Marc_Rafanell_Lopez_Bachelor's_Thesis

American Farmland Bubble (… Again)?
Marc Rafanell López
Tutored by Marta Alonso
Project Code: EWI12
June 2015 (Academic year 2014/2015)
Universitat Pompeu Fabra – Barcelona

Universitat Pompeu Fabra Marc Rafanell López
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ABSTRACT
This study has the goal to determine if there is evidence or not to argue for the existence of a
bubble in the U.S. Farmland in current times. To doso, we look both at historical background
and compare the 1980s crisis with the current situation (Section 2). We also question the
valuation models employed, researching some alternatives and explaining its implications
(Section 3). With the aim to further understand the complexity of irrational behaviors in
markets, we describe the three main categories of bubbles and fads (Section 4). Finally, we
carry an empirical analysis, looking at the descriptive statistics of the main factors
influencing farmland values and their evolution during the last two decades, as well as
examining an OLS regression model that uses Illinois farmland data to check for evidence in
favor of the existence of an irrational bubble (Section 5).
All in all, we conclude that there is no evidence to claim for the existence of an irrational
bubble. Nonetheless, we believe that the U.S. Farmland market might be immersing in a
growing rational bubble, supported by the expected profitability of its underlying economic
determinants. That still should be handled with caution by regulators and investors since a
switch in some independent factors could dramatically change the agricultural real estate
values, and that would have important consequences on the economic performance of many
farmers and landlords.
Keywords: farmland values, speculative bubbles, agricultural commodity market, farmland
valuation, asset pricing models, determinants of farmland values, rational bubbles.
INDEX
INTRODUCTION......................................................................................................................3!
HISTORICAL BACKGROUND: American Farmland Bubble 1980s......................................5!
FARMLAND PRICES EVOLUTION AND PRICING MODELS...........................................8!
Evolution of the American Farmland Market ........................................................................8!
Traditional Farmland Valuation Model................................................................................10!
Hedonic Land Price Valuation Model..................................................................................12!
Real Option Farmland Valuation Model ..............................................................................13!
BUBBLES AND FADS ...........................................................................................................15!
Growing Rational Bubbles ...................................................................................................15!
Irrational Fads......................................................................................................................17!
Information Bubbles.............................................................................................................18!
U.S. FARMLAND EMPIRICAL ANALYSIS ........................................................................18!
Data and Methodology .........................................................................................................19!
Empirical Analysis and Results............................................................................................20!
CONCLUSION ........................................................................................................................22
APPENDIX & REFERENCES .........................................................................................I- XIII

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INTODUCTION
In 2007, arguably the biggest American private real estate bubble burst leading to what has
been defined by many the deepest economic downturn since the Great Depression. The
economic recession did not only affect the United States of America. In a globalized world
such as the current one, this dramatic event spread all over the western world, becoming the
massive financial crisis of the twenty-first century. This paper is not about this crisis, its
consequences nor its origin. Nonetheless, we believe it is necessary to highlight that one of its
major triggers was the American Housing Bubble.
In early March 2011, professor Robert Shiller, Nobel Price winner, laureate economist and
specialist in bubbles, wrote an alarming article in Project Syndicate and the Magazine of
International Economic Policy, where he alerted about the likelihood of the creation of a new
bubble no one was paying attention to, a bubble in the American Farmland Market. In his
own words he defined the farmland market as: “my favorite dark-horse bubble candidate for
the next decade or so […]”.(Shiller 2011a)(Shiller 2011b) Prof. Robert J. Shiller has been
considered a visionary in matter of bubbles since he predicted and warned the world about the
creation and the dangers of the last American housing bubble before it burst and ended up in
such catastrophic consequences (Shiller 2007). Probably because no one listened to him in
2007, when he foreshadowed and alarmed the dangers of the private real estate market
situation, the entire economic community learned the consequences of not acting upon his
warnings, and thus started looking into it and researching about it. Also bringing regulators
into the scene in order to keep an attentive eye and begin to propose regulations that could
stop a theoretical bubble.
From 2011 that Prof. Shiller set the focus onto the Farmland market, many different
academics have been debating about it. Some defend the presence of enough evidence to
support that such a bubble exists, others say that the economic situation of the Farmland
market is not part of a bubble but can be explained by economic fundamentals. The scientific
community seems not to agree, even Prof. Shiller who started the whole warning in 2011,
turned his words and said that the Farmland prices current evolution should be defined more
as an “overreaction” rather than a bubble (Badkar 2013).
Above all, one thing is clear, the Farmland Market has been experiencing a very strong rise
on its nominal prices for the last two decades. In Appendix 1, we have graphed the evolution
of nominal farmland prices per acre in Iowa, which is a good representative state by the fact
of being formed by parts of three of the four most productive and farm intensive regions in
United States: Northern Plains, Lake States and Corn Belt (Appendix 2). For a long time now
the nominal price of farmland per acre has far overpassed the peak reached in 1980s when the

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bubble burst. The picture of this rapid increase in prices makes many jump to alarming
conclusions. Nonetheless, they are forgetting to consider the possibility that those prices
indeed reflect some rational economic fundamentals. The question is clear, is there a real
bubble growing on the American Farmland Market or despite the substantial growth
experienced in the last decade, Farmland Market prices still respond to the rationale of
economic fundamentals.
This topic is, in part, of current interest due to the existing fear that such burst could inflict on
the still recovering American economy. Regulators and experts are aware of the lack of action
and prediction they have been blamed for. It is this fear that probably explains the exceptional
interest this field is attracting. We should not forget though that the entire US Farmland
market was in 2010 “only” worth $1.9 trillion, compared with the $16.5 trillion that
composed the US stock market back then, or the $16.6 trillion that US housing market
accounted for in 2010. Therefore, a hypothetical burst of the Farmland bubble would most
likely not represent a shock such as the one experienced in 2007. Once said that, it is also
worth noting that Farmland in United States represents over 85% on average of the active of a
farmer’s balance sheet. A little drop on this asset’s value would dramatically incline many
farmers towards a possible financial distress and we could see many farmers being forced to
go out of business as it happened in the 1980s.
In this paper we try to get together the broad amount of arguments that have been presented
by many academics up to now. We will try to draw a conclusion on the determination on
whether there is a bubble in the American Farmland market or not. Furthermore we will try to
analyze the actual dangers the American society is facing due to the current price situation.
We believe that a comparison with the previous bubble suffered by farmland in US is a good
point to start.
Finally, before we get involved with the further research, it is good to keep in mind a peculiar
but concise explanation that Prof. Robert J. Shiller stated about the problem on predicting
bubbles, because that is, in part, what this paper will be trying to do: “It is impossible for
anyone to predict bubbles accurately. Bubbles are social epidemics, fostered by interpersonal
contagion. A bubble forms when the contagion rate goes up for ideas that support a bubble.
But contagion rates depend on patterns of thinking, which are, at best, difficult to judge”.

