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Abstract number: 020-0231
Cooperatives and Agribusiness Market Risk Management in a
Brazilian State
Authors’ information:
• Vilmar Rodrigues Moreira
Organization: Pontifícia Universidade Católica do Paraná
Address: Rua dos Bandeirantes, 296 – casa A – 81520-630 –
Curitiba – Brazil
[email protected]
+55-41-8829-6517
• Rainer Kühl
Organization: Justus-Liebig-Universität Giessen
Address: Senckenberstrasse, 3 – 35390 – Giessen – Germany
[email protected]
+49-0641- 99-37270
• Axel Freier
Organization: Justus-Liebig-Universität Giessen
Address: Senckenberstrasse, 3 – 35390 – Giessen – Germany
[email protected]
+49-0641- 99-37270
• Roberto Max Protil
Organization: Pontifícia Universidade Católica do Paraná
Address: Rua Imaculada Conceição, 1155 – 80215-901 – Curitiba –
Brazil
[email protected]
+55-41-3271-1250
POMS 22nd Annual Conference
Reno, Nevada, U.S.A.
April 29 to May 2, 2011
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Abstract
This article discusses the management of the agribusiness market
risks, the influence of
agribusiness cooperatives on this field, and shows an assessment
of the production
portfolio of agricultural commodities in a Brazilian State
considering the risk-return
relationship. Using the Markowitz E-V model we could outline an
efficiency frontier to
determine the necessary changes to be carried out in the State
production portfolio aiming
at building economic efficiency (defined in this article as the
trade-off between risk and
return). The article also assesses the possible influences this
type of organization could
exert on changes towards economic efficiency. Through
questionnaires and interviews
with cooperative managers, it was possible to assess the
cooperatives’ willingness to
motivate changes in their own production portfolio and in the
portfolios of their
members. We could also assess whether there are other causes
that might influence
agribusiness market risk management in the State studied. We
noticed that the reasons
influencing decisions on production preference changes are
related to economic and
rational aspects, such as cooperative strategic focus and member
resistance. Other
possible reasons related to political or social aspects, which
are inherent to the
organizational characteristics of cooperatives, do not exert
significant influence on
diversification decisions as a main management option toward
market risks.
Key-words: Agribusiness, Cooperatives, Risk Management
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Introduction
The competitiveness of agribusiness requires from producers a
permanent revision
in the way their activities are planned and organized including,
for instance, all steps of
production planning and the relationship with their suppliers
and customers.
Competitiveness demands an efficient coordination and
organization of processes where
free negotiation is replaced or complemented by contracts,
coalitions or even by a full
vertical integration (FAO, 2005). Rural producers, especially
the small ones, must seek to
join associations, cooperatives, coalitions or other supporting
ways to strengthen them
and thus indeed play a significant role (GUILHOTO; FURTUOSO;
BARROS, 2000).
The rural associative organizations can show several types of
structure, as for instance
cooperatives. This kind of organization can reach high levels of
vertical integration.
In Brazilian economy, cooperatives are highly representative
concerning
producing and selling agribusiness products. They absorb a large
share of the farms
production and may influence decisions on production and sales
of commodities.
Nowadays there are about 1,500 cooperatives in activity, with
880 thousand members and
124 thousand workers. Cooperatives represent 41.53% of total
agribusiness incomes and
the businesses of their members are more profitable if compared
to the national average
of R$ 123/ha. Non-members: R$ 92/ha; members: R$ 237/ha. The
participation of
cooperatives in the production of some items is also
significant: maize- 17%; coffee-
28%; soybean- 30%; cotton-39%; milk- 40%; wheat- 62%; hogs- 32%
(OCB, 2007). Due
to such participation cooperatives play an important role in the
agribusiness context, thus
cooperatives and their particularities must not be overlooked in
any study concerning
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improvements in agribusiness management, especially those
related to economic
efficiency.
Economic efficiency is defined in this article as the trade-off
between risk and
return, i.e., combined activities in which producers can get a
maximum income with
certain risk levels that might be considered acceptable
(measured by income variability).
Disregarding risks induces rural producers to make decisions
that are not related to their
real practices. Rural producer and cooperative goals towards
achieving the best risk
management is of special interest to all entities or people
involved in agribusiness
activities.
However, normally, especially in Brazil, agribusiness
cooperatives try to invest
their resources considering their cooperative principles and
seeking to a balance in the
economic and social goals. Thus, one of the main challenges
faced by cooperatives is to
balance economic, social and political interests of their
members (ANTONIALLI, 2000).
Economic interest involves enterprise growth of cooperative and
their members . Social
interest is regarding to services and benefits that are expected
from cooperatives by their
members. And political interest usually creates internal
disputes for power and
representation of cooperatives before a community. The inability
of cooperatives for
balancing those interests may increase the lack of
competitiveness and create complex
managerial situations (ANTONIALLI, 2000). This issue raises
relevant questions
regarding the ability of a cooperative to survive in such
globalized and competitive
environment and, at the same time, balancing political
rationality (cooperative principles)
and economic rationality (economic efficiency).
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Furthermore, concerning risk management, especially market
risks, the
agribusiness cooperatives do not always have access or even
opportunity to use some
instruments to cope with risks. In the Brazilian context, for
instance, not all cooperatives
(especially the smaller ones) have access to hedge options such
as forward contracts or
options, mainly due to the lack of offer of such instruments in
the Brazilian financial
market or constraints such as guarantees (MOREIRA, 2009).
Moreover, the production
diversification, which is the main strategy to deal with market
risks, normally depends on
the availability of inputs (normally from members who have
production portfolios more
specialized rather than diversified) and investments in new
technologies, which usually it
is not easily achievable due to difficulties in financing and
the resistance of members
(inertia for changes) - who are the main stakeholders of a
cooperative. These risks are
caused mainly by a path dependency among members and
cooperatives.
The objective of this study is assessing the management of
agribusiness market
risks and its practice in cooperatives. Initially, risks in
agribusiness and cooperative
enterprises are discussed. Afterwards, using the Markowitz E-V
model as a tool to
measure and assess market risks, the agricultural production
portfolio of a Brazilian State
is analyzed by generating an efficiency frontier. Some options
of efficient portfolios
were defined with this procedure. Using these portfolios, it
would be possible to optimize
the relation between risk and return and hence improving
economic efficiency of the
agribusiness in this Brazilian State (concerning to the
risk-return relationship). However,
to achieve these goals it would be necessary changes in the
production levels of some
items. Some aspects of the feasibility of these changes are
discussed considering the
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possible influence that cooperatives might exert on them. The
reasons that could
influence cooperatives in rejecting the proposed changes were
also analyzed in order to
verify whether the cooperative principles somehow might
influence the agribusiness
market risk management through diversification.
