The objective of this paper is to analyse farm strategies and investment behaviour in a sample of
selected Italian farm-households facing different scenarios, with a particular focus on the effects of
the 2003 CAP reform. Models were built for individual households using multi-criteria dynamic
programming, including investment choice. A total of 24 farms were selected for modelling, all
located in Emilia Romagna (Italy). The simulations show a strong effect of both policy and markets
scenarios on household investment, though the latter seems more relevant than the former. However,
decoupling itself shows minor effects in the majority of cases. The models offer useful insights about
the mechanisms of adaptation and their implications for the effects of policies. The main drawbacks
are in the heavy data collection and computational requirements, and in the related difficulties to
achieve a satisfactory degree of representativeness.JRC.J.5-Agriculture and Life Sciences in the Econom

GALLERANI Vittorio

GOMEZ Y PALOMA Sergio

RAGGI Meri

VIAGGI Davide

The objective of this paper is to analyse farm strategies and investment behaviour in a sample of
selected Italian farm-households facing different scenarios, with a particular focus on the effects of
the 2003 CAP reform. Models were built for individual households using multi-criteria dynamic
programming, including investment choice. A total of 24 farms were selected for modelling, all
located in Emilia Romagna (Italy). The simulations show a strong effect of both policy and markets
scenarios on household investment, though the latter seems more relevant than the former. However,
decoupling itself shows minor effects in the majority of cases. The models offer useful insights about
the mechanisms of adaptation and their implications for the effects of policies. The main drawbacks
are in the heavy data collection and computational requirements, and in the related difficulties to
achieve a satisfactory degree of representativeness

GALLERANI, VITTORIO ALESSANDRO

RAGGI, MERI

VIAGGI, DAVIDE

Gomez y. Paloma S.

Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna

Modelling the effect of EU policy reforms on farm investment behaviour

JRC Publications Repository

 1
 
 
 
 
 
 
 
 
 
 
MODELLING THE EFFECT OF EU POLICY REFORMS ON FARM 
INVESTMENT BEHAVIOUR 
 
 
 
V. Gallerani1 - S. Gomez y Paloma2- M. Raggi1 – D. Viaggi1 
 
1 University of Bologna 
2 IPTS – JRC Seville 
Contact:  davide.viaggi@unibo.it, tel +39 051 2096114, fax +39 051 2096105 
 
 
 
 
 
 
 
 
 
 
          
 
              
 
Paper prepared for poster presentation at the 107th EAAE Seminar "Modelling of 
Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 
2008 
 
 
 
 
 
 
 
Copyright 2007 by [V. Gallerani, S. Gomez y Paloma, M. Raggi and D. Viaggi]. All rights reserved. Readers 
may make verbatim copies of this document for non-commercial purposes by any means, provided that this 
copyright notice appears on all such copies. 
 2
Abstract  
  
The objective of this paper is to analyse farm strategies and investment behaviour in a sample of 
selected Italian farm-households facing different scenarios, with a particular focus on the effects of 
the 2003 CAP reform. Models were built for individual households using multi-criteria dynamic 
programming, including investment choice. A total of 24 farms were selected for modelling, all 
located in Emilia Romagna (Italy). The simulations show a strong effect of both policy and markets 
scenarios on household investment, though the latter seems more relevant than the former. However, 
decoupling itself shows minor effects in the majority of cases. The models offer useful insights about 
the mechanisms of adaptation and their implications for the effects of policies. The main drawbacks 
are in the heavy data collection and computational requirements, and in the related difficulties to 
achieve a satisfactory degree of representativeness. 
  
Key words: CAP reform, decoupling, investment, multicriteria, dynamic, models 
 
 
1. Background and objectives  
  
Decoupling of direct payments from production, started in 2003, set a major step in the reform of the 
Common Agricultural Policy (CAP). In the past years a number of studies have addressed the issue of 
the impact of EU policy reforms. These studies concern different territorial levels and in many cases 
focus on the effects of reforms on the market of agricultural products. On the contrary, long term 
effects of policy changes and related impacts on structural and investment behaviour received 
relatively little attention in modelling exercises concerning CAP reform up to now. 
 
