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KLUM@GTAP: Introducing Biophysical Aspects of Land-Use Decisions into a Computable General Equilibrium Model a Coupling Experiment
Abstract
Abstract In this paper, the global agricultural land use model Kleines Land Use Model is coupled to an extended version of the computable general equilibrium model (CGE) Global Trade Analysis Project in order to consistently assess the integrated impacts of climate change on global cropland allocation and its implication for economic development. The methodology is innovative as it introduces dynamic economic land-use decisions based also on the biophysical aspects of land into a state-of-the-art CGE; it further allows the projection of resulting changes in cropland patterns on a spatially more explicit level. A convergence test and illustrative future simulations underpin the robustness and potentials of the coupled system. Reference simulations with the uncoupled models emphasise the impact and relevance of the coupling; the results of coupled and uncoupled simulations can differ by several hundred percent
... Of the 45 studies that were classified as coupled, only five studies employed multidirectional feedbacks between EMs and coupled models (Cai et al., 2015;I. Kim et al., 2013;Ronneberger et al., 2009;Verburg et al., 2009;Wolf et al., 2011). Multidirectional coupled models included two IAMs (Cai et al., 2015;Hoefnagels et al., 2013) as well as agriculture and land-use (I. ...
... Multidirectional coupled models included two IAMs (Cai et al., 2015;Hoefnagels et al., 2013) as well as agriculture and land-use (I. Kim et al., 2013;Ronneberger et al., 2009) and an input-output model (Wolf et al., 2011). Within unidirectional coupled frameworks, outputs from upstream models were used as inputs in EMs (23 studies, e.g., J. Liu et al., 2014) or EM output was used as input in downstream models (16 studies, e.g., Henseler et al., 2013). ...
Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change.
... This HRU concept assures consistency in integrating biophysical features into the economic land-use optimisation model. The advantages of such coupled approaches have been demonstrated by Ronneberger et al. (2009), using the KLUM@GTAP model that combines the global agricultural land-use model KLUM and GTAP-EFL. This latter model is refinement of GTAP-E in terms of industrial and regional aggregation levels. ...
... Notably it makes land quantity data incomparable between GTAP-EFL and KLUM. As a consequence small absolute changes in the area of other crops in KLUM translate into large absolute changes in GTAP-EFL (Ronneberger et al., 2009). This problem can be solved by completely recalibrating the coupled system. ...
Motivated by the conclusions from various modelling studies, modifications to the bioenergy sector regulations are under way in Europe and in the USA to account for emissions from indirect land-use change (ILUC). Despite their influence on the policy-making, evaluations of the capacity of numerical models to estimate ILUC are sparse. To address this void, this paper reviews recent developments in land-use modelling, with a particular focus on the solutions adopted to estimate ILUC due to biofuel production. As indirect effects of bioenergy result from the interplay of various mechanisms, their modelling is a major challenge for land-use science. In recent years, numerical models have been significantly upgraded to provide a more comprehensive vision of the agricultural system. This has been performed by improving the representation of land supply and the biofuel production process in general equilibrium models (e.g., GTAP, MIRAGE, DART). At the same time, modelling systems coupling partial equilibrium models with CGE (e.g., KLUM@GTAP) or economic modules with spatially explicit models (e.g., MAgPIE, GLOBIOM, LEITAP), and modelling architecture combining land-use and life-cycle assessment models (e.g., FASOM/FAPRI/GREET) have been developed. In spite of these advances, some limitations remain and uncertainties are still numerous.
... Improving land modeling within the CGE model such as GTAP-AEZ model (Lee, 2005) and linking a CGE model with a detailed land use model tried in KLUM@GTAP project (Ronneberger, et al., 2006) are two different approaches to handling land use analysis within the GE structure. Others have introduced a land supply structure in their analysis as in LEITAP and EPPA models (Babiker, et al., 2001, Banse andGrethe, 2008). ...
... KLUM, on the other hand, is a global agricultural land-use model that links the economy to global crop allocation to maximise producer returns under certain assumptions about risk. In essence, KLUM@GTAP substitutes the land allocation mechanism within GTAP-EFL where regionally aggregated area changes in cropland determined by KLUM are used to update cropland shares in GTAP-EFL(Ronneberger et al. 2009). ...
Ecosystems and the biodiversity that underpin them are our life support systems. But the impact of declining trends in biodiversity and ecosystem services (BES) on economies and society is not well known outside the context of one-off local case studies. There is an urgent need to better understand and, importantly, to effectively communicate the importance of BES as foundational to the economic prosperity and wellbeing of current and future generations, the benefits of restoring and enhancing ecosystems, and the consequences of a business-as-usual approach which will render sustainable development as embodied in the UN Sustainable Development Goals (SDGs) elusive.
WWF has initiated a new project to help tackle this challenge. Its goal is to generate new evidence on the potential global socio-economic impacts of future changes in BES. This ambitious initiative can provide critical inputs to the wider policy- and decision-making audiences during the discussions leading to 2020. This is a crucial year, as targets under the Convention on Biological Diversity (CBD) and United Nations Framework Convention on Climate Change (UNFCCC) will be reviewed and progress toward the SDGs reported on. The project will also contribute to the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). While the IPBES work programme considers socio-economic drivers of conditions and trends in BES, the focus of this initiative is on modelling the interactions of social and economic development trends on BES, and in turn how future changes in BES impact socio-economic outcomes, wealth and wellbeing.
Phase 1 of the new WWF project aims to scope the current state-of-the-art in BES-economy modelling and research, and to identify what new modelling and analyses should be prioritised to fill key knowledge gaps and deliver critical evidence at key points in time.
This report presents results of the Phase 1 scoping study, the objectives of which were to:
1. Identify, based on the project's theory of change, the anticipated informational needs/demands of relevant international initiatives to protect and enhance global BES (including the current IPBES work programme and the CBD, UNFCCC and SDGs leading to 2020) related to the potential global socio-economic impacts of future changes in BES.
2. Identify the extent to which existing datasets, models and modelling initiatives could be utilised to meet the needs of the relevant international initiatives to protect and enhance BES as identified under Objective 1, and identify key gaps in the existing evidence base and approaches.
3. Develop a set of recommendations on further modelling/analysis that could be undertaken in Phase 2, to help address the key gaps identified under Objective 2 and provide an assessment of the socio-economic impacts of BES loss, protection and restoration.
... Applying the necessary adjustments in the CGE parameters, Ronneberger, Berrittella, Bosello, and Tol (2009) showed that changes in emissions and crop production move in the same direction as changes in GDP and welfare. Changes in trade balance and crop prices move in the opposite direction. ...
Over the years, deforestation in the Philippines resulted in significant reduction in forest cover. Between 1990 and 2013, the Philippines has lost 3.8 million hectares of its forest. This study carries out a quantitative assessment of the potential economic and poverty impacts of the NGP using a computable general equilibrium (CGE) model. In the assessment, a CGE model is specified, calibrated and used to simulate three scenarios: (i) a baseline or a business-as-usual scenario that incorporates the current forest deterioration in the Philippines; (ii) a full NGP scenario which implements a reforestation program that halts and reverses the reduction in the country’s forest cover; And (iii) a partial NGP scenario where only half of the 1.5 million hectare target reforestation is achieved. The assessment indicates that the NGP will result in an improvement in the overall output of the economy. The production of agricultural crops (palay, coconut, sugar, and other agriculture) improves, as well as the processing of these crops into food. Reforestation increases the effective supply of productive land in the country. The factor markets for labor, capital, and land are affected favorably as the overall output of the economy improves. The improvement in factor efficiency decreases the cost of production, which lowers the consumer price of commodities. Food prices decline as agricultural production improves. Lower income groups benefit from declining consumer food prices as their food consumption share in their total expenditure is larger compared to households in higher income groups. Higher household incomes and lower consumer prices lead to reduced poverty. Also, those in extreme poverty benefit the most. Income distribution also improves over time as indicated by a declining GINI coefficient.
... This feature of CGE models, coupled with their flexibility, has led recently to their increased application to the economic assessment of climate change impacts. A growing CGE literature assesses the costs of single impact categories, e.g., Deke et al. (2002), Darwin and Tol (2001), Bosello et al. (2007) on sea-level rise; Bosello et al. (2006) on health; Tzigas et al. (1997), Darwin (1999), Ronneberger et al. (2009) on agriculture; and Calzadilla et al. (2008) on water scarcity. CGE models have been also used to investigate the interactions of multiple impacts, although the techniques are still in their infancy. ...