Risks
The risk and uncertainty concepts have been broadly used in
economics theory,
where risk and uncertainty can be distinguished from each other
based on the knowledge
of the probability of happening an event, such as receiving
income or using resources.
Risk is characterized by situations happening with known
probability; on the other hand,
uncertainty is characterized by situations where the probability
of an unusual
phenomenon cannot be foreseen. Risk can be considered as a
three-dimensional concept,
comprising: event (profit or loss), probability of happening
(usually of an undesirable
event) and time (EHRLICH; MORAES, 2005). Nevertheless, according
to Hardaker et.
al. (2007), this usual distinction between risk and uncertainty
is not useful, since cases
where probabilities are objectively known are exception rather
than frequent situations.
The authors prefer to define uncertainty as imperfect knowledge
and risk as uncertain
consequences – normally the unfavorable ones. Thus, risk is not
value-free, usually
indicating an aversion for some of their consequences. In this
sense, taking risks is to
exposure oneself to unfavorable situations. For many day-to-day
decisions, risks are
usually unimportant since the scope of possible loss is small or
the probability of
suffering that loss is judged to be low (HARDAKER et al.,
2007).
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Since every person has some incentive for his or her activity -
usually a reward,
one of the possible approaches to assess risks is to consider
their closely relation to
opportunities and this reward. A reward may be intrinsic, like
the recognition from family
and friends, or extrinsic, like profit or some earning. In most
cases it is a mix of both and
neither part should be underestimated; but nobody can survive
purely from recognition. It
does not matter whether a reward is intrinsic or extrinsic,
usually it is only possible to get
it when some opportunities emerge, which of a person can or
cannot take advantage of.
And, not less important, a person must have some degree of
motivation and/or the needed
skills in order to take advantage of these opportunities.
Considering the internal and
external aspects, we can shape a “map of opportunity” for each
person differently.
Concerning to entrepreneurs, the Figure 1 shows a map of
opportunity that brings
together aspects of opportunities, motivations and skills.
In some cases individuals are less motivated to use new
opportunities because of
their risk aversion or satisfaction with status quo. Their
awareness of opportunities, their
skills, and motivations to pick them up are dependent on their
subjective evaluation of
their options. In the case of “motivated” but “not skilled” they
may be willing to learn, or
may organize the opportunity by using different skills that
might be provided by other
entrepreneurs in a cooperative way. The aspects of a decision
will influence them not
only once: if aspects change over time, the once made choice
will be under scrutiny
again. From this perception, there are two ways in which a once
chosen opportunity may
fail (over time or instantly):
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a) the opportunity is not covered by the entrepreneur’s skills
or motivation
(internal aspects) (anymore);
b) the once used opportunity is now excluded by regulations or
laws, fails to
generate profits due to increasing competition or volatility or
climate change
etc. (external aspects).
Figure 1 - Map of opportunities
opportunities excluded by law or lack of climatic or market
conditions etc.opportunities which fail
because of weak incentivesor motivation
opportunities which requiretoo much ability / skill
opportunities which passed the external aspects, the competence-
and the incentive- test
External
aspects
entrepreneurial ability
entrepreneurial
motivation
realized opportunities
unidentified opportunitiesunrealized opportunities
Source: Freier (2007) and Röpke (1992)
These two sources of failure contain different potentials to let
the effective result
drift off from the expected result. Hence, these two sources are
the first main distinction
of risk-types: “Internal” and “External”. In the context of
businesses, these aspects are
used in economic literature to differentiate “non-systematic”
and “systematic” risk from
an investor’s point of view.
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In firms risks can happen in several areas. Usually, according
to the economic
approach, a company hopes to obtain returns from its activities
in agreement with its
utility function. Such activities results are subjected to
certain events, and that is why the
achievement of these results is sometimes uncertain. Risk can
mean uncertainty about the
expected return or the probability of undesirable losses
(financial or non-financial).
Nevertheless, although many economists defend risk management,
not all the companies
are involved in this practice in an effective way. Often, risk
management is just
concerned about credit and market risks hence merely price
variability and credit analysis
are the main company concerns (FRENKEL; HOMMEL; RUDOLF,
2000).
Risks in agribusiness enterprises
All agribusiness companies are exposed to some risk level. These
risks might be
of several types such as variability and uncertainty of
production and price. However, the
whole elimination of these risks is usually neither feasible nor
desirable, once it might
also limit the possibility of improved revenues. Companies had
better manage the
advantages of the risk-return relation thus not limiting the
growth possibility brought
about by risk aversion (ZEULI, 1999).
Some risk sources, such as climatic instability and pests, are
intrinsic to
agribusiness. Other risks, as market and institutional risks, in
spite of being also present
in managerial contexts, concerning agribusiness have different
status and characteristics.
Due to the great variety of agribusiness risks sources and the
inherent particularities of
each type of rural producer, there is not a unique managerial
strategy common to all
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producers. Producers face different types of risk and need
different management tools
(USDA, 2008). Some studies show that the producer perceptions of
importance and
influence of each risk can vary a lot depending on the kind of
company and operation
region. Also, their managerial strategies to avoid and reduce
risk consequences can vary
as well (PATRICK et al.,1985; HARDWOOD et al., 1999; GOMES,
2000; POPE, 2003;
FLATEN et al., 2005; PINOCHET-CHATEAU et al., 2005; HARDAKER et
al., 2007;
HEIDELBACH, 2007; USDA, 2008; MOREIRA, 2009).
Frequently, in rural field economic studies assess mainly the
market risks
(FRENKEL; HOMMEL; RUDOLF, 2000), what is partly justified by the
availability of
such risk modeling and assessing methods, especially those
addressed to the utility theory
and using mathematical programming. In Brazil, besides the risk
management types,
sources and strategies aforementioned, we can also mention the
lack of logistic
infrastructure (highways, ports, etc.) as a risk source
influencing the product total cost.
Furthermore, maintaining a high tax burden and one of the
highest basic interest rates in
the world, also contributes to the existence of production,
market, financial and
institutional risks.