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HISTORICAL BACKGROUND: American Farmland Bubble 1980s
In Economics, history seems to repeat over and over until the proper regulation is established.
It is commonly said that the human race is the only one to bump into the same mistake over
and over. The number of economic crisis in history is almost uncountable, and it would be
silly to think that there is any reason to believe it will never stop increasing. A good job that
economists do is to explain the past. It is then when many academics are able to find
similarities among different crisis, but another story comes when is about setting the
regulation needed to avoid to step on the same rock again.
The 1980s American Farmland suffered a crisis that has many similarities with other crisis
too. To start with we will describe the main factors and characteristics of this economic event
in history. As we can observe in Appendix 3 (graph 1) the nominal prices for Farmland were
more o less flat during the 60s. However, it was in the 70s that suddenly its rate of growth
started to climb. Furthermore, if we look at Appendix 3 (graph 2), which shows the inflation-
adjusted version of the price evolution, the growth in real terms looks even more spectacular
due to the high inflation of the time. Indeed, as some academics have argued, land has always
been characterized by being used as a hedge against inflation (Lavin and Zorn 2001). In
Appendix 4 we depicted a more detailed analysis. At first glance we can observe that prices
went up for over a decade and then they dropped. It was indeed in 1982 that the, commonly
defined as a bubble in the Farmland market, burst and then nominal prices suddenly went
down by 27% (38% in real terms) creating huge consequences and economic distress on farm
owners as well as bankrupting many agricultural creditors, and finally making the US
Government bailout the biggest creditors among all, a government-sponsored enterprise
called the Farm Credit System.
So far the description of this crisis looks very much alike to a quite recent one, the 2008
financial crisis, which was indeed originated, among others by the burst of the American
Private Real Estate Bubble in 2007. A clear example of a common feature between those two
crises is the Congress approval of the Farm Credit Act in 1971, where they raised the lending
capacity of banks by allowing them to lend up to 85% (rinsing it from 65%) of the purchase
price of the farm. In the same way, a government-sponsored enterprise, the Farm Credit
System, was the major lender and further enhanced the levels of debt in the farming sector
until it had to be bailed out by the American taxpayers. Our aim in this paper is not to find the
relations between these two crises, which must be said, are far from being the same. But we
would like to point out the tendency of the American system to increase bubbles by making
lending more and more available. The structure of equity and debt is a crucial factor to take
into account when evaluating the risks of a market that might be immerse in a bubble. Once
said that, also state that by no means we aim to define debt as bad or noxious for the

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economy. Lending and borrowing of capital is one of the most important advances from all
times that allowed capital to be invested where it was more efficient. It is only the
combination of a too high level of leverage and the misusage of the economic fundamentals
that can lead to a dangerous situation.
The 1980s American Farmland rise in prices, which led to the creation of a bubble, had
several determinants, among them we find the Malthusian Optimism hypothesis, which stated
that the demand for food would grow exponentially, in a worldwide basis, but the supply of
food was not dynamic enough and would not be able to mime it, leading towards a future rise
of food prices due to the excess of demand.
Bubbles are very hard to predict and even to realize, until it is too late, and this was clearly
the case in 1982. The question we are willing to look at in this paper is whether we have
learned enough already to avoid errors from the past, but also if there is substantial evidence
or not to state that a bubble has formed again in the American Farmland market. Which are
the similarities and indicators that should worry us about the current state of the market?
In comparing the 1980s Farmland market and the current one, some leading difference should
be pointed out, among them we believe it is important to mention the interest rates, the
lending environment, the insurance level and capitalization rates.
First of all we will start by looking at the interest rates, which are traditionally considered as a
key factor for the whole economy. From the economic theory we know that low levels of
interest rates incentive investment. Another interesting factor is the manageability of this tool,
which is under the control of central banks (in the American case, the Federal Reserve).
Given that, and as we can observe in Appendix 7, the interest rate depicted by the risk free
rate of the 10 year US Treasury bond was over 10% in 1980s, while now its around 4% or
less, which justifies up to some extend the current high farmland prices. At the same time, in
that same figure we can observe the interest rate risk premium that farmland owners had to
pay, which has been on a steady rise since before the 1980. This increase is not too strong but
might reflect a perceived increase on the risk on farmland loans by creditors. The rise on the
premium that jumped over 2% and never came back steadily happened before the burst of any
of the bubbles. So in terms of comparing them it does not comprise much newer information.
In addition, another factor we believe is crucial on the comparison between the two moments
in time is the level of debt an average farmer had back in 1980s and now. A time series that
plots the debt-to-equity (assets) ratio can be found in Appendix 8. From that graph we can
clearly see that the level of leverage was substantially higher in 1980s than it is now. The
translation into practical matters of such information is that the risk of bankruptcy is lower in

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the case of a drop in asset value. In other words, even if the farmland were currently over
valuated a drop of its value would signify less financial pressure for landlords.
Another interesting aspect to take into account is the level of insurance that farmers have to
smooth income variability in time and avoid shortfalls in poor production years. As shown by
studies such as Sherrick and Schnitkey 2014 and Pollock 2012, farmland owners have
increased both the degree to which they use insurance, as well as the coverage of those
insurances. This characteristic brings with it two different consequences. First, it diminishes
the risk of bankruptcy due to the reduced volatility in terms of revenues. Second, it increases
the in systematic risk by creating a chain of creditors, which favors the economic activity in a
typical scenario, but it collapses in the case of a bubble busting.
Finally, the fourth aspect we believe it is worth pointing out is the evolution of farmland
capitalization rate. In Appendix 6 we can observe a time series of the farmland’s
capitalization rate compared with the capitalization rate of the risk free asset, 10-yr US
Treasury bond. It is noticeable that in 1980 there was a big gap between those capitalization
rates, with the farmland resulting as a substantially less profitable investment. This low
capitalization rate might have several explanations, but the over valuation of the production
asset looks like a good candidate. Looking at the time series we can also observe that in
recent times, not only capitalization rate gap with the risk free asset has abridged but indeed is
currently the farmland’s capitalization rate that is above.
In this section we have passed through an overview of the biggest American Farmland bubble
in history, which took place in 1980s, and compared it with the current situation to get some
insights of whether the patterns seem to repeat. After a close look it does not look like the
current situation resembles the past experience except for a steady rise of farmland prices.
The Farmland market seems more stable and levels of leverage are substantially lower, which
would make the bursting of such a hypothetical bubble less painful, but also it makes it less
probable. Bubbles are irrational behaviors driven by a rise of contagion rates of
overenthusiasm. Whenever that happens, leverage tends to go up because investors care less
in terms of risk and more about the overestimated returns, but this does not seem to be the
case in current times. The conclusions from this section should not blind us and make us
believe that no bubble exists in the American Farmland in recent times. We still have to
analyze many other reasons that could support the existence of such a bubble. In the
following sections we will jump from the historical perspective towards an empirical analysis
of the current farmland market.

