RISK AND RISK MANAGEMENT STRATEGIES
IN AGRICULTURE:
AN OVERVIEW OF THE EVIDENCE
FINAL REPORT
October 2010
Rural and Environment Analytical Services (REAS)
Rural and Environment Research and Analysis Directorate
(RERAD)
I
TABLE OF CONTENTS
LIST OF TABLES ..................................................................................................................... IV
LIST OF FIGURES ................................................................................................................... IV
EXECUTIVE SUMMARY ........................................................................................................... V
1.
Introduction ....................................................................................................................... 1
2.
Risks in agriculture........................................................................................................... 2
2.1
Defining risks in agriculture ............................................................................................. 2
2.2
Sources of risk in Scottish agriculture .............................................................................. 2
2.3
3.
3.1
3.2
4.
2.2.1
Market or price risk ................................................................................................. 2
2.2.2
Production risk ........................................................................................................ 4
2.2.3
Institutional/policy risk ............................................................................................. 5
2.2.4
Other sources of risk ............................................................................................... 5
Interactions between sources of risk and other issues ..................................................... 6
Measuring Risk in Agriculture ......................................................................................... 8
Trends in volatility in agricultural commodities prices ...................................................... 8
3.1.1
Measuring volatility in UK agriculture commodity prices .......................................... 9
3.1.2
Reasons for increased price volatility in agricultural commodities ......................... 13
Income variability........................................................................................................... 16
Effect of Risk on Farm Production and Investment Choices ....................................... 19
4.1
Effects on production ..................................................................................................... 19
4.2
On-farm risk management strategies and efficiency ...................................................... 20
4.3
Impacts on investment................................................................................................... 20
5.
Dealing with Risks – Risk Management Tools and Strategies in Agriculture ............. 21
5.1
Rationale for government intervention in agricultural risk management ......................... 22
5.2
Risk management related policies in agriculture ............................................................ 24
5.2.1
Price stabilisation policies ..................................................................................... 24
5.2.2
Supporting “on-farm” actions to reduce risk exposure ........................................... 25
5.2.3
Ex ante measures to assist farmers to mitigate/cope with risk .............................. 26
II
5.3
6.
5.2.4
Ex post measures ................................................................................................. 28
5.2.5
Direct payments .................................................................................................... 29
5.2.6
Summary .............................................................................................................. 31
5.2.7
Measuring public support for risk management tools ............................................ 32
Market-based risk management tools in agriculture ....................................................... 34
5.3.1
Agricultural Insurance systems ............................................................................. 35
5.3.2
Mutual funds ......................................................................................................... 39
5.3.3
Hedging price risk – forward contracts, futures and options .................................. 41
Summary ......................................................................................................................... 47
References ............................................................................................................................. 49
III
LIST OF TABLES
Table 1 - Coefficient of variation in EU and World prices for various commodities over
three periods (from Matthews 2010)................................................................................. 9
Table 2 - Coefficients of variation for UK feed wheat and cattle (liveweight) prices over
three periods .................................................................................................................. 10
Table 3 - Frequency of observations substantially outwith trend (2 year moving average),
UK feed wheat prices 1988-2010 .................................................................................. 12
Table 4 - Frequency of substantially different from trend (3-year moving average), UK
cattle prices 1988-2010 .................................................................................................. 13
Table 5 - Volatility in farm incomes EU-15 (1996-2004) ................................................. 17
Table 6 - Index of income volatility for different farm types by selected EU countries 19962004 (index = 100 equals CV = 31.4) ............................................................................. 17
Table 7 – Summary of risk management tools in agriculture .......................................... 21
Table 8 - Summary of crop insurance types ................................................................... 36
Table 9 - Level of insurance subsidies and ad-hoc/calamity fund payments in selected EU
member states ............................................................................................................... 38
LIST OF FIGURES
Figure 1 - UK feed wheat and cattle (liveweight) prices, 1985-2010*.............................. 10
Figure 2 - UK feed wheat prices two-year moving average with ±10% and ±20% bands 11
Figure 3 - UK cattle (liveweight) prices two year moving average with ±10% and ±20%
bands ............................................................................................................................. 13
Figure 4 - Share of MPS, variable and fixed rate payments in the PSE in total farm
receipts for selected OECD countries, 1992-97 and 2002-07 ......................................... 33
Figure 5 - Ratio of trading in wheat futures contracts relative to physical production in the
UK, USA and South Africa, 1989-2003 .......................................................................... 44
IV
EXECUTIVE SUMMARY

This paper reviews the literature on risks in agriculture and the tools available to
manage them. It is one of several papers produced by the Scottish Government
Rural and Environment Analytical Services to contribute to the evidence base for
the Brian Pack Inquiry into the Future of Support for Agriculture in Scotland.

It identifies (in Section 2) the main risks in agriculture to include the following:
▬ Market or price risk: risk of unpredictable changes in prices of both inputs
and outputs due to shocks, trade policy, new markets, etc;
▬ Production or yield risk: disruptions to production arising from weather
related factors (e.g. hail, frost, floods, and droughts), crops and livestock
diseases and pests, and changes in technology.
▬ Institutional and regulatory risks: unexpected changes in regional or
national policy, environmental law, agricultural payments (e.g. Single
Farm Payment), etc.
▬ Financial risk: changes in interest rates, access to credit and value of
financial assets disrupting the financial flows in a business.
▬ Personnel risk: personnel hazards such as injury, illness, or death.

These risks affect farm businesses through fluctuations in income, which can
affect investment on the farm – especially when credit markets are imperfect.
Depending on the risk attitude of farmers, they also affect farmers’ production
choices. In particular, as farmers tend to be risk averse, they may opt for lower
return more certain outcomes at the expense of higher returns but less certain
ones.

An analysis of United Kingdom (UK) feed wheat and cattle prices in Section 3
presents some evidence to suggest that volatility in the prices of these
commodities has increased in recent decades. Together with evidence elsewhere
in the literature, the analysis shows that with successive Common Agricultural
Policy (CAP) reforms, UK and European Union (EU) prices have become more
closely related to world prices due to reduced levels of market price support and
liberalisation of trade with third countries. Additional causes of increased volatility
are also cited in the literature to include growing linkages between energy and
agricultural markets and volatility in crude oil prices; biofuels mandates, which
create artificial demand for feedstocks and make demand for agricultural produce
less responsive to price changes; relatively low global public stocks; and the
speculative activity of investors in futures markets.

The review of the literature suggests that there is some rationale for government
to intervene in managing risks in agriculture due to a range of factors hindering
the perfect functioning of markets for some of the risk management tools and on
distributional grounds. However, as government interventions can incur significant
costs and reduce the incentives for farmers to take private actions to reduce or
manage risks, governments’ efforts should focus on creating an enabling
environment for farmers to manage their own risks – especially as the risks and
V
attitudes towards them tend to be farm specific. Further, considerations for risk
management should take into account the full range of instruments available for
managing risks and the effect of current policies on farmers’ risk environments
and responses to risk.

The review of risk management related agricultural policies across the OECD
identifies intervention purchasing, import tariffs and export subsidies to be the
main tools used to stabilise prices, although there is evidence that some countries
are probably moving away from these approaches. The paper also finds that
policies in other countries have intervened in risk management in agriculture
through subsidies on insurance premiums (e.g. Spain, Portugal, United States of
America (USA), Canada, Greece) and ad hoc payments to farmers in the event of
adverse events affecting agriculture. The paper also finds that although direct
payments (such as those in the USA and EU) are not primarily focused on risk
management, they do have some impact on risk as they contribute to stabilising
farm income and reduce farmers’ aversion to risks.

Finally, the paper identifies from the literature that farmers also have available to
them a number of market-based instruments for managing risks. Forward and
futures contracts and options allow price risk to be shared between buyers and
sellers of agricultural produce, which can offer a more efficient means of
mitigating price related risks. Farmers can also implement a number of on-farm
measures to reduce and mitigate risks, such as diversification within and outwith
agriculture, and invest in appropriate technologies to reduce environment related
risks. They are also opportunities for farmers to pool risk amongst themselves via
mutual funds.
VI
1.
Introduction
1.
Agricultural activity is subject to a wide range of risks due to the variable
economic and biophysical environment in which farming operates. While some of
these sources of risk are faced in common with other industries, many are
specific to agriculture. Their presence affects production choices - with
implications for the overall economic efficiency of agricultural production. Further,
where the realisation of the risks leads to falls in farm incomes, they can
adversely affect the economic welfare of those working in agriculture, with the
potential to constrain future investment and growth of farm businesses. It is
important, therefore, to understand how the presence of risks in agricultural
production affects farming and how the different risks can be mitigated.
2.
In recent years, interest in the risks faced by farm businesses – particularly from
price volatility – has grown as the Common Agricultural Policy (CAP) has
reoriented from price support in favour of direct farm payments.1 Concerns are
also raised that further trade liberalisation would leave Scottish and, more widely,
EU farmers further exposed to the vagaries of world price shocks. The 2007/8
agricultural commodity price spike, in particular, has heightened concerns around
volatility in agricultural markets.
3.
A number of tools are available to manage risks in agriculture and these range
from those that can be provided as part of government policy to those provided
privately through the market or the individual actions of farmers. Given this
background, this paper reviews studies on risks in agriculture and tools available
to manage them. It is one of several papers produced by the Scottish
Government Rural and Environment Analytical Services to contribute to the
evidence base for the Brian Pack Inquiry into the Future of Support for Agriculture
in Scotland.
4.
The paper largely draws on the Organisation for Economic Co-operation and
Development (OECD)2 framework for a holistic approach to understanding risk
and risk management in agriculture. The remainder of the paper proceeds as
follows: Chapter 2 reviews the sources of risk in agriculture, including market or
price, production or yield, institutional or regulatory, financial and personnel risks.
Chapter 3 reviews studies on trends in volatility in agricultural commodity prices,
assesses volatility in UK prices for two key agricultural commodities – wheat and
beef, and examines volatility in farm incomes. Chapter 4 assesses the effects of
risk and uncertainty on farm production and investment. Chapter 5 assesses the
rationale for government intervention to manage risks in agriculture, reviews
agricultural risk management strategies and current policy approaches in the EU
and other OECD countries, agricultural insurance mechanisms and mutual funds,
and a range of market-based risk management tools. Chapter 6 provides some
concluding discussion.
1
For example through the Single Farm Payment
2
OECD project on Risk Management in Agriculture, Trade and Agricultural Directorate:
http://www.oecd.org/agriculture/policies/risk
1
2.
Risks in agriculture
2.1
Defining risks in agriculture
5.
Although definitions of risk vary within the literature, in agriculture risks arise due
to uncertainty over factors determining returns to agricultural production (OECD
2008). Uncertainty in agriculture reflects the nature of most farm production
systems, which is influenced by ever-changing economic and biophysical
conditions. The natural lag between when production decisions are made and
when returns to farming can be realised exposes agricultural enterprises to the
variability, in the intervening period, of a range of factors that determine the value
of production. These include weather, animal and plant health, changes in
agricultural markets and a range of macroeconomic factors. Variability in these
factors results in uncertainty over key determinants of farm income like output
price, yield, and input costs - with implications for farmers’ economic welfare and
effects on the economic (allocative) and technical efficiency of farm production.
6.
Broadly, the variability in these factors affecting production can be separated into
two – anticipated variations occurring seasonally or cyclically, and those that are
unpredictable in nature. Generally, the assessment of risks in agriculture tends to
focus on those factors that tend to vary unpredictably (i.e. where variability is
uncertain), since anticipated variations can be incorporated into production
decisions or provided for.
2.2
7.
Sources of risk in Scottish agriculture
While there are several ways to classify risks, the specific typology is not
considered important as long as all risk factors are accounted for. In the context
of agriculture this paper identifies the following categories of risks (OECD 2008):