Concerning agribusiness cooperatives, it is easy to verify that
they operate in a
naturally risky environment; in addition they are also exposed
to high degrees of financial
and market risks. According to Manfredo and Richards (2007),
several situations
generate those risks to cooperatives. They usually concentrate
their activities in few
commodities, and/or operate in geographically limited areas,
and/or use small marketing
channels. Most small cooperatives have a low production
diversification level and usually
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their commodities (as fruit, vegetables and horticulture) have
neither options in the
forward market nor insurance availability hence they do not have
the opportunity to
manage their risks using market instruments. A lot of
cooperatives also operate in pool
arrangements (sharing losses) where the production of their
members must be sold in a
specific time frame. Despite being interesting to cooperative
members, for they do not
have to be concerned with “market time”, such arrangements limit
the possibility of
maintaining stocks and of selling them whenever price becomes
more attractive. Such
situation might imply high levels of market risks. In addition,
cooperatives usually
operate with low profit margins, cannot have access to financing
through finance market
(stock exchange) and must provide refunds to their members.
These characteristics
demand a high leverage level from cooperatives, and
consequently, they might face high
levels of financial risks.
Zeuli (1999) defends that the strategies for an agricultural
cooperative to reduce
risks concerning availability of raw material supplies needed to
its production and to
income variability would be, respectively, (i) geographical
expansion of its members and
(ii) product diversification according to market demands. The
advantage of the first
alternative is the possible contribution to a larger production
diversification of
cooperative through increasing number of suppliers, but likely
it would imply larger
logistical costs. The advantage of the second alternative is the
possibility for decreasing
risks, but it would be necessary larger investments and
cooperative would face larger
production costs. However, although these strategies are
addressed to improving risk
management and economic efficiency, one of the main obstacles to
use them might be the
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possible tension with some aspects of the cooperative goals.
Increasing the number of
associates (in order to guarantee production supply and to
improve diversification) may
also cause more problems of cooperative governance. Production
portfolio diversification
may cause loss of cooperative strategic focus and conflicts due
to general resistance of
members for changes.
In the last years, some authors have been studying the ability
of cooperatives cope
with several risk types (SHAPIRO; BRORSEN, 1988; ZEULI, 1999;
FERREIRA, 2002;
MANFREDO; RICHARDS, 2007; MOREIRA, 2009). It is verified that
production
and/or activity diversification are the most accepted strategies
for coping with market
risks. However, these strategies may not be easily applied by
cooperatives. These
organizations frequently have low flexibility for changing their
production portfolio; i.e.,
flexibility for changes in cooperatives normally is less
accessible than in commercial
companies. Besides, given the variety of activities and
operations that a cooperative can
perform, different types of risks can emerge from several
sources. In Brazil, for example,
cooperatives are still considered organizations with social
functions and, despite being a
requirement for social performance, the economic performance is
not usually prioritized,
thus bringing about increased financial risks.
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Methodology
Initially, we carried out an analysis of the agricultural
production portfolio of a
Brazilian State – the State of Paraná - through analyzing
historical production series.
Thus for each agricultural activity chosen to be used in the
model it was possible to
assess gross margin variability (difference between price
received by producer and
estimated production costs). The time range considered in this
study was from 1996 to
2006 and gross margins were calculated monthly for each
activity. The gross margin
variability was used as a proxy for risk measurement.
Data sources were the following: SEAB/DERAL (Paraná Agriculture
and Supply
Department/Rural Economy Department) for producer price historic
series;
DERAL(Rural Economy Department), CONAB (Supply National
Company),
AGRIANUAL (Brazilian Agriculture Yearbook) and ANUALPEC
(Brazilian Livestock
Yearbook) for production cost estimation historic series, both
Yearbooks were published
by FNP Consultoria & Agroinformativos; IPA-DI (Wholesale
Price Index variation–
Internal Availability) published by FGV (Getulio Vargas
Foundation) for values
updated; DERAL(Rural Economy Department), ANUALPEC (Brazilian
Livestock
Yearbook) and EMBRAPA (Farming-Livestock Brazilian Company) for
production
historic series.
This study used linear programming to select the optimal
combination of
productive activities that maximizes the total agribusiness
gross margin of Paraná. Mean
gross margins were used as objective-function coefficients.
Regarding restrictions and
considering the analyzed period, ranges of minimum and maximum
production levels and
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needed area for each activity were used. For tillage activities
(soybean, maize, beans,
coffee, wheat, cane, tobacco, cassava, potato, tomato, orange
and grape) the computation
of the area needed for production took into consideration the
2006 total productivity
(total production divided by harvest area).
Yet, although many studies apply linear programming to solve
problems of
optimal combination of agricultural activities, this tool is
inadequate without considering
risks. Linear programming tends to produce extreme solutions
(corners) or only high
specialized solutions that normally do not describe rural
producer reality in a reliable
way. In this work, risk analysis was incorporated through the
Markowitz E-V model
(return-variance) (MARKOWITZ, 1952). This model normally is used
for minimization
in total variance of portfolios. Regarding production portfolio
modeling the goal is
minimization of total variance in historical gross margins of a
given activities set. This
variance can be estimated by: ∑∑=j k
kjkj XXV σ , where Xj is the j-activity’s level and
jkσ is the covariance of the j and k-activity total gross
margins (when j = k, jkσ is the
variance of the j-activity gross margin). According to this
equation, which defines the
gross margin total variance, variance can be expressed by
individual gross margin
variability of the activities and the covariance between
them.
To use the E-V model we initially carried out an analysis of the
historical series to
estimate gross margin variability of the activities (proxy for
risk measurement). The gross
margin variability was calculated through variance. The model
was solved with
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parametric techniques allowing generating the economic
efficiency frontier (risk-return).
The model and the procedures used to generate the efficient
frontier are presented below:
Minimize ∑∑=n
j
n
k
kjkj XXV σ
Subject to ),...,1(1
njXfn
j
jj =∀=∑=
λ ; and further LP model constraints.
Where fj is the expected gross margin of the j-activity and λ is
the parametric
coefficient. The model objective function is quadratic when j =
k, and hence an algorithm
of quadratic programming must be used to solve it. The sum of
the first restriction
represents the accumulation of the multiplication among the
expected gross margins ( fj )
and the activities’ levels ( Xj ), thus defining the expected
total gross margin E (total gross
margin). This sum must be equaled to the parameterλ . Varying λ
from the possible
minimum value for E until the maximum value found in the LP
model, is found a
sequence of solutions relating total gross margins and total
variances, considering the
restrictions imposed to the model. The minimum value for E was
calculated according to
restrictions of minimum production for each activity (smaller
production level of each
activity in the analyzed period). For each value of λ , there is
a value for the gross
margin E whose total variance V is minimum. This set of pairs
defines the efficiency
frontier, where ordinate is equal to the total gross margins and
the abscissa is equal to the
related variances (proxy for the risk) (HAZELL; NORTON,
1986).
