1. VICTORIAN BROAD ACRE
CROPPING FARMLAND VALUES
AND THEIR DRIVERS 2014
Project Report
1. Abstract
The drivers behind the value of broad
acre cropping land are complex and
highly variable. This study aimed to
quantify the effect of a change in
expected yield, expected price,
expected interest rate, soil quality and
size & length of investment. A
spreadsheet was created in Microsoft
Excel so that all receipts and expenses
involved in a purchase of land could be
included. They could then be varied to
study the effect on the maximum price
a farmer should pay if they wish to
earn X% p.a. on their investment. It
was found that yield based on the
properties’ location had the greatest
effect on the maximum price.
Individual farmers’ ability to grow
better yields and market their grain at
better prices also had a large effect, as
well as the length of time they planned
on investing for and the interest rate
they could receive. There was also
large effects on the individuals farmers
ability to grow better yields, market
their grains at better prices, the length
of time they planned on investing and
the interest rate they could receive.
Lachie Morrison 558412
Supervised by Bill Malcolm
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2. Introduction
The value of a block of farmland varies from farmer to farmer due to a number of factors. The purpose
of this paper was to determine the largest factors that influence broad acre cropping farm land values.
These factors included but were not limited to: expected yield, expected price, expected interest rate,
soil quality and size of investment. It was also important to recognise that while a farm is a business
and an asset, strong significance must be placed on the farmer’s family standing. Whether or not there
is someone to take over the farm can ultimately decide whether or not to invest in expansion, hence
the length of investment was also be examined. The cropping regions of Victoria vary a great deal in
both yields and input costs so it was important to assess the differences between these regions. Ouyen
(Mallee), Murtoa (Wimmera), Willaura (South Western) and Teesdale (Central) were the sites chosen
to compare as they represent the major cropping regions of Victoria.
There has beenlittle research done into the value of farmlandcomparedto commercial andresidential
properties (Eves 2010). However, there are a couple of methods used in past literature that attempt
to provide a guide as to how to value land, and also show how actual farmers think through a new
investment.
Makeham and Malcolm (1993)
Makeham and Malcolm preferred to think in terms of “willingness to pay” and “expected return”. In
effect it was suggested that the value of farmland was almost entirely subjective and depended on
the rate of return the individual required from the purchase.
For example if 100ha of cropping land was able to return a net gain of $1000 p.a. and
Joe Bloggs wants to earn 10% p.a. on his investment (ROI), he would be willing to pay
$10,000 for the land. Jill Farmer however only requires a ROI of 8% p.a. and so would be
willing to pay up to $12,500 for the same land.
The discounted cash flow method (DCF) is a way of calculating the true present value of one cash flow
of a project over its life according to equation 1 below:
𝑫𝑷𝑽
𝑭𝑽
(𝟏 + 𝒊) 𝒏
Where: DPV = discounted present value
Equation 1. Discounted Present Value
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FV = nominal value of a cash flow amount in a future period
i = interest rate or discount rate, which reflects the cost of tying up capital and so
represents the opportunity cost
n = time in years before the cash flow occurs
The theory behind discounting a cash flow is simple; $1 today is worth more than $1 in a year’s time.
DCFs have major drawbacks surrounding the assumptions that are required to be made. The discount
rate and predicted cash flows can vary so much as it is virtually impossible to predict incomes and
expenses three years into the future, let alone 10. Regardless, the concept of a DCF is relevant and as
long as the assumptions made are conservative, it is a good tool for calculating net present value of
an investment.
From the first example if Joe Bloggs purchased that land for $10,000 and believed that
after 10 years (n) he would be able to sell the land for $15,000 then the nominal value
of the cash flow (FV) is $5000 ($15,000-$10,000). Joe wants to be relatively conservative
and decides that $1.12 next year is worth $1 this year and so ends up with a discount
rate of 12% (i). In doing so Joe is predicting that after 10 years he will actually have only
gained $1610 worth of today’s money which is the “discounted present value”. 𝐷𝑃𝑉 =
5000
(1+0.12)10 = 1610
The DCF rule can be applied to every single facet of a potential investment from predicted wages to
soil degradation. The sum of every individual present value is called the net present value (NPV) and
is ultimately the value Makeham and Malcolm suggest to use. They say it requires a “defined planning
horizon including the walk-in-walk-out value of land, machinery and livestock. This allows expected
inflation or capital gains over time to be considered.”
