Download 1 - MEDiterranean PROspects

MEDPRO WP 4.a: Management of Environment and Natural
Resources
Inception report on WP4a research activity
Francesco Bosello (FEEM)
Nicola Lamaddalena (MAIB)
Paulo A.L.D. Nunes (FEEM)
Daniel Osberghaus (ZEW)
Consuelo Varela (UPM)
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0 Introduction
The aim of WP4a is to analyze and evaluate the criticalities connected to the management of
environment and natural resources in MED11 countries, their impact on long-term economic growth
and sustainable development in the region, finally to propose some prospective policies. The research
focuses on the domains of, water, agriculture, local coastal environments (the relevance of
biodiversity) their likely interaction with future climate-change trends. Each of these areas will be
investigated by a specific assessment study.
In addition, an environmental-economic integrated climate-change impact assessment exercise will be
performed to estimating the economic implications of climate change in MED11 area highlighting
interrelation among these domains and key drivers that determine sustainable vs. unsustainable
outcomes.
Due to their importance, specific attention will be devoted to adaptation strategies that will be
discussed either in the domain specific assessment or within a more general theoretical framework
investigating the level of governance, uncertainty, timing, cost-effectiveness and equity issues related,
as well as the mitigation-adaptation trade-offs.
1. Task A: Management of agriculture and adaptation strategies.
1.1. Introduction
UPM’s contribution to MEDPRO for WP4a aims to analyze sustainable use of water resources
principally in the agricultural sector in Mediterranean countries under uncertainty conditions. It
intends to serve as an output for looking at the sustainability perspectives in the Mediterranean and as
inputs for the comprehensive MedPro CGE model (WP8). It will have two main parts, following
discussions with Rym Ayadi along the preparation of the DOW and subsequent discussions with
Fancesco Bosello during the KOM: The first part will be a more general analysis with a large
coverage of the Mediterranean region that will likely include the full Medpro country set. The second
part is a more in-depth analysis with field-based and statistically-based modeling that will be limited
to a small selection of countries (one or two maximum) of the Medpro country set.
The specific description of the two parts as well as the tools and data sets is detailed in the section
below.
1.2 Objectives and Methodologies
Part 1: UPM will conduct an analysis of the major environmental, economic and institutional factors
driving water use at country level in the Mediterranean region. This analysis will be conducted using
an econometric approach and, for this reason, the countries included in this analysis will depend on
data availability although the intention is to include all Medpro countries as well as the EU
Mediterranean countries for comparison purposes. Although the agricultural sector will be treated in
more detail in this analysis, the focus will not be narrowed solely to water for agricultural use and
therefore the picture provided will cover the water “production factor” as a whole. Once identified,
these relations will be used to project possible trends in water uses in the future according to defined
scenarios of economic growth and climate change. Data gathering for the econometric estimation has
already started surveying public databases of international organizations such as the World Bank data
catalogue, FAOSTAT, AQUASTAT, Plan Bleu etc. Responsible of this part of the research is the
UPM team (Consuelo Varela-Ortega, Paloma Esteve and Irene Blanco).
Countries to be included:
Med11: Syria, Egypt, Morocco, Turkey, Algeria, Israel, Jordan, Lebanon, Lybia, Palestine and
Tunisia.
Non-Med11: Spain, Italy, Greece and France
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Variables and indicators for the econometric analysis: total and rural population, GDP per capita,
agricultural share of GDP, HDI, agricultural area, irrigated area, cereal yield, total cereal production,
agricultural production value, fertilizer consumption, food consumption, renewable water resources
per capita, water withdrawal per capita, CO2 emissions, electric power consumption, and any other
variable that will reflect the social and economic conditions of the MedPro countries in relation to the
environmental .
The results of this country-based analysis can be used as inputs for the WP4a modeling (with FEEM
and MAIB) of the impacts of environmental conditions, such as climate change, as well as the effects
of demand and supply water management policies (see tasks of WP4a)
Part 2: UPM will also conduct a more in-depth specific work in one selected Mediterranean country
(Syria is the preliminary option). This detailed analysis will be based on the methodology already
developed and applied to Spain at the farm, regional and basin levels. It will provide insights on the
effects of water and agricultural policies and the impacts of climate change on the socio-economic and
environmental conditions of the country selected as well as their vulnerability and adaptation capacity.
