Design Of Agricultural Policies Research Articles

Preferences for sustainable intensification: Do agricultural interventions matter? Plot-level evidence from Senegal

To what extent do agricultural support programs that promote modern intensification shape farmers’ incentives to adopt sustainable agricultural management practices? We answer this question by examining the effects of receiving input subsidies and agricultural extension services on Senegalese smallholder farmers’ preferences for crop diversification, crop rotation, rotational grazing, fallowing, and mulching crop residues. The empirical investigation is based on the 2020/2021 Annual Agricultural Survey (AAS) and uses two identification strategies: selection on observables and the Abadie-Imbens matching approach to account for differences in farmers’ socio-economic backgrounds and biophysical characteristics of plots and the likelihood of benefiting from input subsidies and agricultural extension services. We find heterogeneous responses to extension services and input subsidies. In particular, we find that receiving agricultural extension services is associated with a higher likelihood of adopting crop rotation, rotational grazing and fallow. On the other hand, the effect of receiving fertiliser subsidies is significantly negative for these three practices. The results also indicate that receiving extension services is associated with a lower likelihood of adopting crop diversification, and receiving seed subsidies is associated with a higher likelihood of mulching crop residues. As international research and development organizations consider sustainable intensification as a means to effectively address soil degradation and achieve greater agricultural productivity in sub-Saharan Africa, our findings call for the design of agricultural policies to support smallholder agriculture that take into account unintended consequences in terms of disincentives for the adoption of sustainable agricultural practices.

Decision-Making Model to Support Agricultural Policies in Realizing Economic and Social Sustainability

Abstract Background Achieving economic and social sustainability is the goal of any policy when defining measures. We focus on the beef sector, where many challenges have arisen due to its structural characteristics, such as an unfavourable scale structure, high costs, low efficiency, and a low environmental footprint. This paper presents an example of the support provided by a mathematical programming model in the development of a Common Agricultural Policy Strategic Plan for the period 2023-2027. Methods/approach It is a model based on linear programming that allows such an ex-ante analysis by calculating production plans at the farm level and aggregating the results at the sector level. Objectives When defining the interventions, the question arose as to what the reform of the Common Agricultural Policy will bring and to what extent the sector should be supported in meeting these challenges. These were the concerns of agricultural policy that we sought to support by modelling different scenarios. Results The results show that the situation of the sector will worsen, especially for larger farms, but they also show the great importance of production-related payments to mitigate the negative trend. Conclusions The applied approach proves to be suitable for supporting the design of agricultural policy and achieving greater economic and social sustainability in the sector.

A comparison of animal and plant-based proteins from an economic, environmental, and nutritional perspective in the Republic of Ireland

CONTEXTProtein is a central component of health and nutrition. The current protein production system is unlikely to sustainably meet the growing global demand for protein. Therefore, alternative sources of protein must be considered. OBJECTIVEThis study uniquely compares animal-based (milk, beef meat, sheep meat) and plant-based (cereals and legumes) protein production in terms of land usage. The comparison is carried out across a suite of economic, environmental, and nutritional metrics. As land use decisions are taken at the farm level, the analysis adopts a farm gate approach. Focusing on the supply side, consumption is not considered in the analysis. METHODSEconomic performance is measured through the gross and net margins. Environmental performance is evaluated through farm-level greenhouse gas (GHG) emissions and nutrient (nitrogen and phosphorus) balances. Nutritional performance is measured through the gross protein yield, the protein yield corrected for digestibility and land-use efficiency, i.e., the land needed to generate one kg of (digestible) protein. Results are expressed per hectare and per 100 g of gross and digestible protein to allow for a holistic comparison. The analysis focuses on the Republic of Ireland, a relevant country given the importance of the strong agricultural export focus, the dominance of the livestock sector and the country's ambitious environmental emission reduction targets. RESULTS AND CONCLUSIONSFindings indicate that, on a per hectare basis, milk production on dairy farms has the strongest economic performance and highest GHG emissions amongst the products considered. Crops' gross and net margins are less than half that of dairy farms, but they also show the strongest environmental performance generally. Cereals and legumes have the best nutritional performance, from a protein perspective, whereas sheep meat production returned the lowest gross and digestible protein yields per hectare. Arable crops also show the lowest GHG emissions and nutrient balances on a per unit of protein basis. SIGNIFICANCELand-use policies need to be designed holistically, given the complexity of the agricultural sector. Agricultural policy design currently focuses on income support and on the environmental impact of the agricultural sector, but farmers' livelihood and food and protein security need to be safeguarded. Diversifying agricultural production and increasing plant-based protein production in Ireland, a country with a livestock-focused agricultural sector, could contribute to achieving the climate change targets of the country, provided the necessary policy levers are in place.