Boehlje and Eidman Estimate (1988)
Boehlje and Eidman attempted to estimate land value as shown in equation 2 below:
𝑽 =
𝑹 − 𝑬 − 𝑳 − 𝑰
𝒅
Equation 2. Boehlje and Eidman land value estimate
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Where: V = property value
R = total cash farm receipts
E = total cash farm expenses
L = unpaid family labour
I = interest on non real estate capital
d = pre-tax nominal discount rate
This has the same basic concept as the DCF that Makeham and Malcolm used where there is a form
of discounting value, however it does not reflect the fact that annual percentage capital gain is actually
a percentage of a different value each year.
Barry, Hopkin and Baker (1988)
Barry, Hopkin and Baker took the valuation a step further than Makeham and Malcolm and also
included the issue of how the purchase is financed where Makeham and Malcolm assumed equity
capital and the cost of the debt to be the same. In reality the debt can cost more than just the equity
capital as there is always the possibility of negative cash flows which can cause the debt to actually
cost more if the payments are not able to be met. So even if the end benefit is good it is not always
feasible to actually take out the loan. This addition makes the equation a lot more complex as shown
in equation 3.
𝑵𝑷𝑽 = −𝑰𝑵𝑽 − ∑
𝑷 𝒏 + ( 𝟏 − 𝒕) 𝑰
(𝟏 + 𝒓) 𝒏
+ ∑
𝒂(𝟏 + 𝒇) 𝒏
(𝟏 + 𝒓) 𝒏
+
𝑽 𝒎 − 𝑪 𝒎 − 𝑫 𝒎
(𝟏 + 𝒓) 𝒎
𝒎
𝒏=𝟏
𝒎
𝒏=𝟏
Where: NPV = net present value
INV = the initial investment or deposit
r = the after tax nominal discount rate
Pn = the principal repayment period in n
t = average marginal tax rate
Equation 3. Barry, Hopkin and Baker’s net present value
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f = annual inflation rate
a = annual net return from the land
In = interest repayment period in n
Vm = expected salvage value of the property at time m
Cm = capital gains tax liability at time m
Dm = the debt outstanding at time m
Summary of the Models – reproduced directly from Madden and Malcolm (1996)
“The models of land value examined so far have ranged from the simple income capitalisation method
through to the Barry, Hopkin and Baker method which separates out the costs of finance from the
cost of other capital invested. A summary of the features of the three models examine is given in Table
1. As shown in Table 1 none of the models examined include all of the thirteen key determinants of a
realistic bid price.”
This table gives a clear understanding of both the key determinants set out by Madden and Malcolm
and also which of these determinants are included in each of the three models. It is obvious from the
table that the Boehlje and Eidman model is very simplistic in comparison to the others so for an in
depth inquiry such as this paper it is not as useful. The major differences between the other two is
that the Madden and Malcolm model recognises the fact that it is usually not reasonable to purchase
Table 1. Features of the land value
models contained in the literature.
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new land without spending money on improving the property or purchasing new stock/machinery
which will have a salvage value at the end of the planning horizon. As mentioned previously the Barry,
Hopkin and Baker model also included the debt servicing ability of the individual looking to purchase
the property.
Gregson (2008)
In his thesis Gregson analysed the effect that profit, interest rates and commodity price amongst other
variables had on the value of farmland. He conceded that profit is “notoriously difficult” to measure
in farming with unpaid family labour and management, depreciation and opportunity cost all coming
with serious consistency issues across the market. Interestingly in the three models he constructed,
net profit had no significant effect on land value. This was consistent with Melichar (1979) and Esparon
(2002) and it’s thought that while profit itself doesn’t necessarily effect land value, profit drivers like
rainfall and soil type were important.
It was found that interest rates however did have an effect on land values, where in general higher
interest rates will lead to lower asset prices and vice versa. Gregson explained that it was possible that
it was in fact the availability of credit or the banks willingness to lend that has the largest effect and
not just the interest rate itself – it should be noted that this was different to the findings of a study by
Just and Miranowski (1993).
Gregson concluded that while only one of his models showed a significant effect due to commodity
prices they are still an important factor in determining farmland value. The main issue is that there is
no true way of knowing what the price of the commodity will be in 10 years’ time and so it is not
reasonable to use in an attempt to predict a lands future value.