The objective of this paper is to analyse farm strategies and investment behaviour in a sample of 
selected Italian farm-households facing different scenarios (with a particular focus on the effects of 
CAP). 
 
The simulations are performed using individual household multi-criteria dynamic programming 
models, including investment choice. Simulations are performed for sample of 24 farms located in 
Emilia Romagna (Italy). 
 
The remainder of the paper is organised as follows. Section 2 illustrates the methodology adopted in 
this paper. Section 3 illustrates the empirical application to case studies in Italy. Section 4 reports the 
results, while section 5 provides a discussion. 
 
 
2. Metodology 
 
The approach used in this paper is to model individual households using multi-criteria dynamic 
programming, including investment choice. The models are then used simulate the effects of scenarios 
on investment behaviour. 
 
 3
The reference investment framework for our approach is provided by Gardebroeck and Oude Lansik 
(2004) who develop a comprehensive theoretical model of farm investment, building on the main 
literature concerning investments. One way of implementing such model in a computationally 
tractable way is to adopt dynamic mathematical programming (see e.g., Asseldonk et al., 1999). The 
main drawbacks of such models are in the simplification of the behavioural assumptions, which are 
based on profit maximisation, and in the fact that it assumes the farm as an independent entity. In 
order to deal with at least the first of these problems, Wallace and Moss (2002) propose a multi-
criteria approach and apply it to strategic decisions from the viewpoint of the farm household. 
 
The model used in this paper is the result of the integration of the previous works. It can be generally 
represented as follows: 
 
( ) ( ) ( ) ( ) ( )[ ]xzxzxzxzFxZ Qq ..,,..., 21=         (1) 
s.t. 
Xx∈             (2) 
0≥x             (3) 
 
where: 
Z  = objective function; 
qz  = value of attribute/objective q; 
X  = feasible set; 
x  = vector of decision variables; 
 
The detailed specification is not reported here, but is available in Gallerani et al. (forthcoming). The 
decision variables include allocation of labour (on- and off-farm), allocation of capital (on- and off 
farm), investment and disinvestment decisions, crop mix. The model runs on a 25-years period (2006-
2030). The objective variables are an aggregation of performances over time. They include Household 
worth, Household consumption, Household debt/asset ratio, Diversification in household activities, 
Income certainty, Leisure time. 
 
The simulation has been run under six scenarios (Table 1). 
 
Table 1 – Main characteristics of the scenarios 
Scenario
Payment 2006-
2013
Payment 2014-
2021
Effect financial 
discipline
Prices 2006-
2013
1 Area based = 2006-2013 -10% =
2.1 Decoupled = 2006-2013 -10% =
2.2 Decoupled = 2006-2013 -10% -20%
3.1 Decoupled 0 -10% =
3.2 Decoupled
Linear reduction 
to 0 -10% =
3.3 Decoupled
Linear reduction 
to 0 -10% -20%  
 
Scenario 1 is used as the baseline against which changes are assessed. Scenarios 2 provide a 
decoupling situation with continuation of payments beyond 2013 and with present prices of 
 4
agricultural products (Scenario 2.1) or with a reduction of prices by 20% (Scenario 2.2.). Scenario 3 
assumes changes in payments beyond 2013, with total abolishment (Scenario 3.1) or a progressive 
reduction. The case of progressive reduction is represented with present prices (Scenario 3.2) or with a 
reduction of prices by 20% (Scenario 3.3). 
 