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FARMLAND PRICES EVOLUTION AND PRICING MODELS
As Chavas and Thomas argued on their study, agricultural land is traditionally a good
candidate for bubbles due to its significant transaction costs and overreaction to change in
market fundamentals (Chavas and Thomas 1999). Farmland price evolution has been
traditionally determined by several economic fundamentals, which bring with them high
levels of uncertainty and might lead to overvaluation. Incorrect pricing and the formation of a
bubble could be due to an overreaction or overestimation of the underlying economic
principals, but at the same time the omission of some market fundamentals could mislead the
analysis and bring to the erroneous conclusion that a bubble exists when it does not.
In this section we will explore first the evolution of Farmland prices in recent times to have
an empirical perspective about the current market situation. Afterwards, we will proceed to
overlook and analyze different pricing models that have been proposed by academics and its
implication in terms of the current market data. The study of these aspects will allow us to
draw some conclusions on the rationale behind the argument of an existence of a bubble in
the American Farmland market.
Evolution of the American Farmland Market
Farming and Agriculture in the United States of America has traditionally been an important
sector both to serve its big internal market demand as well as to supply exports, all over the
world. A clear example of it is the fact that over 40% of all U.S. land base was dedicated to
farm and agricultural purposes in 2007 (Appendix 2). This sector has always been also
characterized by its land intensive characteristics, farm real estate represents much of the
value of U.S. farm sector assets, around 85%, which implies that variability in farmland value
has important impacts on farm owners, as well as sector’s financial stability and economic
performance (Nickerson et al. 2012).
Regardless of its structural importance in farmers’ balance sheets, farmland value has not
been traditionally stable. In current times it has been increasing at rates difficult to find in any
other asset with resembling importance. As we can observe in both figures in Appendix 3,
U.S. average farmland prices have been steadily rising, both in nominal and real terms, for the
last two decades. This climb in the prices of farmland values started after the 1980s
Agricultural crisis, where prices drop dramatically after the existing bubble burst in 1982. In
current times, even real, prices have already overpassed the level they were at the peak of the
last century’s bubble. Can we conclude from this, that a new bubble exists?
As we explained in the previews section, the current situation is different in many aspects.
Nowadays we can find several explanations that could arguably sustain a rational view of
such a growth in prices. Among those arguments we believe it is good to highlight the most

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important ones. First of all, it is worth noting that farmland is a capital asset that will
theoretically produce output indefinitely into the future. This concept is the main idea behind
the traditional farmland valuation model, which we will explain in more depth later, and at
the same time brings some of the most important reasons behind this high farm real estate
values. In current times, food production and profitability per acre of farmland has increased
substantially (Huang et al. 2006). In addition to that, farmland, unlike housing sector in its
last bubble, did not increase its supply in terms of acres of land (Tseng 2013), indeed, its
turnover is, and has maintained, extremely low (Gloy et al. 2011), which brings us to believe
that most farmland owners are exploiters who believe that such a high price is reasonable,
rather than speculators, who are willing to buy farmland just to sell it at a higher price a week
after. To look at some numbers we have depicted in Appendix 9, the million of acres, as well
as the percentage that it represents by whether the landlord is an operator or non-operator, and
we can clearly see that, although it is significant, the ownership of non-operator investors
does account on average for a bit less than one third.
The strong trend of rising farm real estate values have also been held by the mere rules of
demand and supply. Both an unprecedented rise on world food demand, conducted mainly by
the increase in developing countries (Olsen and Stokes 2014), as well as the rise in the
internal demand, due to the more than questioned Ethanol policies, which aimed for a
production (using crop) of 13.2 billion gallons by 2012 (Blank, Erickson, and Hallahan 2012),
drove the demand far away from the equilibrium point due to lack on a similar increase of
supply. Consequently, commodity goods, and specially crop prices have been rising strongly
(Appendix 10), and as the Financial Stability Oversight Council stated last year, this has
played a determinant role on farmland prices.
Following the explanation that farmland prices have been driven up by speculators, we can
indeed observe the effect that closeness from urban areas represents. This argument is agreed
to be true, although it has to be taken with caution. First of all, it has been proven that
influence of nearest urban areas has exerted positive influence on farmland prices (Nickerson
et al. 2012). This influence could be explained by the speculative value of the usage of those
lands for private real estate, but also since farmland is a productive factor, it could be
explained by the ease of transportation and access to markets provided. The housing crisis
recently experienced in U.S. has claimed against the speculative argument by observing that
while house prices where dropping after 2007, farmland prices still were growing, as we can
observe in Appendix 5.
Last but not least, and as we already mentioned in the previews section, interest rates and
alternative investment opportunities played a big role in the price evolution of farmland.
Sustained historically low interest rates, as can be observed in the U.S. Treasury bonds

10
representation in Appendix 7, have facilitated the rise of farmland values. As former president
of Kansas Federal Reserve, Thomas Hoenig stated: “Cheap money artificially boosted
farmland prices.” He also warned though that: “When current historically low interest rates
reverse and trend higher, land values will drop dramatically.”
All in all, we have seen that many diverse fundamental factors can help support a rational
explanation of the current state of the farmland market values. As very eloquently Blanchard
and Watson (1982) argued on their leading study about asset valuation, the price of an asset is
determined both by the fundamental component and a rational expectation component. This is
probably true also in farmland’s market, but the question we are here to answer is whether
this valuation has been done correctly, whether there is an additional speculative component,
and consequently, whether the behavior of the market corresponds to a economically logic
situation or not.
In the rest of this section we will describe three different existing models to value farmland
and the consequent rationale of the current market situation under each of the models.
Traditional Farmland Valuation Model
From basic financial theory of asset valuation we know that the main criteria to follow is the
strictly positive sign of the net present value. More in depth, this basic valuation model states
that any company should adopt a project if and only if its properly computed net present value
is positive. In mathematical terms we can use the following formula:
!"# = !! +!
!!!"!!!
1 + !!!!
!
!!!
!
!!!
!!!!!!!!!!!(!. 1)
The expression above shows the general formula to compute the net present value of any
project or productive asset. In the formula we can observe the !! which represents the up front
investment needed for the project at time 0, i.e. the cost of the project. Following we find the
sum of all the expected cash flows duly discounted taking into account the cost of capital
(!!!!) at any point in time. For any project ! represents the economic life of the investment,
and more specifically in the case of land, it is assumed that ! → !∞. Given this we can
reformulate the general expression into the following linear regression model with respect to
the cash flows:
!! = !
!!!"!!!
1 + !!!!
!
!!!
!
!!!
=!∝!+!∝! !"! +!∝! !! +!!!!!!!!!!!!!!(!. 2)