Farm typologies for understanding farm systems and improving agricultural policy

CONTEXTFarm typologies help to identify patterns across a wide range of farm systems and describe heterogeneity in agriculture concisely. They can also support the design of agricultural policies by providing information and knowledge about policy target groups. For example, voluntary agri-environmental schemes could be tailored to specific agricultural landscapes and farm types. Farm typologies, however, are often developed from scratch, with limited connection to previous studies and policy making. OBJECTIVEThe objective of this study is to clarify the purposes of farm typologies in research and agricultural policy making and to develop a framework that allows to increase the usefulness and usability of farm typologies for agricultural policy making. METHODSBased on a review of 13 systematically identified overview studies on farm typologies, we develop a framework that establishes connections between the purposes of farm typologies along the different stages of the policy process. RESULTS AND CONCLUSIONSWe find multiple purposes for farm typologies, the two most common of which are for understanding the characteristics, heterogeneity, and development of farm systems and for policy making. The newly developed framework suggests that connecting knowledge across these purposes could improve the validity, transferability, and relevance of farm typologies for agricultural policy making. Our framework also provides an entry point for encouraging cooperation between developers and users of typologies, and for the improvement of typologies through new data (including behavioural data) and methods such as machine learning. We conclude that future research can build on the existing work on farm typologies but must be aware of the specific challenges that are associated with the use of farm typologies in the policy process. SIGNIFICANCEKnowledge of the prospects and challenges of using farm typologies allows to increase the usefulness and usabilityof these typologies and can contribute to the design of targeted and tailored agricultural policy instruments. By increasing the acceptance, perceived fairness, and legitimacy, this can improve their effectiveness and efficiency, which is urgently needed for a successful transformation to a more sustainable agricultural sector.

Policy approaches for enhanced dairy sector innovation – a review of future pathways and policies for effective implementation of digital agriculture

ABSTRACT Innovation and technology are a feature of New Zealand’s dairy sector. To overcome current challenges, dairy farmers require agile and multi-dimensional innovation, supported by forward-looking and integrated policy from both the sector and government. In this paper, we outline some of the current dairy sector challenges, and potential technologies to address these challenges. We focus on the future for digital agriculture innovation and discuss policy approaches to enable the sector to leverage digitalisation. These approaches include co-innovation, responsible innovation, multi-scale approaches, micro-innovation and poly-innovation and mission-oriented innovation. Digital agriculture and policy may interact in two ways: (1) policy may be used to enhance digital agriculture innovation and, (2) digitalisation itself may act to enhance agricultural policy design and delivery. Overall, innovation policy requires greater directionality, use of policy bundles and a focus on technology as a mediator of new dairy farming practices and institutional configurations.

Disentangling the seasonal effects of agricultural intensification on birds and bats in Mediterranean olive groves