He also acknowledged that the size of the land being sold, family situation and whether or not the
land is expected to achieve capital gains all also affect the value of farmland however they are
“impossible to capture in the simple linear models of relationships between profit, interest rate and
commodity prices” that he used.
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Grains Research & Development Corporation 2012
Water use efficiency ($WUE) is a measure of the gross income efficiency of a farm according to the
rain it receives. It is expressed as dollars of gross income per hectare per 100mm of annual rainfall.
GRDC believe that the value of broadacre land above a threshold value is the product of:
Annual rainfall (each extra mm adds $8/ha to its value)
$WUE derived through employing a crop rotation (this adds $16/ha to land value for each unit
of $WUE)
Freight rate from local depot to port (negative in its effect at -$56/ha for each $/tonne of
freight rate increase)
GRDC claim that “the rise in land value over the last twenty years, for the most part, is a product of
gains in $WUE arising from improved prices and yields.”
This study involved the development of a model in Microsoft Excel which tallied all predicted incomes
and expenses for the purchase of a new block of land to extend the current farm. From there a
maximum “willingness” to pay could be calculated given that the farmer wanted to earn X% p.a. on
their investment. It also included the issue of being able to service the loan and allowed for losses to
be made in a year. The four cropping regions were compared based on market land values from the
Valuer-General’s Guide to Property Values (Valuer-General Victoria, 2013) in order to deduce which
was the “safest” and the most profitable region to invest in. The model was also used to assess the
effect of boom and bust years on the value of the land as well as expected yield, expected price,
expected interest rate, soil quality, the length & size of the investment and the required rate of return.
3. Method, Data and Assumptions
3.1 Method
A spreadsheet was made using Microsoft Excel so that data could be entered and then altered
depending on circumstance. It was set up so that any user can enter the data that is relevant to them
The spreadsheet will then inform them whether the investment is likely to be a good one based on
the figures they entered. Image 1 and Image 2 below show screenshots of the two sheets that require
data entry. The spreadsheet returns the net present value (NPV), equity and cash surplus as well as
yearly cash flows which all form the basis of the decision whether or not to take on the investment.
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Image 1. The “Summary” sheet where the most important data is entered and a summary of the
results is also given.
Image 2. The “Expenses” sheet where the running costs are entered.
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The regions were then compared assuming a $1,000,000 investment and were subjected to sensitivity
analysis. The sensitivity analysis included varying the estimated yield and price received for the crops,
and introducing a drought year into the model.
The length of the investment was then extended to 20 years using data from Teesdale, which then
underwent the same analysis. The effect of a change in interest rate and a lime & gypsum application
was also compared between the 10 and 20 year investments.
3.2 Data, Assumptions and Limitations
All locations used the same port price for the grain however a “freight” expense was included in the
spreadsheet and was calculated as the price at the Geelong port minus the price offered at the local
GrainCorp site (GrainCorp1
, 2014 & GrainCorp2
, 2014). Data specific to the regions was entered based
on estimates from Grains Research and Development Corporation’s (GRDC) Gross Margin Guide
(GRDC, 2014) the Valuer-Generals Guide to Property Values (2013) and farmers local to the area. The
expected prices were set at $250/t for wheat, $240/t for barley and $480/t for canola (GRDC, 2014).
The expected loan interest rate set at 5.5% based on
Table 1. The data used for the locations
Location Average Cereal Yield (t/ha) Average Canola Yield (t/ha) Market Land Value ($/ha)
Willaura 5 2.5 7,000
Teesdale 4 2 5,000
Murtoa 3 1.5 3,100
Ouyen 2.2 1.1 1,100
The spreadsheet assumes that the purchase of the new block of land is entirely funded by a loan from
the bank. The farmers existing land is excluded from the study other than to ensure there is enough
equity to service the loan and so any figures are based on the new land only. For simplicity
improvements and water rights weren’t included and every year the block is dived in three equal parts
growing wheat, barley and canola. There is no option to run livestock and contract rates were used
for everything. A transaction cost of 5.5% of the purchase price was included to cover stamp duty.
All incomes and costs occur in the same time period i.e. sowing expenses were discounted the same
as harvestprofit. This timing issue alsomeansthat the “overdraftinterest” expense was only indicative
and was calculated as: overdraft interest = overdraft interest rate x sum of expenses for the year x 0.5.
