=Paper=
{{Paper
|id=Vol-3293/paper66
|storemode=property
|title=A Methodological Approach for Estimating the Costs and Benefits of Climate Adaptation Measures
|pdfUrl=https://ceur-ws.org/Vol-3293/paper66.pdf
|volume=Vol-3293
|authors=Sabrina Giuca,Marco Gaito,Antonella Di Fonzo,Simonetta De Leo,Guido Bonati
|dblpUrl=https://dblp.org/rec/conf/haicta/GiucaGFLB22
}}
==A Methodological Approach for Estimating the Costs and Benefits of Climate Adaptation Measures==
https://ceur-ws.org/Vol-3293/paper66.pdf
A Methodological Approach for Estimating the Costs and
Benefits of Climate Adaptation Measures
Sabrina Giuca 1, Marco Gaito 1, Antonella Di Fonzo 1, Simonetta De Leo 1 and Guido Bonati 1
1
Council of Research in Agriculture and Analysis of Agricultural Economics-Research Centre for Agricultural
Policies and Bio-economy, Via Barberini, 36, 00187 Rome, Italy
Abstract
This paper investigates on the effectiveness of climate adaptation measures in countering
climate risk damage. Our paper provides a-depth costs and benefits assessment associated with
the adoption of the climate adaptation measures in Italian farms. Concerns about global
warming are currently attracting interest of global policy makers and the issue is central to the
political and scientific debate. This paper use methodology that will be implemented in LIFE
project "ADapation in Agriculture"- ADA which aims to help improve adaptation to climate
change and promote sustainable and inclusive growth in the agricultural sector. In this context,
we provide a methodology framework for costs and benefits assessment of adaptation measures
to climate change and their economic and environmental effects at the farm-level in Italy to
improve farmers ability to face current and future climate risks. We provide an exemplary
estimation model based on entity of damage avoided - deriving by adverse climatic events with
the climate adaptation measures adoption. The results provide a methodology to represent costs
and benefits associated with the reduction of the climatic risk that countering the adaptation
measure. The use methodology approach could be to support farmers in choosing to adoption
of appropriate climate adaptation measures. This framework is a prerequisite for identifying
the specific support interventions for adaptation measures, mainly deriving from rural
development measures to which farmers will be able to access. Our challenge is to outline
specific measures for the agricultural sector, to counteract impacts of climate change also at
local level.
Keywords 1
Climate change, adaptation measures, costs/benefits assessment
1. Introduction
The overall aim of this paper is to investigate on the effectiveness of Climate Adaptation Measures
(CAM) (EU COM 2021/82; Reg. CE 2021/1119) in countering climate risk damage. Our paper provides
a-depth costs and benefits assessment associated with the adoption of the CAM in Italian farms.
Concerns about global warming are currently attracting interest of global policy makers and the issue
is central to the political and scientific debate. According to a Eurobarometer survey of 2021, after
diseases, the economy and world hunger, the climate is considered the fourth emergency in Italy.
However, in Italy, eight out of ten people consider climate change a "very serious" problem (84%,
higher than the EU average of 78%) and more than six out of ten respondents (63%, equal to the EU
average) consider it to be responsible national governments rather than the European Union (56%, in
line with the EU average of 57%). It’s extremely clear and well-known that agricultural is responsible
of climate change but it’s also vulnerable (Parker et al., 2019). In the next decades, the intensification
of hard-to-predict extreme weather events will put pressure on the agricultural sector, impacting
Proceedings of HAICTA 2022, September 22–25, 2022, Athens, Greece
EMAIL: sabrina.giuca@crea.gov.it (A. 1); marco.gaito@crea.gov.it (A. 2); antonella.difonzo@crea.gov.it (A. 3);
simonetta.deleo@crea.gov.it (A. 4); guido.bonati@crea.gov.it (A. 5)
ORCID: 0000-0003-4271-0601 (A. 1); 0000-0001-8299-6398 (A. 2); 0000-0002-5258-4699 (A. 3); 0000-0003-1992-9007 (A. 4); 0000-
0001-5401-0659 (A. 5)
©️ 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
353
farmers' incomes and farm’s survival. According to a Special Report by the European Court of Auditors,
despite more than 100 billion euros being devoted to climate change mitigation (over a quarter of EU
agricultural expenditure in the 2014-2020 period), for over ten years, greenhouse gas emissions
produced by agriculture have not decreased. The report shows that most of the measures financed by
the Common Agricultural Policy (CAP) have limited potential for mitigating climate change; the CAP,
therefore, has failed to incentivize the adoption of effective environmentally friendly practices.