The present study integrates Computable General Equilibrium (CGE) modelling with biodiversity services, proposing a possible methodology for assessing climate-change impacts on ecosystems. The assessment focuses on climate change impacts on carbon sequestration services provided by European forest, cropland and grassland ecosystems and on provisioning services, but provided by forest and cropland ecosystems only. To do this via a CGE model it is necessary to identify first the role that these ecosystem services play in marketable transactions; then how climate change can impact these services; and finally how the economic system reacts to those changes by adjusting demand and supply across sectors, domestically and internationally.
... e in literature. A few studies have estimated the economic impacts of climate change on forest and agriculture sectors in Canada, focusing on either sector at the exclusion of the other. Zhai et al. (2009) estimated a 0.2% GDP loss and 0.2% welfare (equivalent variation) gain for Canada by 2080 from climate change impacts in the agriculture sector. Ronneberger et al. (2009), on the other hand, reported a GDP gain of just under 0.005% for Canada by 2050 from climate-induced changes in the agriculture sector. More recently, Ochuodho and Lantz (2015), estimated climate change impacts in Canadian agriculture sector across the Provinces with GDP gains ranging from 0.37 to 6.34% by 2051. In the forest sector, Oc ...
Computable general equilibrium (CGE) model analyses of economic impacts from climate change have often focused on individual impacted sectors such as forest. However, such an approach may not provide accurate economic impact estimates since climate change will affect multiple sectors simultaneously. Furthermore, imprecise aggregate economic impact estimates may result if one were to add together individual sector impact estimates. We used CGE models to compare economic impacts of individual, additive, and simultaneous climate-induced changes in Canadian and other regions' forest and agriculture sectors over the 2006–2051 period. We found negative additive impact biases in a majority of regions for five of our economic variables including GDP, income, imports, terms of trade, capital, and total output. Positive additive impact biases were found in a majority of regions for four economic variables including welfare, consumption, export, and labor. These findings emphasize the importance of considering impacted sectors simultaneously when using CGE models to evaluate the economic impacts of climate change.
... They assess, for example, the impact of climate change on crop yields and land productivity. In the context of this review, biophysical models were applied mainly to calibrate parameters in economic models [40] or provide data on yields and land productivity [41,42]. Agent-based (AB) models focus on simulating individual actors' decisions. ...
Recent regulations on biofuels require reporting of greenhouse gas (GHG) emission reductions related to feedstock-specific biofuels. However, the inclusion of GHG emissions from land-use change (LUC) into law and policy remains a subject of active discussion, with LUC–GHG emissions an issue of intense research. This article identifies key modelling choices for assessing the impact of biofuel production on LUC–GHG emissions. The identification of these modelling choices derives from evaluation and critical comparison of models from commonly accepted biofuels–LUC–GHG modelling approaches. The selection and comparison of models were intended to cover factors related to production of agricultural-based biofuel, provision of land for feedstock, and GHG emissions from land-use conversion. However, some fundamental modelling issues are common to all stages of assessment and require resolution, including choice of scale and spatial coverage, approach to accounting for time, and level of aggregation. It is argued here that significant improvements have been made to address LUC–GHG emissions from biofuels. Several models have been created, adapted, coupled, and integrated, but room for improvement remains in representing LUC–GHG emissions from specific biofuel production pathways, as follows: more detailed and integrated modelling of biofuel supply chains; more complete modelling of policy frameworks, accounting for forest dynamics and other drivers of LUC; more heterogeneous modelling of spatial patterns of LUC and associated GHG emissions; and clearer procedures for accounting for the time-dependency of variables. It is concluded that coupling the results of different models is a convenient strategy for addressing effects with different time and space scales. In contrast, model integration requires unified scales and time approaches to provide generalised representations of the system. Guidelines for estimating and reporting LUC–GHG emissions are required to help modellers to define the most suitable approaches and policy makers to better understand the complex impacts of agricultural-based biofuel production.
... ed provincial present value GDP impact gains that ranged between 0.37% and 2.47% over the 2006-51 period, depending on the region. Weighting these percentages by the value of GDP in each province and aggregating them results in a 1.7% GDP increase for Canada as a whole. However, Zhai et al. (2009) estimated a GDP loss of 0.2% for Canada as a whole. Ronneberger et al. (2009), on the other hand, found less than 0.005% GDP gain for Canada. Furthermore, for the US region , we estimated GDP impact gain of 0.59%, which was larger in magnitude compared to Zhai et al. (2009) who estimated a GDP loss for US at 0.1%. Additionally , for RW, we estimated a GDP gain of 0.26%. This was higher than the range estimated by ...
The agriculture sector plays an important role in Canada's national and provincial economies. Previous studies have projected significant climate change impacts in agricultural crops in Canada, with considerable variation across regions. In this study, we examined the potential economic impact of climate change on agricultural crops across Cana-dian provinces and territories, the United States, and the rest of the world over the 2006-2051 period using a recursive-ly dynamic, multi-regional CGE model. Two scenarios were defined in the model, including: (1) a baseline scenario where economies grow based on exogenous labor force growth rates and endogenous capital investments; and (2) a climate change scenario where the additional impacts of climate change on agricultural crops were incorporated. Results indicated that the percentage change impacts on agricultural crop production were not always proportional or similar in direction to the resulting impacts on input/output expenditures, trade, GDP or welfare in a region. Price changes, input substitutions, and trade dynamics were the driving forces behind these outcomes. Overall, this analysis can be said to provide the first (and preliminary) estimates of regional economic impacts from climate change in the Canadian agriculture sector. Further analysis is needed to accurately quantify and model the impacts so that they can confidently be used as a baseline when evaluating adaptation options in the sector.
... For instance, Zhai et al. (2009) estimated a 0.2% GDP loss and 0.2% welfare (equivalent variation) gain for Canada by 2080 from climate change impacts in the agriculture sector. Ronneberger et al. (2009), on the other hand, reported a GDP gain of just under 0.005% for Canada by 2050 from climate-induced changes in the agriculture sector. In another study, Ochuodho et al. (2012) estimated a 0.5% to 8% GDP loss for Canada by 2080 from climate change in the forest sector, with substantial regional variation across the country. ...
Computable general equilibrium (CGE) model analyses of economic impacts from climate change have often focused on individual impacted sectors such as agriculture. However, such an approach may not provide accurate economic impact estimates since climate change will affect multiple sectors simultaneously. Furthermore, imprecise aggregate economic impact estimates may result if one were to add together individual sector impact estimates. We used CGE models to compare the economic impacts of individual, additive, and simultaneous climate-induced changes in Canadian and other regions' agriculture and forest sectors over the 2006-2051 period. We found negative additive impact biases in a majority of regions for five of our economic variables including GDP, income, imports, terms of trade, capital, and total output. Positive additive impact biases were found in a majority of regions for four economic variables including welfare, consumption, export, and labour. These findings emphasize the importance of considering impacted sectors simultaneously when using CGE models to evaluate the economic impacts of climate change.
... Applying the necessary adjustments in the CGE parameters, Ronneberger, Berrittella, Bosello and Tol (2009) showed that changes in emissions and crop production move in the same direction as changes in GDP and welfare. Changes in trade balance and crop prices move in the opposite direction. ...
Wide variations in climatic conditions from prolonged dry season to frequent occurrence of super typhoons have significant impact on the Philippines, especially on rural poor households which depend heavily on agriculture and food production for subsistence and income. This paper provides a research framework that can be used to understand the dynamics between climate change and agriculture. The framework incorporates the effects of climate change on agricultural productivity, as well as the effects of agricultural activities and land use on climate change through the emission of greenhouse gasses. The framework uses three simulation models to analyse the impact of climate change: a global CGE model, a Philippine CGE model, and a Philippine poverty microsimulation model.
... Applying the necessary adjustments in the CGE parameters, Ronneberger, Berrittella, Bosello and Tol (2009) showed that changes in emissions and crop production move in the same direction as changes in GDP and welfare. Changes in trade balance and crop prices move in the opposite direction. ...
Wide variations in climatic conditions from prolonged dry season to frequent occurrence of super typhoons have significant impact on the Philippines, especially on rural poor households which depend heavily on agriculture and food production for subsistence and income. This paper provides a research framework that can be used to understand the dynamics between climate change and agriculture. The framework incorporates the effects of climate change on agricultural productivity, as well as the effects of agricultural activities and land use on climate change through the emission of greenhouse gasses. The framework uses three simulation models to analyse the impact of climate change: a global CGE model, a Philippine CGE model, and a Philippine poverty microsimulation model.
