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This document provides a method module for the assessment of the true price of an agricultural or horticultural product, within the public-private partnership ‘Echte en Eerlijke Prijs’. It contains the key methodological aspects to measure and value three impacts of agri-food products and value chains: air, soil and water pollution.

Van Oord Dredging and Marine Contracters asked Wageningen Environmental Research for an assessment of their Supply Chain Sustainability Program, focused in particular on consistency with international environmental agendas and on possible, unforeseen effects. The Integral Conceptual Framework for a Circular Climate-Neutral Society has been used for the assessment. The assessment concludes that the program is adequate. It is well aligned with international agendas and will have a positive impact on air pollution, greenhouse gas emissions and plastic use. However, the issue of biodiversity receives too little attention in the program. It is therefore recommended in the short term to include biodiversity indicators in the monitoring of the program so that long-term actions can be linked to this. Van Oord Dredging and Marine Contracters heeft Wageningen Environmental Research gevraagd om een beoordeling van en een advies over hun Supply Chain Sustainability Program. Het gaat hierbij vooral om de aansluiting op internationale agenda’s en om eventuele onvoorziene effecten. Voor de beoordeling is gebruikt gemaakt van het Integral Conceptual Framework for a Circular Climate-Neutral Society. De beoordeling leidt tot de conclusie dat het een adequate strategie is die goed spoort met internationale agenda’s en een positief effect zal hebben op luchtvervuiling, uitstoot van broeikasgassen en gebruik van plastic. Het thema biodiversiteit krijgt echter te weinig aandacht in de strategie. Daarom wordt aanbevolen voor de korte termijn om indicatoren voor biodiversiteit op te nemen in de monitoring van de strategie, zodat hieraan op lange termijn acties kunnen worden verbonden

Climate change mitigation pathways have highlighted both the critical role of land-use emissions, and the potential use of biofuels as a low-emission energy carrier. This has led to concerns about the emission mitigation potential of biofuels, particularly related to indirect land-use change (ILUC). This arises when the production of biofuels displaces the production of land-based products elsewhere, either directly or via changes in crop prices, leading to indirect greenhouse gas (GHG) emissions. We review a large body of literature that has emerged on ILUC assessment and quantification, highlighting the methodologies employed, the resultant emission factors, modeled dynamics driving ILUC, and the uncertainty therein. Our review reveals that improvements in ILUC assessment methods have failed to reduce uncertainty and increase confidence in ILUC factors, instead making marginal improvements to economic models. Thus, while assessments have highlighted measures that could reduce ILUC, it is impossible to control or determine the actual ILUC resulting from biofuel production. This makes ILUC a poor guiding principle for land-use and climate policy, and does not help with the determination of the GHG performance of biofuels. Instead climate and land-use policy should focus on more integrated protection of terrestrial resources, covering all land-use-related products.

This report generates estimates for the effect of non-tariff measures (NTMs) on trade unit values. Adding to the latest development of the NTM analysis, we account for different types of NTMs for pairs of countries/regions. Our estimates thus provide new insights about the bilaterally distinct effect of specific NTMs. This is particularly interesting for policy makers that like to know which types of measures are relevant for trade from or to specific countries/regions and whether they are trade-hampering or trade-facilitating. We elaborate on the estimation of the price effect (measured in trade unit values) vis-à-vis the standard gravity on trade quantities (measured in trade value). A panel dataset (2012-2015) using the last releases of trade unit values (Berthou & Emlinger, 2011) and UNCTAD NTMs global database is built, and alternative approaches to account for the distinct bilateral impact are tested on beef, white meat (poultry) and milk. The focus is on trade between the EU member states and relevant regions with which the EU is negotiating or has just completed trade agreements: MERCOSUR, ASEAN, Japan and New Zealand. In this report, we do not implement the specific Ad-valorem equivalents (AVE) estimates for NTMs in a simulation model but rather provide a literature review that elaborates on the different approaches to depict NTMs in simulation models. The next step would be the application of the AVEs estimated in a simulation model in order to gauge the economy-wide effects of the respective NTMs under review., JRC.D.4-Economics of Agriculture

It is commonly recognized that large uncertainties exist in modelled biofuel-induced indirect land-use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land-use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic - land-use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land-use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell-based (5 × 5 km2) probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land-use change, such as greenhouse gas emissions.