It assumed that each expense was in the overdraft account for an average of 6 months (hence the ‘x
11. Lachlan Morrison 2014
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0.5’) and while it is clearly inaccurate it is a small enough expense to not have a major effect on the
outcome. Any cash surplus at the end of each year is then used to pay off some of the loan principal.
All expenses were inflated at 2.6% every year however the receipts were inflated at 2% because
historically farm costs have been rising faster than the prices received for the goods (Australian Bureau
of Agricultural and Resource Economics and Science, 2010).
These assumptions and limitations mean that while the results from the spreadsheet will give an
indication of land value, it will not be very accurate. However, because all of the circumstances studied
had the same limitations and assumptions the results are still comparable.
4. Results
The results showed that in nearly every way Willaura was the best place to invest in followed by
Teesdale, Murtoa and Ouyen. The “maximum price” referred to in many of the results is based on the
maximum price that can be paid per hectare given that the farmer wishes to earn 2% p.a. return on
asset (ROA). Unless otherwise stated it is assumed that the investment will run for 10 years. The effect
of average price received for the grains is shown in figure 1 where the more fertile locations had a
greater response. Cash surplus based on yield was then compared in figure 2 assuming a $1m
investment at market land value. Ouyen showed a huge response to a change yield and was clearly
the most profitable at 10% greater than expected yields but also showed the greatest loss if yields
were 10% lower than expected. Yield was halved in one year at a time in figure 3 and only Teesdale
and Willaura could still post a net gain regardless of when the drought occurred. Figure 4 shows the
effect of a farmer’s requirement for ROA on maximum price and again it is the more fertile regions
that show the most elasticity. The effect of soil quality is shown in figure 5 where it was found that
regardless of the year lime and gypsum are applied a block of land that only needs half the application
will be worth 5% more.
Figures 5-9 focus solely on a property at Teesdale and to a large extent analyse the effect of investing
for 20 years instead of 10. In all situations investing for double the time results in being able to afford
to pay extra for the land. Figure 9 is a culmination of all the variables and shows that if each is only
slightly more favourable the maximum price payable can increase dramatically ($2229/ha in this case).
All of the results are based on the assumptions set out in section 3.2. Figure 9 also shows that the
assumptions don’t need to be very far out for a large change in results to occur.
Figure 10 examines the difference results in net present value (NPV) and cash surplus according to the
assumptions made.
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Figure 1. Compares the four locations value response to a $20 increase in the price received for a
tonne of wheat & barley and a $40 increase in the price received for canola. Willaura was the most
elastic showing a $1372.3 increase in land value for every price increase.
Figure 2. Shows the cash surplus at the end of the 10 year investment at varying yields if $1m of land
is purchased at market value for the region. When everything ran as expected Willaura ($212,582)
made the most money followed by Teesdale ($157,063), Murtoa ($132,521) and Ouyen ($102,288).
Ouyen showed the greatest response to yield with a $221,436 increase in final cash surplus for every
5% increase in yield from the expected yield of 2.2 t/ha.
y = 1372.3x + 2821.7
y = 1097.7x + 1299.3
y = 824.9x + 274.1
y = 611x - 894.6
($2,000)
$0
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
210, 200, 400 230, 220, 440 250, 240, 480 270, 260, 520 290, 280, 560
MaximumValue($/ha)
Port Price for Wheat, Barley & Canola Respectively ($/tonne)
Maximum Value at Varying Average Port Prices
Willaura Teesdale Murtoa Ouyen
y = 79191x - 21422 y = 91121x - 114584 y = 113384x - 207308 y = 221436x - 558283
($400,000)
($300,000)
($200,000)
($100,000)
$0
$100,000
$200,000
$300,000
$400,000
$500,000
$600,000
-10% -5% Expected Yield +5% +10%
Surplus($)
Cash Surplus Response to Average Yield at Market Land Value
Willaura Teesdale Murtoa Ouyen
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Figure 3. When the drought occurs in the later years it has slightly less of an effect on cash surplus.
Ouyen never recovers from the drought and money can only be made within 10 years at Murtoa if the
drought occurs in year 8 or later. Note that there is a dip in year 5 because that is the year that lime
and gypsum were applied in the spreadsheet.