... They assess, for example, the impact of climate change on crop yields and land productivity. In the context of this review, biophysical models were applied mainly to calibrate parameters in economic models [40] or provide data on yields and land productivity [41,42]. Agent-based (AB) models focus on simulating individual actors' decisions. ...
Recent regulations on biofuels require reporting of greenhouse gas (GHG) emission reductions related to feedstock-specific biofuels. However, the inclusion of GHG emissions from land-use change (LUC) into law and policy remains a subject of active discussion, with LUC–GHG emissions an issue of intense research. This article identifies key modelling choices for assessing the impact of biofuel production on LUC–GHG emissions. The identification of these modelling choices derives from evaluation and critical comparison of models from commonly accepted biofuels–LUC–GHG modelling approaches. The selection and comparison of models were intended to cover factors related to production of agricultural-based biofuel, provision of land for feedstock, and GHG emissions from land-use conversion. However, some fundamental modelling issues are common to all stages of assessment and require resolution, including choice of scale and spatial coverage, approach to accounting for time, and level of aggregation. It is argued here that significant improvements have been made to address LUC–GHG emissions from biofuels. Several models have been created, adapted, coupled, and integrated, but room for improvement remains in representing LUC–GHG emissions from specific biofuel production pathways, as follows: more detailed and integrated modelling of biofuel supply chains; more complete modelling of policy frameworks, accounting for forest dynamics and other drivers of LUC; more heterogeneous modelling of spatial patterns of LUC and associated GHG emissions; and clearer procedures for accounting for the time-dependency of variables. It is concluded that coupling the results of different models is a convenient strategy for addressing effects with different time and space scales. In contrast, model integration requires unified scales and time approaches to provide generalised representations of the system. Guidelines for estimating and reporting LUC–GHG emissions are required to help modellers to define the most suitable approaches and policy makers to better understand the complex impacts of agricultural-based biofuel production.
... This feature of CGE models, coupled with their flexibility, has led recently to their increased application to the economic assessment of climate change impacts. A growing CGE literature assesses the costs of single impact categories, e.g., Deke et al. (2002), Darwin and Tol (2001), Bosello et al. (2007) on sea-level rise; Bosello et al. (2006) on health; Tzigas et al. (1997), Darwin (1999), Ronneberger et al. (2009) on agriculture; and Calzadilla et al. (2008) on water scarcity. CGE models have been also used to investigate the interactions of multiple impacts, although the techniques are still in their infancy. ...
This paper contributes to the ongoing debate by addressing the economic valuation of the induced climate change impacts on European biodiversity and ecosystem services. Firstly, we evaluate the impacts of climate change on biodiversity and ecosystem services, building upon the Millennium Ecosystem Assessment (MA) conceptual framework, and encompasses the determination of the role of biodiversity in the creation of provisioning, regulating and cultural services. Secondly, we develop an integrated, hybrid valuation approach to assess the economic magnitude of the involved impacts. Finally, we extend state-of-the-art general equilibrium model by introducing a new 'ecosystem' sector into the underlying "market-based" general equilibrium assessment. The estimation results show that induced climate change impacts on biodiversity and ecosystem services involve significant welfare losses, of about 145-170 billion US$ and therefore autonomous adaptation cannot be invoked as the solution to climate change. Furthermore, the distribution of the impacts varies widely according to the nature of the ecosystem service under consideration and to the geo-climatic region. Thus, the decision of including biodiversity and ecosystem services is expected to be a key component of the future climate policy framework, along with the evaluation of exisiting mitigation and planned adaptation strategies.
... To provide this information, spatial land use allocation approaches are employed to downscale aggregate land demands for large world regions to individual grid cells. Examples of such global scale land use allocation approaches can be found in the Global Forest Model (Rokityanskiy et al., 2007), IMAGE (Bouwman et al., 2006), MagPie (Lotze-Campen et al., 2010), KLUM (Ronneberger et al., 2005(Ronneberger et al., , 2009, MIT-IGSM (Reilly et al., 2012;Wang, 2008), GLOBIO3 (Alkemade et al., 2009), GLOBIOM (Havlik et al., 2011), Nexus land use model (Souty et al., 2012(Souty et al., , 2013, and the Global Land use Model (GLM) (Hurtt et al., 2011). ...
Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns.
... The second one consists in coupling partial equilibrium or computable general equilibrium (CGE) models with spatially explicit models including knowledge on biophysical processes (see e.g. KLUM and GTAP; Ronneberger et al., 2009 or GCAM and AGLU; Brenkert et al., 2003). ...
Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers ; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of demand for biomass for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in detail. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
... On the one hand, there is extensive literature in the field of climate change analysis, where model linkages have a long tradition and are accordingly quite advanced. Here, predominantly CGE models are combined with land use models based for example on GIS (e.g., RONNEBERGER et al. (2006)) or coupled with nitrogen models (e.g., SCHAFER and JACOBY (2003)). 2 This research mostly couples economic models with noneconomic models which is only conditionally helpful for our project and thus excluded from the literature survey in this paper. ...
General and partial equilibrium models are the preferred choice of framework in the analysis of agricultural policies, particularly the WTO negotiations. These models have developed at an astonishing pace in the last thirty years. Three decades ago researchers rightly presented simple spread sheet models established on restricted data bases as the state of the art. Fast advancing computer technology and software thereafter quickly enabled the development of comprehensive models which are based on faster software platforms. Today global multi re-gion general or partial equilibrium models covering surprisingly detailed regional and sectoral information have become common fixtures in the analysis of WTO negotiations.
However, this is certainly not the end of the rope as there is no "one size fits all" model to completely handle WTO issues. Rather some models are perfectly fitted for one question (e.g., How does trade develop after the WTO round?), but do not contribute much to answer others (e.g., Does this reduce the number of farms in Germany?). Furthermore, the scientific community and other clients, particularly policy makers, increasingly ask for results on the WTO negotiations which are not only as detailed as possible, but additionally are also consistent over the global, sectoral and farm level. Accordingly, it is obvious to link models that deliver results consistently disaggregated to various levels and thereby offset each others drawbacks.
Given this background the goal of our paper is to explore the use of model chains with the help of a literature overview that comprises the combination of macro and micro models Here, we concentrate on systems that group different models to disaggregate the supply side of the agricultural sector. Additionally, we identify the challenges and pitfalls we have to face by combining these models.
... This feature of CGE models, coupled with their flexibility, has led recently to their increased application to the economic assessment of climate change impacts. A growing CGE literature assesses the costs of single impact categories, e.g., Deke et al. (2002), Darwin and Tol (2001), Bosello et al. (2007) on sea-level rise; Bosello et al. (2006) on health; Tzigas et al. (1997), Darwin (1999), Ronneberger et al. (2009 on agriculture; and Calzadilla et al. (2008) on water scarcity. CGE models have been also used to investigate the interactions of multiple impacts, although the techniques are still in their infancy. ...
The present study integrates Computable General Equilibrium (CGE) modelling with biodiversity services, proposing a possible methodology for assessing climate-change impacts on ecosystems. The assessment focuses on climate change impacts on carbon sequestration services provided by European forest, cropland and grassland ecosystems and on provisioning services, but provided by forest and cropland ecosystems only. To do this via a CGE model it is necessary to identify first the role that these ecosystem services play in marketable transactions; then how climate change can impact these services; and finally how the economic system reacts to those changes by adjusting demand and supply across sectors, domestically and internationally
... There have been several papers/models that have utilized GTAP-E as a starting point, while developing additional components of the CGE model. Ronneberger et al. (2006) link the model with the global agricultural land-use data base 'KLUM' in their assessment of potential climate change impacts. Rosen (2003) developed a version 'GTAP-EX' by augmenting the industrial disaggregation of the GTAP-E model in order to examine the impacts of climate change on health and sea levels. In short, this model has bee ...
Although CGE models have received heavy usage -- particularly in the analysis of broad-based policies relating to energy, climate and trade, they are often criticized as being insufficiently validated. Key parameters are often not econometrically estimated, and the performance of the model as a whole is rarely checked against historical outcomes. As a consequence, questions frequently arise as to how much faith one can put in CGE results. In this paper, we employ a novel approach to the validation of a widely utilized global CGE model -- GTAP-E. By comparing the variance of model-generated petroleum price distributions - driven by historical demand and supply shocks to the model - with observed five-year moving average price distributions, we conclude that energy demand in GTAP-E is far too price-elastic over this medium run time frame. After incorporating the latest econometric estimates of energy demand and supply elasticities, we revisit the validation question and find the model to perform more satisfactorily. As a further check, we compare a deterministic global general equilibrium simulation, based on historical realizations over the five year period: 2001-2006, during which petroleum prices rose sharply, along with growing global energy demands. As anticipated by the stochastic simulations, the revised model parameters perform much better than the original GTAP-E parameters in this global, general equilibrium context.