market or price risk – uncertainty about future changes in prices of both
inputs and outputs due to shocks, trade policy, new markets, etc;
production or yield risk – uncertainty about the quantity from agricultural
production arising from weather related factors (e.g. hail, frost, floods,
droughts),
crop and livestock diseases and pests, and changes in
technology, etc;
institutional or regulatory risk – uncertainty regarding the regional or
national policy and legal environmental for agriculture;
financial – uncertainty about financial flows within a business due to
variability in interest rates, access to credit and value of financial assets; and,
personnel risks – uncertainty due to personnel hazards, such as injury,
illness, or death.
2.2.1 Market or price risk
Output price risk
8.
The length of most agricultural production cycles (ranging from a few weeks to
several years) result in a lag between when a farmer makes production decision
and the product is sold, which means that output prices are often unknown at the
start of the production cycle. This is particularly important because farm
2
businesses are price-takers, as the output of any one farm tends to be too small
relative to the total market supply and thus an individual farm cannot to influence
prices.
9.
The causes of fluctuations in output price are often linked to other sources of risk
within and outwith agriculture, and can be split broadly into effects on market
demand and supply. Thus, it is important when assessing output price risk to
focus not only on output price variability, but also on the variability of the
underlying drivers. For example, unforeseen changes in consumer demand due
to food health scares caused by an animal disease (e.g. BSE, Foot and Mouth
Disease), can have a significant effect on output prices. Similarly,
macroeconomic factors, such as movements in exchange rates and changes in
economic conditions, can alter the relative competitiveness of farm businesses
internationally, which can affect demand for agricultural produce.
10. On the supply-side, impacts on yield that are widespread and have a significant
impact on total market supply (e.g. due to an adverse weather event or plant or
animal diseases affecting a wide area) can have profound affects on market
prices. Such supply shocks do not have to be local to affect the market price for
farmers in a particular region; the spatial integration of agricultural markets
means that disruptions to supply in one regional market can have some effects
on markets in other regions. For example, the drought in Australia in 2006/07 is
cited, among other factors, as a cause of the 2007 global price spike for dairy
products.
11. Broadly, the market price for agricultural commodities is particularly sensitive to
supply shocks due to the generally unresponsiveness of demand for food to
price. This means any changes in the level of supply for a particular commodity
at any given time requires a relatively large change in price to ensure that market
balance is restored or supply equals demand (O’Connor et al 2009).
12. Exposure to output price shocks or the ability to cope with them varies across
agricultural commodities. Most arable crops, such as grains and pulses, can be
preserved and stored allowing farmers more flexibility over when to sell, which
provides a mechanism for coping with some of the output price fluctuations
(although in some instances there can be significant storage costs). In
comparison, other produce, for example livestock products (milk, finished animals
and meat), are highly perishable and can only be stored for extended periods at
very high costs, which limits the scope to deal with output price.3
13. Recent studies have suggested that prices of agricultural commodities in the
European Union and consequently Scotland are becoming more volatile. In
Section 3.1, this paper assesses volatility in UK wheat and cattle prices and
reviews other studies measuring volatility in agricultural commodity markets
across the EU.
3
Some of the volatility for milk and livestock products is managed using forward/production
contracts. These are discussed in Section 5.3.3.
3
Input price risk
14. Unforeseen changes in the prices of inputs to a farm business can result in costs
being higher or lower than expected, which is another source of price or market
risk in agriculture. Generally, the significance of changes in the price of a given
input is determined by the magnitude of the price change and the proportion of
total costs accounted for by the input. This varies by farm sector. For example,
during 2007/8, input prices for Scottish farms increased considerably (feed costs
up by between 50-80%, fertiliser prices up 80%, red diesel prices by 40%),4 but
this largely affected enterprises with intensive input use – pig, poultry and beef
finishers.5
15. Given a number of key agricultural inputs are derived from crude oil; fluctuations
in oil prices attend to be a major driver for variability in agricultural input prices. It
also means that prices for key agricultural inputs (fuel, pesticides and fertiliser)
show strong positive correlation (i.e. prices tend to move together), which
exacerbates the impact of developments in oil markets on the farm business.
Additionally, outputs from some farm sectors (e.g. arable) can be inputs for others
(e.g. livestock); meaning output price volatility for one sector of farming becomes
input price volatility for others.
16. Surveys of farmers consistently rate input price risk lower than output price risk
(OECD 2008, Palinkas & Székely 20086). There are a number of possible
reasons for this. First, the gap between production decision and purchase of
agricultural inputs (e.g. seed, fertiliser) is generally much shorter than the gap to
when output is sold, which means there is a smaller window of vulnerability to
input price fluctuations. Second, input prices are often positively correlated with
output prices in the medium term. For example, a rise in crude oil prices, causing
a corresponding increase in fuel and fertiliser prices, generally affects all
agricultural operations at the same time. The increase in costs feeds into market
price to offset, to some extent, the impact of rising input costs on farm profit
margins, although usually with some lag. 7
2.2.2 Production risk
17. Although the variations in yield from agricultural production can occur for a
number of reasons, extreme or unseasonal weather conditions, in addition to
plant and animal diseases, are often the principal causes. Generally, crops and
extensively reared livestock tend to be more exposed to weather risk than
intensively reared livestock (e.g. poultry and pigs) that are housed and sheltered
SAC (2008) – Assessing the Impact of Increased Feed, Fuel and Fertiliser Costs on Scottish
Agriculture. AA211 Special Study for the Scottish Government.
4
5
SGRERAD (2010) – Economic Report on Scottish Agriculture: 2010 Edition.
Palinkas, P. and Csaba Székely (2008) – Farmers’ perceptions on risk and crisis risk
management, in Meuwissen et al (eds.), Income Stabilisation in the European Union, Ch. 2.
Wageningen Academic Publishers, Netherlands
6
7
Indeed, if an input shock is very short-lived, the increase input costs may have little impact on
output prices.
4
and the physical environment for their production, to some extent, can be
regulated.
18. Animal diseases can contribute to total farm risk in three main ways. First, animal
disease can adversely affect yield by either reducing the growth rate of the
livestock or increasing morbidity. In the worst case, livestock may have to be
culled as part of efforts to contain and eradicate disease, with associated costs.
Second, livestock disease can affect demand, due to loss of access to
international markets following trade restrictions or lower consumer demand due
to public health concerns, or both. This effect often manifests as price risk, as
falling demand puts a downward pressure on prices and results in significant
losses in farm revenue. Third, movement restrictions to control the spread of
disease can lead to market disruptions - leaving farmers unable to sell livestock,
which then grow out of specification and lose value. The outbreaks of foot-andmouth disease (FMD) (2001 and 2007) and BSE demonstrate the unpredictable
nature of animal disease outbreaks and their potential impact on farm
businesses. A 2008 report8 for the Scottish Government estimates that the 2007
FMD outbreak in England to have directly cost the Scottish livestock industry
some £32 million due to loss of export market and movement restrictions. An
earlier FMD outbreak in 2001 is estimated to have resulted in losses to the UK
farming industry amounting to around £355 million – excluding losses that were
compensated for by the government.
19. In the long term, climate change is an additional source of yield risk through its
effects on weather patterns (changing temperature and rainfall patterns, and
potentially generating extreme weather events, etc.) – an effect which is still
highly uncertain (OECD 2008). It is projected, however, that changing climate
may also result in the introduction and increased frequency of pests and
diseases, heightening animal health and crop related risks.
2.2.3 Institutional/policy risk
20. Although some policy interventions in the agricultural sector are often intended to
reduce the level of risk faced by farmers, the policy interventions themselves can
be a significant source of risk. This is because it is often difficult to foresee
changes in government policies, particularly where decisions are influenced by
social and political considerations. Changes in agricultural policy can influence
prices directly, for example through price support policies, or can affect farm
incomes through changes to policies for direct farm payments. Changes in
agricultural support can also have longer-term impacts on farm wealth through
effects on the value of farmland and other agricultural assets (OECD 2008) – with
implications on the financial position of the business.
2.2.4 Other sources of risk
21. Farmers face additional sources of risk that may not be directly related to
agricultural activity. Financial risks arise from changes in the price (interest rates)
Pareto Consulting (2008) – Foot & Mouth Disease Review 2007: Economic Impact in Scotland.
Available at: http://www.scotland.gov.uk/Publications/2008/06/11151009/0
8
5
and availability of credit for financing farm business operations or other farm
household activities. Fluctuations in income from off-farm activities and the value
of on- and off-farm assets can also be a source of risk, although where off-farm
income is weakly correlated to on-farm income, it could be used to reduce the
effect of fluctuations in total farm household income. An additional source of
financial risk facing Scottish, and more widely UK farmers, arises from agricultural
support payments paid in Euros under the Common Agricultural Policy (CAP),
which are obviously subject to exchange rate fluctuations.
22. Farmers also face personnel risk associated illnesses and injuries to staff.
However, given these other risks are not particularly specific to agriculture, there
are not often addressed through agricultural policy and therefore do not form the
main part of the discussion in this paper.
2.3
Interactions between sources of risk and other issues
23. The overall impact of risks on individual farms or across the agricultural sector
depends on the relationships between the different risk sources. Broadly, the
correlation between risk factors can differ significantly, which affects the overall
risk exposure of farm businesses. Where risks tend to occur together but in the
opposite direction (i.e. one effect is positive and one is negative), that is they are
negatively correlated, there is a mitigating effect on overall risk exposure and thus
on farm income variability. On the other hand, risks that are positively correlated
(i.e. tend to occur together and in the same direction) can exacerbate effects on
farm income variability. More generally, where risks are not perfectly correlated at
farm level, total risk exposure will be less than the sum of individual risks (OECD
2009a). Thus, consideration for the relationships between risk factors allows the
possible effects on farm incomes to be determined more accurately and risk
management strategies to be formulated more effectively, although in practice the
nature of interactions between risk sources may be highly complex.
24. It is also important to consider how risk factors affect different farmers. Some
risks are highly correlated between groups of farmers (systemic risk), such as
those in a particular region or country, for example droughts and floods. Price risk
is particularly systemic, with fluctuations in prices affecting all farmers in a market
– often a region or country. On the other hand, some risks are only weakly
correlated or unrelated (idiosyncratic risk) between farmers, such as localised
weather conditions (hail, frost, etc.) and personnel risks.
25. The distribution of risks among farmers has implications for the level of
aggregation at which risk is measured (OECD 2009a). For systemic risks, such
as price risk, a high level of aggregation may be suitable (e.g. region or country
level), as all farmers will face similar levels of risk. Such aggregation is less
suitable for risks that are relatively unsystematic across farmers; for example,
country level averages of yield variation would hide significant variability between
farms or regions within the country.
26. The implications of the relationships between risks can be seen in the example of
price-yield correlations. Conceptually, if a yield shock were large and widespread
causing a significant reduction in supply, then, assuming the level of demand is
unchanged, the market price would be expected to rise. To some extent, this
6
change in output prices should mitigate the negative impact of the yield shock, as
lower output is offset by a higher return for each unit sold. However, although this
may be true at the aggregate level, it is important to consider the incidence of
yield loss across farm businesses. As price shocks tend to be more systematic
across farms than yield shocks, for a given yield shock some farmers will suffer a
more adverse impact than others will. As a result, the compensating effect of a
rise in output price is not felt equally across all farms. In fact, those businesses
least affected by the yield shock benefit the most from the resulting higher prices.
27. In addition to the relationships between risks, it is also important to consider the
probability distribution of outcomes associated with a given risk source. Downside
risk – the probability that an outcome (for example yield or output price) will be
lower or worse than expected – is considered particularly important for agriculture
(OECD 2009a). For example, a “normal” season may be one where most or all
crops achieve the expected yield. However, this outcome tends to be unlikely as
there is a higher probability that yields would be lower than expected. Downside
risk has important implications for the economic welfare of farm households, due
to the negative impact on farm incomes. However, upside risk (the probability
that outcomes will be better than expected) and their impacts on farmer
expectations can have implications for economic efficiency (see Section 4.1).
7
3.
Measuring Risk in Agriculture
28. Risks are often characterised by the probability of adverse outcomes occurring
and the size of the associated losses (OECD 2008). To focus only on the
unpredictable fluctuations, seasonal or cyclical fluctuations and other predictable
influences must be ‘stripped out’ of data in order to get an accurate measurement
of risk (OECD 2009a). An important consideration when using observed data to
measure risk, which affects the measurement of almost all risks in agriculture, is
that data will already reflect the effect of past and current agricultural support
policies and their impacts on the risks facing agriculture. For example, although
many agricultural support policies are designed to reduce price volatility and the
exposure of farm businesses to risks, changes in agricultural policy can
themselves introduce fluctuations in variables such as price and farm incomes,
which are often examined when trying to understand the risks faced by farmers.
29. The following section focuses on measuring output price risk on the basis that
volatility in output prices is cited as the biggest source of the risks faced by farm
businesses. Additionally, the impact of the range of risk sources will manifest, to
some extent, through variations in prices. The measures of income variability are
also reviewed.
3.1
Trends in volatility in agricultural commodities prices
30. Several studies have observed that price volatility has been increasing for a
number of agricultural commodities in recent years. A study by Matthews (2010)9
looked at EU price volatility over three periods relating to different CAP regimes:
(i) the ‘unreformed CAP’ (1985-1992); (ii) the ‘MacSharry’ CAP (1993-2004) with
coupled direct payments and WTO disciplines on border protection; and, (iii) the
‘Fischler’ CAP (2005-2010) with decoupled direct payments and further WTO
disciplines on border protection. Using German prices as a proxy for EU prices,
the study found that volatility in the prices of several agricultural commodities
(wheat, maize, cattle, and rapeseed) has increased over time with successive
CAP reforms. Table 1 shows the results from this study (Matthews, 2010).
31. As can be seen in Table 1, while volatility in world arable commodity prices over
the same period did not increase by much (with the exception of sunflower), there
is a marked increase in the volatility of German prices with some convergence
towards world prices. This could suggest that greater volatility in EU prices may
be due, to some extent, to trade liberalisation and reduction in price support
interventions through CAP reforms.
Matthews, A. (2010) – Paper presented at Joint AES / SFER Conference on ‘The Common
Agricultural Policy Post 2013’. Available at:
http://www.aes.ac.uk/_pdfs/_conferences/201_paper.pdf
9
8
Table 1 - Coefficient of variation in EU and World prices for various commodities
over three periods (from Matthews 2010)
Commodity
Common wheat
Maize
Sugarbeet
Cattle
Rapeseed
Sunflower
1983-1992
1993-2004
2005-2010
Germany World
Germany World
Germany World
5.56
15.09
10.49
20.53
33.53
25.99
6.35
17.73
10.98
20.94
26.01
20.23
1.08
30.17
4.38
19.49
3.08
27.68
4.53
6.93
7.89
15.25
4.85
5.15
11.82
24.14
14.09
21.19
22.13
25.34
18.36
15.91
8.89
21.08
19.97
42.73
Source: Matthews (2010)
32. The results above are consistent with those of an earlier study conducted by the
Futures and Options Association (FOA),10 which assessed volatility in wheat
prices for several EU countries before and after the 1992 MacSharry CAP
reforms. The study finds that volatility in wheat prices increased significantly for
most EU countries after 1992, with a particularly sharp increase for the UK. EU
prices were also found to move more closely with world prices following the
reforms.
33. Other studies provide evidence to support this trend of increasing volatility in the
prices of agricultural commodities. Looking at US wheat and maize prices for the
period 1980-2009, the European Commission (EC, 2009)11 found that the prices
for these commodities have become more volatile, particularly since 2006. The
EC cites a number of potential causes for this trend, including a positive
relationship between prices of crude oil and agricultural commodities, indicating a
link between the markets, and a link between low commodity stocks and high
volatility (see Section 3.1.2 for a more detailed discussion of causes of increased
volatility). A study for the European Dairy Association (Keane and O’Connor,
2009) has also found increased volatility in EU dairy prices for the period 20002009 compared with 1990-1999. Additionally, the FAO Food Outlook (November