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The main coefficients (∝! !!"#! ∝!) represent the effect that respectively cash flows and
interest rates exert onto the value of the asset. A more specific approach to the Traditional
Farmland Valuation Model would be represented by:
!"#$%"&'!!"#$% !! = !
!"#$%&$'!!"#$%&!!"#$!!"#$
!"#$!!"!!"#$%"& − !"#$%&!!"#$%ℎ
!!!!!!!!!!(!. 3)
Formula 3 follows simple algebraic transformation to represent a perpetuity valuation model,
which uses the assumption that ! → !∞, or in less technical terms, the assumption that
farmland is expected to produce income forever.
The traditional valuation model for farmland has been expanded by many agricultural
economists to include other aspects that seem to influence the value of farm real estate in
modern times. Nonetheless, the logic expressed above represents the main aspects of analysis.
From it we can clearly see the over simplicity of this model. In modern times, as we
explained earlier in the section, many other factors influence farmland values, but even if
there were no, the model expressed above does not seem to capture an important aspect of
any valuation: uncertainty. It is a fact that expected future cash revenues from agricultural
activity are at best uncertain, and the same can be argued for the cost of capital. As Huang et
al. (2006), argued land prices reflect not only the current use of land but also the expected
competing potential uses. This expected uses are somehow included in the model explained
above, but the uncertainty inherent to them does not seem to be properly captured.
It is because of this that many authors, such as Turvey (2002) or Huang et al. (2006), further
discussed and presented other valuation models that aim to capture other aspects which
influence the farmland market value in a determinant way. Furthermore, the previous model
does not seem to work on explaining the current market situation and thus it would support
the prediction of the existence of an irrational bubble in the farmland market. In Appendix 11,
we can find some illustrative time series from Iowa’s agricultural results, which show how
the economic fundamental of increase on farmland income would support the current trend in
farm real estate, but would have a harder time to justify its entire climb. It seems clear that the
growth in price of the asset is far too strong to be justified exclusively by the growth
experienced during the same time-lap in farming income. More specifically, Pollock (2012)
proved that using the Traditional Farmland Valuation Model with the current prices, income,
interest rates and expected growths, we find the existence of an irrational bubble in the
market.

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In the following sections we will look at the models presented by Huang et al. (2006) and
Turvey (2002), which have in common the introduction of alternative economic fundamentals
that have impact on farmland values into the valuation model.
Hedonic Land Price Valuation Model
The hedonic technique is a statistical modeling technique that economists use to substitute
proxies for actual measures of returns that are usually not available. This technique has been
broadly used in farmland valuation to include more complex determinants into the model.
Using diverse proxies, the valuation model aggregates all different values to find the
particular value of the land parcel. The hedonic approach has shown to be able to isolate and
analyze the impact of changes in factors that determine the farmland value.
Huang et al. (2006) presented a model for the valuation of Illinois’ farmland, which in general
terms could perfectly work for any other region in the United States. This model stated that a
useful hedonic farmland pricing model must include factors that represent productivity
patterns, neighborhood characteristics, location, as well as environmental situation of land. In
his study, using a hedonic model, he found that farmland values rise with soil productivity,
population density, and personal income but decline with parcel size, ruralness of the county,
and distance to large cities.
His study highlights that nonfarm income factors also exert determinant influence in land
values and thus a model that fails to capture those aspects, most likely suffers from
inaccuracy and big biases.
All in all the hedonic model presented by many academics expands the basic valuation model
into a more complex mathematical framework that includes many alternative factors which
are likely to influence the value of land. This model is definitively convenient to capture more
reasons behind the recent farmland market situation and the effect that factors such as public
policies have had onto the value of farming real estate. The model does not focus though on
the study of the existence of a hypothetical bubble. The Hedonic model helps isolate the
effect that many fundamental factors have on farmland prices, but it does not explore whether
this price is the correct one or not.
As previously stated, the main purpose of this paper is to bring light on the factors that
influence the American farmland values, but more specifically focus on whether a bubble has
formed in the market in recent times. Following these intentions, in the next subsection we
will study another farmland valuation model which studies the uncertainty related with the
farmland income and its implication on the rationale of the current market situation.

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Real Option Farmland Valuation Model
Options are financial instruments that belong to the family of derivative financial instruments.
Any derivative asset is such that its payoffs, and consequently its price, depend on the price
evolution of another underlying asset. Specifically, options are contracts that give the right to
buy or sell the underlying asset at a point in time at a previously agreed price. Among all
options contracts, call and put options are the most common ones. A call option gives the
right to buy the underlying asset at a certain moment in the future (or at any moment before a
that date in the specific case of American Options) at a certain price. In the same way, a put
option gives the right to sell the underlying asset at a certain time at a certain price. It is worth
noting that options give the right, but not the obligation to the owner (the person with a long
position) of the call or put, but it brings the obligation to sell or buy to the person who sells
the contract (the individual with a short position). Logically, the seller of an option charges a
premium that is related with the likelihood of the option ending ‘in the money’ (when the
person holding a long position has the rational willingness to execute the option).
The derivative market is enormous and you can almost find contracts with any kind of
underlying asset you could think of. For the purposes of our study, we will focus on the
commodity options, assuming for simplicity that they are European style, and more
specifically we will focus on the call and put real options.
The importance of this third valuation method presented in the literature is the capability that
option contracts have to capture the uncertainty in cash flows that influence land values. As
we have seen previously in this section, land prices are computed using the expectation of
future events. However, those expectations are uncertain, and it is this uncertainty that not
even with a very complicated extension of the traditional valuation model, which includes all
the relevant economic fundamentals driving farmland values, we would be able to calculate it
correctly. It is true that the cost of capital does include the systematic risk compared with the
rest of the economy. Nonetheless, the one key element ignored in traditional valuation of
farmland values is the uncertainty inherent on many of the fundamentals that determine the
land valuation, but behave independently. Real options modeling is able to justify the
acceptance of projects with negative present values and thus, applied to the current farmland
market, it should be able to bing more light onto whether a bubble exists or not.
The real options model that we will consider in this paper was developed and presented by
Turvey (2002). He focused on the specific real option model that considers hysteresis, which
is the economic condition where the past is somehow related to the present and even to the
future in many different ways. We can find many hysteresis behaviors in financial markets
such as the belief that a drastic fall in traded securities will be followed by a rise, which
makes investors hold securities for too long, especially when they are losing value. Bubbles

14
and fads are indeed an extreme form of hysteresis, where rational beliefs about future
outcomes get trapped in a circle and the previous or actual good performance is translated by
a common hyper-optimistic view into assumed future good performances. To give a specific
example, we could consider the Ethanol policies currently put in place by the United States
Government. Those policies have been more than questioned, and it is very difficult to know
with any certainty until when they will last, or how will they evolve. Then, it is clear that high
corn prices have been influenced by the existence of such policies. Therefore, if suddenly, the
US federal government decides to end the Ethanol programs, corn prices would drop and that
would make farmland prices go down. The purpose of this model is how to include this
inerasable uncertainty in the valuation of farmland real estate.
As Turvey defines in his study: “The true value of farmland under a real options framework is
the fundamental (present) value of the land based on currently observed cash flows, including
expected growth, plus an option on future capital gains above expectations.” In the traditional
valuation model, when the net present value is negative, that implies that the asset has no
value for the investor. In the case of farmland, a productive asset that has infinite economic
life, the value is strictly positive since the possibility for prices to go up in the near future is
always there. Finally, another interesting aspect is that if fads or bubbles are to be caused
because of hysteresis, it must be because the general contagion makes landlords not sell, with
the expectation that they will earn more in a foreseeable future, and that creates market
imbalance with lack of supply for the amount demanded. Turvey proposes that owners of land
have positive valued options to postpone the sale of land in the hopes of higher future capital
gains.
The option model used by Turvey (2002), gives an explanation for prices systematically
above economic fundamentals. Using the real options valuation we find that above the
traditional fundamental value that the buyer would be willing to buy the land for, the seller is
not willing to sell unless a premium, which represents the value associated with the option he
owns, is paid. Landlords own an option on the farmland future increased cash flows and they
want to be compensated for it. This option, which is strictly positive by definition, is created
through a questionable (over) optimism that all fundamental factors supporting growth in
agricultural real estate will maintain their trends and thus profitability will not drop.
Turvey used the model previously mentioned to test whether there was evidence of the
existence of bubbles in Ontario’s farmland from 1971 until 1998. In his study they indeed
found strong evidence for such a bubble in the period of the 1980s crisis (1979-1084), and
also for the period after that, although with less certainty.