Figure 4. The rate of ROA required by the farmer has an increasing effect on maximum price as the
land itself becomes more profitable. At Teesdale the farmer who is investing over 20 years can afford
to pay an extra ~5% than one who is investing for 10 years. The green “Market Value” data points
refer to the ROA received when the market rate is paid for the block of land.
($250,000)
($200,000)
($150,000)
($100,000)
($50,000)
$0
$50,000
$100,000
$150,000
1 2 3 4 5 6 7 8 9 10
CashSurplus($)
Year of Drought
Effect of a 50% Drought in Different Years
Willaura Teesdale Murtoa Ouyen
0.978
1.469 1.827
1.944
1.250
y = -1225.2x + 9421.2 y = -806x + 6225.2 y = -841.2x + 6554.4 y = -475.4x + 3712.3 y = -157.4x + 1257.9
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
$9,000
$10,000
0.00 0.50 1.00 1.50 2.00 2.50 3.00
MaximumPrice($/ha)
ROA Required (%)
Effect of Required ROA on Maximum Price
Willaura Teesdale Teesdale 20 Years Murtoa Ouyen Market Value
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Figure 5. A 20 year investor can always pay $266/ha more than a 10 year investor regardless of the
amount or timing of lime and gypsum application. Land that only requires 1t/ha is worth 5% more
than the land that requires 2t/ha. Note that all of these assume that lime and gypsum are applied
every 5 years starting from the first application.
Figure 6. The relationship between the average interest rate on the loan and the maximum price is
actually a ln(x) relationship. However given the range of interest rates examined a linear relationship
provides a very close estimate that an increase in interest rate offered by the financial institution of
1% equates to a drop in maximum price of around $475/ha.
$4,000
$4,100
$4,200
$4,300
$4,400
$4,500
$4,600
$4,700
$4,800
$4,900
Teesdale 10 years
1t/ha
Teesdale 20 years
1t/ha
Teesdale 10 years
2t/ha
Teesdale 20 years
2 t/ha
MaximumPrice($/ha)
Effect of Soil Quality on Maximum Price at Teesdale
Year 1 Year 3 Year 5
y = -2909ln(x) + 9564.4
R² = 0.9992
y = -2936ln(x) + 9870.6
R² = 0.9997
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
4.00 4.50 5.00 5.50 6.00 6.50 7.00 7.50 8.00 8.50
MaximumPrice($/ha)
Average Interest Rate (%)
Interest Rate's Effect on Maximum Price at Teesdale
Teesdale 10 years Teesdale 20 years
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Figure 7. If the investment is planned to last 20 years instead of 10 years then the farmer can afford
to pay more for the land and still make a 2% p.a. ROA. If everything runs as expected they can afford
to pay an extra $266/ha which jumped to $429/ha more if yield is actually 10% higher.
Figure 8. The 10 year investment had 50% yield in year 1 and the 20 year investment had 50% yield in
years 1 and 11. This resulted in the investor being able to pay an extra $115/ha or 3% more when
investing for 20 years as opposed to 10 years.
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
-10% Expected Yield +10%
MaximumPrice($/ha)
Maximum Price Depending on Yield at Teesdale
Teesdale 10 years Teesdale 20 years
$3,851
$3,966
$3,780
$3,800
$3,820
$3,840
$3,860
$3,880
$3,900
$3,920
$3,940
$3,960
$3,980
Teesdale 10 Years Teesdale 20 Years
MaximumPrice($/ha)
Effect of a 1 in 10 Year 50% Drought on Maximum Price
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Figure 9. “Farmer 1” had the average assumptions set out in section 3.2. “Farmer 2” on the other hand
was investing for 20 years, received a 5% interest rate, could yield 5% higher, could attain $5/t extra
on cereals and $10/t extra on canola and only required a 1.5% ROA. With these minor adjustments
“Farmer 2” could afford to pay 49% more for the same block of land than “Farmer 1”.
Figure 10. Ouyen had the greatest net present value at a discount rate of 8% and capital gains of 2%
yet had the lowest cash surplus after the 10 year investment.