After building the efficiency frontier, we could verify the 2006
production
position in terms of risk-return through assessing its relative
position (production levels
verified in that year) regarding the efficiency frontier. 2005,
2004, 2003 and 2002
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production levels were also analyzed and the points were
positioned in the risk-return
space, thus permitting a comparison with the 2006 situation.
Through the risk-return
analysis, it was possible to assess the needed changes in
agricultural production portfolio
to achieve maximum efficiency. Thus, the changes of production
preferences might
somehow affect the operations of the Paraná’s agricultural
cooperatives. Questionnaires
and semi-structured interviews were applied to cooperative
managers in order to assess
willingness of cooperatives to further the proposed changes in
their production portfolios
and in those of their members. The results are described in the
following chapter.
Assessment of the agribusiness commodities production portfolio
of Paraná
The initial assessment was based on data comprised in the yearly
report called
“Gross Value of Paraná Agricultural Production”, which is
published by DERAL (Rural
Economy Department) belonging to SEAB (Department of Agriculture
and Supply of
Paraná). This department carries out a systematic follow-up of
the State agribusiness
production. Table 1 shows the agribusiness Production Gross
Value (PGV) of Paraná in
2005/2006 and variation in participation of each group in the
last 10 years.
The "Main Cultures" group includes, among others, main grains as
soybean,
maize, coffee, beans and wheat, besides sugar-cane, tobacco and
cassava. The
"Livestock" group includes, among others, poultry, bovine, hog
and milk and egg
production. The "Forest products" group includes production of
wood log. The
"Vegetables and Spices" group includes, among others, potato,
cauliflower and tomato.
The "Fruit Growing" group includes, among others, orange and
grape. We noticed that
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production levels have changed in the last years. This might
reflect the preferences and/or
possibilities of rural producer production. Table 2 shows the
items used in the E-V model
and their representativeness in the 2005/2006 PGV.
Table 1 – Comparison among production gross values (PGV) of
Paraná
Groups PGV 96/97 PGV 05/06 % Variation
(ii / i) Value (R$ mil) (i) % PR Value (R$ mil) (ii) % PR
Main Cultures 9,982,651 48.22 10,764,126 41.76 7.83
Livestock 7,828,407 37.81 9,940,522 38.56 26.98
Forest Products 1,422,717 6.87 3,079,651 11.95 116.46
Vegetables and Spices 922,092 4.45 1,285,895 4.99 39.45
Fruit Growing 536,402 2.59 663,541 2.57 23.70
Floriculture 10,708 0.05 45,405 0.18 324.04
Paraná (PR) Total 20,702,977 100.00 25,779,140 100.00 24.52
Source: Andretta (2008) Notes: PGV = Production Gross Value
(PGV).
Although the state agricultural production seems to be quite
varied (509 items
comprise the whole of PGV of the state), 70.05% of the PGV
comprise only 17 items,
thus presenting a concentration on few commodities. These items
were used as variables
in the model because they are the most representative items in
agribusiness production of
Paraná. Each agribusiness product group and subgroup developed
in the state was
represented by these items, excepting the “Forest products"
group (due to the lack of
historical price and cost records) and the group floriculture
(due to the very low
representation in the PGV). Due to the different prices
collected by producers, beans was
considered as black beans and color beans, and tobacco was
considered as hangar tobacco
and greenhouse tobacco. For these reasons, the model had 19
variables.
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Table 2 – Variables used in the E-V model
Groups/Subgroups PGV% Groups/Subgroups PGV%
MAIN CULTURES 41.76 Livestock 38.56
Summer Grains Poultry
Soybeans 15.193 Chicken 11.031
Maize 9.676 Other birds 3.894
Bean 3.110 Bovines
Coffee 1.863 Ox/cows 5.079
Other 0.424 Other bovines 3.513
Winter Grains Hog
Wheat 2.101 Breed hog 3.614
Other 0.542 Other hogs 1.143
Other Summer Cultures Commercial Livestock
Sugar-cane 4.883 Milk 4.961
Tobacco 2.282 Chicken Eggs 1.673
Cassava 1.536 Other 0.347
Other products 0.023 Silages 1.47
Seeds and Others 0. 126 Other Groups 1.84
FOREST PRODUCTS 11.95 FRUIT GROWING 2.57
VEGETABLES AND SPICES 4.99 Orange 0.663
Potato 1.693 Grape 0.602
Tomato 0.516 Other 1.305
Other 2.23 FLORICULTURE 0.18
Source: Authors and Andretta (2008)
Notes: The items in bold type represent the cultures chosen in
each production group and used
in the model (the choice was based on the significant
representation within each group);
PGV = Production's Gross Value (PGV).
From 1996 to 2006 there was a great variation in agricultural
production levels in
Paraná concerning the 19 items analyzed by the model. Table 3
shows the production
levels variation of the items during the aforementioned period.
Hog production historical
series was only available from 2002 to 2006, and it was obtained
from EMBRAPA (the
Brazilian Company of Agricultural Research). Chicken, ox/cow,
milk and egg historical
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series were obtained from the ANUALPEC (Brazilian Livestock
Yearbook). The other
item production and planted area historical series were obtained
from the DERAL
(Paraná Rural Economy Department). Production level variability
of some items was
very significant, especially soybean (with increasing production
until 2003), maize (with
production breaks in 2002 and 2005), coffee (breaks in 2001 and
2005), wheat (decreased
production between 1996 and 2000; and growth and decrease until
2006).