15
Summing up, even with the inclusion of real options in the valuation model, to capture the
uncertainty of future evolution of the economic fundamentals that define the cash flows of
farmland, the existence of a bubble seems, at least, possible and must be taken into account.
BUBBLES AND FADS
Pricing models have been historically questioned for their accuracy. If we look at financial
literature and more specifically at pricing models for financial assets we easily find that
empirical results do not correspond with the models in place. It is usual to find many markets
where the assets do not represent its theoretical intrinsic value. Therefore, is it that our models
are wrong? Indeed, any specific model such as Black Schools for financial asset pricing are
based on assumptions, and those assumptions are what sometimes do not reflect reality.
In this study we focus on the valuation models for agricultural real estate, to determine if we
can find evidence of a bubble. In this section we will further develop the concept of a bubble
or better said, we will investigate the different kinds of deviations from intrinsic values. To
doso, we will consider the three main categories of price deviation defined by scientific
literature (Camerer 1989). We will study: (1) Growing Rational Bubbles; (2) Irrational Fads;
and (3) Information Bubbles.
The aim of this section is to understand that even if there is a price deviation in farmland
markets, this does not automatically implies the existence of an irrational bubble.
Understanding the conditions and the dangers of each of the three different price divergences
will help us draw conclusions on the current market situation of the U.S. Farmland.
Growing Rational Bubbles
Growing rational bubbles1 are price deviations that are inherent in our current pricing models.
From a mathematical point of view, any valuation model includes difference equations, and
the growing bubbles are defined as constant values, which do not depend on the information,
that govern the price equilibrium. More formally, we must consider ‘Euler’s Equation for
determination of prices:
!. 4 !!!!!!!!! =
[! !!!! !! + !! !!!! !! ]
(1 + !)
In the formula above, we have nothing else than (E.1) reformulated into a probabilistic
version with conditional expectations. The formula tells us that the price at time t will be
determined by the rational expectation of both the revenue produced by this asset in t+1
1!We!will!refer!indistinctively!to!‘growing!rational!bubbles’!both!as!‘rational!bubbles’!and!‘growing!bubbles’!along!the!paper.!!

16
(!!!!), and the price we will be able to resell it at time t+1 (after the profits have been
gathered) (!!!!), all conditioned to the information known at time t, and duly discounted.
Using a simple faming example, the price of land X would be determined by the profits the
farmer expects to get from growing and selling for instance corn, plus the value of the land
after this year, all brought to present value.
A rational bubble must satisfy the form: !! = !
![!!!!]
(!!!)
!or alternatively !!!! = 1 + ! !! + !!
In the later form of the definition of a bubble, we can see that any rational bubble must grow
at a rate (r) for the price to be sustained. This rate must be specifically the rate of cost of
capital for the appropriate risk involved on this bubble. Therefore, a rational investor knows
that he cannot make excess profits from a bubble. Probability that a stochastic bubble will
burst is given by [1 − (1 − !)!
], being n the number of periods. Given that ! ≠ ∞, and thus
assuming that the bubble will ‘eventually’ burst at some point, a rational investor must know
that a such a bubble is a negative-sum game and after the last transaction all investors on
average will have negative profits.
Finally, if we further develop Euler’s Formula we include a rational bubble to set the
equilibrium, giving us the following version of the valuation model:
!. 5 !!!!!!!!! = !
![!!!!|!!]
(1 + !)!
!
!!!
+ !!
This valuation model states that the price of an asset such as land, with infinite economic life,
will be determined by the sum of all its future cash flows duly discounted plus a rational
bubble, which does not depend at all on the productivity of the asset, and it self-fulfills.
Nonetheless, it is a rational bubble.
Finally, for a growing rational bubble to exist some conditions must be satisfied:
(1) Investors, or land buyers in our case, must be either risk neutral or risk lovers. If they
were risk averse, the risk inherent in a bubble, which we must remember that it is a
negative-sum game, would make the investment unappealing to them.
(2) The asset must be durable. It is clear that farmland is a durable asset, indeed land is
considered to have an infinite economic life. Otherwise, if it were to be non-durable,
investors would not see the possibility of resale of the asset and thus a rational bubble
would never grow.
(3) The asset must have a limited supply. Scarcity is a needed assumption because if the
asset could increase its supply as a reaction on the increase of the price through the
bubble, the price would be driven down and the bubble would no longer exist. In the
case of farmland in U.S., the condition seems to be met since the supply of land have
not increased regardless of the tremendous rise in prices experienced in recent times.

17
Besides the empirical argument, from a theoretical point of view it is also
understandable that land in general is by definition an asset with bounded supply, i.e.
in the United States there are ‘x’ acres of land and any demand higher than ‘x’ will
result in excess of demand.
Therefore, we could say that farmland is a suitable candidate to experience growing rational
bubbles.
Irrational Fads
Fads or irrational bubbles are deviation from the intrinsic price produced by social patterns
and common social euphoria, which lead to over-optimistic beliefs and mispricing. Camerer
(1989) defined fads as “deviation between prices and intrinsic value, !!, that slowly revert to
its mean of zero.” More formally, we can define fads in a similar way as we did with rational
bubbles (E.5):
!. 6 !!!!!!! = !
! !!!!|!!
1 + ! !
!
!!!
+!!!!
!. !.!!!!!!!!!! = !!! + !!
In the expression above, we can see that a fad is defined just as a rational bubble when its
coefficient ! = (1 + !). At the same time, if ! = 0, no fad exists. But in the traditional
definition of an irrational fad, ! < 1, and thus this coefficient is called the decay factor. This
simple modification makes fads an irrational investment since the price does not respect any
economic rationale that would induce an investor to be willing to ship into it and bear the risk.
Nonetheless, that does not imply that fads do not exist in real life. Indeed, they do exist
because investors are overconfident and they believe they will not be the losers and they will
be able to bet on it before it disappears (before it comes back to its mean of zero).
This specific kind of irrational behavior is especially difficult to test, although it is the most
dangerous since the burst of the irrational bubble would be rapid and unpredictable. The most
commonly used method to test whether a market is likely to experience fads is the test of
volatility. In this test of volatility, it is checked if the basic assumption in market efficiency of
! !! !! = 0 is satisfied. Empirical tests prove that variance is too high in many markets to
be explained by rational models (Blanchard and Watson 1982; Engle 1983; Fama and French
1988).
Our question is though, whether the American farmland market is likely to experience
irrational bubbles, but from a theoretical point of view farmland does not look like a potential
candidate since the trend of rising prices does not seem correlated with social euphoria
(Badkar 2013).