$4,592
$6,821
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
Farmer 1 Farmer 2
MaximumPrice
Comparing Two Farmers With Different Views on
the One Block of Land at Teesdale
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
$400,000
$450,000
Willaura Teesdale Teesdale 20
Years
Murtoa Ouyen
Difference Between NPV and Cash Surplus
NPV Cash Surplus
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5. Discussion
Of the four locations examined Willaura is certainly deemed to be the safest to invest in given the
current land values. As seen in figure 2 if a 10 year period played out according to plan then an
investment in a farm in Willaura would yield a cash surplus 35% higher than the same investment at
Teesdale, 60% higher than Murtoa and 108% higher than Ouyen. Therefore if the assumptions made
in this study are correct then land at Ouyen is quite overpriced while land at Willaura is under-priced
by comparison.
5.1 Port Prices Figure 1
The price available for the goods produced had a large and varying effect on the value of the land. An
increase of $20 in cereals and $40 in canola added anywhere from $611/ha in Ouyen to $1372/ha in
Willaura. This difference in response was solely due to the different yields of the areas. In fact it was
found that a linear relationship exists between an increase in land value due to a change in price
received and expected yield:
𝑰𝒏𝒄𝒓𝒆𝒂𝒔𝒆 𝑰𝒏 𝑳𝒂𝒏𝒅 𝑽𝒂𝒍𝒖𝒆 = 𝟏𝟑. 𝟔𝟎𝟑𝟓 ∗ 𝒀𝒊𝒆𝒍𝒅 + 𝟎. 𝟓𝟑𝟏𝟗
Where:
Increase in land value = Increase in value of land ($/ha) for every $1 increase in cereal price
and corresponding $0.50 increase in canola price.
Yield = Cereal yield and corresponding canola yield
For example if John was looking to buy in an area that had a wheat yield of 3.5 t/ha and thought that
he could market their wheat $5 better than Dave who is also looking to purchase the same block. John
would be able to pay an extra $240.7/ha:
13.6035 x 3.5t/ha + 0.5319 = 48.144 per $ increase in sale price
48.144 x $5 = $240.7/ha
This is based on the current assumptions and also assumes that expenses will increase at a rate
according to yield.
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5.2 Yield Figure 2
Willaura was the least responsive to a change in yield which means two things; starting with the same
dollar investment a technology/practice that increases yield is going to be less effective in Willaura
than Ouyen (the most yield sensitive). Secondly if average yields aren’t as good as it was first hoped
then it is less of an issue at Willaura because at market land value Willaura is the only location that
can still post a profit if yield is 10% lower than expected. Ouyen on the other hand is high risk but high
reward if the farmer thinks they can improve the yield beyond expected.
5.3 Drought Figure 3
When an equal dollar investment was undertaken in the four locations and given the assumptions
made Teesdale and Willaura were the only ones to still be able to make any money when a drought
occurred in any of the ten years of the investment. While a boom year would likely recover a portion
of the losses experienced during a drought year, a conservative farmer would always assume that they
would endure more drought years than booms. The results in figure 3 suggest that current land values
at Ouyen and Murtoa are likely overpriced due to the losses experienced with a single drought.
5.4 Return on Asset (ROA) Figure 4
When the actual current market rate for land in the areas is concerned Willaura again proves to be
the best to invest in as far as percentage return on the value of the land (ROA). It showed an ROA of
1.9% at market land value whereas if the assumptions are correct only 0.98% could be earned at
Ouyen. Teesdale and Murtoa as always are somewhere in between at 1.47% and 1.25% respectively.
A 1% drop in ROA proved to cause a very similar percentage increase in all the regions between 16%-
18%.
5.5 Soil Quality Figure 5
When 1t/ha of both lime and gypsum needs to be applied to the soil it is only worth an extra $13/ha
to be able to wait until year 5 for the first application. If double the lime and gypsum (2t/ha) needed
to be applied then the farmer could afford to pay $38/ha more if they could wait until year 5 for the
first application. The farmer could always pay 5% more if they only had to apply 1t/ha instead of 2t/ha.
If the assumptions are correct this means that at Teesdale even if the soil quality isn’t as good, the
timing of lime and gypsum application still doesn’t have a huge effect on the maximum price payable.
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5.6 Interest Rate Figure 6
Interest rates offered by the financial institutions appeared to have a large effect on the maximum
price payable. According to the assumptions made maximum price would drop roughly $475 for every
unit of interest rate increase. This has significant implications when it comes to purchasing land
because every farmer has different financial situations and varying levels of “risk” according to the
banks, and so will be offered very different interest rates on their loans. Interest rates also vary a great
deal due to external market forces out of the control of the farmer. Assuming a low or even current
interest rate to be the average across a 10 year investment puts that farmer at great risk of losing
money if interest rates were to rise.