Extension to another country cannot be assured due to budget and data availability constraints.
Responsible of this part of the research is the UPM team (Consuelo Varela-Ortega, Paloma Esteve and
Irene Blanco).
The economic modeling comprises microeconomic models at farm level, at irrigation community level
(WUAs) and aggregated analysis at regional level. The development of field-work based economic
models allows for testing different policy and climate scenarios at various levels of aggregation
through the characterization of farm types. This analysis will allow for the assessment of the socioeconomic impacts, such as farm income, labor use, employment and cost-effectiveness of policies as
well as of the environmental impacts such as, water use, drought resilience, aquifer recharge and
environmental flows.
The economic and hydrology models are used in an integrated platform, and in the case of
microeconomic models these can be up-scaled at regional level to represent a River Basin a water
catchment or aquifer (using the WEAP hydrology model) and easily represented through GIS.
This detailed analysis will be used as inputs for the CGE-FEEM model for obtaining specific results
on the country-level aggregate effects under uncertainty conditions of specific environmental,
agricultural and market policy changes, as well as of environmental changes (such as drought impacts
and water availability constraints) , and climate change. The results of this modeling analysis will
provide an information base for the MedPro comprehensive CGE model (WP 8).
The summarized description of models, tools and data sets is the following:
Tools:
In the Mediterranean:
• Econometric analysis (STATA) of macro data (country level) for understanding the relation
between agriculture, water and socio-economic variables)
• Microeconomic analysis (farm level) for specific countries, mathematical programming economic
models: Syria and other country could be selected (pending on data availability and collaboration
with other partners).
In Spain (for a methodological framework and comparative base) :
• Agriculture, Water and Climate change policy mapping. Stakeholder mapping
• Integrated modeling framework of economic (farm based, risk-based mathematical
programming model of constrained optimization, GAMS) –agronomic (Aquacrop) and
hydrology (WEAP) models
• Analysis of Farmers’ Vulnerability under different water and agricultural scenarios with
econometric models (STATA), math programming modeling (GAMS) and classification trees
(CART, Classification and Regression Trees)
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• Stakeholder participatory Scenario Development (Conceptual modeling, Fuzzy Cognitive maps,
storylines)
Data:
In the Mediterranean:
• Farm types, agronomic, economic, technical and structural data at the farm level for Syria (to be
updated) and for other MED11 country, which will be selected according to data and resources
availability.
• Database under development from public international databases such as the World Bank Data
Catalog, AQUASTAT or FAOSTAT.
In Spain:
Pending on financial resources and on data and information availability for the potentially selected
country (es) of the Medpro country set, the research experience in Spain will be used for this part of
the research. In principle we have selected Syria as a potential , due to the potential use ICARDA data
set, IWMI studies, SEI-WEAP hydrology models and previous work conducted by C. Varela-Ortega .
However, the selection of a country (es) for this in-depth analysis remains open and pending on
discussions with the FEEM team and the other partners of Medpro coming from the selected countries
as well as the FEMISE network.
For Spain data available are:
• Large and detailed knowledge base that comprises data and information at farm level that includes
field work data, different types of surveys and interviews: farm types, crop distribution, water
requirements, irrigation techniques, yields, crop prices, labor, etc. Statistical analysis. Expert
surveys and interviews. Field work in the Guadiana Spanish river basin (data base of 150 farms
aprox.)
• Stakeholder mapping at regional and sub-basin levels, consultation and meetings: Well established
contacts with farmers, environmental conservation groups, Guadiana Basin Authority, regional
agricultural departments, research centers, farmer unions, independent water associations, etc.
• Data on land use by province (Statistical Yearbook. Spanish Ministry of Environment and Rural
and Marine Affairs).
• Data on agriculture and water in Spain (also for regions and provinces) from Spanish databases.
(Integrated System for Water Information. Spanish Ministry of Environment and Rural and Marine
Affairs)
• General statistical data from the regional and national administration (National Statistics Institute)
• Future projections on water demand and water supply for 2015.
• Specific available data and sources:
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Irrigation districts. Shapefiles from the Spanish Ministry of Environment and Rural
and Marine Affairs.
DEM (Digital Elevation Model): 200 x 200. Spanish National Geographic Institute.