18
Information Bubbles
Information bubbles are related with the concept of asymmetric information. The (Strong)
Efficiency Market Hypothesis assumes that all participants have the same information
because all relevant information is present on prices. Therefore, no investor can make money
by looking at past prices, since current prices are already reflecting such information.
Many have questioned the applicability of the Efficiency Theory because it does not seem to
fit empirical data. Furthermore, it could be argued that the assumption that all information is
public and reflected in prices is at least not always true.
This is the case for information bubbles, when investors have different information or even
use different methods to value land in the economic world, it is feasible that prices will
deviate from the intrinsic value. These deviations can both be rational or irrational. It all
depends on whether the investor does actually own some valuable information, and he is
doing an economic rational valuation of it.
For purposes of our study, we could find some cases where the asymmetric information is
likely to exist such as investors who know from inside information that U.S. Gov. subsidies to
ethanol policies will remain (or will stop). Nonetheless, and even though we believe this
category of price deviations is an important one, for simplicity, we will assume for the rest of
the study that no investor uses any not-public information such as the one mentioned above.
In a same way we are aware that on the seller side, he has a position of advantage in terms of
inside information on the farmland he is selling. For the macro-perspective of this study
though, both parties will effectively know all relevant information.
U.S. FARMLAND EMPIRICAL ANALYSIS
Literature and analysis about farmland prices is wide, and you can find many authors who
conclude that a bubble exists (both currently and in 1980s)(Turvey 2002; Pollock 2012), as
well as authors who throughout their analysis do not find enough evidence to conclude the
existence of such speculative behavior (Huang et al. 2006; Badkar 2013). The aim of this
study is to bring more light and contribute to the economic literature through both an
overview of the research done by others and the empirical data and factors that influence the
farm real estate in the United States. In addition, we will also end our study with an analysis
of empirical data using farmland prices and comparing their evolution with some factors we
consider that have an important impact on the determination of prices. With this study, we
aim to find some ground to defeat the hypothesis that an irrational behavior has been
governing the current state of the market in the U.S. Farmland.

19
Data and Methodology
For the analysis in this paper we will use several datasets. First of all we will use the farmland
prices from 1970 until 2014 provided by United States Agricultural Department (USDA)
National Service of Statistics. This dataset is composed by the average value per acre of
farmland each year gathered through surveys and transaction recordings. This dataset, which
is displayed in Appendix 3 (Panel 2), will be used in real terms holding 2009 as the base year.
In addition to our main dataset we will use data to proxy some factors we believe are
determinants for the price of farmland. To keep our study away from complications that
would blind us in front of the real trends, we will only consider the five main factors that we
believe can explain this current rise in values. The first two factors we must consider are the
ones already included in the traditional valuation model: (Factor 1) cash earnings and
(Factor 2) interest rates. Cash earnings will be represented by revenue from crop in the US,
we use crops because it is the most widely produced commodity and because it is a good
representative for the food price increase. We will use the revenue instead of the price per
bushel because through this we already include the moderate change in productivity that has
similar intuition from an analytical point of view. Our second factor, interest rate, will be
included through data from the Federal Reserve. We will use US Treasury 10-year bonds to
represent the interest rate prevailing in the economy. As we have seen in Appendix 7,
farmland interest rates have been following a similar trend with respect to the risk-free
benchmark.
After considering the two main factors, as we have been discussing throughout the whole
paper, we believe that some other factors, which tend to be ignored, do actually have an
impact on farmland values. Specifically, we will focus on (Factor 3) non-agricultural land
prices and (Factor 4) corn futures. The influence of non-agricultural land prices will be
brought by two different concepts. First, private real estate market evolution, which as we can
observe in Appendix 5 suffered a huge drop in value in the 2008 crisis. Second, the influence
that closeness to urban areas has on farmland values. In Appendix 14, we can observe the
value of farmland conditioned to its distance to major cities. Finally, we have the expected
future value of corn, which is represented by the settlement price on traded corn futures
presented in Appendix 15.
Finally, the methodology used in this paper will be a qualitative, rather than quantitative,
study of trends looking at cross-factor influences on the farmland values. In addition to that
we will complement these descriptive statistics with an interpretation of the OLS regression
study carried out by Huang et al. (2006) using different factors that influence Illinois’
farmland values.

20
Empirical Analysis and Results
This last section of the study will take a final look at the empirical data and draw some
arguments about the likelihood of the existence of a speculative bubble in the U.S. Farmland
market. Our main dataset is presented in Appendix 3 (Panel B), which shows us the big rise in
prices experienced during the last two decades in farmland prices. This strong growth has
made many academics call for the existence of a bubble in this sector. Furthermore, as we did
previously, if we look at Appendix 5, we can see that Farmland prices were following growth
rates similar to private housing sector, but in 2007 (when the real estate bubble burst),
farmland prices keep on going up. From this picture some have argued that the farmland
bubble kept on growing and it will burst at some point, but it could also be that farmland
prices sustain this high growth due to some economic fundamentals that do not support
private real estate.
We will start by looking at the two main factors (considered under the traditional valuation
analysis). Both factors have been behaving in the same direction as farmland prices. As we
can observe in Appendix 10, agricultural land profitability has been growing at strong rates in
the last two decades and especially since 2005, where the gross value of production was
approximately 260 dollars per acre per year, until 2011, where it was approximately 840
dollars per acre. That implies that productivity in dollar terms more than tripled in just six
years. Even after the drop of prices in 2012, currently the acre production is approximately
600 dollars per year. This rapid and sustained growth clearly supports the evolution of
farmland values. Indeed expectations of future cash flows are even higher and this, in
conjunction with the historically low interest rates we can observe in Appendix 7, makes the
present value of farmland exceptionally high. This high market valuation definitively supports
the rational argument behind the exceptionally high prices.
Furthermore, if we look at our third factor (Appendix 14), we see that urban areas have had a
huge influence on the value of farmland. As presented by Nickerson et al. (2012), the
increasing expectations of investors on the possible future values of farmland for other
purposes such as private real estate, commercial real estate, rural practices or forest
conservation areas. This third factor also has helped push farmland values higher.
Finally, the fourth factor we look at is corn future contracts’ price at current times. As
presented by Turvey (2002), options and futures can help explain the uncertainty not captured
by farmland traditional valuation. The complex financial markets when pricing those
commodity derivatives consider other factors, and this brings more light into the picture, as
well as more reliability behind the rationale supporting prices. In Appendix 15 you can
observe the settlement price for futures at different maturities. At first glance we can say that
longer into the future, investors hope corn will be more valued. This upward slopping curve