 
3. Case studies and empirical application 
 
The case study concerns the modelling of a sample of real farms located in Emilia Romagna (Northern 
Italy). Farmers’ sample was selected in order to fit in the intersection of the following categories: 
different altitudes (plain/mountain); different specialisation (arable crops, livestock, trees), different 
technology (conventional, organic). The survey included information about farm and household 
structure, expectations, reaction to planned and intended investment, as well as about potential reforms 
such as decoupling of EU payments. A total of 24 farms were selected for modelling. Their 
characteristics are summarised in Table 2. 
 
Table 2 – Main characteristics of the farms modelled 
H
ou
se
ho
ld
 
C
O
D
E
Le
ga
l S
ta
tu
s 
(1
)
N
. h
ou
se
ho
ld
 
m
em
be
rs
A
ge
 fa
rm
er
U
se
 e
xt
er
na
l 
la
bo
ur
M
em
be
rs
 
w
or
ki
ng
 o
ff 
fa
rm
H
ou
sh
ol
d 
de
bt
/a
ss
et
 ra
tio
La
nd
 o
w
ne
d 
(h
a)
La
nd
 re
nt
ed
 in
 
(h
a)
La
nd
 re
nt
ed
 o
ut
 
(h
a)
Te
ch
no
lo
gy
SF
P 
(e
ur
o)
SF
P/
in
co
m
e 
ra
tio
N
um
be
r o
f r
ig
ht
s 
(h
a)
ITMCA09 LC 4 76 no yes 35% 34 0 0 C 1050 6% 5
ITMCA16 LC 6 60 yes yes 0% 17 60 0 C 7000 20
ITMCA21 LC 4 76 no yes 10% 41 0 0 C 5000 7% 22
ITMEA54 FR 4 39 no yes 0% 25 25 0 O 4000 20
ITMEA57 FR 4 60 no yes 0% 70 35 0 O 9000 9
ITMEA63 LC 2 56 no no 0% 11 33 0 O 900 6% 2
ITMCL76 LC 6 42 no no 30% 11.93 85 0 C 15500 39
ITMCL77 FR 4 64 no no 2% 11.34 34.03 0 C 11000 19% 27
ITMCL79 FR 6 34 no yes 0% 7.65 7.15 0 C 6722 16% 17
ITMEL46 LC 5 59 no no 0% 22 26 0 O 2000 4
ITMEL61 LC 4 64 no no 0% 150 7 0 O 14000 47% 157
ITPCA15 FR 3 44 yes yes 10% 17 106 0 C 17000 57% 33
ITPCA19 FR 5 45 yes yes 3% 65 45 0 C 28500 29% 101
ITPCA23 FR 3 47 no no 17% 0 24 0 C 11500 36% 40
ITPCA27 FR 2 61 yes yes 1% 324 0 0 C 58000 176
ITPEA51 FR 2 50 no no 0% 7 2.9 0 O 1500 3% 9
ITPEA66 FR 3 48 no yes 0% 5 0 O 500 2% 5
ITPCL08 FR 3 63 yes yes 0% 17.4 7 0 C 12000 15% 11
ITPCL78 LC 3 55 no yes 2% 45.37 11.34 0 C 32500 68% 81
ITPCL80 LC 4 55 no no 8% 5.7 46 0 C 0 0% 0
ITPEL59 FR 4 39 yes no 0% 140 110 0 O 10000 25
(1) LC = Limited company; FR = Family run
(2) C = Conventional; O = Organic
Pl
ai
n 
Li
ve
st
oc
k
M
ou
nt
ai
n 
A
ra
bl
e
M
ou
nt
ai
n 
Li
ve
st
oc
k
Pl
ai
n 
Ar
ab
le
 
 
The structure of the sample was chosen in order to represent the complexity of farming systems in the 
area, characterised by a strong heterogeneity of specialisation, structure and connection with non-
farming activities. Tree crops are not considered here as they are only moderately affected by EU 
payments. 
 
 5
Models were calibrated using mostly primary household/farm information collected during the survey. 
The use of secondary data was restricted to the market values of farm assets, mostly not known to the 
farm, and the calculation of revenues from single crops. For the latter purpose, regional FADN 
information was used. The data collection was conducted in 2006 and information was referred to the 
most recent year available. 
 
