreads may also reflect alternativemanagement sharing arrangements, thepersonal relationship between the farmerand landowner, the landowner’sobligation for paying social security taxeson share income but not cash rentincome, election of use value of farmlandin estate transfers, and combinations ofcash and share rent. However, theFBFM data do not reflect these potentialeffects.

Finally, the influences of agency andtransactions costs could not be directlyaddressed in the context of the availabledata. Moreover, the cash-share ratio wasnot significant for the unadjusted spreadmodel, and its positive significance for theadjusted spread model implies a riskresponse rather than an agency response. By promoting incentive alignment betweenthe contracting parties, the share leasecould reduce the landowner’s monitoringrequirements, which would otherwise behigher under share leasing, and promoteefficient resource use.

Under such conditions, the landownerwould benefit from reduced agency costsby more than the apparently small rentalspread, and the farmer may be burdenedby more than the spread he/she payswould suggest. Alternatively, the highagency costs of sharing managementunder share leasing with multiplelandowners as farm sizes increase couldfavor cash leasing. These possiblerelationships warrant further study.

References

Allen, D. W., and D. Leuck. “RiskPreferences and the Economics ofContracts.” J. Amer. Society of FarmManagers and Rural Appraisers85(1995):447S51.

Babcock, B. A., E. K. Choi, and E.Feinerman. “Risk and ProbabilityPremiums for CARA Utility Functions.” J. Agr. and Resour. Econ. 18(July 1993):17S24.


Barry, P. J. “The Cash/Share Combinationin Farmland Leasing.” J. Amer. Societyof Farm Managers and Rural Appraisers65(2002): forthcoming.

Barry, P. J., C. L. Escalante, and S. Bard. “Economic Risk and the StructuralCharacteristics of Farm Businesses.” Agr. Fin. Rev. 61(Spring 2001):73S86.

Barry, P. J., L. M. Moss, N. L. Sotomayor,and C. L. Escalante. “Lease Pricing forFarm Real Estate.” Rev. Agr. Econ.22(Spring/Summer 2000):2S16.

Barry, P. J., N. L. Sotomayor, and L. M.Moss. “Professional Farm Managers’Views on Leasing Contracts and LandControl: An Illinois Perspective.” J.Amer. Society of Farm Managers andRural Appraisers 62(1998S99):15S19.

Bierlen, R., L. Parsch, and B. Dixon. “HowCropland Contract Type and TermDecisions Are Made: Evidence from anArkansas Tenant Survey.” Internat. Foodand Agribus. Mgmt. Rev. 2(1999):103S21.

Bullen, G. “Farmers’ Leasing Practices inIllinois.” Coop. Ext. Ser., University ofIllinois, Urbana-Champaign, 1999.

Cheung, S. N. Theory of Tenancy. Chicago,IL: University of Chicago Press, 1969.

Dasgupta, S., T. O. Knight, and H. A. Love. “Evolution of Agricultural Land LeasingModels: A Survey of the Literature.” Rev. Agr. Econ. 21(Spring/Summer1999):148S76.

Freund, R. J. “Introduction of Risk into aRisk Programming Model.” Econometrica24(1956):255S63.

Illinois Farm Business Farm ManagementAssociation. Unpublished data forsingle-operator Illinois FBFM grainfarms, 1995S1998. FBFM website onlineat http://web.aces.uiuc.edu/fbfm/.

Kocherlakota, N. R. “The Equity Premium:It’s Still a Puzzle.” J. Econ. Lit. 34(March1996):42S71.

Lattz, D. H., C. E. Cagley, and D. D. Raab. “Summary of Illinois Farm BusinessRecords.” College of Agricultural,Consumer, and EnvironmentalSciences, University of Illinois, Urbana-Champaign, 1998.

Meyer, J. “Two Moment Decision Modelsand Expected Utility Maximization.” Amer. Econ. Rev. 77(1987):421S30.

Reiss, F. J. “Farm Tenancy Arrangementsin the U.S.A.” J. Amer. Society of FarmManagers and Rural Appraisers48(October 1984):16S24.

Reiss, F. J., and C. J. Koenig. “FarmLeasing Practices in South-EasternIllinois Counties.” Dept. of Agr. Econ.,University of Illinois, Urbana-Champaign,July 1980.

Robison, L. J., and P. J. Barry. TheCompetitive Firm’s Response to Risk. New York: McGraw-Hill, 1986.

Robison, L. J., and R. G. Myers. “OrderingRisky Choices.” In A ComprehensiveAssessment of the Role of Risk in U.S.Agriculture, eds., R. E. Just and R. D.Pope, pp. 41S52. Boston: KluwerAcademic Publishers, 2002.

Sotomayor, N. L., P. N. Ellinger, and P. J.Barry. “Choice Among Leasing Contracts.”Agr. Fin. Rev. 60(2000):71S84.

Tsiang, S. C. “The Rationale of the Mean-Standard Deviation Analysis, SkewnessPreference, and the Demand for Money.” Amer. Econ. Rev. 62(1972):354S71.

U.S. Department of Agriculture, NationalAgricultural Statistics Service. Agricultural Economics and LandOwnership Survey. USDA/NASS,Washington, DC, 2001.

Williams, J. C. “Commodity Futures andOptions.” In Handbook of AgriculturalEconomics, eds., B. L. Gardner andG. C. Rausser, pp. 746S816. Amsterdam: Elsevier, 2001.

Rental spreads for share versus cash leases in Ilinois

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