Assessing the spatio-temporal impact of agricultural intensification on species and communities is key for biodiversity conservation. Here, we investigated the seasonal effects of olive grove intensification at both local (farming practices and grove structural complexity) and landscape scale (land-cover diversity) on birds and bats, at species and community-level. Both groups were surveyed during spring, summer, and autumn in 60 sites representing varying levels of olive grove intensification throughout the Alentejo region (southern Portugal). At the local scale, the number of chemical applications was used as a proxy for the intensification of farming practices and a Structural Index, which accounted for within-grove variability in tree density and features, was used as a measure of grove structural complexity. At landscape scale, we quantified the proportion of the major land-cover types potentially affecting birds and bats. We found that the abundance of ca. 77% of the species analyzed (ca. 84% and 55% of birds and bats respectively) was negatively related to olive grove intensification in at least one season. The Structural Index was the most influential factor at both species and community-levels, especially for birds, with a consistent and strong effect across seasons. Chemical applications had a stronger negative effect on birds, whereas the amount of olive grove cover had a stronger detrimental effect on bats. Birds and bats showed a variable response to predictor variables depending on the season, particularly for the bat community. Our study shows differences in bird and bat responses associated with the spatio-temporal variability of the agricultural intensification components. On the one hand, birds and bats showed a seasonal pattern of association with the different components of olive grove intensification, probably due to their ecological and biological requirements. On the other hand, the responses of both groups also appear to be scale-dependent: while birds seem to respond to in-farm or local intensification more strongly, bats seem to be more influenced by landscape-scale simplification. Overall, we highlight the importance of the structural complexity of olive groves for birds and bats, an aspect that should be considered in the design of agricultural policies aiming to promote biodiversity conservation.

Using Experiments to Design and Evaluate the CAP: Insights from an Expert Panel

SummaryOver the last twenty years the Common Agricultural Policy (CAP) has considerably evolved, by introducing new objectives and instruments to address the increasing number of challenges ahead. These changes call for the use of innovative tools to analyse agricultural policy design and evaluation. During the last European Association of Agricultural Economics conference, a panel of experts presented their points of view on how experiments can enhance the CAP evaluation toolkit. In this article we summarise the main insights emerging during this session. We present a review of the different existing experimental approaches followed by some examples of their application in the study of the CAP and a discussion of the potential hurdles to the use of experimental results to design actual policies. From the different contributions it emerges that experimental approaches may represent effective tools to improve the design and evaluation of the CAP. However, a potential hurdle to their wider use is that experimental results often fail to be confirmed when applied to large‐scale policy interventions. In this article we discuss some potential solutions to the main problems affecting the scalability of experimental results, and we provide some insights on how experiments can help to improve the CAP further.

Reduction of the Economic Risk by Adaptation Measures to Alleviate Heat Stress in Confined Buildings for Growing-Fattening Pigs Modelled by a Projection for Central Europe in 2030

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers such as increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulate investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures (AMs) to reduce heat stress. A simulation model driven by meteorological data was used to calculate indoor climate for 1981 to 2017. This dataset was extrapolated for a projection in the year 2030. The heat stress was calculated for a business-as-usual livestock building and for several AMs. For 2030, the expected value of the reduction of the gross margin was calculated by EUR 3.98 a−1 per animal place for the business-as-usual scenario. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980 between EUR 0.03 a−1 and EUR 1.02 a−1 per animal place. The efficiency of other AMs to reduce heat stress is distinctly lower (between EUR 2.62 a−1 and EUR 3.80 a−1 per animal place). The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development.

Multi-temporal phenological indices derived from time series Sentinel-1 images to country-wide crop classification

Crop classification is a crucial prerequisite for the collection of agricultural statistics, efficient crop management, biodiversity control, the design of agricultural policy, and food security. Crops are characterized by significant change during the growing season, and this information can be used to improve classification accuracy. However, capturing variation in vegetation cover requires a reliable source of valid data. Sentinel-1 radar images are a good candidate, as they supply information about Earth’s surface every six days, independent of weather and light conditions. In this paper, we present a method for crop classification based on radar polarimetry. We propose a set of multi-temporal indices derived from time series Sentinel-1 images that aim to characterize crop phenology. A big data, object-oriented classification technique is developed and tested on 16 crop types for the whole of Poland. Our analysis found that overall accuracy varied (regionally) from 86.36 to 89.13% in 2019, and from 85.95 to 89.81% in 2020. F1 scores for individual crops varied from 0.73 to 0.99, and the use of our multi-temporal phenological indices increased F1 scores by about 0.14 compared to calculations using only basic parameters. Results obtained for the whole country demonstrate the efficacy of the method and its resistance to environmental conditions.