Southeast Asia is at a time one of the most vulnerable region to the impacts of a changing climate, with millions of its inhabitants still trapped in extreme poverty without access to energy and employed in climate-sensitive sectors, and, potentially, one of the world’s biggest contributors to global warming in the future. Fortunately, major Southeast Asian countries are also implementing policies to improve their energy and carbon efficiency and are discussing if and how to extend these further. The present study aims to assess the implications for energy consumption, energy intensity and carbon intensity in the Southeast Asia region of a set of short-term and long-term de-carbonization policies characterized by different degrees of ambition and international cooperation. The analysis applies two energy-climate-economic models. The first, the fully dynamic Integrated Assessment model WITCH, is more aggregated in the sectoral and country representation, but provides a detailed technological description of the energy sector. The second, the ICES Computable General Equilibrium model, offers a richer sectoral breakdown of the economy and of international trade patterns, but is less refined in the representation of technology. The joint application of these two complementary models allows the capture of distinct and key aspects of low- carbon development paths in Southeast Asia.
Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.
Questo rapporto nasce dalla collaborazione fra APAT (Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici) e il CMCC (Centro Euro-Mediterraneo per i Cambiamenti Climatici) ed è stato realizzato all'interno del percorso organizzativo per la Conferenza Nazionale sui Cambiamenti Climatici (CNCC), promossa dal Ministero dell'Ambiente e della Tutela del Territorio e del Mare e organizzata da APAT il 12-13 Settembre 2007 a Roma. I principali risultati sono stati presentati nel workshop preparatorio alla CNCC "Le Zone Alpine Italiane: Implicazioni economiche del cambiamento climatico e strategie di adattamento". Saint-Vincent, 2-3 luglio 2007. Commenti e suggerimenti sono benvenuti all'indirizzo economics@apat.it entro la fine di gennaio. © APAT and CMCC 2 Nota introduttiva Questo rapporto nasce da un lavoro di collaborazione fra APAT (Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici) e il CMCC (Centro Euro-Mediterraneo per i Cambiamenti Climatici) realizzato all'interno del percorso organizzativo per la Conferenza Nazionale sui Cambiamenti Climatici (CNCC), promossa dal Ministero dell'Ambiente e della Tutela del Territorio e del Mare e organizzata da APAT il 12-13 Settembre 2007. APAT ha ritenuto importante realizzare uno studio sulla valutazione economica degli impatti dei cambiamenti climatici e delle relative misure di adattamento in Italia, al fine di fornire una prima analisi e alcuni strumenti metodologici su questa tematica.
The main objective of this project is the assessment of vulnerability to climate change impacts and adaptation measures. Therefore, the main aim of this project was to set up an Integrated Assessment Framework (IAF), which allows to analyze which regions in Europe are potentially vulnerable to climate change and to identify which adaptation measures could potentially be promoted at the EU level.
Land use is a key factor to social wellbeing and has become a major component in political negotiations. This paper describes the mathematical structure of the European Forest and Agricultural Sector Optimization Model. The model represents simultaneously observed resource and technological heterogeneity, global commodity markets, and multiple environmental qualities. Land scarcity and land competition between traditional agriculture, forests, nature reserves, pastures, and bioenergy plantations is explicitly captured. Environmental change, technological progress, and policies can be investigated in parallel. The model is well-suited to estimate competitive economic potentials of land based mitigation, leakage, and synergies and trade-offs between multiple environmental objectives.
We investigate the stability of International Environmental Agreements (IEA) by applying game theory. The paper extends further our previous research on farsightedly stable coalitions and preferred farsightedly stable coalitions (Osmani & Tol 2009). The integrated assessment model FUND provides the cost-beneflt payofi functions of pollution abatement for sixteen difierent world regions. The stability concept of D'Aspremont et al. (1983) and farsighted sta- bility of Chwe (1994) are compared. D'Aspremont stability assumes that players are myopic while farsighted stability assumes perfect foresight of the players and predicts which coalitions can be formed when players are farsighted. The D'Aspremont stable coalitions are frequently subsets of farsightedly stable coalitions. Furthermore, farsightedly stable coalitions can be frequently the largest size stable coalition, that game theory without side payments can reach. Additionally, they bring always the biggest improvement in environmental and welfare. All farsightedly stable and D'Aspremont stable coalitions are found and their improvement to environment and welfare are computed.
Global Warming Potentials (GWPs) are evaluated with historical temperature by applying them to convert historical CH4 and N2O emissions to equivalent CO2 emissions. Our GWP analysis is based on an inverse estimation using the Aggregated Carbon Cycle, Atmospheric Chemistry, and Climate Model (ACC2). We find that, for both CH4 and N2O, indices higher than the Kyoto GWPs (100-year time horizon) would reproduce better the historical temperature. The CH4 GWP provides a best fit to the historical temperature when it is calculated with a time horizon of 44 years. However, the N2O GWP does not approximate well the historical temperature with any time horizon. We introduce a new exchange metric, TEMperature Proxy index (TEMP), that is defined so that it provides a best fit to the temperature projection of a given period. By comparing GWPs and TEMPs, we find that the inability of the N2O GWP to reproduce the historical temperature is caused by the GWP calculation methodology in IPCC using simplifying assumptions for the background system dynamics and uncertain parameter estimations. Furthermore, our TEMP calculations demonstrate that indices have to be progressively updated upon the acquisition of new measurements and/or the advancement of our understanding of Earth system processes. © Springer Science + Business Media B.V. 2009.
I define the rate of inequity aversion, distinguishing between the pure rate and the consumption rate. I measure the rate of aversion to inequality in consumption as expressed in the development aid given by rich countries to poor ones between 1965 and 2005. There is an ambiguous relationship between the pure rate of inequity aversion and the consumption rate, driven by the rate of risk aversion. However, for a reasonable choice of the rate of risk aversion, rich countries are shown to be inequity averse, and increasingly so over time. The social cost of carbon is very sensitive to equity weighting and assumptions about the rate of risk and inequity aversion. Estimates of the consumption rate of inequity aversion for recent data suggest that the equity-weighted social cost of carbon is less than 50% larger than the unweighted estimate.
Oil spills are a major cause of environmental concern, in particular for Europe. We extend the traditional approach of assessing the welfare losses for individuals potentially affected by an oil spill, by taking into full account the implications of the probabilistic nature of the related externalities. Our approach differs from the traditional one in three respects: it allows for risk aversion; it adopts an ex-ante rather than an ex-post perspective; it allows for subjective oil-spill probabilities (held by the lay public) more than for expert-assessed probabilities. We illustrate this methodology with a case study on the Aegean Sea.
In this paper a simple strategy for pricing and hedging a swap on the Japanese crude oil cocktail (JCC) index is discussed. The empirical performance of different econometric models is compared in terms of their computed optimal hedge ratios, using monthly data on the JCC over the period January 2000–January 2006. An explanation to how to compute a bid/ask spread and to construct the hedging position for the JCC swap contract with variable oil volume is provided. The swap pricing scheme with backtesting and rolling regression techniques is evaluated. The empirical findings show that the price-level regression model permits one to compute more precise optimal hedge ratios relative to its competing alternatives. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:464–487, 2008
The Matthew effect has that recognition is bestowed on researchers of already high repute. If recognition is measured by citations, this means that often-cited papers or authors are cited more often. I use the statistical theory of the growth of firms to test whether the fame of papers and authors indeed exhibits increasing returns to scale, and confirm this hypothesis for the 100 most prolific economists.
This study uses country-level panel data on consumption in Ireland and seven other OECD countries to examine the evolution of Irish consumption patterns as Ireland underwent rapid macroeconomic growth. Consumption levels obviously increased due to substantially higher incomes, but it is less clear how the shares of different types of goods purchased have changed or whether Ireland's consumption mix has converged with that of other high-income countries. Rankings based on a simple distance measure of consumption similarity suggest that Ireland moved from a "low-income" pattern similar to Portugal or Greece to a "high-income" pattern like that of Canada between 1995 and 2003. Using static and dynamic Almost Ideal Demand System models, we first estimate long- and short-run Irish price and income elasticities for nine categories of commodities between 1976 and 2003. These results provide evidence of substantial habit formation in aggregate consumption. We then estimate a long-run cross-country model covering six aggregate commodity groups between 1975 and 2003. The analysis shows that Ireland's demand parameters remain more similar to those of Greece than to higher-income OECD countries in the sample. Although Ireland has overtaken most other OECD countries in per capita income, it is still converging to a higher-income consumption pattern. We foresee further convergence of Irish expenditure patterns towards a pattern typical of high-income countries.