Land use cover (CORINE90, CORINE2000, CORINE changes): 85 classes. Scale
1:100.000. Spanish National Geographic Institute.
Soils&Geological data from the Join Research Center.
Administrative Divisions: regions, sub-regions, provinces and municipalities.
Shapefiles from the Spanish National Geographic Institute.
River Basin boundaries, reservoirs, rivers, streamgages, irrigation cannals, diversions,
etc.). Historical data from 1950 to present day. Shapefiles. From the Guadiana River
Basin Authoriy.
Minimum environmental flow requirements. From the Guadiana River Basin
Authority.
Monthly interpolated data from 1901: Tmean, Pmean, humidity, wind, vapour
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pressure, cloud cover. From the CGIAR-CSI Geo Portal (0.5 degrees resolution)
2. Task B: Management of water resources and adaptation strategies.
2.1 Introduction
Many regions of the Mediterranean are already at risk of desertification and their access to water is
limited with negative consequences on land productivity, agricultural activity and health status of the
population. Under climatic change, water scarcity is projected to increase in the very next decades
(EEA, 2005a, 2005b; EEA, 2008; IPCC, 2007). It can entail a dramatic worsening of the economic
and living standards of poorer Mediterranean regions where agriculture still contributes a large share
of GDP and provides the main source of employment (such as the North African countries), generate
or exacerbate conflicts (Mostert, 2004, Deconinck, 2002), and threaten health status. Moreover it will
also impose adaptation costs to the richer regions that today are only marginally affected like the
Southern European economies (see Iglesias et al. 2006, Rosenzweigh and Iglesias, 2003). Even more
serious is the fact that many strategies to cope with water scarcity, like water desalination and deep
water pumping usually entail an increased energy use, and thus higher energy prices, potentially
higher food prices, increased foreign energy dependence in energy-importing countries, and ultimately
higher GHG emissions (Klein et al. 2007).
2.2 Objectives and Methodology
Starting form the description of the current situation, task 4a2 will assess the major pressures on water
resources in MED11 regions as they would be determined by future different economic, agricultural,
and climatic development scenarios and their implications for the productivity of the agricultural
sector.
The first step of this assessment consists in estimating the relationship between water availability and
crops productivity in main MED11 regions for major crops.
This relationship will be investigated by IAMB and UPM. The research will potentially integrate data
from two sources. If possible, information from the FAO AquaCrop model will be used. AquaCrop is
a water-driven simulation model that simulates the yield response to water of most of the major
herbaceous crops cultivated worldwide. Contacts with Dr. Pasquale Steduto (one of the model
developers) and deputy director of the FAO Land and Water Department, have been taken. If this will
prove to be insufficient or infeasible with respect to the timing of MEDPRO, IAMB can produce this
information in house, elaborating on its data base (extended information on crop yield and water
productivity for the main crops of Mediterranean agriculture integrated with information on crop
response to water to be retrieved in the scientific literature and duly elaborated).
Responsible for the integration of AquaCrop data and the final estimation of impacts on the
agricultural sector are Nicola Lamaddalena with IAMB team and Consuelo Varela-Ortega.
The second step of the research will consist in the discussion of possible future developments for
water availability and their impacts on productivity using data on expected climatic changes.
A third phase of the research, starting from the identified relationship between water use and crops
productivity, will be devoted to the analysis of best practices to optimize water use.
An integrated planning has to seek to increase water productivity, irrigation having a significant
saving potential, within the constraints imposed by the economic, social and ecological context.
In the Mediterranean areas, the farmers are frequently constrained to apply deficit irrigation strategies
and the ability to manage water supply in accordance with the sensitivity of crop’s growing stages to
water stress is of particular importance. Furthermore, in those situations, the economic aspects of
WUE would get additional importance due to farmer’s interest to improve economic return from the
investments in irrigation water supply.
The improvement of water use efficiency in Euro-Mediterranean agriculture would have relevant
environmental benefits by means of quality and quantity of water resources available in
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accumulations, groundwater aquifers and water courses. Other benefits could be in stabilizing of
agricultural production and income of farmers that would contribute to reduce the urbanization process
and abandonment of agricultural land. Furthermore, water saving in agriculture could attenuate the
problems of water allocation for different uses.
The application of a series of best practices at different levels will allow for managing the demand and
improve the efficiency of water use.