The integration of environmental objectives in the common agricultural policy\u2014partisan politics in the European Parliament

This study examines the policy preferences of political groups in the 8th European Parliament regarding the design of agricultural policy and the integration of environmental goals therein. Due to the high degree of Europeanization of the Common Agricultural Policy, the analysis of party positions at the EU level is particularly interesting. To what extent are the positions of political groups changing against the background of the increasing public awareness for environmental and animal welfare issues in agricultural policy? By means of a discourse network analysis of the plenary debates on selected policy proposals during the 8th term of the European Parliament, the positions of the political groups in agricultural policymaking are explored. The comparative analysis clearly reveals differences in problem perceptions and preferred policy solutions between the different political groups. Substantive differences are apparent between the EPP on the one side and the Greens/EFA and the GUE/NGL on the other side. EPP members still mostly represent traditional agricultural goals such as food security and income support for farmers, whereas the Greens/EFA and the GUE/NGL deputies promote a change towards a more environmentally and animal welfare friendly agricultural policy. At the same time, the analysis reveals a broad consensus across political groups regarding the general need to increasingly integrate sustainability concerns in the design of the future Common Agricultural Policy.

Values of farmers – Evidence from Germany

Against the background of fundamentally changing political and social requirements of agricultural production, the requirement profile of farmers has changed. The future of agriculture is widely discussed. To prepare a ground for future debates and policy programme design, it is essential to obtain an understanding of which values underlie the behaviour of farmers. This paper applies Schwartz's value theory to a large quantitative survey (N = 787) of German farmers. In addition to the overall value portrait, different value portraits within the sample of farmers are analysed. Farmers of the sample first and foremost prioritise self-transcendence values followed by openness to change. Conservation and self-enhancement are ranked to be less important within the value priorities of farmers. Furthermore, three different value portraits are identifiable within the sample. These groups differ significantly in their risk attitude and involvement in structural diversification. Implications for agricultural policy design and agricultural management are derived from the results.

Measuring the Impact of the Multiple Cropping Index of Cultivated Land during Continuous and Rapid Rise of Urbanization in China: A Study from 2000 to 2015

With the continuous and rapid rise of urbanization in China, land use transition research has been carried out extensively. Multiple cropping is the content of land use recessive morphology research, and it is also a common agricultural system in China. Accordingly, further research on multiple cropping index (MCI) can enrich the land use transition research and help to evaluate China’s food security. In order to examine the spatiotemporal changes and factors influencing the MCI of cultivated land in China, we collected MODIS remote sensing image data and land use classification data and conducted a remote sensing inversion on China’s MCI from 2000, 2005, 2010, and 2015. The spatial distributions and evolution processes of the MCI were explored through spatial mapping, statistical analysis, and processing with the Geographic Information System; moreover, the influencing factors of MCI were explored quantitatively with principal component regression. The results were as follows: (1) at the provincial scale, the average MCI across Guangdong, Guangxi, Hainan, Henan, Anhui, and Jiangsu was high; meanwhile, the average MCI across Heilongjiang, Inner Mongolia, Ningxia, and Qinghai was low. Between 2000 and 2015, the number of provinces with low MCI increased gradually, and the average MCI decreased greatly in the southern provinces. (2) At the county scale, the Taihang Mountains, Qinling Mountains, and Hengduan Mountains formed the boundary of China’s single cropping and multiple cropping indices. Dynamic changes in China’s MCI were obvious, and the number of counties with MCI change values lower than 0 increased gradually. Last, (3) natural conditions, nonagricultural process, cultivated land quality, and agricultural intensification demonstrated different degrees of impact on the MCI; in particular, the influence of nonagricultural industries, pesticides, and agricultural plastic film on the MCI proved especially important. Future research should strengthen the existing work on related transformations in farmers’ livelihoods, especially in terms of the return of rural labor force, the body of agricultural production, agricultural ecological issues, and the balance between increased crop production and reduced environmental pollution. In addition, agricultural policy design should pay more attention to cultivated land quality, the farmer who cultivates the land, and the multiple cropping potential of cultivated land.