We used the GTAP-W model - GTAP version 5 with water resources added - to estimate the impact of hypothetical Doha-like liberalization of agricultural trade on water use. Three conclusions emerge. First, the change in regional water use is less than 10 per cent relative to the baseline in 2010, even if agricultural tariffs are reduced by 75 per cent. Second, patterns are non-linear. Water use may go up for partial liberalization, and down for more complete liberalization. This is because different crops respond differently to tariff reductions, but also because trade and competition matter too. Third, trade liberalization tends to reduce water use in water scarce regions, and increase water use in water abundant regions, even though water markets do not exist in most countries.
Using the FUND model, an impact assessment is conducted over the 21st century for rises in sea level of up to 2-m/century and a range of
socio-economic scenarios downscaled to the national level, including the four SRES (IPCC Special Report on Emissions Scenarios)
storylines. Unlike a traditional impact assessment, this analysis considers impacts after balancing the costs of retreat with
the costs of protection, including the effects of coastal squeeze. While the costs of sea-level rise increase with greater
rise due to growing damage and protection costs, the model suggests that an optimum response in a benefit-cost sense remains
widespread protection of developed coastal areas, as identified in earlier analyses. The socio-economic scenarios are also
important in terms of influencing these costs. In terms of the four components of costs considered in FUND, protection dominates, with substantial costs from wetland loss under some scenarios. The regional distribution of costs
shows that a few regions experience most of the costs, especially East Asia, North America, Europe and South Asia. Importantly,
this analysis suggests that protection is much more likely and rational than is widely assumed, even with a large rise in
sea level. This is underpinned by the strong economic growth in all the SRES scenarios: without this growth, the benefits
of protection are significantly reduced. It should also be noted that some important limitations to the analysis are discussed,
which collectively suggest that protection may not be as widespread as suggested in the FUND results.
The integrated assessment model FUND 2.8n is applied in an assessment to estimate the magnitude of the general market and non-market impacts of temperature changes
caused by a possible shutdown of the thermohaline circulation (THC). The monetized impacts of this change in environmental
conditions are determined for 207 individual countries for two scenarios: one warming scenario in which the THC weakens but
remains intact, and another in which the THC breaks down. Eight different response patterns are identified. The dominant pattern
is that a THC shutdown has an offsetting effect on the underlying warming trend. Depending on whether the impacts of warming
are initially beneficial or detrimental, the economic effects of a THC shutdown show distinct regional variability. Key economic
sectors affected are water resources and energy consumption, as well as cardiovascular and respiratory diseases among health
impacts. The maximum national impact of a shutdown of the THC turns out to be of the magnitude of a few per cent of GDP, but
the average global impact is much smaller. The results indicate that the temperature effect of a THC shutdown does not create
an insurmountable economic threat on a global scale, but may cause severe damages to individual countries. However, a consideration
of other climatic impacts such as precipitation and sea level changes is likely to alter the identified trends in economic
development.
The h-index is a recent but already quite popular way of measuring research quality and quantity. However, it discounts highly-cited
papers. The g-index corrects for this, but it is sensitivity to the number of never-cited papers. Besides, h- or g-index-based
rankings have a large number of ties. Therefore, this paper introduces two new indices, and tests their performance for the
100 most prolific economists. A researcher has a t-number (f-number) of t (f) if t (f) is the largest number for which it holds that she has t (f) publications for which the geometric (harmonic) average number of citations is at least t (f). The new indices overcome the shortcomings of the old indices.
Hitherto the task of valuing differences in environmental quality arising from air pollution and noise nuisance has been carried out mainly by using the hedonic price technique. This paper proposes a different approach to derive information on individual preferences for local environmental quality. It analyses data drawn from the German socio-economic panel in an attempt to explain differences in self-reported levels of well-being in terms of environmental quality. Mindful of existing research a large number of other explanatory variables are included to control for socio-demographic differences, economic circumstances as well as neighbourhood characteristics. Differences in local air quality and noise levels are measured by how much an individual feels affected by air pollution or noise exposure in their residential area. The evidence suggests that even when controlling for a range of other factors higher local air pollution and noise levels significantly diminish subjective well-being. But interestingly differences in perceived air and noise pollution are not capitalised into differences in house prices.
Using a simple model designed for transparency but nonetheless calibrated to support the much-quoted damage estimates of the Stern Review of the Economics of Climate Change, we demonstrate significant sensitivity of those results to assumptions about the pure rate of time preference, the time horizon, and the rates of risk and equity aversion used to compute certainty- and equity-equivalent annuities. Most importantly, we demonstrate enormous sensitivity to presumed constant regional vulnerability and underlying assumptions about adaptive capacity. Manipulation of any of these parameters one at a time across reasonable ranges can diminish damage estimates by as much as 84% or, in the case of extending the time horizon with the Review's low discount rate, increase damage estimates by 900%. We also confirm the usual result that limiting atmospheric concentrations to specific benchmarks above 400 ppm cannot eliminate all damages. Nonetheless, we applaud the Stern Review author team for reconfirming that the climate problem can be approached productively as an economic problem whose solutions can be explored with the tools of decision analysis.
An important barrier towards the introduction of fuel cell vehicles running on hydrogen is the lack of widespread refueling infrastructure. The niche of buses for public transport, taxis and deliverers with a local application area might not be large enough to generate the reductions of fuel cell vehicle costs that are necessary for a general technology switch. Thus, fuel availability at trunk roads probably plays a crucial role in generating demand for these also from private consumers. In this paper, we assume that consumers are more likely to consider buying a fuel cell vehicle the more frequently they are exposed to hydrogen refueling opportunities on long distant trips. We introduce a tool to test different small-scale initial distributions of hydrogen outlets within the German trunk road system for their potential success to generate a large-scale adoption of fuel cell vehicles. The tool makes use of agent-based trip modeling and geographic information system supported spatial modeling. We demonstrate its potentials by testing a ring shaped distribution of hydrogen outlets at highway filling stations. We find that the structure of an optimized initial distribution of filling stations depends on what drivers consider a sufficiently small distance between refueling opportunities.
Agriculture is the largest consumer of freshwater resources – around 70 percent of all freshwater withdrawals are used for food production. These agricultural products are traded internationally. A full understanding of water use is, therefore, impossible without understanding the international market for food and related products, such as textiles. Based on the global general equilibrium model GTAP-W, we offer a method for investigating the role of green (rain) and blue (irrigation) water resources in agriculture and within the context of international trade. We use future projections of allowable water withdrawals for surface water and groundwater to define two alternative water management scenarios. The first scenario explores a deterioration of current trends and policies in the water sector (water crisis scenario). The second scenario assumes an improvement in policies and trends in the water sector and eliminates groundwater overdraft world-wide, increasing water allocation for the environment (sustainable water use scenario). In both scenarios, welfare gains or losses are not only associated with changes in agricultural water consumption. Under the water crisis scenario, welfare not only rises for regions where water consumption increases (China, South East Asia and the USA). Welfare gains are considerable for Japan and South Korea, Southeast Asia and Western Europe as well. These regions benefit from higher levels of irrigated production and lower food prices. Alternatively, under the sustainable water use scenario, welfare losses not only affect regions where overdrafting is occurring. Welfare decreases in other regions as well. These results indicate that, for water use, there is a clear trade-off between economic welfare and environmental sustainability.
A bioeconomic model of key fisheries of the Barents Sea is run with scenarios generated by an earth system model of intermediate complexity to assess how the Barents Sea fisheries of cod (Gadus morhua) and capelin (Mallotus villosus) are affected by changes in the Atlantic thermohaline circulation (THC) arising from anthropogenic climate change. Changes in hydrographic conditions have an impact on recruitment success and survival rates, which constitute a lasting effect on the stocks. The economic development of the fisheries is determined for the 21st century, considering a purely stock size based and a coupled stock size-hydrography based harvesting strategy. Results show that a substantial weakening of the THC leads to impaired cod stock development, causing the associated fishery to become unprofitable in the long run. Simultaneous improvements in capelin stock development help the capelin fishery, but are insufficient to offset the losses incurred by the cod fishery. A comparison of harvest strategies reveals that in times of high variability in stock development, coupled stock size-hydrography based management leads to more stable economic results of these fisheries than the stock size based fishing strategy.