5.7 20 Year Investment Figures 4-9
According to the assumptions a 20 year investment in comparison to a 10 year investment brought
more money when land was purchased at market value or alternatively allowed the farmer to pay
extra for the land and still earn the same ROA. At the assumed rates of everything a block of land at
Teesdale was worth $266/ha (5.8%) more to a 20 year investor. No matter the timing of lime and
gypsum (figure 5) it was still worth an extra $266/ha. However, if 2t/ha needed to be applied then a
20 year investor could only pay and extra $226/ha, which is still a significant improvement.
Figure 5 showed that 20 year investors have the greatest advantage at an interest rate of 5.5%
($266/ha). Their advantage gradually depletes either side of 5.5%, however at an interest rate of
8.05% there was still a significant advantage of $241/ha. A 20 year investor was also more drought
tolerant as seen in figure 8. When faced with the equivalent level of droughts the long term investor
could afford to pay $115/ha (3%) more.
This is all basically occurs because over time the size of the loan decreases and so therefore the
average interest expense is lower in a longer term investment.
5.8 NPV and Cash Surplus Figure 10
Most of the previous studies mentioned in section 2 used a discounted or net present value (NPV)
equation to compare investments with a set discount rate. This study did not use any of the equations
used in the past literature because none of them truly reflected the nature of a farm loan. Farm loans
are typically “interest only” loans with the expectation for the principal to be paid back as cash
becomes available. This also means that if a loss is made then the loan will be renegotiated and
increased, which also raises the interest payments each year. Makeham & Malcolm’s (1993) model
doesn’t take into account a loan and instead assumes that the money would be invested anyway and
the investor would just use it as a tool to compare potential investments to a base discount rate. The
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true effect of a variable loan was shown at Ouyen which had the highest NPV of the $1m 10 year
investments yet the lowest cash surplus. This was caused by massive losses in years 5 and 10 due to
lime and gypsum application, thus raising the debt figure and therefore the loan interest after those
years. This shows that just because an investment has a better NPV than another, it’s not necessarily
a better investment because it must be financed. This is a view shared by Makeham & Malcolm and
while the ability to service the loan wasn’t included in their model, they certainly discussed its effect
to a great extent about it in their paper.
It is important to remember that this study assumed that the potential purchase is actually just an
extension on the current property. It analysed whether the new land can support itself and in reality
a loss on the new block could very well be supported by the existing farm and no new loan is required.
It also didn’t take into account family factors such as number of kids wanting to farm nor did it consider
proximity to the current farm and/or towns & cities like other studies did.
5.9 Risk
One of the biggest factors in any investment is its level of risk. The number one question farmers have
when faced with the data presented in this study is, “I know that if I do “x” better I can afford to pay
“$y” more for the land but does that mean I should?” The answer is no, and it’s because of risk. For
example as discussed previously in section 5.7 a 20 year investor in land at Teesdale can afford to pay
$266/ha more and still make the same level of return if the assumptions made are correct. The fact is
that a lot can happen in 20 years and figure 9 shows that if the assumptions are only marginally wrong
then that can have big consequences on the maximum price payable. The data from this study should
instead be used to say that a 20 year investor can’t afford to pay any more than $266/ha more than
the same 10 year investor. As shown in figure 4 a farmer investing for 20 years in Teesdale at market
land values can make 24% more ROA. The conservative farmer would take that to be a bit of a bonus
leeway knowing that things aren’t likely to pan out as planned. So instead of offering the full $266/ha
more that they could afford to pay according to the results they may look at figure 7 and decide that
they would only offer $120/ha. This would allow them some breathing space knowing that they can
still make the return even if their average yields are actually 10% lower. The same can be applied to a
farmer who believes they can get a slightly better interest rate or market their grain $20 better etc.