2007)12 finds that volatility in world wheat and maize prices has been increasing
gradually for the last decade, with a sharp increase in volatility during 2007/8.
However, in its December 2009 Food Outlook13 shows that price volatility for a
number of agricultural commodities was somewhat higher during the 1970s.
3.1.1 Measuring volatility in UK agriculture commodity prices
34. In this section, the paper attempts to measure volatility in the prices of UK wheat
and cattle prices. Time series data for UK wheat and cattle prices is assessed
and the degree of variation in price is then measured by calculating the coefficient
Alizadeh, A. and Nomikos, N. (2005) – Agricultural Reforms and the Use of Market Mechanisms
for Risk Management. Study commissioned by the Futures and Options Association.
10
European Commission DGAGRI (2009) – ‘Historical Price Volatility’.
http://ec.europa.eu/agriculture/analysis/tradepol/commodityprices/volatility_en.pdf
11
Available
at:
FAO Food Outlook (November 2007 – Special Feature: High prices and volatility in agricultural
commodities.
12
FAO Food Outlook (December 2009) – Special Feature: The food price crisis of 2007/2008:
Evidence and Implications.
13
9
of variation (CV) – a measure of the standard deviation (variability) of a set of
observations relative to their mean. An alternative, and graphical, approach to
assessing volatility is also presented; this measures the percentage of price
observations that substantially exceed the trend in prices (measured by a moving
average).
Figure 1 - UK feed wheat and cattle (liveweight) prices, 1985-2010*
Wheat
£/tonne
190
Wheat
Cattle
UK FEED WHEAT AND CATTLE (LIVEWEIGHT) PRICES
Average UK Weekly Market Price
180
160
170
140
150
120
130
100
110
80
60
90
40
70
20
50
1985
0
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Source: Defra Weekly Commodity Prices (May 2010)
*To May 2010
35. Figure 1 shows weekly market prices14 for UK feed wheat and cattle between
1985 and 2010. Significant variation in prices is visible over this period – some of
it seasonal to reflect annual rises and falls in prices. However, the seasonal
fluctuations become less evident as volatility increases in later years. Cyclical
variations can also be seen in cattle prices, although these are less pronounced.
The spike in cereal prices experienced in late 2007 and early 2008 can be seen
clearly in prices for feed wheat. Cattle prices also rose during this period.
Table 2 - Coefficients of variation for UK feed wheat and cattle (liveweight) prices
over three periods
1985/6-1992*
1993-2004
UK Feed Wheat
7.55
25.18
UK Cattle (liveweight)
7.56
14.76
Note: *UK Feed Wheat – 1985-1992, UK Cattle 1986-1992 (due to data availability)
2005-2010
32.96
17.08
36. Whereas Matthews (2010) calculated coefficients of variation for three periods
relating to different CAP regimes, the three periods covered in Table 2 have been
chosen to provide, roughly, an equal number of observations in each period.
Additionally, the price data used was not adjusted for trend, cyclical or seasonal
fluctuations, so the CVs may over- or underestimate the level of unsystematic
14
Weekly market price data are averaged from daily observations, therefore this may disguise
volatility in daily prices
10
variation in prices,15 and are thus not directly comparable to those in Matthews
(2010).16 Table 2 shows a clear increase in the volatility of both feed wheat and
cattle prices, with the increases most pronounced for the former. Assuming that
predictable (e.g. seasonal) influences have been reasonably consistent over time,
the results in Table 2 are consistent with findings from other studies that show
increasing volatility in the prices for these commodities.
Figure 2 - UK feed wheat prices two-year moving average with ±10% and ±20%
bands
Wheat
£/tonne
190
UK FEED WHEAT PRICES
Average UK Weekly Market Price
Feed wheat
Moving average
+20%
-20%
+10%
-10%
170
150
130
110
90
70
50
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
37. An alternative graphical presentation of the increase in price volatility is shown in
Figure 2 and Figure 3. The number of price observations that vary substantially
from the trend is assessed to provide a measure of the extent of price variability
in each period.17 For the purposes of this exercise, moving averages are
calculated (two years for wheat prices and three for cattle prices) in order to
smooth out cyclical or seasonal price fluctuations. Price bands of ±10% around
the moving average are then calculated and the number of price observations
outwith these bands is assessed in order to provide a measure of price
volatility.18
15
Where cyclical fluctuations diminish (i.e. move opposite to) the effect of non-cyclical influences
on price, CV measurements are likely to underestimate unpredictable volatility. On the other hand,
where cyclical fluctuations exaggerate (i.e. move in the same direction as) non-cyclical
fluctuations, CV measurements are likely to overestimate the level of unpredictable volatility in
prices
16
Additionally, whereas weekly price data is used in this paper, Matthews (2010) uses monthly
price data, which will disguise weekly fluctuations in price.
17
This method has been adapted largely from O'Connor et al (2009)
18
An additional interpretation of these results may be that such observations are those that differ
substantially from farmers expectations, if it is assumed that farmers formulate expectations
based on previous prices. However, there are significant issues with this interpretation. While
farmers are generally very responsive to price movements in the previous period when making
production decisions, they will also make use of available information on likely future price
11
38. Figure 2 shows the two-year moving average for UK feed wheat prices and the
±10% and ±20% bands around this. Many of the price observations fall outwith
the ±10% band, suggesting that prices tend to be volatile and the band might be
too narrow to assess trends in volatility. However, fluctuations outwith the ±10%
band do indicate where spikes and falls in prices were particularly large. The
±20% band appears to contain all seasonal fluctuations, with only particularly
large peaks and troughs, such as those in 2003-2005 and 2007 onwards, falling
outwith this band.
Table 3 - Frequency of observations substantially outwith trend (2 year moving
average), UK feed wheat prices 1988-2010 19
1988-1994
357
71%
16%
13%
29%
100%
0%
0%
0%
Number of observations
% Within 10% trend
% above trend +10%
10% moving
% below trend -10%
average band
% outwith trend ±10%
% Within 20% trend
% above trend +20%
20% moving
% below trend -20%
average band
% outwith trend ±20%
1995-2001
355
56%
9%
35%
44%
91%
0%
9%
9%
2002-2010
427
19%
36%
44%
81%
58%
29%
13%
42%
39. Table 3 presents the number of price observations that are outwith and within the
bands around the moving average shown in Figure 2. The main result in Table 3
is that the percentage of observations that fall outside the ±10% and ±20%
moving average bands (i.e. those that could be deemed to indicate unexpected
price movements based on historical data) increase over time. This result is
consistent with the findings in Table 2, which shows rising price volatility in UK
feed wheat prices.
movements. One principal source of this information is futures markets, where contracts prices
tend to reflect the current expectations of traders regarding future prices (see Section 5.3.3).
19
Measurements from 1988 due to two-year moving average for wheat from 1986 and three-year
moving average for cattle from 1985. Dates of periods assessed also differ slightly from those in
table 2 in order to achieve a more even distribution of observations in each.
12
Figure 3 - UK cattle (liveweight) prices two year moving average with ±10% and
±20% bands
Cattle
p/kg liveweight
190
UK CATTLE (LIVEWEIGHT) PRICES
Average UK Weekly Market Price
Cattle (livesweight)
Moving average
+10%
-10%
+20%
-20%
170
150
130
110
90
70
50
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Table 4 - Frequency of substantially different from trend (3-year moving average),
UK cattle prices 1988-2010
Number of observations
% Within 10% trend
% above trend +10n%
% below trend -10%
% outwith trend ±10%
% Within 20% trend
% above trend +20%
% below trend -20%
% outwith trend ±20%
1988-1994
366
72%
28%
0%
28%
95%
5%
0%
5%
1995-2001
321
59%
0%
41%
41%
94%
0%
6%
6%
2002-2010
427
69%
31%
0%
31%
85%
15%
0%
15%
40. Figure 3 and Table 4 present a similar analysis for UK cattle prices. Increases in
price volatility are also evident, although increases are more pronounced and
consistent for observations outwith the 20% band (i.e. there has been a
consistent increase in observations that substantially differ from the trend).
Compared to wheat, there are also fewer observations falling outwith the bands
around moving averages, which is consistent with the CV measurements in Table
2.
3.1.2 Reasons for increased price volatility in agricultural commodities
41. Trade liberalisation and the removal of price support policies under successive
CAP reforms have commonly been cited among the causes of increased volatility
in EU agricultural commodity prices, as the European market has become more
exposed to shifts in world markets. Several other factors have also been cited to
explain the increased volatility in agricultural commodity prices. These include: (i)
increased linkages between agricultural commodity markets and energy markets;
(ii) relatively low public and private stocks of agricultural commodities; and (iii)
activities of investors in futures markets.
13
(i) Agricultural commodity markets are becoming more strongly linked to energy
markets
42. Energy markets influence prices of agricultural commodities in two main ways
(Defra 2008).20 First, volatility in crude oil prices contributes indirectly through
input prices, particularly fuel, synthetic fertilisers and pesticides – all derived from
crude oil. The upward trend in real crude oil prices over time and increased
mechanisation means that these inputs account for a greater proportion of total
costs of agricultural production, particularly for the relatively intensive sectors.
Both the EC (2009) and World Bank (2010)21 provide evidence of a relatively
strong positive correlation between crude oil and agricultural commodity prices.
An example of this relationship is the way high cereal prices in 2007-8 coincided
with historically high crude oil prices.
43. Second, volatility in energy markets also affects agricultural commodity prices
directly through increased demand for biofuel feedstocks when mineral oil prices
are high. While it is not yet clear whether mineral fuel prices have ever risen to
levels where liquid biofuels relying on agricultural commodities become
competitive and fluctuations in crude oil prices affect demand for biofuels beyond
levels required to meet mandated blending requirements, the World Bank (2009)
suggests this might be the case for maize. Notably, there is evidence that for oil
prices above US$50 per barrel, maize prices tend to move closely with oil prices.
44. Mandates for biofuels in fuel mixtures based on volume (such as in the EU) may
also exacerbate price volatility in agricultural markets by reducing the sensitivity
of demand to price changes. Given the mandate sets a floor below which
quantity demanded cannot fall, short-term fluctuations in supply (e.g. due to a
yield shock) require large changes in price in order to bring demand and supply in
balance (Matthews 2010). The FAO (2009) argues that increases in mandates,
particularly in the USA, contributed to the running down of global grain stocks,
which has been cited as part of the cause of the 2007-8 commodity price spikes
(see below).
(ii) Relatively low public and private stocks of agricultural commodities
45. The management of stocks of agricultural commodities can stabilise market
prices by building up stocks when supply is relatively high – protecting prices
from falling, and selling back onto the market when there is a shortfall in supply –
relieving any upward pressures on prices. Currently, global stocks of wheat and
maize relative to demand (stock-to-use ratio) are significantly lower than levels in
the 1980s, although the bulk of declines occurred in the early 90s (FAO 2009).
The European Commission (EC 2009) provides some evidence of an inverse
relationship between stock levels and volatility in US wheat prices over the past
three decades; i.e.-low stock levels have generally coincided with higher levels of
Defra (2008) – The Impact of Biofuels on Commodity Prices. Available
http://www.defra.gov.uk/evidence/series/documents/impact-biofuels-commodities.pdf
20
Baffes, J. and Haniotis, T (2010) – Placing the 2006/08 Commodity Price Boom into
Perspective. World Bank Policy Research Working Paper 5371.
21
14
at:
price volatility. FAO (2009) and Defra (2010) cite low stocks as the key factor in
rising price volatility in 2007/8, caused by high grain demand from China and
India, in addition to rising global demand for feedstocks for biofuels. This would
have left commodity markets more vulnerable to supply-shocks, such as drought
in Australia, which significantly affected wheat supplies. However, the World Bank
(2010) suggests that rising grain demand from developing countries could not
have been a significant cause of the price spike, citing data showing the rate of
growth in world grain demand slowed during the past decade. In addition, the
greatest price rises were in wheat and rice, for which demand was relatively
stagnant during past decade.
(iii) Investor activity in futures markets
46. Futures markets allow farmers to hedge against price risk by fixing prices in
advance of the actual delivery of commodities (see Section 5.3.1 for full
discussion of futures markets). The activity of investors in futures markets is
important in ensuring an adequate supply of funds to agricultural markets and
increases the number of buyers and sellers, which is essential for markets to
function effectively. Investors use commodity futures to diversify their portfolio of
financial assets as part of their risk management strategies. Some investors also
seek to gain in futures markets by ‘betting’ on the direction of movement in the
value of futures contracts or options in order to earn a profit. Under certain
conditions, such activity (or ‘speculative trading’) may create false trends and
drive up futures prices (EC 2009). The potential gains from investor trading are
greater in markets were price fluctuations are wider and less predictable.
Therefore, the increased volatility in agricultural markets may be both a result of,
and driver for, speculative activity in futures markets.
47. However, the evidence is mixed on whether speculative trading contributed
significantly to price volatility. The OECD (2010)22 finds no relationship between
the number of trades in index and swap funds with the increase in price volatility
during the 2007/8 spike (or in other periods). Additionally, a Defra/HM Treasury
(2010)23 report finds that the number of contracts on index funds was relatively
stable between 2006 and 2008, which is contrary to the argument that greater
levels of trading resulted in the 2007/8 price spike.24 The FAO Food Outlook
(December 2009) asserts that low stock levels were the cause of the price spike,
and that the fall in stock levels was not consistent with high prices caused by
speculative trading.25 The World Bank (2010), however, suggests that while the
Irwin, S. H. and D. R. Sanders (2010), “The Impact of Index and Swap Funds on Commodity
Futures Markets: Preliminary Results”, OECD Food, Agriculture and Fisheries Working Papers,
No. 27, OECD Publishing. doi: 10.1787/5kmd40wl1t5f-en
22
Defra (2010) – The 2007/08 Agricultural Price Spikes: Causes and Policy Implications. Annex 6:
Speculation and the food price spikes of 2007/8.
23
24
During this period, the total value of contracts rose. However, the report views this as a
symptom of high futures prices (as higher prices increase the value of contracts) rather than a
cause.
25
An increase in prices due to speculative trading would be expected to increase stocks, as high
prices reduce demand while no physical trade of commodities takes place through speculative
trades.
15
fundamentals of demand and supply will be the main drivers for commodity
markets in the long term, speculative activity does appear to affect prices in the
short-term and can amplify price cycles (including variation caused by the other
factors discussed here).
48. What is not clear from the literature is whether the trend for greater volatility is
expected to persist. Low commodity stocks are a sign of sustained increases in
demand relative to supply. Stocks for some commodities have recently increased
significantly, as supply expands in response to higher prices. Moreover, while
evidence suggests that reforms to the EU CAP have so far contributed to higher
volatility in EU prices, more general reform of agricultural support policies and the
removal of trade barriers may in the long-run have a dampening effect on
volatility in world markets, by allowing countries more freedom to import produce
when supply is low and export when supply is high.
3.2
Income variability
49. If the policy concern about risks in agriculture is the impact on the economic
welfare of those earning income from agriculture, then an assessment of farm
income variability is also important.26 Volatility in farm incomes can adversely
affect economic welfare, particularly where credit markets are imperfect and
opportunities to borrow to smooth consumption are limited. Additionally,
unpredictable variations in farm income, by affecting farm liquidity, can reduce the
ability of farm businesses to invest in order to improve productivity and
profitability, and consequently affect the future economic welfare of those working
in agriculture.
50. Farm incomes tend to vary significantly over time due mainly to price and yield
fluctuations, changes in variable costs, and changes in the value of agricultural
support payments - particularly if payments are subject to exchange rate
movements (e.g. direct payments to Scottish farmers under the CAP). The
degree to which individual risk sources (described in Section 2.2) manifest in
variations in income depends on the relationships between sources of risk, as
discussed in Section 2.3, and the effect of public and private risk management
strategies in reducing and mitigating risks. Farm incomes also vary, not only with
time, but also across businesses, even for those of the same type and size. As a
result, measuring volatility of aggregated farm income can hide significant
variations at the individual farm level.
51. Several studies have assessed variability in incomes at the farm level. Vrolijk et al
(2009)27, using data from the Farm Accounts Data Network (FADN), conducted a
detailed assessment of income variability at farm-level for different farm types
26
Strictly, the entire farm household income should be assessed, including on- and off-farm
incomes, in order to deduce impacts on farm household economic welfare (Phimister et al 2004).
However, there is often insufficient data on off-farm incomes to include in analyses.
Vrolijk et al (2009) – Volatility of incomes, prices and yields in the European Union. Report
2009-005, LEI Wageningen UR, The Hague.
27
16
across EU countries. Some of the main results from this study are summarised
below.
Table 5 - Volatility in farm incomes EU-15 (1996-2004)
Type of farming
Field crops
Horticulture
Wine
Other permanent crops
Dairy
Grazing livestock
Intensive livestock*
Mixed
Coefficient of variation of family farm income
31
37
33
33
28
31
53
29
Source: Vrolijk et al (2009)
* Mostly pigs and poultry.
52. Table 5 shows the coefficient of variation (CV) in farm incomes at the farm level
for different farm types across EU-15 countries. It is clear that the variations are
considerably higher in intensive livestock farms (mainly pigs and poultry), which
may be due, at least in part, to the much lower level of market support for these
