AN ANALYSIS ON AGRICULTURAL INCOME EXPECTATIONS
MLR. Arranz, J.J. Garcillan, M.P. Pérez and M.D. Soto
Facultad de Ciencias Econémicas y Empresariales (Universidad de Valladolid)
Avda. Valle Esgueva, 6, 47011 Valladolid, SPAIN
Phone: 83 - 42 33 28. Fax: 83 - 42 32 99. E-mail: juanjo@esgueva.eco.uva.es
INTRODUCTION
The world production of barley is ranked in fourth place in agricultural productions, after wheat, corn and rice. Itis
primarily used for feeding animals and for the production of beer. Europe and North America are the biggest
producers in the world, while Spain is the EU country with the largest surface devoted to this cultivation. The
Spanish region of Castilla-Ledn is the one that obtains the highest production. The agricultural sector in this region
employs 16% of the active population and contributes with 12% to its GNP (gross national product)and thus to the
importance of an analysis on the viability of its exploitation.
The objective of this work is to build up a dynamic system model of a representative exploitation in the agricultural
sector from a specific area in the autonomic community of Castilla-Le6n, in order to be able to evaluate whether
C.A.P. (common agricultural policy) rent perception objectives are being fulfilled. Initially we suppose that the owner
of the exploitation has a quantity of land of a certain quality, fully devoted to barley cultivation in dry land, machinery
differentiated by time of usage and purpose, a certain liquidity to meet the expected costs during a period of time that
concludes with new income contributions and lacks financial costs. Further, we consider that the exploitation policy
is to buy seed for the sowing and sell to the product to market price after the harvest and insure its expected harvest
yield. The sowing is planned to be carried out at two different moments; thus, if the weather conditions are good, half
of the land is sowed in the autumn and the rest always in winter. The work factor is contributed by a single qualified
person, except the harvest of the grain which is performed by three persons.
In the causal diagram we distinguish between four subdiagrams that correspond to differentiated processes for the
farmer's rent attainment: production attainment, cost formation, income formation and decision evaluation subsystem
as a function of results.
PRODUCTION
The development of the barley plant is the result of sequential and dependent biological processes that take place
during a period of time between October and July the following year. They start with the sowing and end with the
harvest. Though it is possible to consider different stages (Molina Cano, J.L. 1989), we group them into five: seed
sowing, stalk formation, stalk growth, ear formation and finally ripening and harvest. The result of each one of these
sequential processes may be altered by the behaviour of two external random variables: rain and temperature,
which we group in the causal diagram under "climatological conditions". In statistical terms, it may rain between 200
\/m? in dry years and 450 I/m? in wet years in the selected area. The temperatures vary according to the month of the
year, but the association of water-temperature turns out to be essential to the success of the cultivation. Under the
denomination "catastrophe" we also include the possibility of meteorological situations, not frequent but possible,
that may hinder one of the processes, and thus the subsequent ones, from finishing. These events of almost entire
harvest loss occur on some occasions, latest in 1995. Figure 1 contains the causal diagram of the expected autumn
sowing production. Winter sowing can be considered analogous.
Figure 1
Teniger
humidity temperature at seed
he csadidiomy
|
\ vf poy
eeu
climatological
‘conditions|
expected
sucker ame
Broduction “real production
cimacioges
condtions 2 OM climatclogiol &
ee ‘condos al
r* “s oath: ‘exploitation
ruasents can
ot
selon ais
‘conditions ripening and
climatological “he harvest
conditions 4
In the causal diagram a variable is associated with each result of the biological process that gathers production
expectations as a function of the biological result. These expectations may be modified as a function of the results of
the subsequent processes, which is a common characteristic in cereal development. In the variable technology we
include other elements like machinery used, seed quality and nutrients added to the soil before and after the sowing,
which also affects the result of the production. The contribution of these factors to the result is not statistically proved,
thus we will base our modelisation of the system on expert opinions.
COST FORMATION
All inputs necessary to obtain the production have an associated cost. Discarding the land redemption cost, we have
machinery redemption costs, maintenance, repairs and energy costs and costs of seeds and nutrients used during
the growth and maturing process of the plant. When the grain is harvested we also have a cost associated with the
harvest and finally we have the cost of the agrarian insurance. Furthermore, we will have to consider financial costs
when the farmer decides to turn to the financial market in search of capital. It can be observed that all costs, except
financial ones, are a function of the extension of the cultivated exploitation. Figure 2 contains the causal diagram of
the annual costs associated to the exploitation.
Figure 2
mien
way Tas quay ination
rutterts seed price < \ we
ee
mane Y
inahtics
cauipaxS voros cons ae _—
pre Hlerslenaot as
vas
financial costs a
Sp areas
INCOME FORMATION
Income is obtained by the farmer of the exploitation by means of the subsidies from the C.A.P. and sales of the
production obtained. The subsidies from the EU are determined according to the quantity of exploited land and the
area where the cultivation is carried out. If we suppose that the farmer has 40 hectares (Ha.) in the area of study, and
therefore, is not obliged to withdraw 15% of the surface from cultivation, the EU assigns him an average production
of 2,2 Tm/Ha. and a subsidy of 15.294 ptas. per Ha. during the period of 1995-96. Although the future evolution of
these aids is still to be determined, it seems evident that they represent an important percentage of the farmer's rent.
In order to be able to know the income per production it is necessary to determine the price of barley. This price can
change from day to day but the variations experienced in one year are within limits that do not noticeably affect the
rent of the farmer under study (variations have reached 0,5 ptas. in the current year). However, world, communitarian
and, especially, national production do influence the so-called seasonal price. Figure 3 represents the relationship
between the variables that determine the income. The possibility of a catastrophe is included in the diagram. In such
acase, there would not be any production and consequently, no sale, so the income would be obtained from
agrarian insurance and communitarian aids.
Figure 3
real production exploitation
Bey Fi a extension
production
erage yield
4 proton emi vi
income through
batey price ———¥F_income ~y en ge
pepe ta
; total income
international ang catastrophe
reduction u_ tat
FORMATION OF DECISIONS
Profits are determined by income minus costs, ie if we deduct taxes we get the farmer's rent. Now itis possible to
compare the result with the average rent obtained by other sectors located in the same area and obtain conclusions
about the objectives pursued by communitarian aids. If the comparison between rents is acceptable, the farmer may
decide to stay in the sector. Age plays an important role in this decision. If the farmer has a rent surplus and
expectations of future rent, he may opt for either improving the technology used in the productive process or
increasing the quantity of land. Note that the value of land has increased because C.A.P. subsidies are guarantied.
In any case, the possibility of the farmer turning to the financial market, in order to obtain capital for investments,has
also to be considered.
Figure 4
total income total costs farmer's age ‘exploitation technology
extension
profit before tax ‘sector withdrawal
rr a
genet prose > en Se rent margin ‘accumulation
ther sector's fj rent A YS ‘
rt ‘threshold sare
the sector
Figure 4 contains the possible decisions that the farmer may make after a productive period and it closes the
feedback loop of the dynamic system.
REFERENCES
Melero, R., Machuca, A.D. 1995. A model for learning about the agricultural business system. Proceedings of the
1995 International System Dynamics Conference. Tokyo: T. Shimada and K. Saeed.
Molina Cano, J.L. 1989. La cebada. Morfologia, fisiologia, genética, agronomia y usos industriales. Madrid: Mundi-
Prensa.
Tiffin, R., Renwick, A. 1996. Estimates of Production Response in the UK Cereal Sector Using Nonparametric
Methods. European Review of Agricultural Economics 23 (2): 179-94
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