“Risk” can vary even between regions with the more fertile regions being more risk adverse as seen in
figures 1, 2 & 3. In all cases Willaura is the only location that consistently makes some money under
all the stresses applied to it in the spreadsheet. Ouyen is definitely the riskiest investment as a drop
in expected average yield by only 10% resulted in a nearly $340,000 loss over 10 years from a $1m
investment. Conversely if average yields are 10% higher than expected then according to the
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assumptions upwards of $550,000 could be made over the 10 years. This is a hugely risky investment
keeping in mind that a 10% drop in average yield is only a drop from 2.2t/ha to 2t/ha.
6. Conclusion
There are many factors that affect the value of broad acre cropping land, but the most important
factor is fertility. If the assumptions made in this study are correct, a property that can yield 5t/ha of
wheat could be worth seven times as much as a property that can only yield 2.2 t/ha. It was found
that by comparison land at Willaura could be under-priced and land at Ouyen could be over-priced.
So perhaps land at Teesdale and Murtoa are therefore relatively close to the correct price in
comparison. However, not one of the locations studied showed a ROA of over 2% when average sale
price was paid for the land. If one drought year was introduced it also became very hard to turn over
any profit during a ten year investment. Both ROA and drought susceptibility suggested that land
everywhere in Victoria is over-priced. This could be because many agricultural purchases aren’t made
for the sole purpose of making short term money, but are instead for long term asset investment.
Lime and gypsum requirement only had a small effect on the price at Teesdale. Factors that were
found to have a significant effect on the price a farmer can pay for land included interest rate received,
required return, length of investment and their ability to market the grain for better prices.
7. Acknowledgements
There are two people inparticularwho without their helpthis study couldnever have been completed.
Bill Malcolm took time out of his very busy schedule to edit the spreadsheet and answer my many
questions so that everything actually made sense. Many hours were spent talking to Andrew Morrison
nutting out numbers and just exactly what they all mean, this provided some much needed clarity and
another angle on the findings. Greg Cracknell must also be thanked for his help with the spreadsheet
and for explaining just what a bank wants from a potential agricultural investment. Lastly there would
be no project without Graham Brodie who was in charge of the “Industry Project” subject. His lectures
and general advice was very valuable.
8. References
Australian Bureau of Agricultural and Resource Economics and Science 2010 ’Australian Commodity
Statistics 2010’ Accessed on 14/8/14, Available at
http://data.daff.gov.au/brs/data/warehouse/pe_abares99001762/ACS_2010.pdf
Barry, P.J, Hopkin, J.A. and Baker, C.B 1988. Financial Management in Agriculture, The Interstate
Printers and Publishers, Danville, Illinois.
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Boehlje, M.D and Eidman, V.R 1988. Farm Management, John Wiley & Sons, New York.
Esparon, N. 2002. ‘The determinants of prices of farmland in Victoria 1988-1997: Regional, activity and
farm perspectives’ Unpublished Phd Thesis, Institute of Land and Food Resources, The University of
Melbourne.
Eves, C 2010 ‘NSW Rural Land Performance 1990-2008.’ Australasian Agribusiness Review, 18:85-102
GrainCorp1
2014. ‘GrainCorp Daily Contract Prices – Victorian Mallee and Wimmera’ Accessed on
16/8/14, Available at http://www.graincorp.com.au/daily-contract-prices/Northern%20VIC%20-
%20Wheat.pdf
GrainCorp2
2014 ‘GrainCorp Daily Contract Prices – Eastern Victoria’ Accessed on 16/8/14, Available
at http://www.graincorp.com.au/daily-contract-prices/Eastern%20VIC%20-%20Wheat.pdf
Grains Research & Development Corporation 2014 ‘Farm Gross Margin & Enterprise Planning Guide’
Accessed on 14/8/14, Available at http://www.grdc.com.au/FarmGrossMarginGuide
Grains Research & Development Corporation 2012 ‘Capitalising on rising land values: long term trend
is our friend’ Farm Business Update, 7:1-2
Just R, and Miranowski J. 1993. ‘Understanding farmland price changes’ American Journal of
Agricultural Economics, 75:156-168
Makeham, J.P. and Malcolm L.R. 1993. The Farming Game Now. Cambridge University Press,
Melbourne.
Melichar E. 1979. ‘Capital gains versus current income in the farming sector’, American Journal of
Agricultural Economics. 61:1085-1092
Valuer General Victoria 2013, ‘A Guide to Property Values 2013’ Accessed on 14/8/14, Available at
http://www.dtpli.vic.gov.au/property-and-land-titles/property-information/property-prices