Using a simple model designed for transparency but nonetheless calibrated to support the much-quoted damage estimates of the Stern Review of the Economics of Climate Change, we demonstrate significant sensitivity of those results to assumptions about the pure rate of time preference, the time horizon, and the rates of risk and equity aversion used to compute certainty- and equity-equivalent annuities. Most importantly, we demonstrate enormous sensitivity to presumed constant regional vulnerability and underlying assumptions about adaptive capacity. Manipulation of any of these parameters one at a time across reasonable ranges can diminish damage estimates by as much as 84% or, in the case of extending the time horizon with the Review's low discount rate, increase damage estimates by 900%. We also confirm the usual result that limiting atmospheric concentrations to specific benchmarks above 400 ppm cannot eliminate all damages. Nonetheless, we applaud the Stern Review author team for reconfirming that the climate problem can be approached productively as an economic problem whose solutions can be explored with the tools of decision analysis. © 2008 Elsevier Ltd. All rights reserved.
Increasing water scarcity combined with an increasing demand for food and water for irrigation call for a careful revision of water use in agriculture. Currently, less than 60% of all the water used for irrigation is effectively used by crops. Based on the new version of the GTAP-W model we analyze the effect of potential water savings and the welfare implications of improvements in irrigation efficiency worldwide. The results show that a water policy directed to improve irrigation efficiency led to global and regional water savings, but it is not beneficial for all regions. The final effect on regional welfare will depend on the interaction of several different causes. For instance, higher irrigation efficiency changes opportunity costs and reverses comparative advantages, modifying regional trade patterns and welfare. For water-stressed regions the effects on welfare are mostly positive. For nonwater scarce regions the results are more mixed and mostly negative. The results show that exports of virtual water are not exclusive of water abundant regions. © 2010 International Association of Agricultural Economists.
Export Date: 8 August 2009
Source: Scopus
One characteristic of a Geographic Information System (GIS) is that it addresses the necessity to handle a large amount of data at multiple scales. Lands span over an area greater than 15 million km2 all over the globe and information types are highly variable. In addition, multi-scale analyses involve both spatial and temporal integration of datasets deriving from different sources. The currently worldwide used system of latitude and longitude coordinates could avoid limitations in data use due to biases and approximations. In this article a fast and reliable algorithm implemented in Arc Macro Language (AML) is presented to provide an automatic computation of the surface area of the cells in a regularly spaced longitude-latitude (geographic) grid at different resolutions. The approach is based on the well-known approximation of the spheroidal Earth's surface to the authalic (i.e. equal-area) sphere. After verifying the algorithm's strength by comparison with a numerical solution for the reference spheroidal model, specific case studies are introduced to evaluate the differences when switching from geographic to projected coordinate systems. This is done at different resolutions and using different formulations to calculate cell areas. Even if the percentage differences are low, they become relevant when reported in absolute terms (hectares).
A rational, successive g-index is proposed, and applied to economics departments in Ireland. The successive g-index has greater discriminatory power than the successive h-index, and the rational index performs better still. The rational, successive g-index is also more robust to difference in department size.
We use a panel dataset of UK workers, combined with risk data at the four-digit industry level, to look for evidence of compensating wage differentials for workplace risk. We discuss various econometric problems associated with the hedonic wage approach, namely the instability of the estimates to specification changes, unobserved heterogeneity and endogeneity. We find evidence of significant compensating wage differentials and Values of a Statistical Life (VSL) figures only under the most restrictive assumptions, i.e. when we assume that there is no unobserved heterogeneity and that all regressors are exogenous. However, the VSL values are large and vary dramatically with the inclusion or exclusion of industry and/or occupation dummies, as well as with the addition of nonfatal risk. When we specify models that allow for heterogeneity and endogeneity of risk and of other regressors, we find no evidence of compensating wage differentials. We conclude that if compensating differentials for risk exists, econometric problems and the changing nature of labour markets prevent us from observing them. We also conclude that models and techniques for panel data that account for unobserved heterogeneity and endogeneity present a completely different picture about compensating wage differentials than that inferred by most wage-risk studies, which have generally used single cross-sections of data.
This paper analyses the potential welfare gains of introducing a technology transfer from Annex I to non-Annex I in order to mitigate greenhouse gas emissions. Our analysis is based on a numerical general equilibrium model for a world-economy comprising two regions; North (Annex I) and South (non-Annex I). In a cooperative equilibrium, a technology transfer from the North to the South is clearly desirable from the perspective of a [`]global social planner', since the welfare gain for the South outweighs the welfare loss for the North. However, if the regions do not cooperate, then the incentives to introduce the technology transfer appear to be relatively weak from the perspective of the North; at least if we allow for Southern abatement in the pre-transfer Nash equilibrium. Finally, by adding the emission reductions associated with the Kyoto agreement, our results show that the technology transfer leads to higher welfare in both regions.
1] Humans have transformed the surface of the planet through agricultural activities, and today, $12% of the land surface is used for cultivation and another 22% is used for pastures and rangelands. In this paper, we have synthesized satellite-derived land cover data and agricultural census data to produce global data sets of the distribution of 18 major crops across the world. The resulting data are representative of the early 1990s, have a spatial resolution of 5 min. ($10 km), and describe the fraction of a grid cell occupied by each of the 18 crops. The global crop data are consistent with our knowledge of agricultural geography, and compares favorably to another existing data set that partially overlaps with our product. We have also analyzed how different crops are grown in combination to form major crop belts throughout the world. Further, we analyzed the patterns of crop diversification across the world. While these data are not sufficiently accurate at local scales, they can be used to analyze crop geography in a regional-to-global context. They can also be used to understand the global patterns of farming systems, in analyses of food security, and within global ecosystem and climate models to understand the environmental consequences of cultivation.
Energy is an important commodity in many economic activities. Its usage affects the environment via CO2 emissions and the Greenhouse Effect. Modeling the energy-economyenvironment-trade linkages is an important objective in applied economic policy analysis. Previously, however, the modeling of these linkages in GTAP has been incomplete. This is because energy substitution, a key factor in this chain of linkages, is absent from the standard model specification. This technical paper remedies this deficiency by incorporating energy substitution into the standard GTAP model. It begins by first reviewing some of the existing approaches to this problem in contemporary CGE models. It then suggests an approach for GTAP which incorporates some of these desirable features of energy substitution. The approach is implemented as an extended version of the GTAP model called GTAP-E. In addition, GTAP-E incorporates carbon emissions from the combustion of fossil fuels and this revised version of GTAP-E provides for a mechanism to trade these emissions internationally as well as domestically. The policy relevance of GTAP-E in the context of the existing debate about climate change is illustrated by some illustrative simulations of the implementation the European emissions trading scheme in 2005. It is hoped that the proposed model will be used by individuals in the GTAP network who may not be themselves energy modelers, but who require a better representation of the energy-economy-environmental linkages than is currently offered in the standard GTAP model.
This paper describes the GTAP Land Use Data Base designed to support integrated assessments of the potential for greenhouse gas mitigation. It disaggregates land use by agro-ecological zone (AEZ). To do so, it draws upon global land cover data bases, as well as state-of-the-art definition of AEZs from the FAO and IIASA. Agro-ecological zoning segments a parcel of land into smaller units according to agro-ecological characteristics, including: precipitation, temperature, soil type, terrain conditions, etc. Each zone has a similar combination of constraints and potential for land use. In the GTAP-AEZ Data Base, there are 18 AEZs, covering six different lengths of growing period spread over three different climatic zones. Land using activities include crop production, livestock raising, and forestry. In so doing, this extension of the standard GTAP Data Base permits a much more refined characterization of the potential for shifting land use amongst these different activities. When combined with information on greenhouse gas emissions, this data base permits economists interested in integrated assessment of climate change to better assess the role of land use change in greenhouse gases mitigation strategies.