enterprises. The results also reveal substantial variation between countries.
Table 6 - Index of income volatility for different farm types by selected EU
countries 1996-2004 (index = 100 equals CV = 31.4)
Field
Crops
Horticulture
Belgium
87
101
Denmark
109
158
France
113
126
Germany
134
130
Ireland
82
Italy
78
82
Netherlands
217
174
Portugal
116
111
Spain
97
145
Sweden
186
UK
137
89
Source: Vrolijk et al (2009)
Other
permanent
crops
145
177
182
144
85
146
184
122
98
Dairy
61
102
85
101
73
75
113
112
99
177
109
Grazing
livestock
81
99
121
121
75
291
112
90
140
171
Intensive
livestock
193
264
179
191
200
85
475
169
153
231
173
Mixed
94
118
96
158
84
61
216
126
76
148
131
53. Table 6 shows relative (indexed) income volatility for different farm types across
EU-15 countries. Although there is considerable variability between countries, the
highest volatility in farm incomes is evident among the North West EU Member
States, which the authors attribute to the financial structure of farms in these
countries. The difference in volatility across countries and farm types is also
explained by differences in the risk environment and the nature of agricultural
systems. The general high variability in incomes for intensive livestock farms can
be seen in Table 6.
54. In common with output prices, while variation in farm incomes is important, the
level of down-side risk in farm incomes – that is, the probability that incomes will
be lower than expected, is often more important from an economic welfare and
17
investment perspective. If low income in one year is offset by high income in the
next, then farm households are more able to ‘smooth’ their income and minimise
impacts on welfare. Conversely, persistently low incomes over extended periods
can pose severe liquidity constraints and ultimately affect the economic viability of
the farm business. However, persistently low incomes can also indicate structural
issues rather than problems of volatility per se.
55. A study by Phimister et al (2004)28 assesses the dynamics of farm incomes in
Scottish agriculture between 1988 and 2000. The study uses FADN data to
assess the length of time spent by farms in ‘low income’ groups (a relative
measure defined by bottom fifth of farm business incomes), and the degree of
mobility of farms between income groups. The study found that there was a high
degree of mobility in relative income of farms, with most farms spending only a
short period in the ‘low-income’ group. If credit markets function efficiently, these
farms will be able to smooth income through borrowing and therefore minimise
welfare impacts associated with income volatility. However, a significant number
of farms experienced repeated spells in the ‘low income’ group, suggesting that
low-income risk is an important issue for Scottish farm businesses.
Phimister, E., Roberts, D. and Gilbert, A. (2004) – The Dynamics of Farm Incomes: Panel data
analysis using the Farm Accounts Survey. Journal of Agricultural Economics, 55, 2, pp197-220.
28
18
4.
Effect of Risk on Farm Production and Investment
Choices
56. The presence of risks in agriculture influences farm production and investment
choices in a number of ways, including (a) the choices farmers make for the
specific mix of commodities they produce and inputs used to produce these
commodities; (b) strategies to manage and cope with risk; and (c) dynamic or
investment impacts when the resolution of uncertainty results in a negative
impact on farm incomes.
57. The nature of the first two of these impacts on farm businesses will depend
principally on the attitude of farmers towards risk. In general, farmers may be riskaverse (i.e. they dislike riskier outcomes), risk loving (prefer riskier outcomes) or
risk neutral. However, studies within the agricultural sector have found that
farmers tend to be averse to risk (OECD 2008); preferring outcomes that are
more certain, although larger farms are relatively less risk-averse.29
4.1
Effects on production
58. Of the risk sources discussed in Section 2, price and yield risk tend to influence
farm production decisions most directly. In the absence of instruments for
managing risks, economic analysis of production under uncertainty often
suggests that farmers will base their choices on some “expected outcome” (e.g.
expected yield or price – a weighted average of the possible outcomes taking into
account the probabilities of different outcomes being realised). Risk-averse
producers will tend to prefer “low-risk and low-return” outcomes at the expense of
higher payoffs that are more uncertain. In practice, this means that producers
may choose low-risk production technologies and low risk crops at the expense of
innovation and riskier choices that potentially offer higher returns. This will
generally lead to a lower average income and lower levels of economic efficiency,
as resources may not directed towards the most profitable farm enterprises.
59. This may be reflected in a reluctance of farmers to adopt new production
techniques and technologies that may improve farm efficiency and profitability but
result in some (perceived) increase in the variability of returns. Where support
policies reduce income variability, either through direct payments or indirectly
through, for example - market price support, farmers may be more willing to
undertake riskier activities, effectively maintaining the riskiness of their portfolio
(Vrolijk et al 2009).30
60. It is important to highlight here that it is not only the risk that output prices will be
lower than expected (‘downside’ risk) that affects economic efficiency. Higher
than expected prices (‘upside’ risk) has implications for economic efficiency, as a
profit-maximising farmer would choose to produce more of a particular commodity
Agricultural support policies can affect farmers’ attitudes to risk. See Section 5.2 for further
discussion.
29
Vrolijk et al (2009) – Volatility of incomes, prices and yields in the European Union. Report
2009-005, LEI Wageningen UR, The Hague.
30
19
at a higher price (assuming input costs and prices of other commodities are
unchanged), reallocating resources towards the more profitable enterprise.
4.2
On-farm risk management strategies and efficiency
61. There are several institutional mechanisms for reducing or managing risks (see
Section 5.2), however, agricultural producers may implement on-farm strategies
to manage risk. One such approach is the diversification of farm business income
by redirecting investment and labour time away from the farm towards non-farm
activities, especially those generating income not strongly correlated with on-farm
business income. To the extent that such diversification will compete for
resources (e.g. labour time and capital) with agricultural production, it may reduce
agricultural production or capacity.
62. Diversification can also occur at farm business level. In this case rather than
specialising in enterprises that gives the highest rate of return, the farm business
is diversified to include other enterprises where returns are not positively
correlated or that are less risky. However, this will result in a lower average
income and lower economic efficiency, as resources are not directed towards the
most profitable farm enterprises.
63. In the face of increasing trade liberalisation, farmers may experience conflicting
pressures arising from the need to specialise activities in order to exploit
production efficiencies and maintain competitiveness, while ensuring that risk
exposure is minimised through on- and off-farm diversification. However, where
risks can be managed efficiently and effectively through market-based risk
management (see Section 5.4), businesses will be more able to specialise while
mitigating the level of risk faced.
4.3
Impacts on investment
64. While there are several risk management options available to farmers, these
often only provide partial protection for potential losses. Where the remaining risk
exposure causes returns and farm income to vary, and this variation is uncertain,
it can make it difficult for farm businesses to plan long-term investment. For
example, volatility in output prices can make it more difficult for farmers to identify
trends in prices, which is often a basis for making long-term investment decisions.
In the presence of such volatility, the level of investment by risk averse producers
is likely to be lower than in a risk free environment, which in turn has negative
impacts on long-term productive capacity in agriculture.
65. In addition, where unexpected shocks result in significant income losses, this can
constrain future farm investments. This is largely a product of inefficient credit
markets; otherwise, farm businesses should be able to borrow to smooth their
income for any fluctuations.
66. The impacts described above provide a conceptual discussion of how levels of
input use, output and investment in agriculture may fall below optimal levels in a
production environment characterised by risk or uncertainty. In reality, farmers’
levels of risk exposure and responses to risk vary with the policy environment and
this is discussed in the following sections.
20
5.
Dealing with Risks – Risk Management Tools and
Strategies in Agriculture
67. There is a broad range of tools that can be employed in agriculture to manage
risks. The aim of this section is to outline the main risk management tools and
strategies, including policies that may be implemented by government,
mechanisms provided by the market, and actions that may be undertaken
privately on-farm to reduce and cope with risks. Due to a lack of data across a
sufficient number of risk management strategies, this section does not assess the
evidence on the success or otherwise of such strategies.
68. Tools for managing risks in agriculture can be split into those that reduce or
mitigate risk or those for coping with risks (OECD 2009a). First, risk reducing
strategies are generally preventative measures aimed at reducing overall risk
exposure e.g. vaccination of livestock to promote herd immunity to disease.
Second, risk-mitigating strategies allow farmers to lessen the potential effect of
remaining risks, such as insurance against disease outbreaks. Finally, risk coping
strategies involve measures to assist in dealing with the impacts of risk once an
adverse event has occurred e.g. disaster relief payments in the event of a
disease outbreak. Table 7 sets out the range of risk management tools.
Table 7 – Summary of risk management tools in agriculture
Risk Reduction
Farm / household
/ community
Market
 Technological  Training on
choice
risk management
Risk Mitigation
 Diversification
in production
 Crop sharing
Risk Coping
 Borrowing
from neighbours /
family
 Intracommunity charity
Government
 Macro policies
 Disaster prevention
(flood control…)
 Prevention of diseases
 Futures
 Tax system income
/options
smoothing
 Insurance
 Counter-cyclical
 Vertical
Programme
Integration
 Border and other
 Production/mar measures in the case of
ket contract
contagious disease
 Spread sales
outbreak
 Diversified
 Market-price support
finance
(intervention buying, buffer
 Off-farm work
stocks)
 Selling
 Disaster relief
financial assets
 Social assistance
 Saving /
 All agricultural support
borrowing
programs
 Off-farm
income
Source: adapted from OECD (2009a)
69. As discussed in Section 5.2, interventions by government can alter the incentives
for farmers to act privately to manage risk. Conversely, private actions taken by
farmers, using a combination of farm-level and market-based means to manage
risk, reduce the need for publically provided risk management support. Indeed,
21
there will be a considerable level of interaction between most strategies and tools
to manage risk. For this reason, the OECD (2009a) recognises the importance of
taking a holistic approach when assessing risk management tools in agriculture.
Such an approach needs to consider the whole risk landscape faced by farmers
and the impact of current agriculture policy interventions on farmers’ exposure
and responses to risk when formulating risk management strategies.
5.1
Rationale for
management
government
intervention
in
agricultural
risk
70. Government intervention in markets can incur costs and create economic
distortions. Thus, any interventions to manage risks in agriculture must be
justified with a clear rationale, with any costs outweighed by benefits or returns to
intervention. Ideally, governments should intervene only when the market has
‘failed’ (or is expected to fail) to provide a satisfactory outcome, and this outcome
can be improved by government policy. The HM Treasury Green Book 31 sets out
the two main grounds for policy intervention by government:
i.
to address inefficiencies in the operation of markets and institutions; or,
ii. on equity or distributional grounds.
71. With this in mind, the relevant question in the context of managing agricultural
risk is whether there is any efficiency or distributional issues arising from private
risk markets, i.e. is there a market failure. Inefficiencies can arise in agricultural
risk markets from three sources: (i) imperfect (or costly) information; (ii) the
existence of ‘externalities’; or (iii) where insufficient competition in agricultural risk
markets give rise to market power for providers of risk management instruments
(e.g. insurers).
(i) Information costs
72. Markets for risk management services in agriculture require information on the
magnitude and probability of losses faced by farm businesses in order to function
efficiently (Bielza Diaz-Caneja et al. 2009). The highly unpredictable and diverse
nature of risks in agriculture means this information is often unknown or very
costly to acquire, both for farmers and for providers of risk management services.
The result is that the coverage of information is incomplete and unequal between
participants in risk markets (e.g. farmers and insurance companies). In
agriculture, problems of incomplete or asymmetric information tend to be greater
in yield risk than price risk as farmers have more control over the former.
Asymmetric information can lead to some farmers being ‘priced out’ of markets
for risk management services, as providers cannot distinguish between high and
low risk businesses and so set premiums based on average risk, making
protection (such as insurance) prohibitively expensive for farmers who are less
‘risky’ than average. Additionally, informational problems provide scope for ‘moral
hazard’, as farmers may take fewer measures to reduce risk in the knowledge
HM Treasury (2003) – The Green Book: Appraisal and Evaluation in Central Government.
Available at: http://www.hm-treasury.gov.uk/data_greenbook_index.htm
31
22
that they will receive compensation, such as an insurance payout, in the event of
an adverse outcome. Given the costs of acquiring and processing a suitable level
of information are likely to be particularly prohibitive or burdensome for smaller
farms, it also gives rise to distributional or equity issues.
73. Thus, regarding information costs, there may be a direct role for government to
intervene to facilitate research to generate missing information (e.g. into weather
patterns, disease prevalence to quantify risk) (OECD 2009a). Government can
also take steps to reduce the costs of sharing information between, for example,
farmers and insurance companies, in order to overcome problems of asymmetric
information.
(ii) Externalities
74. In economic terms, an externality exists when there is some cost or benefit that
accrues to an outside party from a market transaction or decision that is not fully
factored into market prices (and hence the decision). A relevant example for
agriculture is that of animal and plant disease. In these cases, the provision of
insurance will require the insurer to obtain information to inform the level of risk
that an individual business applying for insurance may suffer a loss due to plant
or animal disease. However, for any single business, the risk of a loss will
depend not only on the level of investment in bio-security by that business, but
also in the bio-security of neighbouring farms. Thus, to be able to determine the
premium, the insurer needs information beyond that of the applicant, which can
be costly to obtain. In this case, externalities in agriculture can exacerbate
information problems, meaning the provision of insurance for potential losses due
to animal and plant diseases is most likely to remain incomplete – provided at
sub-optimal levels or not provided at all.
(iii) Market power
75. Where a market is characterised by very few suppliers, as is the case in many
markets for agricultural insurance, the suppliers will tend to have some power to
influence market prices and ultimately the ability to generate economic rent or
“abnormal profits”. Bielza Diaz-Caneja et al. (2009) and Garrido and Bielza
(2009) suggest there is, indeed, a lack of competition in EU agricultural insurance
markets. The result is that even subsidies on insurance premiums do not always
benefit farmers, as suppliers of agricultural insurance are able to capture such
subsidies as economic rent. In such cases, Government may have a role in
improving market competition by, for example, removing barriers to entry to
increase competition in the insurance market.
(iv) Distributional concerns
76. In addition to economic efficiency grounds, government intervention may be
justified by concerns over the distribution of market outcomes. It is possible to
argue that agricultural enterprises are less able manage risk privately than
operators in other industries due to the relatively small size of many farm
businesses, and the relatively low profit margins on which they operate
(Matthews 2010). Additionally, risk exposure in agriculture may be high relative to
other industries, due to the greater uncertainty on the wide range of factors on
23
which agricultural businesses depend. As discussed in Section 2.2.1, agricultural
output prices are particularly volatile due to the unresponsive nature of demand
for food products to price changes and to the presence of other risk sources,
such as weather and disease. The ability to cope with and manage risk also
differs within agriculture and between agricultural businesses, due to the type of
enterprises, size of business and other factors.
77. Thus, there may be justification for intervention by government on the basis that
farm businesses and households are more vulnerable to some risks than those
that draw their income from other sectors. This is particularly important if existing
social welfare arrangements do not provide them with a sufficient safety net.
78. Any benefits from intervention by government on the above grounds must be
weighed against the potential costs or market distortions. Notably, government
interventions in agricultural risk markets can ‘crowd-out’ market solutions and
reduce the incentives for farmers to manage risk privately. Furthermore, as
highlighted in Section 2, policy intervention can itself be a source of risk if
provision changes frequently or unexpectedly.
5.2
Risk management related policies in agriculture
79. Table 7 sets out the range of policies that can be implemented by government to
reduce the agricultural industry’s exposure to risk and to assist farmers to cope
with adverse outcomes. While all agricultural policies affect the risk environment
faced by farmers and their responses to risk, certain policies can be seen as
more targeted at reducing or mitigating risk or helping farmers cope with adverse
outcomes. Within the EU, the CAP is the main driver for agricultural policy and
among its objectives is the stabilisation of agricultural markets.
5.2.1 Price stabilisation policies
80. There is a range of policy instruments that have traditionally been used at country
or regional levels to reduce the exposure of the agricultural industry to market or
price risks. Broadly, these policies are targeted at addressing problems
associated with output price volatility. A broad list of these policies is provided
below.