Table 3 – Variation of agricultural production levels of Paraná–
1996-2006
Items 1996-
1997
1997-
1998
1998-
1999
1999-
2000
2000-
2001
2001-
2002
2002-
2003
2003-
2004
2004-
2005
2005-
2006
Soybean 2,20 11,11 6,00 -7,12 19,83 10,87 15,19 -7,25 -6,53
-58,66
Maize -2,29 2,36 10,61 -16,06 72,25 -22,32 46,10 -24,08 -21,83
36,84
Black beans -4,53 -0,86 14,35 -7,98 -10,74 35,65 10,58 -4,94
-16,88 34,38
Color beans -1,21 8,20 16,29 -15,64 -1,54 31,76 17,26 -9,14
-16,48 58,86
Coffee 42,86 23,64 4,41 -7,04 -78,79 396,43 -15,83 26,50 -41,89
61,63
Wheat -17,98 -7,37 -4,11 -58,60 207,18 -15,33 100,39 -2,27 -8,10
-57,03
Sugar-cane 4,80 8,46 1,41 -14,17 17,10 3,55 16,36 -0,52 -12,93
21,59
Hangar tobacco 23,81 -23,08 20,00 -6,25 6,67 20,83 22,41 26,76
18,89 1,87
Greenhouse tobacco 22,22 -22,73 17,65 -5,00 10,53 19,05 20,00
26,67 21,05 2,17
Cassava 13,82 10,23 6,32 9,66 -4,37 -4,18 -28,52 19,91 12,73
13,21
Chicken 4,52 17,16 16,61 12,36 18,31 16,37 8,31 12,57 9,96
-0,76
Ox/cow -7,22 1,56 -0,96 0,19 8,88 -10,46 -0,40 3,18 5,78
1,46
Hog -5,32 -9,05 4,84 3,33
Milk 4,36 2,85 6,15 4,29 5,06 5,03 7,86 11,86 5,18 5,80
Eggs -23,92 4,17 8,29 0,16 3,34 7,81 28,64 3,95 -12,19 -2,67
Potato -8,82 -11,03 4,58 5,19 -8,33 10,94 -7,59 -4,76 -8,62
10,38
Tomato -10,00 13,33 2,94 12,38 16,95 15,22 3,14 -1,83 15,53
9,68
Grape -3,13 96,77 4,92 7,81 15,94 -6,25 0,00 29,33 -22,68
-9,33
Orange 44,97 27,31 25,45 5,80 -17,26 31,13 -16,16 19,88 -8,29
12,88
Source: ANUALPEC, DERAL, EMBRAPA
Note: Values expressed in percentages
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20
There are several reasons for production level variability, such
as climatic
variation, including rain lack or excess, technological level
variation, credit availability
and producer debt level, demand and price variation, among
others. Frequently, when
agribusiness production is going through crisis concerning some
cultures there is a great
migration to other more profitable cultures. However,
agricultural product prices reflect
the balance between supply and demand, so a product showing good
profitability in a
certain moment may usually be sub-supplied considering its
potential demand. In this
case, increased supply caused by production migration may
decrease prices and hence be
unfavorable to new producers. In this context, one of the
consequences of variation in
production levels is the gross margin variability, especially
because market supply
variations influence directly the prices paid to producers.
Variations of supply and
demand (in some cases), caused by seasonal or stationary
factors, are of very important to
the analysis of agricultural price behavior (AGRIANUAL, 1998).
The Table 4 shows the
price variation of the items used in the model.
As quoted above in the methodology section, we used linear
programming to
select the optimal combination of productive activities which
maximizes the total
agribusiness gross margin of Paraná. The gross margins were
calculated monthly from
1996 to 2006 as the difference between the price received by
producer and the estimated
production costs. The averages of gross margins were used as
objective-function
coefficients. Maize, wheat, milk and eggs showed negative
average margins. Theses
results of negative margins were likely caused by the high
variation in production levels
of maize and, by the constant growth of production levels of
wheat, milk, and egg, which
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21
caused an increased supply. Concerning wheat, for instance,
although Brazil is not self-
sufficient its excessive production supply usually causes
commercialization problems,
especially because the wheat production in the south area (where
the state of Paraná is
located) is not exported to the rest of the country due to high
logistical costs.
Table 4 - Variation of commodities prices of the study –
1996-2006
Items 1996-
1997
1997-
1998
1998-
1999
1999-
2000
2000-
2001
2001-
2002
2002-
2003
2003-
2004
2004-
2005
2005-
2006
Soybean 6,37 -21,95 4,34 -7,84 8,08 23,14 -2,72 -5,68 -33,51
-8,52
Maize -22,46 10,54 7,27 3,20 -30,99 46,74 -14,73 -9,80 -13,98
-12,61
Black beans 34,76 45,55 -47,88 -36,32 116,16 -10,13 -22,80 -8,76
9,38 -33,02
Color beans -29,76 81,00 -38,95 -26,28 33,19 9,94 -6,90 -27,59
17,59 -17,51
Coffee 39,42 -18,20 -11,13 -16,04 -42,79 -11,89 18,95 11,47
19,59 -4,61
Wheat -25,46 -6,11 12,78 -5,18 2,05 30,86 -8,89 -17,69 -25,69
8,73
Sugar-cane 2,10 -1,46 -20,92 -3,12 15,97 -5,49 -0,39 -8,39 2,64
19,02
Hangar tobacco -19,97 10,48 -19,18 -9,40 8,19 6,99 -3,43 2,27
-10,96 -0,97
Greenhouse tobacco -15,38 8,01 -11,96 -13,24 -4,71 10,34 -0,03
-4,01 -1,82 -2,54
Cassava -5,60 -13,08 23,83 7,53 -49,28 14,96 169,51 12,33 -54,95
-23,89
Chicken -11,07 -3,36 -6,65 -3,85 -4,97 3,49 2,76 -4,28 -11,76
-13,72
Ox/cow 0,33 4,76 6,23 1,44 -6,75 -1,95 -7,68 -5,84 -15,15
-4,16
Hog 20,33 -14,27 1,72 -6,46 -0,28 -16,97 4,14 27,22 -12,14
-32,30
Milk -8,34 -7,96 -6,51 4,19 -18,01 -7,06 4,83 -0,16 -3,75
-8,05
Eggs 10,48 -5,01 -11,24 -2,14 -4,71 1,29 24,31 -15,01 -14,40
-21,87
Potato 5,22 9,70 -43,48 7,21 48,03 -24,87 -11,06 -28,77 60,08
-11,50
Tomato -16,20 14,27 -2,59 -12,43 -12,68 3,41 -13,06 16,31 -3,30
-20,63
Grape -30,55 2,68 -8,27 -26,22 -13,06 7,69 -19,18 -7,81 13,81
14,00
Orange -26,10 17,58 16,51 -11,37 13,15 26,72 -4,79 -20,45 -8,39
20,18
Source: DERAL
Note: Values expressed in percentages
The maximization of the LP model showed results with significant
production
level variations of some items when compared with 2006
production levels. If we
consider a possible level adjustment in production of some
items, the gross margin
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22
potential growth could be around 36%. Considering 2006
production levels, in the
optimized model the items with favorable estimated margin
(positive) showed increased
or stable production limited by the historical maximum area
(farming items) or historic
maximum production. The items with unfavorable estimated margin
(negative) had their
production decreased, limited by historic minimum area
parameters or historical
minimum production.
Figure 2 – Paraná agribusiness efficiency frontier – 2002 to
2006 analysis
20062006-Efficient
Possible maximum
2005
2004
20032002
1.700
1.900
2.100
2.300
2.500
2.700
2.900
3.100
3.300
3.500
2.300 2.800 3.300 3.800 4.300
Gross M
argins (E
)Millions
Total Variance (V)
Trillions
Efficiency Frontier
Source: Authors
Using historical production, the analysis stated the position of
points representing
the 2002 to 2006 production portfolios in the risk-return space,
considering portfolio total
gross margin (E) and total variance (V) for each year. This
allowed comparing the
production position of each year and the possible viable
variations aiming at maximum
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23
efficiency (in terms of market risks measured by the risk-return
relationship). The
analysis showed that 2006 total variance could be considerably
reduced still keeping the
same profitability level (compare the positions of “2006” and
“2006-Efficient” points).