 
4. Results 
 
The results are illustrated grouping farms according to the four main farming systems identified: 
Mountain Arable, Mountain Livestock, Plain Arable, Plain Livestock. Results are expressed for 
scenarios 2.1 to 3.3. as percent change with respect to Scenario 1. 
 
In the case of mountain arable farms, investment tended to show little reaction to decoupling (scenario 
2.1), but reacted sharply to price changes (scenario 2.2) and, to a lesser extent, to payment cuts 
(scenarios 3.1, 3.2 and 3.3). The reaction tended to be more often characterised by an increase in 
investment in the first period and by a decrease (in some cases a total halt) in investment in the second 
period (Table 3). 
 
Table 3 – Impact of the scenarios on investment - Italy – Mountain - Arable 
2.1 2.2 3.1 3.2 3.3
ITMCA9 0% 0% 0% 0% 0%
ITMCA16 0% 17% 10% 2% 17%
ITMCA21 0% 0% 0% 0% 0%
ITMEA54 0% 751% 0% 0% 2269%
ITMEA57 0% 26% 10% 10% 26%
ITMEA63 0% 0% 0% 0% 0%
ITMCA9 0% 0% 0% 0% 0%
ITMCA16 0% -118% -44% -89% -53%
ITMCA21 0% -101% 0% 0% 0%
ITMEA54 0% -100% 0% 0% -100%
ITMEA57 -1% -100% -100% -100% -99%
ITMEA63 0% 0% 0% 0% 0%
2006-2013
2006-2013
 
 
Livestock farms tended to have a sharper reaction to decoupling and to have a generally more 
homogeneous patter of reaction to the other scenarios, though impacts on investment still tended to 
reflect a variety of strategies (Table 4). 
 6
 
Table 4 – Impact of the scenarios on investment1 - Italy – Mountain - Livestock 
2.1 2.2 3.1 3.2 3.3
2006-2013 IT M C L 67 -41% -307% -41% -41% -331%
IT M C L 76 -25% 17% -5% -25% -24%
IT M C L 79 0% 0% 0% 0% 0%
IT M E L 46 0% -295% -181% -181% -314%
IT M E L 61 0% 0% 0% 0% 0%
2014-2021 IT M C L 67 -39% -100% -39% -39% -100%
IT M C L 76 -4% 0% -1% -2% -3%
IT M C L 79 0% 0% 0% 0% 0%
IT M E L 46 0% -100% -100% -100% -100%
IT M E L 61 0% 1% 0% 0% 0%  
 
In this case, however, the effect of investment is negative whatever the scenario. 
 
As a reaction to decoupling, investment in plain, arable crop farms tended to either decrease or stay 
stable, with one exception (Table 5). 
 
Table 5 – Impact of the scenarios on investment - Italy – Plain - Arable 
2.1 2.2 3.1 3.2 3.3
ITPCA15 0% 2% 0% 0% 1154%
ITPCA19 -127% -127% -127% -127% -127%
ITPCA23 0% -2% -4% -120% 0%
ITPCA27 -3533% -4423% -15191% -3675% -15237%
ITPEA51 0% 0% 0% 0% 0%
ITPEA66 0% 0% 0% 0% 0%
ITPCA15 0% -15% 0% 0% -114%
ITPCA19 -40% -40% -40% -40% -40%
ITPCA23 96% 38% 93% 66% 42%
ITPCA27 -112% 28% -114% -119% -100%
ITPEA51 0% 0% 0% 0% 0%
ITPEA66 - - - - -
2006-2013
2006-2013
 
 
Farms reacted either immediately or in the second period. Price decreases tended to cause a drop in 
investments in the second period, though at least one farm reacted with a temporary increase in 
investment in the first period (scenario 2.2). Payment cuts also caused a reduction in investment, 
though this was far less relevant than price reduction (scenarios 3.1, 3.2 and 3.3). 
 