Intervention purchasing & public storage – reduces price fluctuations in
domestic markets by building up public stocks when supply is relatively high
to stop prices from falling to very low levels, and selling stocks when supply
is relatively low to prevent prices rising to very high levels.

Export subsidies – stabilises domestic prices by facilitating exports of excess
domestic supply, hence preventing domestic prices from falling. Effectively,
subsidies enable price variability in domestic markets to be exported onto
world markets.

Import tariffs – sufficiently high tariffs can protect producers from variability
in world prices by limiting imports. However, this can be at the expense of
higher prices and reduced choice for domestic consumers.
24
81. In the EU, direct price support was the main means of supporting farmers up until
the early 1990s. It comprised largely of a combination of intervention purchasing,
variable import levies and export subsidies. Successive reforms have reduced the
level of market price support in the EU, with a reorientation of support towards
direct payments, replacement of variable import levies with fixed import tariffs,
and a reduction in export subsidies. However, market price support (MPS) for
some cereals, dairy products, sugar and fruits and vegetables still accounts for a
substantial share of support provided under the CAP.
82. In the USA, considerable market price support is provided for dairy and sugar.
The dairy price support programme aims to maintain market prices at the
legislated support level through intervention purchasing of dairy products
(including butter, cheese and dried milk) from dairy processors. Although support
is aimed at dairy processors, the scheme has a stabilising effect on the price that
farmers receive. The U.S. Sugar Programme also uses price supports
mechanisms, domestic marketing allotments and tariff-rate quotas to keep USA
sugar prices above world market levels. Market price support for other
commodities is provided indirectly through a system of marketing loans,
discussed in 5.3.2, in addition to some import tariffs and quotas.
83. In Canada, price support is provided primarily for milk, poultry and eggs, through
a combination of import tariffs and production quotas designed to balance
demand and supply.
84. In addition to stabilising markets, market price support policies that maintain
domestic prices artificially above world prices also provide transfers to farmers,
the burden of which is borne by taxpayers (when public budgets are used to
purchase stocks or subsidise exports) and consumers (through higher prices). In
fact, in some instances the transfers and their impacts on farm income can be the
main driver for price support policies. However, such policies reduce the
incentive for farmers to use more effective and efficient measures in private risk
markets to manage price risk.
5.2.2 Supporting “on-farm” actions to reduce risk exposure
85. In a range of countries, policies also exist to assist the agricultural industries to
manage at farm-level a range of risk factors affecting farming. These measures
are different from the price stabilisation policies in Section 5.2.1 in that while they
may be available to all farmers in a country or region as a matter of policy, it is
often up to agricultural businesses to choose when they want to use them to
manage risks. Consequently, the outcomes of these measures reflect, to some
extent, the risk perception of farmers. Some of these policies are listed below.

Subsidising private storage – assists the agricultural industry in dealing with
short-term problems of over-supply by storing excess produce to prevent
prices from falling to levels that are too low and spreading sales over time.
Support is provided to meet the costs of storage, which can be substantial
for perishable produce.

Market withdrawals – provides compensation to farmers for the withdrawal
of produce from the market. Like subsidies on private storage, it is intended
25
to deal with short term problems of oversupply, especially where it is not
feasible to store the excess supply at reasonable costs – e.g. in the case of
perishable fruit and vegetables. The withdrawn produce is either destroyed
or distributed for free in a way that should not affect market demand.

Marketing Loans – allow farmers to keep their crops when prices are low by
enabling them to borrow an amount equal to the value of the crop, valued at
a given loan rate. The loan provides a cash flow that allows farm businesses
to hold onto produce when prices are too low without putting pressure on
business finances. Crops effectively act as collateral on the loan until such
a time when they are sold and the loan is repaid. In addition to reducing
price risk, in the USA where marketing loans have been used, they also
provide income support to farm businesses by allowing a repayment lower
than the actual loan rate if market prices do not recover above the loan rate
in a crop year. Similar to Marketing Loans, Loan Deficiency Payments
(LDPs) allow farm businesses to receive the same benefits as through
marketing loans when prices are lower than commodity loan rates, without
the need to take out a loan and subsequently repay it.

Support to production techniques – provides subsidies to reduce the costs to
farmers of adopting or investing in technical measures on-farm that would
enable them to manage risks.