As a key adjunct to the process of policy formulation, market models are often called upon to quantify possible opportunities and threats. Significant improvements in computational power, database and modelling capacity contributed to a widespread usage of computable general equilibrium (CGE) frameworks in an array of policy fields. Curiously, however, in contrast to modelling efforts in, for example, the biophysical sciences, CGE model findings are seldom subjected to any systematic validation procedure. A cursory review of the literature reveals isolated single country CGE model validation exercises, although with a dearth of available data, there is a paucity of equivalent studies which implement such a procedure in a global CGE context. This paper takes a first step in this direction by proposing a systematic methodological procedure for evaluating global CGE model performance, using a consistent macro and sectoral historical time series dataset and validation statistics taken from the biophysical literature. Focusing on sectoral output trends, the results show that model simulation performs better than extrapolation from past trends. Notwithstanding, simulation error remains high in some sectors, particularly in small economies which have undergone rapid growth. Further econometric tests reveal that simulation error is mainly caused by sector specific factors rather than country specific characteristics. The latter observation is consistent with previous research on productivity specifications in CGE models, which in concert with the validation techniques proposed in this paper, serves as a promising avenue of future research.

This article analyzes the consequences of enhanced biofuel demand in regions and countries of the world that have announced plans to implement or expand on biofuel policies. The analysis considers not only mandatory blending targets for transportation fuels, but also voluntary ones. The chosen quantitative modeling approach is two-fold: it combines a multi-sectoral economic model (LEITAP) with a spatial bio-physical land use model (IMAGE 2.4). This paper adds to existing research by considering biofuel policies in the EU, the US and various other countries with considerable agricultural production and trade, such as Brazil, India and China. Moreover, the combination of the two modeling systems allows for the observation of changes in both economic and bio-physical indicators. The results show that some indicators with high political relevance, such as agricultural prices and greenhouse gas emissions from land use, do not necessarily react proportionally to increasing demand for agricultural products from the biofuel sector. This finding should be considered when designing biofuel policies because these indicators are directly relevant for food security and climate change.

This paper analyses the consequences of enhanced biofuel production in regions and countries of the world that have announced plans to implement or expand on biofuel policies. The analysis considers biofuel policies implemented as binding blending targets for transportation fuels. The chosen quantitative modelling approach is two-fold: it combines the analysis of biofuel policies in a multi-sectoral economic model (MAGNET) with systematic variation of the functioning of capital and labour markets. This paper adds to existing research by considering biofuel policies in the EU, the US and various other countries with considerable agricultural production and trade, such as Brazil, India and China. Moreover, the application multi-sectoral modelling system with different assumptions on the mobility of factor markets allows for the observation of changes in economic indicators under different conditions of how factor markets work. Systematic variation of factor mobility indicates that the ‘burden’ of global biofuel policies is not equally distributed across different factors within agricultural production. Agricultural land, as the pre-dominant and sector-specific factor, is, regardless of different degrees of inter-sectoral or intra-sectoral factor mobility, the most important factor limiting the expansion of agricultural production. More capital and higher employment in agriculture will ease the pressure on additional land use – but only partly. To expand agricultural production at global scale requires both land and mobile factors adapted to increase total factor productivity in agriculture in the most efficient way.

One objective of Computable general equilibrium (CGE) models is the analysis of economy-wide effects of policy measures. The focus of the Factor Markets project is to analyse the functioning of factor markets for agriculture in the EU-27, including the Candidate Countries. While agricultural and food markets are fully integrated in a European single market, subject to an EU-wide common policy, the Common Agricultural Policy (CAP), this is not the case for the agricultural factor markets capital, labour and land. There are partly serious differences with regard to member state regulations and institutions affecting land, labour and capital markets. The presentation of this heterogeneity of factor markets amongst EU Member States have been implemented in the CGE models to improve model-based analyses of the CAP and other policy measures affecting agricultural production. This final report comprises the outcome of a systematic extension and improvement of the Modular Applied GeNeral Equilibrium Tool (MAGNET) model starting from an overview of the current state of the art to represent factor markets in CGE models to a description of work on labour, land and capital in MAGNET.