The technical solutions consider different levels of application:
- Large scale distribution networks
- On farm irrigation systems
- On field management practices
Combined with non technical practices i.e. the role of Water Users Associations, Operation and
Management activities, Irrigation Management Transfer, Participatory Irrigation Management and set
up of appropriate tariff rules.
This phase of the investigation, jointly conducted by UPM and IAMB will build upon existing
knowledge, and aims to derive perspective insights i.e. identifying those measures that could be more
promising according to future development trends in the MED11 area. UPM will focus more on
institutional and farm practices while IAMB more on technical measures and water management.
Particularly insightful success stories will be included as examples of good practices. The first step is a
throughout survey work. Nicola Lamaddalena with IAMB team and Consuelo Varela-Ortega, Paloma
Esteve and Irene Blanco from UPM are responsible for this.
3. Task C: Assessment of Marine Ecosystems goods and services (coastal areas, biodiversity) and
management strategies.
3.1 Introduction
In a “more strictly” economic perspective, two main streams of research were developed for studying
tourism industries:
1) research aiming at understanding the correlation between economic growth and tourism
specialization in selected countries;
2) research aiming at understanding the determinants that explain tourists choice and demand.
The relationship between tourism specialisation and economic growth is one of the main topics under
discussion in the growing field of tourism economics. Since the seminal works of Copeland (1991),
Hazari and Sgrò (1995) and Lanza and Pigliaru (1995), the role played by tourism in the process of
national development has captured increasing attention. In the last few years, many papers have
attempted, mainly theoretically, to understand the real mechanisms at work, but many shadows
prevent light being shed on this issue. On the empirical side, the cross-country evidence is mainly
based upon the works of Brau, Lanza and Pigliaru (2004 and 2007).
For the second research stream, there exist a high number of studies, aiming at targeting the variables
affecting tourists’ destination choice and the elasticity of touristic demand to price changes. (see for a
detailed survey, Candela and Figini 2004).
For the MEDPRO project FEEM will focus on the second research stream and start from a general
question: What does affect the choice of a tourism destination?
Naturally relevant explanatory variables are many: income, tourism services prices, distance and cost
of transportation, exchange rates (Dritsakis, 2004; Witt and Witt 1995; Hamilton et al., 2005; Bigano
et al., 2007; Lise and Tol, 2002). Furthermore, among the relevant tourism pull factors, several studies
consider the types of tourism attractions of which a destination can take advantage, for instance art and
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local culture, wine and gastronomic production (Medina, 2003; Poria, 2003; Hamilton, 2004, Brunori
and Rossi, 2000; Telfer, 2001; Correia et al., 2004). Resident population tourist population density can
also affect the destination choice. It is studied that some consumers prefer crowded destinations, other
enjoy locations “far from the madding crowd”. Fads and fashion affect the destination choice (see
Candela and Figini 2004).
Several studies have been focusing on the relationship between climate and tourism demand.
Temperature is often considered as the most relevant climatic variable, since most climate parameters,
such as humidity, cloudiness and weather extremes, tend to depend on temperature. (see Bigano et al.,
2007; Hamilton et al. (2005 a; b); Lise and Tol (2002). Environmental amenities are considered by
most studies as a relevant component of tourism demand determinants and they can be viewed as a
growth factor for the tourism industry (Wunder, 2000; Naidoo and Adamovicz, 2005; Green, 2001).
To our knowledge, however, an under-studied key factor affecting touristic coastal destinations choice
is the amount of biodiversity in the tourism destination.
3.2 Objectives and methodologies
The research overall goal is to analyse and measure the role of biodiversity on (domestic and national)
tourists’ decisions about the final (worldwide) coastal destination in MED11 region and how this
could change in a future subjected to climatic changes.
Therefore, we focus on:

What is the role played by biodiversity-related variables in explaining tourists’ choice
behaviour?

Is biodiversity an important factor driving touristic consumption (in terms of choice of
touristic supply/final destination/days of stay), other than the usual variables detected and
measured by the above surveyed tourism economics literature?

Is it possible to find an empirically robust relationship between tourist profile (domestic vs
international tourists; tourist on a trip or on holiday; short vs long-term stays) and particular
biodiversity indicators (purity of the water, presence of protected flora and fauna species and
so on)?