Economic assessments of the impacts of climate change are rare. Even rarer are papers on the higher order economic impacts. The paper by Claudia Kemfert (2002) is therefore welcome. Most economic impact studies use direct costs as an approximation of welfare losses. According to the direct cost method, a welfare loss is approximated by price times quantity, where the quantity is the physical impact of climate change (see Pearce et al., 1996, and Smith et al., 2001, for an overview). The direct cost method ignores that the impact may change the price (the partial equilibrium effect), that changes in one market may have effects on other markets (the general equilibrium effect), and that climate change may alter investments (the growth effect). Using a dynamic computable general equilibrium model, Kemfert is able to look at all economic effects of climate change impacts on nature, human health, forestry, water resources, and energy consumption. Only four other papers use a similar methodology. Scheraga et al. (1993) use now outdated climate change scenarios and climate change impact studies, and only sketch the assumptions and results. The papers by Darwin et al. (1995) and Darwin and Tol (2001) are limited to the impacts on agriculture and coastal zone, respectively; the model used there is a static CGE.
En la UE se ha estimado que los costes de la congesti�n representan el 2% de su PIB y que el coste de la poluci�n del aire y ruido supera el 0,6% del PIB, siendo alrededor del 90% de los mismos ocasionados por el transporte terrestre. Ante este hecho y el continuo aumento de la demanda del transporte privado frente al p�blico para los desplazamientos, muchos abogan por una conjunci�n de medidas tanto restrictivas como alternativas al uso del coche. Dentro de las primeras se encuentra el establecimiento de un peaje o una tarifa por el uso de las carreteras, medida que aunque desde el punto de vista de la Teor�a Econ�mica es la manera m�s eficiente para corregir el fallo de mercado que supone la congesti�n, desde la visi�n de pol�ticos y del p�blico no goza de gran aceptaci�n. En este trabajo se pretende hacer una simulaci�n de los efectos que tendr�a sobre el bienestar social de la implantaci�n de una medida de este tipo en la Bah�a de C�diz. In the European Union it has been estimated that the congestion cost are the 2% of the gross domestic product and the cost of pollution and noise is over 0,6%, olso it is known that the 90% of this cost are caused by overland transport. For this reason and for the always increasing demand of private transport, there are professionals who thinks that the solution have to be restrictive measures added to alternatives to the car. road pricing is a restrictive measures that for the economic theory is the most efficient way to solve congestion cost but for politicians and user of transport is not always accepted. In this study we are going to simulate road pricing for commuters in the Bah�a of C�diz and then it will be estimated welfare effects.
We test the hypothesis that models should be coupled to accurately project the impacts of climate change on the agro-economic and agro-environmental system. We couple the LPJ-C global dynamic vegetation model for crops to the global agricultural land-use model KLUM. Potential crop yields, from LPJ-C, and crop prices drive the land-use decisions; cropland allocation from KLUM scale the carbon entering the soil litter pool in LPJ-C. Through the crop prices, economic effects are projected directly on the carbon cycle. Global change impacts are projected on the agricultural sector and can be economically assessed. The coupled model performs reasonably well for the observed climate and prices for 6 crops in Europe on a 0.5x0.5 longitude-latitude grid. We estimate the impact of climate change on agriculture in Europe for A1 and B2 scenarios of the IPCC. The coupled model reproduces the essential processes and interactions of the modeled system. Simulations with the uncoupled models are used to estimate the accuracy added by the model coupling. Sign and size of the biases from ignoring the feedbacks are substantial for some parameters, and particularly their spatial pattern, while for other parameters (e.g., the European total of soil organic carbon) biases are negligible. The answer to the question “Should models be coupled?” is “It depends on what you’re interested in”.
In this paper we investigate the potential production and implications of a global biofuels industry. We develop alternative approaches to consistently introduce land as an economic factor input and in physical terms into a computable general equilibrium framework. The approach allows us to parameterize biomass production consistent with agro-engineering information on yields and a "second generation" cellulosic biomass conversion technology. We explicitly model land conversion from natural areas to agricultural use in two different ways: in one approach we introduced a land supply elasticity based on observed land supply responses and in the other approach we considered only the direct cost of conversion. We estimate biofuels production at the end of the century could reach 221 to 267 EJ in a reference scenario and 319 to 368 EJ under a global effort to mitigate greenhouse gas emissions. The version with the land supply elasticity allowed much less conversion of land from natural areas, forcing intensification of production, especially on pasture and grazing land, whereas the pure conversion cost model led to significant deforestation. These different approaches emphasize the importance of somehow reflecting the non-market value of land more fully in the conversion decision. The observed land conversion response we estimate may be a short turn response that does not fully reflect the effect of long run pressure to convert land if rent differentials are sustained over 100 years.
This paper describes two global models: (1) an Agricultural Demand Model which is used to compute the consumption and demand for commodities that define land use in 13 world regions; and, (2) a Land Cover Model, which simulates changes in land cover on a global terrestrial grid (0.5° latitude by 0.5° longitude) resulting from economic and climatic factors. Both are part of the IMAGE 2.0 model of global climate change. The models have been calibrated and tested with regional data from 1970–1990. The Agricultural Demand Model can approximate the observed trend in commodity consumption and the Land Cover Model simulates the total amount of land converted within 13 world regions during this period. Some degree of the spatial variability of deforestation has also been captured by the simulation. Applying the model to a “Conventional Wisdom” scenario showed that future trends of land conversions could be strikingly different on different continents even though a consistent scenario (IS92a from the IPCC) was used for assumptions about economic growth and population. Sensitivity analysis indicated that future land cover patterns are especially sensitive to assumed technological improvements in crop yield and computed changes in agricultural demand.
Climate change could have far‐reaching effects on agriculture, trade patterns, development and food security. This article examines quantitatively the impact of climate change on food production and numbers at risk of hunger, allowing for factors such as latitude and farming practice. Globally, a doubling of atmospheric carbon dioxide (CO2) level may lead to a small to moderate decrease in food production, but developing countries would bear the brunt of the consequences. To prevent widespread hunger, the agricultural industry should develop management programmes for hot and dry conditions, in conjunction with measures to slow the growth of the human population and reduce emissions of greenhouse gases.
This paper describes two global models: (1) an Agricultural Demand Model which is used to compute the consumption and demand for commodities that define land use in 13 world regions; and, (2) a Land Cover Model, which simulates changes in land cover on a global terrestrial grid (0.5 latitude by 0.5 longitude) resulting from economic and climatic factors. Both are part of the IMAGE 2.0 model of global climate change. The models have been calibrated and tested with regional data from 1970–1990. The Agricultural Demand Model can approximate the observed trend in commodity consumption and the Land Cover Model simulates the total amount of land converted within 13 world regions during this period. Some degree of the spatial variability of deforestation has also been captured by the simulation. Applying the model to a Conventional Wisdom scenario showed that future trends of land conversions could be strikingly different on different continents even though a consistent scenario (IS92a from the IPCC) was used for assumptions about economic growth and population. Sensitivity analysis indicated that future land cover patterns are especially sensitive to assumed technological improvements in crop yield and computed changes in agricultural demand.
This paper describes the IMAGE 2.0 model, a multi-disciplinary, integrated model designed to simulate the dynamics of the global society-biosphere-climate system. The objectives of the model are to investigate linkages and feedbacks in the system, and to evaluate consequences of climate policies. Dynamic calculations are performed to year 2100, with a spatial scale ranging from grid (0.50.5 latitudelongitude) to world regional level, depending on the sub-model. The model consists of three fully linked sub-systems: Energy-Industry, Terrestrial Environment, and Atmosphere-Ocean. The Energy-Industry models compute the emissions of greenhouse gases in 13 world regions as a function of energy consumption and industrial production. End use energy consumption is computed from various economic/demographic driving forces. The Terrestrial Environment models simulate the changes in global land cover on a gridscale based on climatic and economic factors, and the flux of CO2 and other greenhouse gases from the biosphere to the atmosphere. The Atmosphere-Ocean models compute the buildup of greenhouse gases in the atmosphere and the resulting zonal-average temperature and precipitation patterns. The fully linked model has been tested against data from 1970 to 1990, and after calibration can reproduce the following observed trends: regional energy consumption and energy-related emissions, terrestrial flux of CO2 and emissions of greenhouse gases, concentrations of greenhouse gases in the atmosphere, and transformation of land cover. The model can also simulate long term zonal average surface and vertical temperatures.
Land use plays a vital role in the earth system: it links human decision-making to the terrestrial environment and is both driver and target of global environmental changes. However, decisions about how much land to use where and for what purpose (and the related consequences) are still poorly understood. This deficit is in contrast to the fundamental need for global analysis of future land-use change to answer pressing questions concerning, e.g. future food security, biodiversity and climate mitigation and adaptation.