Technical assistance and extension – Advisory services to farmers to
provide information and encourage uptake of production and marketing
techniques to reduce risk exposure.
86. Marketing Loans and LDPs as used in the USA can improve the stability of farm
incomes and stabilise market prices by reducing supply when prices are low.
Further, this reduces the need for public intervention purchasing to support
market prices, if this is a policy goal. The improved stability of farm incomes may
also make it easier for farm businesses to plan investment decisions. Canada
also operates a form of Marketing Loans through the Advance Payments
Program – providing loan guarantees to farm businesses in order that they can
borrow to improve their cash flow if they need to hold onto their stock. Advances
are provided through producer organisations, up to a limit of $400,000, with the
first $100,000 interest free. Coverage includes livestock and a range of crops and
producers have up to 18 months to repay advances.
5.2.3 Ex ante measures to assist farmers to mitigate/cope with risk
87. Ex ante risk mitigating and coping measures include the range of instruments that
governments can put in place in order to assist farmers in dealing with adverse
outcomes before these are actually realised. Some of the commonly cited ex
ante risk mitigating and coping measures include the following:
Countercyclical payments
88. Typically, countercyclical payments protect farmers against fluctuations in price or
income, with payments triggered if prices or incomes fall below a given level. In
the USA, schemes for countercyclical payments have been in place since 2003
26
but the payments account for a relatively small proportion of total farm support
(around US$4bn in 2006, compared to US$31bn total US farm support). The USA
scheme provides protection against crop price risk and makes payments to
producers with historic programme payment acres32 (or ‘base acres’) – with the
result that farmers that did not grow any eligible crops in the reference year
cannot receive payments.
89. The USA countercyclical payment scheme reduces the degree of price risk faced
by farmers as it provides support to counteract factors having negative impacts
on farm market receipts. However, the effectiveness of the scheme in maintaining
farm revenues is in some cases limited. First, the effectiveness of countercyclical
payments depends on the correlation between the production of the farm in the
year paid and production in the reference year. For example, where a farm only
grew wheat in the reference year has switched entirely to soybean production; it
will not be entirely protected against movements in soybean prices unless
soybean and wheat prices move together. Second, the scheme protects only
against price risk and does not account for impacts on farm revenue caused by
low crop yield.
90. An alternative to the standard USA countercyclical scheme is the Average Crop
Revenue Election Scheme (ACRE), which is an area-based crop-revenue
guarantee scheme designed to address some of the problems associated with
countercyclical payments. The scheme is voluntary and provides farm businesses
with protection against both price and yield risk by making payments when farm
revenues fall below a minimum level, although farmers must accept reductions in
payments made through other schemes.
91. ACRE payments are only made when two conditions are satisfied: if (a) a farm’s
revenue is below its ACRE revenue guarantee, and (b) the state’s actual revenue
is below the state revenue guarantee. This provides a safeguard against perverse
incentives that revenue guarantees can introduce, as a farm with low revenues
will only receive a payout if the revenues across the state as a whole are below
the guaranteed level, meaning that farms that do not take adequate on-farm risk
management are not rewarded.
92. In Canada, countercyclical payments are made through the AgriStability scheme,
which is part of a wider Business Risk Management Suite.33 The scheme
provides support for larger falls in income. Farmers supply a reference margin
based on an average from the last 5 years and payments are triggered if current
margins fall below 85% of the reference. As the scheme is based upon margins, it
provides coverage of output and input price risk in addition to yield risk.
93. Subsidies to reduce the cost of premiums – the provision of direct subsidies on
insurance premiums or support for reinsurance costs to reduce the cost to
32
Base acres are defined as the land on farm that was eligible to receive payments in 2002, along
with the area planted to other commodities now covered y support. It refers to total cropland on a
farm and not individual land parcels.
33
The suite is comprised of the following: AgriInvest, AgriStability, AgriRecovery, AgriInsurance,
and the Advanced Payments Programme.
27
farmers of getting private insurance can increase provision and coverage of
insurance in agriculture. In the EU, a number of Member States provide subsidies
on insurance premiums varying degrees (see Section 5.3.1).
The USA
Department of Agriculture (USDA) provides significant subsidies to reduce the
cost of premiums for agricultural insurance, which is provided by private
companies under the supervision of the USDA Risk Management Agency (RMA).
94. Public insurance – While subsidised agricultural insurance products in most
countries are provided by private sector, in some countries, e.g. Greece, Cyprus
and Canada, they are publically provided. Under these systems, farmers must
take a mandated level of insurance with the Government, which meets some of
the costs associated with these products. See Section 5.3.1 for further
discussion.
95. Income tax smoothing mechanisms – Allow taxable income to be spread over a
number of years or tax to be paid when the farmer is most able (e.g. in high
income years) in order to smooth disposable income for those working in
agriculture. These are commonly used in other OECD countries including
Australia, Canada, New Zealand and the USA. For example, income tax
smoothing is provided for Australian farmers through two systems. The Income
Tax Averaging Scheme allows farmers to be taxed at their average rate of
income over a rolling five-year period. The Farm Management Deposit Scheme
allows farmers to reduce their tax liabilities by depositing pre-tax income in good
years to be drawn as income in low-income years, with a cap on deposits of
AU$400,000. In March 2010, there were 35,084 farmers in the scheme with total
holdings of AU$2.4billion. In the EU, arrangements for income tax smoothing
mechanisms are at Member State level.
96. Support to diversification of activities – assists farm businesses (through
information, training and financial support) to diversify out of agriculture or
specific enterprises in order that they can have other sources of income not
correlated with traditional farming activities.
5.2.4 Ex post measures
97. Unlike ex ante measures, which are put in place or selected by farm businesses
before the uncertainty associated with agricultural production is resolved, ex post
measures tend to be reactionary – only deployed to address adverse outcomes
after they have already occurred. Below is a range of ex post measures typically
deployed across the EU and other OECD countries.
98. Disaster relief and ad-hoc payments – provided to farmers on an emergency
basis to fully- or partially compensate losses in output or income. They are
essentially countercyclical in nature as payments are made when business
conditions are poor, which may be due to many causes, such as animal disease,
a natural disaster, etc. Such ad hoc payments are common in the EU, where they
are financed from national budgets outside the CAP, although they often have to
comply with State Aid rules. Examples in the UK include payments to farmers
following the 2001 and 2007 foot and mouth disease (FMD) outbreak.
28
99. In the USA, the Non-insured Crop Disaster Assistance Program (NAP) provides
disaster support payments for crops that cannot be covered through insurance
markets. Support for other agricultural sectors, such as livestock, is largely
through emergency payments, e.g. in the event of natural disasters or difficult
economic conditions (low commodity prices, condemnation of milk or animals,
bankruptcy etc). In Canada, the AgriRecovery scheme provides disaster relief to
fill the gaps not covered by other programmes in the Business Risk Management
Suite. Because such payments are ad hoc, there is always some uncertainty as
to whether and how they will be paid, thus they tend to have their own risks. To
address this problem, both the USA and Canadian schemes have formal
processes to determine when payments are triggered, which improves the speed
at which payments can be made.
100. The Australian government also provides ad hoc support payments to assist farm
businesses incurring yield losses because of droughts – a significant risk factor in
Australia. New Zealand also operates an adverse recovery programme but this
provides support only in very exceptional circumstances.
101. While ad-hoc payments are designed to assist farmers in coping with an adverse
event, they can themselves be a source of uncertainty, as farmers often do not
know their level in advance. In addition, ad hoc support can reduce the incentives
for farmers to act proactively to reduce or mitigate risk if they believe they can
rely on ex post payments.
5.2.5 Direct payments
102. Direct payments to farmers form a significant part of agricultural support in the EU
and USA. In Scotland, direct payments under the CAP are made through the
Single Farm Payment (SFP) and Less Favoured Area Support Scheme (LFASS).
One of the most important changes made as part of 2003 CAP reforms was the
decoupling of direct payments from production for most commodities in order to
reduce the market-distorting effects of farm payments and encourage farmers to
be more responsive to market forces.
103. The primary aim of these payments is to provide income support to farmers. In
the EU, farmers are also required to meet requirements on the environmental and
agricultural condition of land in order to receive payments. As discussed in
Section 3.2, prices for agricultural commodities in the EU have become more
volatile with successive CAP reforms, which has led to some (including the
OECD) to assert that CAP reform would contribute to greater income volatility
(Anton & Giner 2005)34. However, according to the European Commission,35
decoupled direct payments play an income stabilising role, as they provide a fixed
stream of income to farm businesses. This is supported by a study by Cafiero et
Anton, J. and Giner, C. (2005) – Can Risk Reducing Policies Reduce Farmer's Risk and
Improve Their Welfare? Paper prepared for presentation at the 11th Congress of the EAAE
(European Association of Agricultural Economists), Copenhagen, Denmark, 24-27 August 2005.
34
European Commission (2005) – Communication on Risk and Crisis Management in Agriculture,
COM (2005) 74, Brussels.
35
29
al (2007)36 on risk management under the post-2003 CAP, which finds that the
fixed stream of income provided by direct payments can increase the stability of
farm incomes even if farm revenues from the market have become more volatile.
104. While this suggests that decoupled payments under the EU CAP can increase
the stability of farm incomes, they have several weaknesses as an income
stabilisation tool. Firstly, payments are fixed based on either the historic reference
period or area, and therefore do not vary to provide additional support to farmers
in years of low income; essentially, the payments are not countercyclical
(Matthews 2010). Secondly, as the distribution of direct payments is often
determined by the size of the farm business (measured by hectares of land or
intensity of production), the greatest beneficiaries in absolute terms tend to be
larger businesses that are most likely to be able to implement private strategies to
manage risk and volatility in income. In the context of Scottish or, more widely,
UK agriculture, direct payments represent additional exchange rate risk for
farmers, as payments are made in Euros and converted to Pound Sterling at a
rate set by the European Central Bank.
105. Despite these limitations, there are some additional risk-related effects of direct
payments such as the SFP. The fixed and relatively guaranteed income stream
provided by direct payments (depending upon compliance with requirements for
good agricultural and environmental condition of land) may improve the access of
farm businesses to credit markets, increasing the ability of farmers to borrow to
aid cash flow in difficult times.
106. Several studies have demonstrated that agricultural support policies designed to
support or stabilise incomes, such as the SFP, significantly affect farmers’
production choices and responses to risk (OECD 2008). Such support influences
farmers’ decisions through insurance and wealth effects (Heynessey 1998).37 The
insurance effect arises from the risk-reducing effect of such policies. The wealth
effect arises when increases in average income affect farmers’ responses to risk
by influencing their attitudes to risk. As discussed earlier (see Section 4.1),
farmers tend to be averse to risk; that is, they will accept a lower average income
in order to achieve an outcome that is more certain. Wealth has been found to be
a key determinant of risk aversion, with wealthier individuals tending to be less
averse to risk (OECD 2008). Therefore, by affecting the wealth of farm
households, agricultural support payments can alter farmers’ attitudes to risk.
107. This is supported by a recent study38 into the effect of the CAP on the risk
attitudes of farmers in Finland, which found that Finnish farmers became
significantly less averse to risk following accession into the EU in 1995 and
adoption of the CAP. Prior to accession into the EU, income support for
agricultural enterprises in Finland was provided through price support (primarily
Cafiero et al (2007) – Risk and Crisis Management in the Reformed European Agricultural
Policy, Canadian Journal of Agricultural Economics, 55, 419-441.
36
Heynessey, D.A. (1998) – The Production Effects of Agricultural Income Support Policies under
Uncertainty. American Journal of Agricultural Economics, 80, 1, pp46-57.
37
Koundouri et al (2009) – The effects of EU agricultural policy changes on farmers’ risk attitudes,
European Review of Agricultural Economics, 36, 1, 53-77.
38
30
through target prices for crops). Area and headage payments under the CAP
increased support payments to Finnish farmers considerably (due mainly to low
average yields in Finland relative to the rest of EU), providing a significant wealth
effect, which resulted in farmers becoming less averse to risk (measured by the
production decisions made by farmers). While this offers some evidence of the
wealth effect, the authors of the study emphasise that caution should be taken
when generalising these results, as the study focussed on only one risk source
(yield risk) and the results may arise, at least to some extent, due to the particular
nature of Finnish agriculture.
108. If risk attitudes are affected by support policies under the CAP, with farmers
becoming less risk-averse, this is likely to have impacts for farm production.
Farmers who are less averse to risk will be more willing to take riskier options,
such as inputs or outputs that have less certain outcomes but ultimately have
higher expected returns. Additionally, farmers may seek to specialise farm
operations in enterprises with the highest returns, rather than diversify
investment. Furthermore, many farmers can use market-based risk management
tools as an effective means to manage additional variability in market revenues.
109. Farmers in the USA also receive direct payments that are decoupled from
production based upon historic area and yield for supported crops. Direct
payments account for a large percentage of total farm support in the USA and are
focussed on arable crops.
5.2.6 Summary
110. In summary, agricultural support policies aimed at reducing the level of and
assisting farmers in coping with risk can reduce adverse effects of a risk on the
production choices of farmers and their economic welfare. However, there are a
number of issues with such interventions. Firstly, publically provided risk
management is likely to crowd out the development of private risk markets
(OECD 2009a). This is problematic when market-based solutions are more
efficient at managing risk than those that are provided publically. For example,
derivative-based instruments, such as futures and options (see Section 5.3.3) can
be a highly efficient way of mitigating price risk compared to price stabilisation
policies. Similarly, publically provided agricultural insurance systems may be less
efficient and offer a more limited range of services compared to a competitive
sector of private insurance companies (albeit a significant level of subsidies
would be required to achieve a similar coverage).
111. Secondly, government interventions can introduce perverse incentives where the
level of support or compensation is conditional upon an adverse outcome over
which the farmer has some control. There is considerable scope for perverse
incentives in countercyclical schemes, particularly where these schemes are
based on farm incomes or margins (such as AgriStability in Canada). This is
because farmers may be less likely to take autonomous actions to reduce or
mitigate risk in the knowledge that they will receive payments in an adverse
event. Similarly, farmers can become reliant on ad-hoc and calamity payments.
This is clearly related to the first point above, with public payments reducing the
incentives for farmers to use market-based instruments, which ultimately
increases the public costs associated with risks in agriculture.
31
112. These issues arise due to the effect of these schemes in transferring risks
associated with agricultural production from farmers to government. This gives
rise to an additional issue in that the costs of dealing with agricultural risks are
borne ultimately by the taxpayer rather than by agricultural businesses.
5.2.7 Measuring public support for risk management tools
113. All agricultural support policies whether targeted directly at risk or not, affect the
risk environment in agriculture and farmers’ behaviour. Nevertheless, by
analysing both the share of risk-related measures in the total Producer Support
Estimate (PSE) and the share of these measures relative to the size of the
agricultural industry in each country, a picture can be drawn of the degree of riskrelated support provided across OECD member countries and regions. The PSE
is an indicator compiled by the OECD to provide a measure of annual monetary
value of gross transfers to farmers arising from agricultural support policies. The
individual policy measures in the PSE database can be categorised according to
the type of support provided - including risk-related measures.
114. OECD (2009b) decomposes the PSE into categories using two separate
typologies. The first differentiates policies according to whether payment rates
are variable or fixed. The following categories are used:

Market Price Support (MPS) – Transfers from consumers and taxpayers to
agricultural producers from policy measures that create a gap between
domestic and international market prices for agricultural commodities. This
includes intervention purchasing & public storage, export subsidies, and
import tariffs and levies.

Variable rate payments – Payments based on output, area, animal numbers,
revenue or income that are determined at a variable rate. These typically
represent countercyclical measures, as payments rates will normally vary
according to market conditions. Examples include payments under
countercyclical and ACRE support schemes in the USA and payments under
AgriStability and AgriInsurance in Canada.

Fixed rate payments – Payments based on output, area, animal numbers,
revenue or income at a fixed rate. This includes direct payments to farmers
at fixed rates, such as the EU Single Farm Payment.

Other payments – Is a residual category. This includes a number of policies
that are classed as risk-related in Table 7, such as disease prevention
measures and support for provision of training to land managers.
32
Figure 4 - Share of MPS, variable and fixed rate payments in the PSE in total farm
receipts for selected OECD countries, 1992-97 and 2002-07
Source: OECD 2009b
115. Figure 4 presents the breakdown of PSE as a percentage of total farm receipts
(%PSE) into these categories for selected OECD countries and the OECD
average. Two bars are shown for each country; the first represents an average of
1992-1997 and the second represents an average of 2002-2007. There are large
differences in both the level and composition of support between countries. EU
support is highest as a percentage of total farm receipts (~32% in 2002-07).
116. Variable rate (countercyclical) payments are negligible in the EU, and relate
mostly to disaster relief payments. This is in contrast with support in the USA and
Canada, where variable rate payments make up a much larger share of PSE demonstrating the more countercyclical nature of USA and Canadian agriculture
support policies as set out in Section 5.2. In fact, total PSE as a proportion of total
farm receipts is considerably lower than in the USA and Canada (~22% in
Canada and 14% in USA in 2002-07) when compared to the EU, possibly
evidence that farm support policies in these countries currently give higher priority
to risk management when compared to direct income support.
117. The levels of support relative to farm receipts are lowest in Australia and New
Zealand, with PSE making up only around 6% and 1% respectively of total farm
receipts in 2002-07. The level of support in Australia has fallen significantly
between the two periods, with MPS reduced dramatically in 2002-07. In both
these countries, agricultural reforms have greatly reduced the level of support
provided to farmers, with remaining programmes focussed on support to promote
self-reliance and enhance international competitiveness. The last remaining
33
income support programme (Farm Help) in Australia was discontinued in June
2008.
118. In summary, decomposing the PSE for the selected OECD countries has shown
that while EU support under the CAP has moved towards fixed, decoupled
payments, there remains a high level of market price support when compared to
the other countries analysed. Additionally, Figure 4 has shown that total support
to agriculture in the EU as a percentage of total farm receipts are above the
OECD average and considerably higher than support in other comparable
countries. This could be a factor explaining the low uptake of market-based risk
management tools in the EU relative to the other countries analysed (see Section
5.9.4), as such support lowers the incentives for farmers to invest in these tools.
5.3
Market-based risk management tools in agriculture
119. In addition to risk management tools that may be provided by governments, there
is a range of market-based tools that farmers can use to reduce and mitigate risk.
The basis of all market-based schemes is risk sharing or risk pooling. Through
market mechanisms, agents (farmers, consumers/processors, traders) are able to
share risks that are not strongly correlated, thereby sharing the burden and cost
of risk. A number of market-based tools work specifically to mitigate price risk.
These are derivative-based schemes, such as forward contracts, futures and
options. Other tools, namely insurance, can also provide cover for yield risk,
although the extent to which they account for the range of factors that contribute
to yield risk varies widely.
120. The nature and use of market-based risk management tools differs greatly
between countries, largely due to differences in agricultural policy. As discussed
earlier, agricultural policy can both discourage farmers from taking private actions
to manage risks by directly providing protection against risks, or can incentivise
the use of market-based tools by providing subsidies to reduce associated costs
(e.g. subsidies on insurance premiums), or by compelling their use (such a
mandated level of insurance cover). Indeed, while the provision of these riskpooling tools is made through the market, in the majority of countries there is
often significant government involvement in agricultural insurance markets
through subsidies in insurance premiums or the direct provision of insurance.
121. Some variation between countries also arises from natural differences in the risk
environment (climate and other local factors) and its effects on farming. The Food
and Agriculture Organisation (FAO)39 suggests that market-based tools are
generally not adequately understood and used by farmers. This view is supported
by Alizadeh and Nomikos (2005),40 which asserts that only a few EU farmers
have adequate knowledge and resources to make effective use of market-based
tools.
FAO (2006) – An introduction to market-based instruments for agricultural price risk
management. Available at:
39
40
Alizadeh and Nomikos (2005), Agricultural Reforms and the Use of Market Mechanisms for
Risk Management. A study commissioned by the Futures and Options Association (FOA).
Available at: http://www.foa.co.uk/publications/agricultural_report_2005.pdf
34
122. Section 5.3.1 looks at the nature and use of agricultural insurance systems in the
EU and various OECD countries, while Section 5.3.3 looks at the use of forwards,
futures and options.
5.3.1 Agricultural Insurance systems
123. Agricultural insurance products are a type of risk-pooling measure for farm
businesses, in which premiums paid by participants are used to cover losses
incurred by individuals within the pool. Risk pooling is most effective when the
risks insured by participants are not strongly correlated (i.e. is not systemic),
meaning that payouts in any one period will be small relative to total contributions
to the pool through premiums. In the absence of subsidies on premiums or
support for reinsurance, agricultural insurance tends to focus on yield risk (and
specific factors that contribute to this) rather than price risk, as the latter is highly
systemic. In general, price risk is shared most effectively between buyers and
sellers where this risk is negatively correlated, through mechanisms such as
forwards, futures and options markets. These tools are discussed in Section
5.3.3.
124. A report for EC Joint Research Centre (JRC)41 sets out two requirements that
must be met in order for a risk to be insurable:

The adverse effects of asymmetric information must be managed

The implications of systemic risks (i.e. those that are likely to occur at the
same time among insured parties) must be overcome
125. Problems associated with asymmetric information were discussed in Section 5.1,
and can result in incomplete markets and provide scope for moral hazard.
Systemic risks present a particular issue for insurance due to the probability that
the insurer will face a large number of claims at the same time. In order to insure
against systemic risks, insurers must charge very high premiums and build up
large capital reserves. Government support in the form of state guarantees or
reinsurance can reduce these premiums. Alternatively, premiums can be
subsidised directly to increase affordability to farmers. Without such government
support, therefore, insurance coverage of systemic risks in agriculture tends to be
very poor and in many instances non-existent, with coverage confined to single,
scattered risks, such as hail and fire. To date, most agricultural insurance
systems have remained quasi-market in nature as they rely on government
subsidy.
126. In many countries, the private agricultural insurance market has largely been
stifled by government support policies. For example, ad-hoc or calamity
payments made by governments following adverse events may reduce farmers’
incentives to invest in insurance (OECD 2009) if they believe such payments are
41
Bielza Diaz-Caneja et al (2009), Risk Management and Agricultural Insurance Systems in
Europe. JRC Reference Reports. Available at
:http://mars.jrc.it/mars/content/download/1515/8548/file/LR_IPSC_Reference_report_agriculture_i
nsurance.pdf
35
always going to be made in the event of adverse outcomes in agricultural
production. Thus, due to differences in agricultural policy environments, the type
and coverage of private insurance products differ widely across countries and
between crops and livestock.
Table 8 - Summary of crop insurance types
Risks covered
Yield risk
Insurance type
Single-risk
Combined risk
Yield insurance
Whole-farm yield insurance
Yield & price risk
Revenue insurance
Yield, output and
input price risk
Index insurances
Income insurance
Area-yield insurance
Area-revenue insurance
Narrowest coverage and most
common form, insuring against
the occurrence of an adverse
meteorological event from a
single source (e.g. hail)
Also covers other meteorological
events, such as frost.
Insures against an adverse effect
on the yield of a given crop due
to a meteorological event, rather
than the occurrence of the event
itself
Accounts for the yield of all crops
produced by the farm, paying out
only if total production falls below
a given level.
Insures against price as well as
yield risk, paying out if the total
value of farm production falls
below a threshold
Also takes account of costs of
production (only exists in USA)
Compensation paid to insured
farmers if statistical yield for a
predefined area falls below
trigger level.
Compensation paid if average
revenue (area yield multiplied
area price) falls below trigger
level.
Source: Bielza Diaz-Caneja et al (2009)
127. Most livestock insurance products mainly cover non-epidemic diseases and
accidents. Crop insurance products, which are more developed, are summarised
in Table 8 according to the type of risk insured. Coverage of yield risk ranges
from single-risk insurance (normally covering hail and some other scattered risks
such as fire), which is the most common type of crop insurance, to whole-farm
yield insurance, which accounts for all crops produced by the farm. In general,
the level of insurance premiums increases with the number of risk factors
covered.
128. Revenue insurance accounts for price risk in addition to yield risk, with payout
made if revenue falls below a certain level. In principle, revenue insurance
products should be cheaper than yield insurance given yield and output price risk
tend to be negatively correlated (so that a fall in yield is compensated by a rise in
36
price and vice versa) (Alizadeh & Nomikos 2005). However, as discussed in
Section 2.3, while this relationship may exist at the aggregate level, it is much
less likely to hold at the farm-level, as the incidence of a given yield shock is likely
to differ among farms. Income insurance accounts for the effect of changes in
total costs in addition to total revenue on farm income.
129. Broadly, when compensation under the insurance products presented above is
triggered entirely by outcomes at the individual farm-level, there is significant
scope for “moral hazard” problems, as there is an incentive for farmers to reduce
the extent of on-farm measures that reduce risk exposure once insured. This is
particularly relevant to income insurance, where there are a number of factors
within the control of the farmer (especially production costs) and outcomes are
reliant upon how well the farm is managed (Alizadeh & Nomikos 2005). Problems
of moral hazard can be overcome by the use of area-based or index insurances.
In these instances, area-yield or revenue insurances compensate farmers only if
the average yield or revenues for a predefined area fall below a set level (based
upon an index), which may be a statistical average of levels in previous years.
While this guards against moral hazard problems, area-based insurance is only
effective in providing protection if the risk factors covered exhibit relatively strong
correlation between farmers in the area – a condition that would also increase the
cost of the insurance.
130. In order to address problems of prohibitively high premium costs caused by
systemic risks, many governments subsidise reinsurance costs and/or premiums
to increase the affordability of insurance. Garrido and Bielza (2009) and Bielza
Diaz-Caneja et al (2009) review agricultural insurance systems in the EU and find
wide variation between coverage and uptake of insurance between countries. As
would be expected, there is a direct relationship between the level of government
involvement in agricultural insurance markets and the level of coverage, with
subsidies on insurance premiums and reinsurance enabling coverage of more
systemic risks and higher uptake by farmers due to reduced premiums.
131. These studies also reveal broadly two different approaches to addressing yield
risks in EU countries, as can be seen in Table 9, which summarises data on the
level of insurance subsidies and ad-hoc / calamity fund payments in selected EU
member states, along with the types of insurance provided. The table shows that
Belgium, Netherlands, Germany and the UK (including Scotland) do not provide
subsidies to agricultural insurance. Germany and the UK, and to some extent
Belgium, have in the past relied mostly on ad-hoc payments to support farmers in
adverse events. In the absence of premium subsidies, coverage is limited to
single risk insurance in these countries.
37
Table 9 - Level of insurance subsidies and ad-hoc/calamity fund payments in
selected EU member states
Country
Singlerisk ins.
Combined
insurance
Yield
insurance
Insurance
subsidies /
Coverage
€million / %)
(1)
Belgium
Cyprus
France
Germany
Greece
P
GC
P
P
P
GC
P
GC+GS+G
PS
-
Italy
Netherlands
Portugal
Spain
UK
PS
P
PS
PS
P
PS
PS
PS
PS
-
PS
-
0
4.4 / 50%
5 / 2.4%
0
No data
(100% public
scheme)
180 / 67%
0
32 / 68%
232 / 41%
0
Ad-hoc and
fund
payments /
year
(€million) (2)
17.2
7.2
155.6 (3)
112.3
70.1
113.3
3.0
3.7
379.5
Source: Bielza Diaz-Caneja et al (2009)
(1) Annual subsidies. Data year not provided by the source.
(2) Yearly average of payments. Period of data varies by country, but mainly over the period
1995-2005.
(3) 50% of funding comes through private contributions from taxes on agricultural insurances
-: Not existing
G: Public non-subsidised
P: Private non-subsidised
GS: Public partially subsidised
PS: Private partially subsidised GC: Public compulsory partially subsidised
132. On the other hand, Spain, Portugal, Cyprus and Greece have extensive
government involvement in insurance markets. In Spain and Portugal, publicprivate partnership systems exist, where the state provides premium subsidies
and reinsurance while private companies administer insurance programmes and
cover a share of the risk; little support is provided through ad-hoc / calamity
payments. In Greece and Cyprus, insurance is subsidised and publicly
administered, with private companies only covering risks not covered by the
public system, although both countries also provide a significant level of ad hoc
support. The effect of subsidies on insurance premiums is clear; where no
subsidy is provided, private insurance tends to cover only single risks (hail, fire),
with higher levels of support increasing coverage to combined risks and yield
insurance.
133. There are merits and drawbacks to both approaches. Agricultural insurance, as
cover is determined ex ante, avoids to some extent the uncertainty associated
with ad-hoc payments, which are determined only once an adverse event has
occurred. However, both approaches can introduce perverse incentives, as
farmers may reduce the level of autonomous or on-farm measures to reduce or
mitigate risks.
134. Outside of the EU, the USA also provides a high level of subsidies on insurance
premiums. USA subsidies to insurance premiums amount to around
38
US$1.9billion42 including support for administrative costs of insurance companies
and reinsurance costs. In sum, total effective support to insurance amounts to
around 72% of premiums in the USA, compared to an average of around 32% in
the EU. As a result, US agricultural insurance markets are highly developed, with
around 45% of total crop production value insured (compared to around 23% in
the EU), and yield and revenue insurance is provided widely (Bielza Diaz-Caneja
et al 2009).
135. In Canada, agricultural insurance is provided publicly through the AgriInsurance
scheme, (part of the Business Risk Management Suite), which covers yield risk
for a range of commodities, including crops and livestock. Payments are made to
producers in the event of a yield shock on an individual crop basis, rather than
whole-farm yield. The scheme is partially subsidised, with total subsidies
accounting for 66% of premiums.
136. Subsidies are not provided to agricultural insurance systems in Australia and New
Zealand and, as a result, the coverage of private insurance schemes tends to be
limited to single perils, such as hail, fire and other isolated risks.
137. Although premium subsidies greatly increase the coverage of risks offered by
insurance markets and the uptake of insurance by farmers, there are downsides
to subsidy insurance, not least the costs to government. It is likely that the
efficiency of premium subsidies, that is the benefit per unit of expenditure, falls as
the size of the subsidy increases, as additional risks become increasingly more
expensive to insure. According to the World Bank (2010)43, government
subsidised insurance schemes have, historically, performed very poorly, with the
level of claims far exceeding the premiums paid by farmers, although this has
improved as provision of insurance has been transferred to private companies.
Further, if agricultural insurance markets are dominated by a small number of
large insurance companies (i.e. are not competitive) subsidies will, at least in
part, be captured by insurance companies rather than being passed onto farmers
in the form of lower premiums. Subsidies may also ‘crowd out’ other marketbased risk management tools, such as those discussed in 5.3.3.
5.3.2 Mutual funds
138. Mutual funds can be considered a special type of insurance in which participants
tend to be the owners of the fund. Risk is shared between members, who pay a
participation premium to cover administration and possible reinsurance costs,
with funds paid out to businesses to partially or fully compensate for economic
losses incurred.
139. Often, funds operate on a local or regional basis. Generally, this is an effective
and sustainable risk management tool when risks are not correlated among
42
Figures here are taken from Bielza Diaz-Caneja et al (2009)
Mahul, O. and Stutley, C. (2010) – Government support to agricultural insurance: Challenges
and opportunities for developing countries. World Bank report.
43
39
affiliated farmers.44 However, where risks are correlated among members of a
mutual fund, economic losses to members will most likely occur at the same time
– with the result that the paying out of compensations can put a strain on financial
resources of the mutual fund and ultimately its sustainability, especially where
opportunities to borrow are limited. Funds that operate on a local or regional
basis may be more susceptible to systemic risks, as some risks (such as weather
and contagious animal diseases) tend to affect geographically proximate farmers.
One benefit of regionally based funds is that they can reduce scope for moral
hazard, as farmers will be more familiar with the risks faced by other members
and there may be a degree of social control. To address problems of systemic
risks, funds may seek to reinsure risks (at the cost of a greater premium) or link
with funds in other regions that have a difference incidence of risks in order to
share the burden of losses.
140. Following from the above discussion, yield risks, particularly those that are
relatively isolated, are more suited to coverage through mutual funds than price
risk, which tends to be highly correlated among farmers. Price risk is more
effectively shared through other market-based mechanisms, such as forward and
futures contracts (see Section 5.3.3).
141. Mutual funds have the added advantage that where they are professionally
managed on behalf of the farmer, they provide small farm businesses with a
professional service for risk management, which may otherwise be prohibitively
costly for individual fund members.
142. In Canada, a form of mutual account for farm businesses is provided through the
AgriInvest scheme, which is designed to cover small or short-term falls in income.
The Canadian government, through Agriculture and Agri-Food Canada (AAFC),
matches farmer contributions up to CAD$22,500 each year, upon which two
withdrawals can be made by the farmer. Producers have the flexibility to draw
upon the funds to cover small declines in margins (of less than 15%), or for risk
mitigation and other investments, and earn interest on deposits. An advantage of
this scheme is in incentivising farmers to invest funds in order to provide for future
falls in income, caused by either output or input price risk or yield shocks.
However, as separate funds are not linked in order to pool risks, the scheme may
not be the most efficient way of managing these risks. Pooling funds and risks,
where risks are not perfectly correlated, would allow greater coverage of risks for
a given contribution to the fund.
Provisions under the CAP
143. Article 68 of Council Regulation (EC) No 73/2009 makes provisions for Members
States to grant, from their national ceilings for the Single Farm Payment (SFP),
support for a range of measures including the establishment by farmers of mutual
funds for animal and plant diseases and environmental incidents. The mutual
funds will provide affiliated farmers financial compensation for economic losses
caused by outbreaks of animal or plant diseases or environmental incident.
When economic losses are less likely to occur at the same time for all members – i.e. there is
systemic risk.
44
40
144. It appears from the regulation that Article 71 aims to encourage farmers to take
responsibility in managing risks affecting their businesses – most notably through
the pooling of risks across businesses that is offered by mutual funds.
Specifically, the mutual fund option will provide farmers with a mechanism to
contribute to a common pot of money, from which affiliated farmers incurring
economic losses can receive compensation.
145. The EC regulations do not make any specific provisions for how mutual funds
should be organised or managed, although there are requirements for co-funding
and the conditions on which the fund will pay out. It is left up to Member States to
determine the form that the mutual funds may take.45 Thus, if the mutual funds
for farmers in Scotland were to be supported through Article 71, the Scottish
Government would need to establish through domestic legislation a framework
through which farmers can organise themselves to share risks and make
compensation to members of their fund who incur economic losses as a result of
outbreak of animal and plant diseases or an environmental incident.
5.3.3 Hedging price risk – forward contracts, futures and options
146. As highlighted in Section 2.2, output price risk – that is, the probability that output
price may change during the production cycle of a commodity – is the key risk
faced by farmers and the mechanism through which many other sources of risk
manifest. A number of market-based tools are designed specifically to mitigate
price risk. Forward contracts, futures and options work to share risk by exploiting
the negative correlation of price risk between producers and buyers; that is, a fall
in price is a benefit to the buyer but a cost to the producer and vice versa. These
mechanisms allow price risk to be ‘hedged’ by enabling producers (buyers) to sell
(buy) a commodity at a future time, at a price (tentatively) fixed today (FAO
2006), reducing price risk for both buyer and seller.
147. It should be noted that these instruments are not aimed at improving the financial
outcome (i.e. expected price) for participants; rather, they are designed to reduce
the uncertainty around the expected price. The main features of each of the three
instruments are briefly outlined46 and then the nature and use of the instruments
in the UK/EU and other OECD countries is discussed. Alizadeh and Nomikos
(2005) outline four key benefits of market-based risk management tools in dealing
with fluctuations in prices:

They give risk-averse producers the opportunity to participate in risky
activities (i.e. activities that have uncertain outcomes) which they would not
otherwise undertake;

Consequently, trading away price risk using agricultural derivatives gives
more efficient outcomes than managing risk through on-farm methods (e.g.
diversification of investment into other enterprises), as farmers can pursue
the most profitable activities;
Article 71(2a) provides that “‘mutual funds’ shall mean a scheme accredited by the Member
States in accordance with its national law…”
45
46
Much of the detail in this section is based upon FAO (2006) and Alizadeh and Nomikos (2005).
41

By mitigating price risk, market-based tools can stabilise farmers’ incomes,
resulting in more stable expenditure on farm inputs and family consumption.
This can improve the resilience and security of rural businesses and
employment, reducing their reliance on government support policies.