However, the fight against climate change will continue to be one of the strategic objectives of the CAP
even in post 2020. Following a public consultation launched by the European Commission on the CAP
Future, in 2017 the Commission has presented three legislative proposals for the CAP 2023-2027
reform, approved after three years of negotiations. The Commission included three general objectives
in its reform strategy, including "to bolster environmental care and climate action and to contribute to
the environmental and climate objectives of the EU" and nine strategic goals focused on social,
environmental, and economic factors, including "contribute to climate change mitigation and
adaptation" (Reg. 2021/2117). In this context, scientific research on the effectiveness of climate
adaptation measures for farmers contributes to the debate on the reduction of economic and
environmental risks related to climate change under different fields of analysis (De Leo et al., 2022;
Giuca et al., 2022). At the first, the scientific literature suggests that climate change impacts on
agriculture to be site-specific (El Chami and Daccache, 2015). For this reason, adaptation measures
show efficacy by more heterogeneous results and the adopation vary across regions and agrosystems.
A field of existing literature focuses on the factors that drive the willingness to take adaptation measures
and the socio-economic (Frame et al., 2018) and agronomic conditions (Ulukan et al., 2008; Dednath
et al., 2021) influencing their adoption. Kabir and Alam (2021) provide a conceptual model for
identifying the determinants affecting farmers in the adoption of adaptation measures to climate change.
In the same direction, a field of existing literature focuses on the factors that drive the willingness to
take adaptation measures. The results show that farmers' adoption of adaptation measures appears to be
influenced by socioeconomic factors such as age, education level, household size, household income,
farm size and agricultural experience (Bryan et al., 2009; Masud et al., 2017 [a], 2017 [b]; Kabir et al.,
2020). This consideration suggests that climate change measures are a robust part of public policies, at
local, national, and global levels.
2. Data and Research Methodology
The methodology illustrated will be implemented in LIFE project "ADapation in Agriculture"- ADA
(execution stage) which aims to help improve adaptation to climate change and promote sustainable
and inclusive growth in the agricultural sector. In this context, we provide a methodology framework
for costs and benefits assessment of adaptation measures to climate change and their economic and
environmental effects at the farm-level in Italy to improve farmers ability to face current and future
climate risks. The methodology approach is based on collect cost and benefit data deriving from: i) desk
research; ii) questionnaire administration with CAWI methodology (Computer Assisted Web
Interviewing). The data are obtained through questionnaires and cross-sectional data are collected from
Italian FADN detector. The questionnaire includes questions closed and open-ended response and used
samples and standardized questions to carry out a structured interview; iii) open interview to
agricultural experts.
Data collected, stored in a database, are:
• The range of costs to be incurred for the implementation of the measure2.
• Degree of effectiveness of the measure in relation to the risks (high, medium, low).
• Further economic benefits.
• Environmental benefits.
• Possibility of public funding.
2
We collect range investment costs, and average annual cost per hectare. These annual costs taking into account the depreciation of the
investment and the maintenance cost of the investments.
354
This collect data are used in an exemplary estimation model to evaluate cost and benefits of CAM
adoption. The exemplary estimation model is based on entity of damage avoided - deriving by adverse
climatic events - with the CAM adoption. Adverse weather events are growing frequently. Considering
the average of the yields’ losses in agriculture in last year with strong effect on income (European
Environmental Agency, 2021), for simplified our model assume that adverse climatic events can cause
damage on average equal to or greater than 30% of the value of the farm's production with a high
likelihood. The damage is calculated using FADN data and the average farm value Gross Production
farm is considered for type of farming and its economic size.
The benefit of each measure is calculated on estimate effectiveness of the measure to prevent/reduce
such damage.
The following assumptions were made regarding effectiveness of the measure:
• High = capable of reducing the damage from 70% to 100%
• Medium = capable of reducing the damage from 30% to 70%
• Low = capable of reducing the damage from 10% to 30%
In our approach we considered the average damage reduction based on the previous assumptions.
Furthermore, other economic benefits are considered. Benefits related to the improvement of
production quality, the possibility of benefiting from CAP payments, the environmental benefits that
can have positive economic repercussions, as they are increasingly appreciated and requested by
consumers.
The adoption of the measure could entail economic benefits independent of the occurrence of the
adverse climatic event. The measure could provide a qualitative improvement of the production
(organoleptic properties, better size that allows a better placement on the market etc…) and / or an
increase in yields. The economic value of this benefit depends on the adaptation measure, as well as on
the specificity of the farm, so can be suitably valued based on the measure considered.
The possibility of receiving public contributions deriving from the CAP must be considered (e.g.:
measures of Rural Development Program) and this public support differs according to the adaptation
measure considered.
Furthermore, we wanted to recognize a small economic value, of symbolic type, that we could value
in a little percentage of the value of production, that we will be tailored for each measure, to any
environmental benefits brought about by the implementation of the measure.
Aware of the difficulty of estimating the economic value of these benefits, we felt right to consider
their contribution.
In fact, environmental benefits are increasingly pleasant by consumers and can therefore have
positive economic repercussions as they are increasingly appreciated and requested by consumers. In
the long term they can also increase yields.
Finally, the overall average benefit is compared to the average cost to be incurred for the adoption
CAM.