Besides, profitability could also increase significantly with a
similar risk level (compare
the positions of “2006” and “Possible Maximum” points). Except
for 2002 and 2003, the
other years showed similar risk levels, and the 2004 total gross
margin was the highest
recorded. Year 2002 showed the best risk-return relationship,
when compared to the 2006
efficiency frontier. Therefore, in terms of risk-return, 2002
was the year showing the
most efficient production portfolio (compared with the 2006
situation).
Table 5 shows production portfolio of each year analyzed by the
efficiency
frontier and the possible 2006 portfolio variations aiming at
economic efficiency. Except
for milk and eggs using respectively thousands of liters and
dozens as measuring units,
the other items use tons as measuring units. According to model
results if it were possible
to consider efficient portfolio production (column 2006 E), then
the real 2006 production
(column 2006 R) would have a reduction of 37.8% in total
variance (risk) with a similar
total gross margin. On the other hand, with the possible maximum
production estimated
by the linear model (column Max. LP) with a practically stable
risk level (-2.3%), the
2006 total gross margin could reach 36%.
The percentiles of variation indicating necessary changes in the
accomplished
2006 portfolio (2006 R) towards the efficient portfolio (2006
E), indicate a decreased
production for items with large variability in gross margin
and/or low or negative
expected margin, considering the period from 1996 to 2006. As it
was already mentioned,
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24
2004, 2005 and 2006 showed similar risk levels (V), with larger
total gross margin in
2004. It would be necessary to build efficient frontiers for
each year in order to identify
needed changes in 2002-2005 portfolios which could represent a
maximum efficiency in
risk-return.
For the most representative items of the State PGV (soybeans,
chicken and
maize), Paraná cooperatives have, respectively, high, low and
medium degrees of
production absorption from their members. Most items that
according to the model
should vary their production levels in order to improve
risk-return relationship are
significant in cooperative activities. For a scenario of risk
decrease (-37.8% in the
portfolio total variance), keeping the same total gross margin
through production level
changes, as shown in "2006 R" turning into levels indicated in
"2006 E", cooperatives
receive from their members some items which their production
level should have been
reduced, such as soybeans, maize, beans, wheat, cassava and
milk. Among the items
which their production level should have been increased,
cooperatives receive the
production of coffee, hog and potato.
For some items that could improve the risk-return relationship,
there are no
records of production absorption by cooperatives; and among them
we highlight grape
production. For the scenario of total gross margin increase
(+36.3%) keeping almost the
same risk level (decrease of only 2.3% in the portfolio total
variance) through changes in
production levels, indicated in "2006 R" changing to levels
indicated in "Max. LP",
cooperatives receive maize, wheat and milk production
(considering the items that should
have their production reduced in this scenario). Among the items
that should have their
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25
production increased in both scenarios, only bovine and grape
productions are not
absorbed by cooperatives.
Table 5 – Efficient portfolio scenarios and production evolution
analysis
2006 R 2006 E Var. Max. LP Var. 2005 2004 2003 2002
Margins (E) 2422518 2422518 0.0% 3301308 36.3% 2334639 2746372
2568170 2508924
Variance (V) 3895,0 2422.1 -37.8% 3807.1 -2.3% 3802,8 3851.1
4504.2 2592.7
Soybean 9466.4 5593.6 -40.9% 10041.6 6.1% 9552.7 10219.9 11018.7
9565.9
Maize 11697.4 8745.0 -25.2% 8745.0 -25.2% 8548.4 10934.6 14403.5
9857.5
Black beans 344.3 265.6 -22.9% 420.1 22.0% 255.5 307.9 323.7
293.2
Color beans 474.7 321.7 -32.2% 524.1 10.4% 299.1 358.2 394.3
335.9
Coffee 139.4 196.2 40.7% 196.2 40.7% 86.4 148.3 117.3 139.1
Wheat 1204.7 691.8 -42.6% 691.8 -42.6% 2804.2 3051.2 3121.5
1557.5
Sugar-cane 34461.6 34461.6 0.0% 34461.6 0.0% 28342.4 32550.2
32721.4 28120.7
Hangar tobacco 108.9 44.2 -59.4% 108.9 0.0% 107.2 89.7 70.5
57.6
Greenhouse
tobacco 46.7 46.7 0.0% 46.7 0.0% 45.9 38.4 30.2 24.7
Cassava 3789.2 2413.6 -36.3% 4082.7 7.7% 3347.4 2968.8 2476.3
3464.0
Chicken 2081.1 2097.1 0.8% 2097.1 0.8% 2097.1 1907.0 1694.0
1563.9
Ox/cow 557.1 564.4 1.3% 564.4 1.3% 548.6 518.7 503.0 505.1
Hog 403,2 432.0 7.2% 432.0 7.2% 389.6 371.6 408.8 432.0
Milk 2665.4 1514.5 -43.2% 1514.5 -43.2% 2518.9 2394.5 2141.5
1985.3
Eggs 3279.8 2279.7 -30.5% 2279.7 -30.5% 3370.1 3837.7 3692.5
2870.3
Potato 585.3 637.1 8.9% 1010.3 72.6% 530.0 580.4 609.0 659.4
Tomato 204.1 204.1 0.0% 204.1 0.0% 186.3 161.4 164.3 159.5
Grape 67.8 101.5 49.7% 101.5 49.7% 74.9 96.7 74.9 75.1
Orange 411.7 411.7 0.0% 411.7 0.0% 365.2 397.9 332.3 396.3
Source: Authors
Notes: Values in thousand; R = real production; E = efficient
production (potential)
In both scenarios assessed by this analysis, production level
variation (little or
great) would have some impact on cooperatives' activities.
Hence, changes in the trade
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26
commodities portfolio of cooperatives could exert some kind of
influence in the
agribusiness risk-return relationship of Paraná. Considering
that cooperatives might
motivate such changes, they could be able to help their members
in decreasing the
variability of their income, thus decreasing market risks.
However, it is important to highlight that results regarding
necessary variations to
use the 2006 efficient portfolio consider only the economic and
rational approaches due
to application of the Markowitz model (E-V analysis). From other
perspectives, such as
the social or market strategy ones, these variations might be
unfeasible. In cooperative
context, especially in Brazil, economic rationality may conflict
with political and social
rationality (strongly present in the cooperative principles).