For the sake of this study, biodiversity is defined as the stock of endogenous fauna and flora in coastal
tourism destination. Biodiversity in tourism destinations has several economic dimensions, spanning
from use, non use, option, bequest values. Biodiversity is interpreted as one of the spurring elements
for the choice of the touristic coastal destination.
The main methodological steps will be built upon the following pattern:

Integrating the original data set from World Tourism Organization (with information on
tourism flows) with climate variables and biodiversity related variables from Conservation
International and other relevant microeconomic information (for instance: percentage of “free”
beach vs, “upon payment entry” beach; price of selected touristic services etc.).

Performing the estimation of a demand function for coastal tourism destinations, specifying
the role of climate and biodiversity related variables in explaining tourist choice behaviour
translated in number of arrivals. This estimation is targeted to the MED11 regions.

Performing projections on possible future developments of tourism arrivals embedding in the
estimated model future changes in temperature increases and related impact on biodiversity.
4. Task D: Integrated assessment of climate change impacts in MED11 region
4.1. Introduction:
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In dealing with the economic assessment of climate change impacts, the relevant literature proposes a
partial and a general equilibrium approach.
The first offers an assessment of costs which does not take into account the feedback that an economic
perturbation into a sector or activity exerts on the rest of the systems. Albeit the many differences in
direct costing techniques, the process leading to final results can be described as:
(Economic cost of climate change) = (“Quantity with Climate Change” – “Quantity without Climate
Change”) x (“Price”).
These methodologies are largely diffused in the literature (see e.g. Fankhauser, (1994); Yohe et al.
(1996); Yohe and Schlesinger, (1998), (1995), Volonte and Nicholls, (1995) Gambarelli and Goria
(2004) for sea-level rise; Hamilton et al., 2005a,b; Hamilton and Tol, 2007; Amelung et al., 2007,
Elsasser and Burki, 2002; Scott et al., 2004; 2007; OECD, 2007 for tourism, the survey of Viscusi and
Aldy (2003) for health). Their strength is their relatively easier applicability and perhaps a smaller
degree of uncertainty in the estimated values as a more limited number of simplifying assumptions on
economic dynamics are necessary compared to a general equilibrium approach.
Their major shortcomings is that they cannot measure possible rebounds on costs that a changing
economic context can impose with a smoothing or amplifying effect on initial impacts.
To capture these processes a systemic perspective is necessary. This concept is made operational by
Computale General Equilibrium (CGE) models. At the beginning, CGE models were developed
mainly to analyse international trade policies and to a lesser extent public sector policies. But, soon,
due to their great flexibility, they started to be applied to environmental taxation and climate change
impact assessment The peculiar feature of CGE models is market interdependence. As a consequence,
CGE models can capture and describe the propagation mechanism induced by a localised shock onto
the global context via price and quantity changes and vice versa. Moreover they are able to assess the
“systemic” effect of an impact usually represented by the final consequence on national GDPs .
4.2 Objectives and methodologies
Aim of Task 4a.4 is to apply a Computable General Equilibrium (CGE) model, with a world coverage,
but detailing the MED11 area singling out its major economic systems, to provide an economic
assessment of the climatic change impacts for the regions identified in tasks 4a.1 to 4a.3.
The sectoral detail of the model will focus primarily on market services and agricultural sectors as
impacts on recreational activities (in the model part of the services sector) due to changes in coastal
area ecosystem/biodiversity and changes in agricultural land productivity due to changes in water
availability and agricultural practices are the main inputs expected from tasks 4a.1 to 4a.3.
The geographical and sectoral detail of the model will thus be approximately the following:
Regional detail
Sectoral detail
- Egypt,
Rice
- Morocco
Wheat
- Tunisia
Cereals
- Turkey
Vegetables and Fruits
- Lybia+Algeria (aggregated)
Oil seeds
- Israel, Jordan, Lebanon, Palestine, Syria, Livestock
(aggregated)
- Mediterranean EU
Industry (more or less disaggregated)
- Rest of EU
Services (more or less disaggregated)
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- Rest of Africa
- Rest of the World (More or less aggregated)
If data will be available, an effort will be made to add to the model a richer specification of the
agricultural sector representing some more representative crops for the MED 11 region.