In our exemplificatory estimation model we have assumed the follow possible average annual costs
per hectare:
• low: 250
• medium: 500
• high: 1000
• very high: greater than 2000
The cost per hectare was multiplied by the average UAA (utilized agricultural area) of farm type
and class of economic size. The farm average UAA come from FADN data (2017-2018-2019).
Taking into account the average annual costs of implementing the measures and the related benefits
is possible to calculate the follow evaluation indicators:
• Impact of the net benefit3/ on cost (net benefit/cost)
• Cost impact on gross production (cost/gross production)
• Incidence of the benefit on the gross production (loss avoided)/(net benefit/gross production)
3
Net benefit = Benefit – Cost.
355
3. Results and Conclusions
The results provide a methodology to represent costs and benefits associated with the reduction of
the climatic risk that countering the adaptation measure. The use methodology approach could be to
support farmers in choosing to adoption of appropriate CAM. This framework is a prerequisite for
identifying the specific support interventions for adaptation measures, mainly deriving from rural
development measures to which farmers will be able to access.
This paper contributes to the research issue providing a methodological framework and in-depth
assessment of adaption measures capability to reduction economics and environmental damage due to
climate risk.
In this paper we apply the methodology approach to the following type of farms: open field
horticulture, fruit, wine. Table 1 shows the data that were used to estimate the cost-effectiveness of
adopting the measure.
Table 1
FADN data used for the simulation of the cost-effectiveness of adopting the measure (average values)
Production
Supply chain Farm size UAA (ha)
value (€)
Open field horticulture Large 260.790 20,2
Open field horticulture Medium 73.161 3,5
Open field horticulture Small 24.964 1,5
Fruit Large 248.332 23,7
Fruit Medium 65.321 7,0
Fruit Small 21.908 2,8
Wine Large 240.397 29,0
Wine Medium 47.128 7,7
Wine Small 16.566 3,5
Considering only the benefit deriving from the effectiveness of the measure in avoiding probable
damage, estimated at 30%, the results obtained are shown in table 2.
356
Table 2
Impact of the net benefit on cost
Supply Hight effective Medium effective Low effective
Farm size
chain 250 500 1000 2000 250 500 1000 2000 250 500 1000 2000
Open field
Large ***** ***** ***** *** ***** ***** *** # ***** *** # ##
horticulture
Open field
Medium ***** ***** ***** **** ***** ***** ***** *** ***** **** ** ##
horticulture
Open field
Small ***** ***** ***** **** ***** ***** **** ** ***** *** # ##
horticulture
Fruit Large ***** ***** **** ** ***** ***** *** # **** ** # ##
Fruit Medium ***** ***** **** ** ***** **** ** # **** ** # ##
Fruit Small ***** ***** **** * ***** **** ** # *** # ## ##
Wine Large ***** ***** **** * ***** **** ** # *** # ## ##
Wine Medium ***** ***** **** # ***** *** # ## ** # ## ##
Wine Small ***** **** ** # **** ** # ## ** # ## ##
If benefits minus costs is higher than cost the legend is: for values from 0% to 10% = * = convenient; for values from 10%
to 50% = ** =good; for values from 0% to 100% = ***very good; for values from 100% to 200% = **** high; > 200 =*****=
very high. If the costs exceed the net benefits the following legend should be considered when assessing the cost-
effectiveness of the measure: for values from 0% to 50% = consider the value of additional benefits; for values from >50%
consider farm specificities.
The simplified model considering the supply chains involved (fruit and vegetable; wine) the main
considerations emerge.
If the adaptation measure is highly effective its adoption for farms is convenient for each average
costs considered. It’s exception medium/small wine farms in case of cost per hectare is very high. In
this type of farm, the convenience could be achieved by considering any additional benefits. If the
measure has low effectiveness and implementation costs are high and/or very high, the adoption of the
measure should be evaluated according to farm specificities and considering any further benefits. In
case of a high average cost the presence of additional benefits might be sufficient for horticultural and
fruit farms.
In the case of a measure with moderate effectiveness and very high costs the farm specificities must
be considered.
The limitation of the model consists in its exemplification due to the use of average data and
estimates that cannot be replaced by the structural, economic and patrimonial characteristics and also
by the productive context in which the farm is situated. However, the model findings provide interesting
information for adaptation measures.
Yet, it should provide a valuable tool to support environmental economists and policies. Climate
changes directly affect productivity by affecting the profitability of farmers, especially small and
medium-sized farmers, and their ability to survive, also negatively affecting the quality of production.
This consideration suggests that climate change measures is a robust part of public policies, at local,
national, and global levels. In addition, an overview of possible policies to support adaptation to climate
change in agriculture was created. In line with the EU adaptation strategy (EU COM 2021/82), our
paper contributes to scientific literature to make farmers more resilient to climate change. Our challenge
is to outline specific measures for the agricultural sector, to counteract impacts of climate change also
at local level.
357
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