The impact of globalization on trade, production and land use was key to the Doha development round. Although many studies have shown the positive influence of liberalization on trade and production, the environmental questions remain unanswered in most studies. Here we present a combination of an economic (Global Trade Analysis Project, GTAP) and a biophysical (IMAGE) model. The methodology is innovative as it combines state of the art knowledge from both the economic and biophysical worlds. First, the treatment of agriculture and land use is improved in the economic model. For example, information from the OECD Policy Evaluation Model (PEM) was incorporated to improve the agricultural production structure and a new land allocation methodology was introduced using regional land supply curves to facilitate the conversion of idle land to productive land while giving consideration to the level of intensification. Secondly, the adapted economic model is linked to the biophysical modeling framework IMAGE allowing feedbacks of detailed heterogeneous information on land productivity to the economic framework. While often a rather pessimistic picture is portrayed for future developments of the agricultural sector in the EU (especially in liberalizing scenarios), our results show that no drastic decrease in land for agricultural purposes is expected for the EU25 the coming 30 years, since the global food market will experience an increase in demand because of expected growth in GDP and population in many developing countries. Moreover, the negative impact of liberalization of agricultural policies on European agricultural land use is small because on the one hand loss in EU's competitiveness leads partly to extensification instead of land abandonment, and secondly, the recent agricultural reforms of the EU changed the protection from market to income support which has less production effects. Changes in land use will be more outspoken in developing countries like Africa.
In this paper, a new methodology for global estimation of crop productivity is proposed. This methodology integrates Erosion Productivity Impact Calculator (EPIC) model with Geographic Information System (GIS) and Inference Engine (IE) technique. EPIC was developed by USDA to analyze the relationship between soil erosion and agricultural productivity just at field level. With the integration of GIS, EPIC can be extended to the application of global or regional level. In this integration, IE is developed to determine possible crop combinations, the optimum starting and ending dates of growth cycle for each crop type and grid cell, in order to ensure best possible crop yields for both rain-fed and irrigated conditions. A case of global crop productivity estimation is tested with GIS-based EPIC in 2000. National averages are computed to be comparable to yields in FAO statistics. The comparison indicates that the GIS-based EPIC is able to simulate crop productivity at global level. In addition, with the global climate change data provided by the Intergovernment Panel on Climate Change (IPCC) from the first version of the Canadian Global Coupled Model (CGCM1), GIS-based EPIC is run for scenarios of future climate in the year of 2010, 2020, 2030, 2040, and 2050 to predict the effects of global warming on main crop yields. Results show the global warming will be harmful for most of the countries, and an efficient adaptation to alternative climates tends to reduce the damages.
One hundred and three estimates of the marginal damage costs of carbon dioxide emissions were gathered from 28 published studies and combined to form a probability density function. The uncertainty is strongly right-skewed. If all studies are combined, the mode is $2/tC, the median $14/tC, the mean $93/tC, and the 95 percentile $350/tC. Studies with a lower discount rate have higher estimates and much greater uncertainties. Similarly, studies that use equity weighing, have higher estimates and larger uncertainties. Interestingly, studies that are peer-reviewed have lower estimates and smaller uncertainties. Using standard assumptions about discounting and aggregation, the marginal damage costs of carbon dioxide emissions are unlikely to exceed $50/tC, and probably much smaller.
Integrated Coastal Zone Management (ICZM) forms a generally accepted concept to ensure sustainable development in the coastal zone. The implementation of the ICZM framework as formulated, e.g. by the World Coast Conference, is often constrained by the political system within which it should be applied. This is the case in the People's Republic of China. This study takes a political science perspective based on approaches inherent in neo-institutional and administrative theories. This way the relevant political structures are explained and the impacts that the transformation of the socio-economic system had on institutions are located. This is extended by the reflection of related political power distribution. This part of the analysis mainly contains existing knowledge on (integrated) CZM in China but evaluates it from a so far neglected point of view. The second part of the paper is taking the successful local ICZM approach of Xiamen and a proposed approach for Shanghai as an example to show that the adaptation of a working approach to other parts of the country is impossible without modifications to the organizational structures of decision-making and implementation. So far the literature emphasizes mostly modifications in content. An important reason for structural elements being comparably important is the choice of ICZM issues and the local power distribution. It furthermore shows that these are also the determining factors obstructing the upscaling of a local approach to the national level, a fact, which constrains the formulation of national guidelines in China and leaves only the bottom-up alternative of introducing ICZM to China—a hard task that leaves a disproportional responsibility to the local governmental level.
Adaptation to climate change and mitigation of climate change are policy substitutes, as both reduce the impacts of climate change. Adaptation and mitigation should therefore be analysed together, as they indeed are, albeit in a rudimentary way, in cost-benefit analyses of emission abatement. However, adaptation and mitigation are done by different people operating at different spatial and temporal scales. This hampers analysis of the trade-offs between adaptation and mitigation. An exception is facilitative adaptation (enhancing adaptive capacity), which, like mitigation, requires long-term policies at macro level. Facilitative adaptation and mitigation not only both reduce impacts, but they also compete for resources.
This paper offers a practically motivated method for evaluating systems’ abilities to handle external stress. The method is designed to assess the potential contributions of various adaptation options to improving systems’ coping capacities by focusing attention directly on the underlying determinants of adaptive capacity. The method should be sufficiently flexible to accommodate diverse applications whose contexts are location specific and path dependent without imposing the straightjacket constraints of a “one size fits all” cookbook approach. Nonetheless, the method should produce unitless indicators that can be employed to judge the relative vulnerabilities of diverse systems to multiple stresses and to their potential interactions. An artificial application is employed to describe the development of the method and to illustrate how it might be applied. Some empirical evidence is offered to underscore the significance of the determinants of adaptive capacity in determining vulnerability; these are the determinants upon which the method is constructed. The method is, finally, applied directly to expert judgments of six different adaptations that could reduce vulnerability in the Netherlands to increased flooding along the Rhine River.
This paper describes the theoretical and empirical features of G-Cubed, a multi-country, multi-sector intertemporal general equilibrium model. G-Cubed combines the attractive features of macroeconometric models and computable general equilibrium models into a unified framework. It has been used to study a variety of topics including: greenhouse gas policy, trade liberalization, tax policy and macroeconomic policy. This paper is a technical description of the model's design.
A bioeconomic simulation model of the two interacting fish species cod (Gadus morhua) and capelin (Mallotus villosus) and their fisheries is presented and applied to assess the consequences of changes in the population dynamics of these important fish stocks in the Barents Sea. In each scenario, the population dynamics of the fish species are changed by reducing the reproduction-induced productivities and/or the carrying capacities. Stock sizes and landings of fish are calculated for each fishing period, and the net present values of profits from fishing are determined for time periods prior to and after the change in population dynamics. Results show that reduced growth rates or carrying capacities lead to lower stock levels and consequently to smaller catches. There is only a small short-term economic impact on the fisheries, but the long-term consequences are pronounced. In some cases, greater fishing activity in the first few years after the change ill population dynamics causes harvests to remain stable despite diminishing stock sizes. This stabilizes the returns from fishing in the short term, but veils the apparent negative long-term impact on the fisheries resulting from adversely affected stock dynamics. (c) 2006 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.
Economic analyses of emission permit trading have mainly looked into the cost effectiveness and cost saving potential of international permit trading compared to a pure national trading system. Little attention has been drawn to the environmental effectiveness of international trade in greenhouse gas emission permits. Less environmental ambitiousness caused by relatively low emission reduction targets in some countries might lower the permit price on the international market, but might also reduce environmental effectiveness. This paper considers the question under what conditions domestic markets of emission permits would and should merge to become an international market when environmental integrity has to be preserved and how environmental and cost effectiveness could be combined. In a two-country model three different policy instruments of the importing country are examined, namely a price instrument (tariff) and two quantity instruments (discount and import quota). All instruments restrict trade. The importing country (and regulator) prefers an import tariff and an import quota to a carbon discount. If the exporting country releases additional permits, the importing country should not try to keep total emissions constant, as
World Development Indicators, the World Bank's respected statistical publication presents the most current and accurate information on global development on both a national level and aggregated globally. This information allows readers to monitor the progress made toward meeting the goals endorsed by the United Nations and its member countries, the World Bank, and a host of partner organizations in September 2001 in their Millennium Development Goals. The print edition of World Development Indicators 2005 allows you to consult over 80 tables and over 800 indicators for 152 economies and 14 country groups, as well as basic indicators for a further 55 economies. There are key indicators for the latest year available, important regional data, and income group analysis. The report contains six thematic presentations of analytical commentary covering: World View, People, Environment, Economy, States and Markets, and Global Links.
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