The model will be used to assess climate change impacts, i.e. phenomena that, albeit already
occurring, will become particularly relevant by the end of the century.
A preliminary step to the analysis is thus the projection of a social-economic counterfactual baseline
representing future scenarios of economic development “without” climate change. These scenarios
will be based on the “storylines” defined within MEDPRO, and, if necessary, will be integrated with
information from other sources (like e.g. the IPCC SRES scenario family). The counterfactual scenario
building exercise consists in modifying factor productivities, endowments stock and population to
replicate the suggested regional growth paths. The indicative time frame for this exercise is 20042050.
Once the baseline has been defined, the impacts assessed by tasks 4a.1 to 4a.3 will be translated in
suitable economic input to be processed by the CGE model. Specifically:
Scenarios of changes in agricultural production produced by UPM and scenarios of water scarcity in
the Med 11 area produced by IAMB will be translated into land or crop productivity changes, and
finally scenarios of changes in coastal areas ecosystem services produced by FEEM will be translated
into changes in recreational services demand. All these changes, specified for the MED 11 regions
represented in the CGE model and defined all along the simulation period will constitute a set of
economic “shocks” imposed to the model baseline. The model will then determine a new economic
equilibrium in which the difference between pre and post shocks regional GDPs will provide the
economic measure of climatic impacts. Finally, an indicator-based analysis will provide a wider
picture on sustainability than that obtainable with the simple assessment of GDP changes.
5. Task E: Assessing adaptation strengths and weaknesses in the MED11 regions.
5.1. Introduction
Beside economic costs of climate impacts, adaptation matters for assessing the total economic costs of
climate change. First, because it has the potential to (possibly considerably) decrease the climate
impacts that would have occurred without adaptation (reduced climate damage = adaptation benefits),
second because achieving these benefits comes at a cost. So the total economic costs of climate change
(neglecting mitigation) are described by
Climate impacts – adaptation benefits + adaptation costs.
Adaptation to climate change will be inevitable in the MED11 countries. Water scarcity is affecting
one main source of income (agriculture). Another important sector, namely tourism, may suffer from a
loose of biodiversity and increasing temperatures. For both sectors there are adaptation techniques
available – the desalination was already mentioned in section 2.1, and diversification in the tourism
sector may part of a coping strategy for climate-induced adverse effects in this sector. Also other
sectors, like the health system and the traffic and energy infrastructure, are relevant for analyzing
adaptation in the MED11 countries. However, it is questionable to what extent the region is capable to
adapt to a changing climate and which determinants and limitations exist for adaptation. Another
interesting topic is how costly adaptation in the MED11 countries will be and who will bear the costs.
Quantifying these benefits and costs is not easy – the uncertainty which is inherent in climate change
projections is even higher for projections of adaptation, since important parameters like the
effectiveness of adaptation measures are not known ex-ante. The definition of adaptation makes a
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detailed projection even trickier: The IPCC defines adaptation as the “adjustment of in natural or
human systems in response to actual or expected climatic stimuli or their effects, which moderates
harm or exploits beneficial opportunities” (IPCC 2007, p. 869, WG2, Glossary). To which extent
changes in economic and social systems are solely attributable to climate change remains an open
question. That means uncertainty is an important aspect in analyzing adaptation. Most researchers
have tackled uncertainty by defining different scenarios (e.g. low and high adaptation scenarios).
Reviewing the literature, it becomes clear that the estimated costs of adaptation hinge very strongly on
these underlying assumptions (which climate scenario and/or adaptation scenario is being used)
(World Bank 2009).
The timing of adaptation is another issue that is relevant for adaptation research. Early adaptation may
require higher costs (not only because of discounting, but also because of possibly decreasing prices of
adaptation technologies), on the other side it has also the potential to reduce early climate impact
costs. The question of timing under uncertainty is a typical problem of real option theory, which will
therefore be analyzed in connection with adaptation in the MED11 countries.
5.2 Objectives and Methodologies
The aim of Task E is to supply an overview about the adaptation strengths and weaknesses of MED11
regions. The ZEW assessment is based on two steps. Firstly, a theoretical approach is built up as a
basis for analyzing adaptation from an economic perspective. Secondly, a literature overview in form
of three separate country-case studies and a systematic matrix will be provided. The matrix is to show
private and public adaptation costs under various scenarios abstracted from the literature.