Furthermore, great changes in
production preferences of the analysed items could mean great
investments in productive
structure of cooperatives. Although desirable for whoever is
involved in agribusiness
activities, any movement aiming at a decreasing in variability
of agribusiness income
would influence directly rural producer safety, especially
concerning the smaller ones
that are a majority in Brazil.
Influence of cooperatives in market risk management of
agribusiness
A questionnaire was sent to agribusiness cooperatives of Paraná
in order to assess
whether they were willing to foster the changes towards
improving risk-return
relationship proposed by the model. Afterwards, it was made
interviews with managers of
four selected cooperatives. The goal was to understand which
could be the reasons
influencing such cooperatives in not to accept the changes
proposed by the model.
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27
The questionnaire was sent to sixty-five cooperatives included
in the OCEPAR's
(Cooperative Organization of Parana) records. There were a total
of 14 respondents
representing a population sample of 21.5%. According to OCEPAR
data (OCEPAR,
2008) on incomes, the sample stands for 52% of cooperative
revenues in the State.
Moreover, the sample represents 33% of total cooperatives
members of the State. There
is a high absorption of member's production on the sampled
cooperatives part, most of
them absorbing over 70% of such production. The questionnaire
was designed to be
answered mainly by managers, directors, superintendents or
presidents of cooperatives.
Actually, there was a significant participation of these people
who answered the
questionnaire.
The questionnaire included a list of reasons that could
influence the cooperatives
in not to foster or invest in the production of items analyzed
by the proposed economic
efficiency model. The main objective was to assess, from the
viewpoint of particular
characteristics of cooperative principles, whether or not the
cooperatives were willing to
foster changes in agribusiness production portfolio and, the
influences that could affect
their decision-making process. When answering the questionnaire,
the respondents were
asked not to take into consideration questions concerning to
increase or maintenance of
production of items that have already been fostered by the
cooperatives. In addition, they
were asked to consider technical and economic feasibility,
cooperative absorption ability,
and geographic expansion possibility regarding regions that are
not suitable for a
particular culture. The aforementioned hypotheses were set forth
seeking to set apart the
reasons for not fostering production investments, thus guiding
the interviewers to focus
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28
on the listed reasons. They should rate each reason as exerting
high or low influence
over the cooperative decision-making. The reasons and their aims
are shown in Table 6.
Table 6 – Reasons not to invest in the agribusiness items
included in the risk-
return analysis model.
Reasons Aims
1 – Unbalance between
economic and social
objectives of cooperative
Investigating whether cooperative principles (that are reflected
on social
objectives), which normally emphasize differences between
cooperatives and
other commercial organizations, could to some extent influence
decisions
impacting on the diversification level of cooperatives and their
members.
2 – Choices are in opposition
to cooperative principles
Investigating whether there is some evidence that cooperative
principles
might influence decisions on fostering or investment in
diversification.
3 – It would not provide
common welfare
Assessing the items that would not be desirable options when
seeking
diversification. Those items would represent activities that
could arouse
resistance to invest in production on the cooperatives part.
4 – Would not bring
economic progress to
cooperative members
Assessing the agribusiness items that would arouse resistance
from
cooperatives to diversify the portfolio of cooperative member
production.
5 – Incompatibility with the
cooperative strategic focus
Checking the differences between the cooperative strategic
focuses
concerning their willingness to diversify.
6 – Incompatibility with the
cooperative production
history
Assessing whether past production decisions might influence on
present
decisions.
7 – Possible resistance to
changes on cooperative
members part
Assessing whether cooperative members would resist to changes
regarding
diversification proposals including the consequent alterations
of production
preferences.
Source: Authors
Table 7 shows, in a summarized way, the economic efficiency
scenarios generated
through the E-V analysis (presented in Table 4), comprising the
items recommended for
changes in production levels according to objectives shown in
the scenarios. Table 7 also
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29
includes a list of reasons which would strongly influence the
decision not to invest in or
foster the production of those items. In order to decrease the
total variance of the
agricultural production portfolio in the State of Paraná and
maintain the same total gross
margin level (scenario 2006 E), it would be necessary to
increase production of coffee,
poultry, bovine, hog, potato and grape; besides decreasing or
maintaining the production
level of the other items. To maximize the total gross margin and
maintain the same risk
level (scenario Max. PL), it would be necessary to increase
production of soybeans, black
beans, coffee, cassava, poultry, bovine, hog, potato and grape
production; besides
decreasing or maintaining production level of other items.
Table 7 – Strongly influential scenarios and reasons
Items Variation to
2006 E Reasons
Variation to
Máx. PL Reasons
Soybeans -40.9% 6.1% Black beans -22.9% 22.0% 3, 4, 5, 6, 7
Color beans -32.2% 10.4% 3, 4, 5, 6, 7 Coffee 40.7% 5, 6 40.7% 5, 6
Cassava -36.3% 7.7% 1, 2, 5, 6, 7 Poultry 0.8% 5, 6, 7 0.8% 5, 6, 7
Bovines 1.3% 5, 6, 7 1.3% 5, 6, 7 Hogs 7.2% 2, 4, 5, 6, 7 7.2% 2,
4, 5, 6, 7 Potato 8.9% 1, 2, 3, 5, 6, 7 72.6% 1, 2, 3, 5, 6, 7
Grape 49.7% 1, 2, 5, 6, 7 49.7% 1, 2, 5, 6, 7
Source: Authors
Subtitles: 1 – Unbalance between cooperative economic and social
objectives; 2 – Choices are in
opposition to cooperative principles; 3 – It would not provide
common welfare; 4 – Would not
bring economic progress to the cooperative members; 5 –
Incompatibility with the cooperative
strategic focus; 6 – Incompatibility with the cooperative
production history; 7 – Possible
resistance to changes on the cooperative member part.
Among the reasons not to invest in or foster production,
soybeans would be the
least item influenced by them. Reasons 5 and 6 were common to
all items (except
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30
soybeans) in both scenarios. This means that incompatibility
with cooperative strategic
focus and production history would be the reasons mostly
influencing decisions not to
invest in or foster production.
In the scenario of total variation reduction with the same level
of total gross
margin (scenario 2006 E), the most mentioned reasons besides 5
and 6, were reasons 2
and 7. In this case, unbalance between economic and social
objectives of cooperatives,
and possible resistance to changes on the part of cooperative
members might be the most
influential reasons in not to invest in or foster bovine, hog,
potato and grape production.