21
for derivatives shows the expectations of investors that corn will have a higher price in the
future. The fourth factor again supports the high prices on farmland market because
prospective profits from farmland are expected to be even higher.
Finally we will interpret the OLS regression presented in Appendix 15, which includes eleven
proxies to control for most of the factors influencing land values. After running the regression
it is clear to conclude that since all coefficients do fit into the model correctly, no speculative
bubble seems to exist.
Proceeding to do the analysis, we must first notice that all coefficient turn out to be
statistically significant at 99% confidence, and !!
is almost 80%. In terms of coefficients we
will explain them one by one:
1. Size represents the number of acres of each land sold and it turns out to have a
slightly negative coefficient (-0.540) indicating that bigger lands sell for lower price
per acre. This can be easily understood by the bargaining power of big investors.
2. Class is a proxy for the quality of land, captured by the improvements made on this
land. The coefficient turns out to be positive (0.064), as rational Economics would
suggest. Also, since farmland is a productive factor, if it is more productive, it is
more valuable.
3. SPR is another proxy for the quality of land, but in this case measures the
productivity index of the land. As we would expect the coefficient is positive (0.725).
4. DICH and DICI represents proxies for the distance to a major city influence. DICH
represents the distance from Chicago of Illinois farmlands, and DICI captures the
distance to any near city over 50k inhabitants. As we argued before, both have
negative coefficients (-0.311 and -0.039) because the farther a land is the less positive
influence it gets from urban areas. It is also clear that Chicago has much more
influence than any other city in the State.
5. Beale stands for whether the land is in an urban or rural condominium with a scale
from 0 up to 10. The effect is slightly negative (-0.094) which follows the same logic
as DICH and DICI.
6. !"#!! denotes the consumer price index, lagged to respect some econometric
specifications presented in the original paper. The coefficient is also negative and
proportionally strong (-0.482), which supports the arguments previously presented of
land being a traditional hedge against inflation and price increase.
7. !"!90 is related with the population density living in a square mile in 1990. The
effect shows to be positive bringing the intuition that more populated areas have
higher values associated with land.

22
8. Income embodies the U.S. average income per capita in real terms. Its coefficient also
shows to be positive which clearly follows basic economic rationale.
9. Farm Density controls for the swine density around the farmland. This specific factor
is considered in the study due to the fact that in Illinois the swine industry has been
accused to damage properties near where they establish. The coefficient is as
expected negative (-0.207). Scale is also related with the swine production but in this
case it is conditioned by the size of the swine production facility. The coefficient is,
again, as expected positive (0.060) since bigger producers of swine have shown to
proportionally damage less the value of near properties.
From the analysis of those coefficients, as well as the fact that the OLS model seems to fit in
a reasonable way the price evolution of Illinois farmland (!!
= 0.798), we can say that
economic rationale justifies the market behavior in the last two decades. Hence, we can argue
that after studying the different factors that influence farmland values there is no evidence for
the existence of an irrational bubble or fad.
CONCLUSION
Throughout our analysis we have considered many different factors that are key determinants
of farmland prices in the United States. After the careful consideration of historical
background indicators as well as current empirical data we come to the conclusion that not
enough evidence is present to claim for the existence of an irrational bubble or fad in the U.S.
Farmland market nowadays. We have seen that current agricultural real estate values are
exceptionally high, but the growth experienced has shown to be supported by its economic
fundamentals. An irrational bubble is built from social contagion. Farmland high prices
however are something not many people even know about. It is clearly not a fashion, such as
private real estate was in 2008. Therefore, if it is not an irrational behavior of investors and
landlords what is driving prices up, what is it?
We believe that farmland values have been experiencing strong and sustained growths backed
by economic rationale based on the ‘bright’ future of its fundamental determinants.
Unfortunately, this does not dissolve all dangers in the current market situation. As we have
seen, current balance sheets and specially farm owners leverage ratios are stronger than they
were in 1980s. Even so, farmland values do represent more than 80% of an average farmer’s
balance sheet. This makes a sudden drop in values, an important threat. What would make
farmland values unexpectedly fall, if those values are based on economic fundamentals? Our
hypothesis is that farmland values are following the model of a growing rational bubble with

23
the expectation that fundamentals backing farmland values will keep on the same tendency in
the future. This rationale valuation model presents farmland as an attractive investment.
The danger inherent in a rational bubble is that since price is by definition away from its
intrinsic value, a change on the rate of growth of the bubble would make farmland prices
drop. A change in the rate of growth could be induced by the fact that some fundamentals
change. From our point of view, investors and landowners are under-considering the chances
that some factors change. We predict a threat in diverse factors, the future of which is too
independent from farmland performance or even traditional farmland market drivers, but
meanwhile its influence on the price is clearly elementary. Government policies play a
decisive role. If the controversial ethanol program would be finally dropped or even reduced,
this would drastically change corn prices and thus reduce farmland profitability. In a similar
fashion, if Janet Yellen decides to eventually end with the historically low interest rates (as
many predict she would not take long to do), farmland values would also drop rapidly.
All in all, we have presented arguments that support the current state of the market in US
Farmland. We believe that no evidence is present to argue for a speculative irrational bubble
in the farmland real estate. Alas, we support the existence of a rational bubble instead. This
growing bubble has its roots in economic rationale. Nonetheless, in this dynamic world of
ours, regulators should address the threats of a change in economic determinants in order to
prevent a painful financial distress in the worst-case scenario. Overoptimistic behaviors are
dangerous and warnings and limitations should be imposed before it is too late.
Further study should address the future worst-case scenarios and the impact that these would
have on farmland values and consequently on farmers and landlords, creating also financial
distress for agricultural creditors and most probably ending up in another farmland crisis.

i
APPENDIX & REFERENCES
APPENDIX(..........................................................................................................................................(II!
APPENDIX!1.!AVERAGE!NOMINAL!FARMLAND!PRICE!IN!IOWA,!195082012!.........................................!II!
APPENDIX!2.!ACRES!IN!LAND!OF!FARM,!2007!..............................................................................................!II!
APPENDIX!3.!US!AVERAGE!FARMLAND!PRICE,!196082012!...................................................................!III!
APPENDIX!4:!INFLATION8ADJUSTED!AVERAGE!FARMLAND!PRICE,!1968888!.....................................!IV!
APPENDIX!5:!COMPARATIVE!PRICE!CHANGE!..............................................................................................!IV!
APPENDIX!6:!CAPITALIZATION!RATE!FOR!FARMLAND!VERSUS!US!TREASURY!......................................!V!
APPENDIX!7:!FARMLAND!INTEREST!RATE!PREMIUM!..................................................................................!V!
APPENDIX!8:!DEBT!RATIO!IN!THE!US!AGRICULTURAL!SECTOR!..............................................................!VI!
APPENDIX!9:!FARMLAND!OWNED!BY!KIND!OF!LANDLORD!BY!REGION,!2007!....................................!VI!
APPENDIX!10:!CROP!PRICES!EVOLUTION,!..................................................................................................!VII!
APPENDIX!11:!REVENUE!AND!PRICE!EVOLUTION!OF!FARMLAND,!195082012!...............................!VIII!
APPENDIX!12:!CASH!RENT!AND!RENT8TO8VALUE,!199882014!.............................................................!IX!
APPENDIX!13:!FAMING!INCOME!AND!CAPABILITY!TO!SERVE!DEBT,!197082012!..................................!X!
APPENDIX!14:!FARMLAND!VALUE!CONDITIONED!TO!DISTANCE!TO!POPULATION!CENTERS,!2008!....!X!
APPENDIX!15:!CORN!FUTURES!.......................................................................................................................!XI!
APPENDIX!16:!TABLE!OF!COEFFICIENTS!FORM!A!OLS!HEDONIC!MODEL!REGRESSION!.......................!XI!
REFERENCES(..................................................................................................................................(XII!