The differentiation of public and private adaptation is crucial in the theoretical framework of
adaptation. While private measures are autonomously taken the public action has to be justified from
an economic point of view. The governmental intervention into markets can be reasoned by (a) market
failure, (b) security of supply considerations and (c) equity aspects. The ZEW will provide the theory
of these three aspects of governmental action. Concerning point (a), a closer look at externalities and
public goods issues will be done. Relating to point (b), the focus lies on elementary goods and
services, which includes food and therefore the agricultural sector as well as the water supply and
energy. Regarding point (c), equity principles differentiated into horizontal and vertical fairness
(Atkinson and Stiglitz 1980) will be taken into account. For the public adaptation the national
government is taken as aggregate. Where literature and statistics allow insights about the specific
governmental level in responsibility the information will be provided.
Beside the differentiation of public and private responsibilities in adaptation, the aforementioned
aspects of timing, uncertainty will be included in this qualitative theory-led analysis. Furthermore, the
double trade-off between adaptation and mitigation (Tol 2007) will be investigated with a special
focus on the MED11 countries. Finally, the theoretical analysis is concluding by elaborating the effect
of MED11-countries’ adaptation capacities on the participation in international climate negotiations.
This theoretical approach will build the basis for an in-depth assessment of the adaptation strengths
and weaknesses in the MED11 countries. ZEW will conduct three country case studies focusing on the
economic sectors which are probably affected the most by climate change. The concrete selection of
analyzed sectors will be decided upon after looking at the literature, but agriculture and water scarcity
will definitely play major roles. In these main parts of the case studies, the work of ZEW will base
upon quantitative and qualitative inputs of the partners in the work package. For other sectors, e.g.
adaptation of infrastructure, health sector (demographics), tourism and important industries the outputs
of other work packages within the MEDPRO project will be incorporated as much as possible. Beside
these inputs from project partners, the case studies will rely upon existing literature, bringing together
knowledge on climate impacts in different sectors and adaptation options.
In order to structure the various estimations an overview in matrix form will be provided to classify
the strengths and weaknesses of the MED11 region based on two to four main climate scenarios,
depending on the input of MEDPRO partners and existing literature.
6. Scenario Building.
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All the analyses defined under WP4a will be performed for a “Bau (projections over current trend
scenario”), a “Sustainable Euro-Med scenario” and a “Decline and conflict scenario”.
In terms of emissions and climate-change physical impacts, this implies to define a BAU emissions, a
high emission and a low emission growth scenarios. These will be consistently associated to a BAU
economic (read GDP) growth/energy consumption population scenario, high economic growth/energy
consumption population growth scenario, sustainable economic growth/energy consumption scenario
(this last will be characterized by the same GDP growth as the BAU, but higher energy efficiency and
lower carbon intensity) which will be embedded in the economic model used within task D .
In this way tasks A to C will be integrated consistently with task D that will assess the economic
implications of the impacts assessed by the former. Finally, the overall analysis of adaptation options
and potential under the different scenarios will be performed by task E.
7. Data transfer to WP8
The information made available to WP8 for the subsequent economic assessment will be:
Changes in crop productivity for major MED11 regions up to 2050 for the different scenarios
considered.
Changes in water availability in major MED11 regions up to 2050 for the different scenarios
considered.
Changes in recreational services (tourism) demand linked to change in recreational attractiveness of
ecosystem services up to 2050 for the different scenarios considered.
Potential role of adaptation practices in water and agriculture in decreasing the adverse effects
quantified.
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References:
Amelung, B., S.Nicholls, and D.Viner (2007), “Implications of Global Climate Change for Tourism
Flows and Seasonality”, Journal of Tourism Research 45: 285-297.
Atkinson, A.B., Stiglitz, J.E. (1980): Lectures on Public Economics, McGraw Hill, London.
Bigano A., Hamilton J.M., Tol R.S.J. (2007), The impact of Climate Change on international and
domestic tourism: A simulation study, The Integrated Assessment Journal, Vol. 7, Issue 1, pp.
25 – 49.
Brau, R., A. Lanza, and F. Pigliaru (2004), How fast are tourism countries growing? The cross
country evidence, in A. Lanza, A. Markandya, and F. Pigliaru (eds.), The Economics of Tourism
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