In plain livestock farms, investments tended to stay steady with decoupling, while an increase seemed 
to prevail with price reductions, at least in the first period (Table 6). 
                                                 
1 Investments were already negative in the baseline scenario in the farm ITML76 
 
 7
 
Table 6 – Impact of the scenarios on investment - Italy – Plain - Livestock 
2.1 2.2 3.1 3.2 3.3
2006-2013 IT P C L 08 0% 5% 0% 0% 2%
IT P C L 78 0% 113% 22% 0% 137%
IT P C L 80 0% 3% 0% 0% -141%
IT P E L 59 3% -49% 7% 10% -54%
2014-2021 IT P C L 08 0% -23% 0% 1% -41%
IT P C L 78 0% 8% 2% 1% -14%
IT P C L 80 0% 0% 0% 0% -100%
IT P E L 59 -1% -22% -4% -3% -32%  
 
A reduction in payments causes partly the same reaction in the first period, and, in some farms, also in 
the second. Such investments have mostly to be interpreted as the need to adapt capital stock as a 
consequence of changing incentives.  
 
 
5. Discussion 
 
The simulations show a strong effect of both policy and markets scenarios on investment, though the 
latter seems more relevant than the former. Decoupling itself shows negligible or no effect in the 
majority of cases, while only 4 farms out of 24 (16%) show important reactions in terms of 
investment, mostly with a reduction. Effects are rather diversified among the various farm 
specialisations and the single farms. 
 
The model offer useful insights about the mechanisms of adaptation and their implications for the 
effects of policies. Taking into account of the whole household decision problems, it allows 
considering trade offs between on-farm and off-farm use of resources (labour, capital). It also allows 
including land buying/selling and investment path given the initial resource endowment. The use of a 
dynamic perspective allows identifying adaptation paths, anticipation and long term effects of policy 
decisions. The main drawbacks are in the heavy data collection and computational requirements, and 
in the difficulties to achieve a satisfactory degree of representativeness. 
 
Acknowledgements 
The research reported in this paper was carried out within the study on “Investment behaviour in 
conventional and emerging farming systems under different policy scenarios” coordinated by the 
IPTS, Seville. The authors would like to acknowledge Daniel Deybe (European Commission DG 
RTD) and Wolfgang Munch (European Commission DG AGRI) for having taken part in intensive and 
frequent discussions on the methodological approach, as well as on the findings, interpretations, and 
conclusions. However, the views expressed in this paper are entirely those of the authors, and do not 
necessarily reflect those of the institutions for which they work. 
 
References 
Asseldonk, (van) M.A.P.M., Huirne, R.B.M., Dijkhuizen, A.A. and Beulens, A.J.M. (1999). Dynamic 
programming to determine optimum investments in information technology on dairy farms, 
Agricultural Systems, 62: 17-28. 
 8
Gallerani V., Gomez y Paloma S., Raggi M., Viaggi D. Investment behaviour in conventional and 
emerging farming systems under different policy scenarios, Technical report, IPTS, Seville 
(forthcoming). 
Gardebroek, C. and Oude, Lansink, A. G. J. M. (2004). Farm-specific Adjustment Costs in Dutch Pig 
Farming, Journal of Agricultural Economics, 55 (1): 3-24. 
Wallace, M. T. and Moss, J. E. (2002). Farmer Decision-Making with Conflicting Goals: A Recursive 
Strategic Programming Analysis, Journal of Agricultural Economics, 53 (1): 82-100. 
 
 
 


Modelling the Effect of EU Policy Reforms on Farm Investment Behaviour

http://ageconsearch.umn.edu/bitstream/6444/2/pp08ga19.pdf

Modelling the Effect of EU Policy Reforms on Farm Investment Behaviour

Abstract

Similar works

Full text

Available Versions

Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna

JRC Publications Repository