ii
APPENDIX
Appendix 1. Average Nominal Farmland Price in Iowa, 1950-2012
The figure above depicts the evolution of the average nominal farmland price per acre in Iowa
from 1950 until 2012.
Source: USDA, National Agricultural Statistics Service.
Appendix 2. Acres in land of farm, 2007
The map above illustrates the distribution in Acres of land dedicated to farms by regions in
United States in 2007. Source: USDA, National Agricultural Statistics Service.

iii
Appendix 3. US Average Farmland Price, 1960-2012
In the Figures above you can observe the evolution from mid 20th
century until current times
(2012) of U.S. average farmland values. In both graphs we are able to distinguish the
Farmland bubble experienced during 1980s, as well as the current price rise. To add some
technical perspective, and allow the analysis in real terms, the second graph is represented in
an inflation-adjusted scale.
Source: USDA, National Agricultural Statistics Service, US and State-Level Data (1850-
2012), Farm Real Estate Values.

iv
Appendix 4: Inflation-Adjusted Average Farmland Price, 1968-88
Source: USDA, National Agricultural Statistics Service, and Federal Reserve Database.
Appendix 5: Comparative Price Change
The graph above illustrates the evolution of prices in Farmland properties, Stock market, and
House Prices in United States of America from 2002 until 2012. This interval allows us to
focus on the evolution each of those markets had after 2008 crisis. The red interval indicates
the ‘black’ period from the end of 2007 until late 2008, when the crisis clearly hit the
American Economy. Source: Farmland prices from USDA, National Agricultural Statistics
Service (Farm Real Estate Average Value per Acre); stock prices from Dow Jones Industrial
Average; and house prices from Standard &Poor’s Case-Shiller Index.

v
Appendix 6: Capitalization Rate for Farmland versus US Treasury
The time series above compares the evolution of the capitalization rate for Farmland in
Illinois (which is part of the Corn Belt) and for the 10-year US Treasury bond (which is
commonly used as proxy for risk-free asset). The time series starts 12 years before the burst
of the 1980s farmland bubble and comprises until 2012. Source: USDA, National Agricultural
Statistics Service and the Federal Reserve Database.
Appendix 7: Farmland Interest Rate Premium
The figure above depicts the evolution of both farm mortgages interest rates and the spread
with respect to the 10-year US Treasury bonds, used as a proxy for risk free asset.
Source: Federal Reserve of Chicago and Federal Reserve Database

vi
Appendix 8: Debt Ratio in the US Agricultural Sector
The figure above reflects the evolution of both Debt-to-Equity ratio and Debt-to-Assets ratio
for the US Agricultural Sector from 1970 until 2014. Source: USDA, National Agricultural
Statistics Service.
Appendix 9: Farmland Owned by Kind of Landlord by Region, 2007
The figure above expresses the million of acres owned by operator and non-operator
landlords in the different U.S. agricultural regions in 2007. Source: USDA, National
Agricultural Statistics Service.

vii
Appendix 10: Crop Prices Evolution,
This time series plots the Crop prices (dollars per bushel – in the left axis), as well as the
quantity produced per acre and the revenue per acre that it represents (in the right axis). It is
worth noticing that the increase in profitability per acre is due to an increase of price per
bushel, not due to an increase of productivity, which can be observed to increase but in lower
scale. Source: USDA, National Agricultural Statistics Service.
0!
1!
2!
3!
4!
5!
6!
7!
8!
0.00!!
100.00!!
200.00!!
300.00!!
400.00!!
500.00!!
600.00!!
700.00!!
800.00!!
900.00!!
!!!!Total,!gross!value!of!production!
Yield!(bu./planted!acre)!
Harvest8period!price!(dollars/bu.)!

viii
Appendix 11: Revenue and Price Evolution of Farmland, 1950-2012
In the Figure above we can find: the evolution of (A) average land price per acre, (B) average
corn yields per acre, and (3) the average corn price per bushel in Iowa from 1950 until 2012.

ix
Appendix 12: Cash Rent and Rent-to-Value, 1998-2014
In the graph above we find the cash rent evolution by region and aggregate US average, as
well as the US average rent-to-value ratio for farmland from 1998 until 2014.
0%!
1%!
2%!
3%!
4%!
5%!
6%!
7%!
8%!
0!
50!
100!
150!
200!
250!
300!
2014!
2013!
2012!
2011!
2010!
2009!
2008!
2007!
2006!
2005!
2004!
2003!
2002!
2001!
2000!
1999!
1998!
APPALACHIAN! CORN!BELT!
DELTA!STATES! LAKE!STATES!
MOUNTAIN! NORTHEAST!
NORTHERN!PLAINS! PACIFIC!
SOUTHEAST! SOUTHERN!PLAINS!
US!TOTAL! Rent8toValue!Ratio!

x
Appendix 13: Faming income and capability to serve debt, 1970-2012
In the graph above we can observe the ability to pay the current debt on farmland, given its
adjusted net returns. The solid line represents once more the farmland values in nominal
terms, and the doted line depicts the capability of repayment that landlords have.
Appendix 14: Farmland value conditioned to distance to population
centers, 2008
The graph above reflects the influence that closeness to urban areas has onto the value of farm
real state in 2008. Four different categories have been represented, to infer the effect of bigger
(>25k and >50k) cities with respect to small (>10k and >5k) ones. Source: USDA, National
Agricultural Statistics Service.

xi
Appendix 15: Corn Futures
The graph above plots the yield curve for the prices on Corn Futures at different maturities.
Source: Euronext and Chicago Board Options Exchange.
Appendix 16: Table of coefficients form a OLS Hedonic Model
Regression
This table represents the coefficients from an OLS
regression model build by Huang et al. (2006),
which considers the effect of several factors on the
dependent variable farmland values (ln). *** stands
for 99% statistical confidence, ** for 95% and *
and 90%. Source: Huang, Haixiao, Gay Y. Miller,
Bruce J. Sherrick, and Miguel I. Gómez. 2006. “Factors
Influencing Illinois Farmland Values.” American
Agricultural Economics Association 88 (2): 458–470.
!$150.00!!
!$155.00!!
!$160.00!!
!$165.00!!
!$170.00!!
!$175.00!!
!$180.00!!
!$185.00!!
!$190.00!!
!$195.00!!

xii
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