In such scenario, coffee and grape, that would have the greatest
changes in production
levels, the common reasons in not to invest in or foster
production are related to
incompatibility with strategic focus (reason 5) and production
history of cooperatives
(reason 6).
Concerning the total gross margin maximization with a little
change in portfolio
total variance (scenario Max. PL), black beans, coffee, potato
and grapes should be the
items with more changes in their production levels. The reasons
1 and 2, which are
related to important characteristics that could differ
cooperatives from other
organizations, might influence decisions not to invest in or
foster production of cassava,
hog, potato and grape production. This scenario analysis
highlights the indication of
reason 7 to almost all items. Hence, concerning almost all items
that could improve the
risk-return relationship thus maximizing the total gross margin
at the same risk level
through increasing production level, the resistance of
cooperative members could make
that scenario be unfeasible.
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31
Concerning all the listed items, we found evidence showing not
to invest in or
foster production each item was influenced by at least one of
the reasons. The most
frequently reasons mentioned were incompatibility with strategic
focus of cooperatives
and lack of providing opportunities for economic progress to
cooperatives members.
Nevertheless, each listed reason would exert different degrees
of influence on the items.
The reasons which most influenced the items were incompatibility
with strategic focus of
cooperatives (reason 5) and with the cooperative's historic
production (reason 6), and
possible resistance to changes on cooperative members part
(reason 7). The other reasons
showed low degree of influence.
Furthermore, as mentioned above, semi-structured interviews with
managers of
four agro-industrial cooperatives in the State of Paraná were
made in order to analyze
how cooperatives deal with market risks, as well as managers'
opinion regarding the
efficient portfolio scenarios developed by the study. Table 8
shows the characteristics of
the interviewed cooperatives. The interview comprised questions
about practices on
market risk management in cooperatives, general perception of
the proposed two efficient
portfolio scenarios developed through the E-V analysis and
possible reasons that could
influence the decision not to invest in or foster production,
mainly emphasizing the
commodities assessed by the model. The answers permit to assess
to what extent
cooperatives are willing to foster diversification and the
reasons which could mostly
influence the unfeasibility of this practice.
Our investigation started by openly asking the interviewed to
point out general
reasons that could influence the decision not to invest in or
foster production of the model
-
32
items. Most of the answers pointed out the technical
restrictions as main reason. No
answer mentioned possible inconsistence between economic and
social objectives of
cooperatives. All the respondents emphasized that if there is
technical and economic
feasibility, there is no production restriction regarding items
able to bring about economic
progress to cooperative and its members.
Table 8 – Characteristics of the interviewed cooperatives
Coop. Income in 2007
(R$ mil)
Commodities
included in the
model portfolio
Respondent(s) function(s) Academic degree
1 3,466,242.72 Soybeans, maize, coffee e wheat
Internal Coop. Auditor Administration
Internal Coop. Auditor Advisor
Administration and accounting
2 1,015,569.11 Soybeans, maize, Coffee, wheat and orange
Commercial superintendent
Administration
3 590.,440.50 Soybeans, maize, Black beans, wheat, hog and
milk
General manager Agronomist
4 206.000,00 Soybeans, maize, Black beans, wheat and bovine
Financial director Agronomist
Source: Authors
Afterwards, the same group of reasons mentioned on Table 6 was
shown to the
interviewed, aiming at investigating the possible influence of
items not related to
technical feasibility, but concerning particular organizational
characteristics of
cooperatives and their economic and social objectives. The
question asked to analyze the
reasons was the following: “Is there any agribusiness item which
the cooperative is not
willing to invest in or foster production, due to the following
reasons?”
The aforementioned part of the interview allowed us a detailed
analysis of the
reasons that could influence diversification decisions. The
analysis results showed that
-
33
the main reasons for the possible failure of proposals aiming at
increasing diversification
(as the main management answer to market risks) are related to:
technical and economic
feasibility, historical of cooperatives' production and possible
resistance to changes on the
part of cooperative members. The aforementioned results are
compatible with the
questionnaire results. According to the respondents some
remarkable aspects of the
cooperatives principles, such as social commitment and
objectives, would not influence
significantly the diversification decisions.
Such conclusion reinforces another research on Paraná State
cooperatives which
through interviews with cooperative members concluded that
economic and commercial
aspects are the main reasons for rural producers to join a
cooperative and remain there as
a member. In other words, independently of cooperative
principles, cooperatives
prioritize the needs of their members, and those members
prioritize their revenue
maintenance and expansion rather than social development (SILVA;
SALANEK FILHO,
2009). These considerations reinforce the path dependence among
cooperatives and
members, especially related to economic rather than social
aspects.
Conclusions
This paper shows an analysis of production portfolio of
agribusiness commodities
in the State of Paraná, some choices to improve its risk-return
relationship and the
possible influences of agricultural cooperatives in such
context. Through a risk-return
analysis carried out according to the Markowitz E-V model, we
could outline an
efficiency frontier that allowed us to develop two scenarios of
efficient portfolios. In one
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34
scenario would be possible to decrease the total variance (proxy
for market risks) of the
2006 portfolio. In another one, it would be possible to increase
the total gross margin of
the portfolio with an almost same risk level.
Considering the rural producer characteristic of avoiding risks
and the economic
principles of financial value generation, it is possible to
consider two basic strategies to
increase the agribusiness activity value: increasing investment
return expectations; and,
decreasing such expectation variations (risk). Nevertheless, the
aforementioned strategies
frequently are not trivial activities. As showed in this paper,
to risky activities or with low
attractiveness gross margin it would be necessary great changes
in production levels in
order to decrease the portfolio's overall risk. Yet, according
to cooperative managers such
changes could be unfeasible due to the strategic focus of
cooperatives and to the high
degree of resistance to changes on the part of members
(inertia).
In summary, through analyzing questionnaires and interviews we
inferred that the
main reasons for the possible unfeasibility of change proposals
in the portfolio aiming at
economic efficiency in terms of risk-return are related to the
strategic focus of
cooperatives and to the cooperative members’ resistance. Reasons
related to cooperative
principles and their economic and social objectives, which
effectively make cooperatives
be different from other kind of companies, apparently do not
exert much influence. This
fact shows that cooperatives have a more rational behavior when
making a decision
rather than being influenced by cooperative principles. Thus, we
can infer that
organizational specificities of cooperatives, represented by
economic and social
principles or objectives, would not exert much influence on
managerial responses
-
35
towards diversification as a way to improve risk-return
relationship. Hence, it is possible
to infer that possible influences of cooperative principles on
market risk management
through diversification would be insignificant in the Paraná
cooperative context. The
possible tension between political and economic rationality is
not so important and does
not have great influence on cooperative management, at least in
Paraná.
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