Following from the previous point, the effective use of market-based tools by
farmers can reduce pressure on taxpayer-funded support policies and can
be the least-cost way to manage market risks in many circumstances.
Forward contracts
148. Forward contracts are a private agreement between the seller and buyer to
deliver a specified quantity of a commodity at an agreed time and price. Contracts
detail arrangements for outcomes in which quantity and/or quality do not meet the
agreed level (e.g. discounts, premiums). As payment is not normally made at the
beginning of the contract yet the seller is obliged to produce the commodities,
there is an inherent default or credit risk in forward contracts. Despite this, the
guarantee of the contract can improve farmers’ access to credit markets.
149. There are different types of forward contracts. The most common is the fixedprice contract, which protects producers and buyers against down-side risk (for
sellers, the possibility that market prices will fall, for buyers, the possibility that
they will rise) but leaves sellers (buyers) open to the possibility that market prices
will rise above (fall below) the fixed contract price (upside risk). Minimum price
contracts give farmers the opportunity to benefit from price rises, usually at the
expense of some premium, but these are much less common. The agreed price
in forward contracts is often set using some reference point, for example by
assessing prices in the futures market (see next section).
Futures markets
150. Futures are a more sophisticated means of sharing price risk. In the simplest
form, futures are standardised forward contracts (i.e. futures contracts for a given
commodity are of a set quantity) that are traded on exchanges. The exchange
house guarantees payment of a contract in case of default, removing credit risk.
There are significant transaction costs to users of futures exchanges in the form
of commission and brokerage fees.
151. Futures markets are primarily a means of hedging price risk rather than buying
and selling goods as only a very small percentage of trades in futures result in the
delivery of the commodity. Indeed, a futures contract (i.e. a promise to supply
goods) can be sold without actually producing or selling the commodity, as long
as an equivalent contract is bought before the due date (‘closing’ the position). An
important factor for participants in futures markets is basis risk. ‘Basis’ is the
difference between local cash prices and the relevant futures contract price and a
greater difference reduces the effectiveness of futures markets in hedging price
risk.
152. Farmers can also benefit indirectly from futures markets without participating in
the markets. Trading prices of contracts will generally reflect the current
expectations of traders regarding future prices. Farmers can therefore use this
42
information on expected future prices to make better-informed production
decisions, although price risk will still exist because of unexpected influences on
price not foreseen by traders (i.e. those risk sources discussed in Section 2.2).
Options
153. Options differ from futures contracts in that they can be used to guarantee a
minimum price rather than a fixed price. Therefore, options give producers the
opportunity to benefit from upwards movements in price in addition to providing
protection against price falls. This is because under an options contract
(specifically a ‘put’ option), the buyer of the contract (e.g. a producer) is not
obliged to sell the commodities whereas the seller of the contract (e.g. a
processor) is obliged to buy them – therefore, the producer can choose to sell if
the movement of price is favourable and choose not to sell if price falls.
154. The cost of this function is the option premium, which is a non-refundable
payment that the buyer of an option pays to the seller at the time of buying an
option. In practice, opportunities for farmers to utilise options are limited, as
options premiums tend to be prohibitively high.
Use of forwards, futures and options in the UK/EU and other OECD countries
155. Detailed data on the use of these tools in different countries is relatively scarce.
Available information suggests their use in the UK and EU is low relative to other
countries, such as the USA and Australia. Alizadeh and Nomikos (2005) assess
the ratio of trade in wheat futures contracts over physical production in the UK,
USA and South Africa, with a higher ratio indicating greater use of futures
markets.47 Figure 5 presents the results.48 Trade in wheat futures relative to
physical production is much lower in the UK than the USA throughout the period,
and is lower than South Africa from 1999 onwards following reforms to market
price support and price control measures in South Africa, which significantly
increased the demand for private risk-management tools.
47
Some of the difference in ratios could also be explained by greater activity of investors in
markets, who trade but do not produce commodities.
48
This ratio in all countries is much greater than one, as quantities traded on futures exchanges
are much higher than physical production – few trades actually lead to the delivery of goods, and
positions are ‘closed’ (i.e. an equivalent contract to buy a quantity of commodities is bought to
cancel a position to sell) before delivery / payment is required.
43
Figure 5 - Ratio of trading in wheat futures contracts relative to physical
production in the UK, USA and South Africa, 1989-2003
Source: Alizadeh and Nomikos (2005)
156. Palinkas and Székely (2009) have reviewed the use of various risk management
tools by farmers in the USA and several EU countries (Germany, Hungary,
Netherlands Poland, and Spain). Using data from a survey of EU farmers and
secondary data from farmers in the USA, the study finds that although the use of
hedging through futures markets is lower in the EU countries surveyed (around
2.3% farmers49), around a third of EU farmers used forward contracts compared
to around 10% of US farmers. The use of derivatives markets in the EU is
expected to rise due to 2003 CAP reforms and increased price volatility.
157. The use of derivatives is a major focus of risk management in Australian
agriculture. Agricultural policy reforms in Australia have all but removed market
price support policies in order to create a more market-oriented agricultural
sector, and the level of agricultural support from other policies is low relative to
other OECD countries. Australian farmers are highly exposed to volatility in world
price markets due to the openness of the Australian market to international
market and the low level of agricultural support, which itself is made more volatile
by the domestic price support policies of regions such as the USA and the EU. In
response, Australian farmers have become highly sophisticated in the use of
commodity derivatives (OECD 2000, Alizadeh & Nomikos 2005), although
evidence in the USA suggests that these tools are also widely used in that
country probably reflecting the structure of USA agriculture. Involvement in these
markets is often at the individual farmer level, facilitated mostly through farmers’
cooperatives and financial institutions.
49
It should be noted that although only 2.3% farmers in the survey use futures markets to hedge
price risk, the proportion of production hedged is likely to be significantly higher as larger farm
businesses are more likely to use futures markets than smaller enterprises.
44
Increasing the use of market-based risk management tools in the EU
158. Alizadeh & Nomikos (2005) discuss a number of barriers to the use of derivatives
in the EU and provide a range of recommendations to promote greater use. In
addition to the crowding-out of market-based instruments by CAP policies
discussed in Section 5.3, the report cites insufficient knowledge and training on
the part of the farmers in the use of market based tools. Another key issue,
particularly for smaller farm businesses, is affordability. Transaction costs can be
high, and farm businesses are often required to pay significant deposits to open a
trading account with brokers. Arising partly from this, a mixed perception of
derivatives among farmers is also a cause for low uptake, with farmers instead
preferring alternative risk management methods, such as diversification of
activities and production contracts, which are likely to be less efficient in
managing risk.
159. The authors provide a number of recommendations to promote the use of marketbased tools. These are summarised below:

Establishing an educational and training programme for agricultural risk
management: providing training on both the mechanics of agricultural
commodity markets and the use of market-based tools to producers,
consultants and organisations that farmers use to seek advice on managing
risk.

Channelling market based risk management products through farmerfocussed organisations: Investing and building relationships with farmerfocused organisations, such as Cooperatives, Farmer Controlled Businesses
and Merchants. This can help particularly in reducing the costs of marketbased tools for small-scale farmers, by improving opportunities for collective
action in risk management activities.

Development and marketing of flexible derivative instruments: Improving the
range and flexibility of market-based risk management tools to reflect better
the diversity of agricultural businesses in the EU.

Proactive involvement of exchanges, banks and financial institutions:
Encouraging financial institutions to work more closely with the farming
community to provide more suitable market-based risk management
instruments, in addition to providing appropriate infrastructure and training.

Agricultural policy management: Reducing the barriers to development and
growth of derivatives markets for agricultural commodities caused by
support arrangements under the CAP.
160. An additional cost and barrier to the use of derivatives is basis risk, which is the
difference between cash and futures prices. The OECD (2009a) cites evidence
that there is an increasing lack of convergence between cash and futures prices
on world exchanges for agricultural commodities, which increases the costs to
farmers of using futures markets. However, analysis by Alizadeh and Nomikos
(2005) provides evidence that the European futures exchange Euronext.liffe has
45
provided good performance, as measured by basis risk, for UK and French
farmers, although less so for farmers in Germany, Spain, Portugal and Ireland.
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6.
Summary
161. This paper has reviewed risks in agriculture and tools that can be used to
manage them, both through public policy and through the market. The main
findings emerging from this review are discussed below.
162. It is clear that agriculture faces a range of risks, many of which are specific to the
industry. Fluctuations in the market price for agricultural products are often cited
as the principal risk source by farmers and the insensitivity of demand for
agricultural produce means prices have to change by relatively large amounts to
bring demand and supply into balance following a supply shock. Additionally,
production risks arising from changes in weather or animal and plant diseases
are a significant source of risk, and can cause fluctuations in price due to effects
on market supply and demand. Fluctuations in input prices are also a significant
source of risk. These risks ultimately affect farm businesses through fluctuations
in income, and the precise nature of this impact depends upon the relationship
between risk sources, which is highly complex. Production decisions are also
likely to be affected by the presence of risks, as farmers tend to be risk averse,
meaning that farmers may accept lower returns in exchange for outcomes that
are more certain. Furthermore, fluctuations in income can constrain the ability of
farm businesses to invest, which can affect future income.
163. Analysis of fluctuations in UK feed wheat and cattle prices undertaken for this
paper supports findings in the literature of a trend for increased volatility in prices
of agricultural commodities. Additionally, a range of evidence is available in the
literature of increased volatility in EU and world market prices. Evidence suggests
that some share of increased volatility in EU prices may be the result of
successive CAP reforms, which have reduced the level of market price support
and liberalised trade with third countries, bringing EU prices more in line with
world prices. Additional sources of volatility were also cited in the literature:
growing linkages between energy and agricultural markets and volatility in crude
oil prices; biofuels mandates, which create artificial demand for feedstocks and
make demand for agricultural produce less responsive to price changes; relatively
low global public stocks, with evidence that volatility in cereals prices increases
when stocks are low; and speculative activity of investors in futures markets,
although there mixed evidence about whether such activity led to the 2007/8 price
spike.
164. The uncertainty associated with other factors that affect agricultural production is
potentially greater in the long-term due to climate change, which may have as yet
unknown effects on temperatures and rainfall, including extreme weather events,
and the range of animal and crop diseases and pests.
165. A range of instruments is available to help (a) reduce the level of risk, (b) mitigate
remaining risks, and (c) cope with the adverse effects of risks. Some are policies
that can be implemented publically by government, while others are provided
through the market or implemented on-farm.
166. A review of policies finds there is a significant level of government intervention in
agriculture through direct payments and other risk-related policies, in both the EU
47
and other OECD countries. Analysis suggests that there is some rationale for
governments to intervene in risk management in agriculture. This arises primarily
due to problems of costly information, which can lead to incomplete markets.
Additionally, high transaction costs associated with market-based tools can give
rise to an equity motive for intervention, where these costs are disproportionately
high for smaller businesses. However, government interventions can incur
significant costs and can reduce the incentives for farmers to take private actions
to reduce or manage risks.
167. Price stabilisation policies, such as intervention purchasing, import tariffs and
export subsidies, to reduce price risk are present in the majority of OECD
countries, but are gradually being phased out in order to reduce market distortion.
Market-based solutions, such as futures and options contracts, can be highly
efficient ways of mitigating price risk and use of these tends to be highest where
support provided by price stabilisation policies is particularly low, such as
Australia and South Africa, as these policies reduce the incentives for farmers to
invest in market-based solutions.
168. Two broad approaches to managing crop risk through government policy were
identified; (i) through subsidies to agricultural insurance systems to increase
uptake and broaden coverage (e.g. Spain, Portugal, USA, Canada, Greece), and
(ii) compensate farmers through ah-hoc or calamity payments (e.g. UK,
Netherlands, Germany). Some countries, such as Australia and New Zealand,
provide little support either for agricultural insurance or through ad-hoc payments.
Support that is more comprehensive is provided in the USA and Canada in the
form revenue and income stabilisation schemes.
169. Direct agricultural support payments account for the majority of EU agricultural
support under the CAP and a substantial proportion of support in the USA. While
these payments tend to distort markets less than direct price support, there is still
a significant effect on farmers’ behaviour through wealth and insurance effects,
which can affect farmers’ attitudes to risk.
170. Additionally, farmers can implement a number of on-farm measures to reduce
and mitigate risks, such as diversification within and outwith agriculture,
investment in appropriate risk prevention technologies and collaboration with
other farmers through mutual funds to pool risks. Private actions undertaken by
farmers, either on-farm or using market-based tools, can reduce the public
burden of agricultural policies designed to assist farmers in mitigating or coping
with risk.
171. Thus, in choosing when and how to intervene in risk management in agriculture
there is need to assess the feasibility and cost-effectiveness of the various risk
management strategies. Such an assessment needs to consider the full range of
instruments available for managing risks and, in particular, take into account the
effect of current agricultural policies on farmers’ risk environments and responses
to risk.
48
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