Food-energy-water nexus of different cacao production systems from a LCA approach

This study presents an evaluation of the food-energy-water nexus (FEWn), complemented by a thorough life cycle assessment (LCA), of four young cacao production systems: two full-sun monocultures and two agroforestry systems under conventional and organic management. Land footprint (LF) for food production, non-renewable cumulative energy demand (NR CED) for energy, total water footprint (TWF) for water, and three efficiency indicators for the FEWn were all analysed. In addition, ten LCA impact categories were evaluated in relation to two functional units (kilograms of cacao output and kilograms of total crop output, i.e., cacao + other crops). The integrated analysis of the FEWn and the LCA framework reveals how agroforestry systems and organic management report better environmental performances for almost all indicators and impact categories considered, except for the TWF. However, given that the systems analysed have no irrigation, between 96.3% and 99.8% of the TWF corresponds to green water, i.e., soil moisture from precipitation. Green water has lower environmental impacts and opportunity costs than the water used to manufacture inputs (WFinput). Accordingly, when the efficiency of the nexus is measured in relation to the WFinput, organically managed systems produce more food/energy per unit of water used. Our results show how production diversification and organic and cultural management practices can improve energy efficiency and reduce the use of water associated with the inputs and, consequently, improve the nexus, as well as the rest of the environmental impacts analysed. The design of agricultural policies focused on sustainability should strongly favour the establishment of agroforestry systems, particularly those that are organically managed.

Crop Classification Based on Temporal Signatures of Sentinel-1 Observations over Navarre Province, Spain

Crop classification provides relevant information for crop management, food security assurance and agricultural policy design. The availability of Sentinel-1 image time series, with a very short revisit time and high spatial resolution, has great potential for crop classification in regions with pervasive cloud cover. Dense image time series enable the implementation of supervised crop classification schemes based on the comparison of the time series of the element to classify with the temporal signatures of the considered crops. The main objective of this study is to investigate the performance of a supervised crop classification approach based on crop temporal signatures obtained from Sentinel-1 time series in a challenging case study with a large number of crops and a high heterogeneity in terms of agro-climatic conditions and field sizes. The case study considered a large dataset on the Spanish province of Navarre in the framework of the verification of Common Agricultural Policy (CAP) subsidies. Navarre presents a large agro-climatic diversity with persistent cloud cover areas, and therefore, the technique was implemented both at the provincial and regional scale. In total, 14 crop classes were considered, including different winter crops, summer crops, permanent crops and fallow. Classification results varied depending on the set of input features considered, obtaining Overall Accuracies higher than 70% when the three (VH, VV and VH/VV) channels were used as the input. Crops exhibiting singularities in their temporal signatures were more easily identified, with barley, rice, corn and wheat achieving F1-scores above 75%. The size of fields severely affected classification performance, with ~14% better classification performance for larger fields (>1 ha) in comparison to smaller fields (<0.5 ha). Results improved when agro-climatic diversity was taken into account through regional stratification. It was observed that regions with a higher diversity of crop types, management techniques and a larger proportion of fallow fields obtained lower accuracies. The approach is simple and can be easily implemented operationally to aid CAP inspection procedures or for other purposes.

Effects of government supports and credits on Turkish agriculture

PurposeDomestic supports on Turkish agriculture have substantially increased over the past decade while empirical evaluation of their output impact is limited. Also, the existing literature often neglects potential spatial spillover effects of agricultural policies or subsidies. The purpose of this paper is to quantify the direct and spillover effects of Turkish agricultural domestic measures and agricultural credits use on the added agricultural value.Design/methodology/approachThis study applied a spatial panel model incorporating spatial interactions among the dependent and explanatory variables to evaluate the impact of government support and credit on Turkish agricultural output. A provincial data set of agricultural output values, input factors and government subsidies from 2004 to 2014 was used to model the spatial spillover effects of government supports.FindingsResults show that a one percent increase in agricultural credits in a given province leads to an average increase of 0.17 percent overall in agricultural value-added per hectare, including 0.05 percent from the direct effect and 0.12 percent from the spillover effect. Contrary to agricultural credits, a one percent increase in government supports in a province generates a mixed direct and spillover effects, resulting in an overall reduction of 0.13 percent in agricultural value-added per hectare in Turkey.Research limitations/implicationsThis study could be extended by controlling for climate, biodiversity and investment factors to agricultural output in addition to input and policy factors if such data were available.Originality/valueThis study fills the gap in the literature by determining the total effect, including direct and spatial spillover effect, of domestic supports and credits on Turkish agricultural value. The findings provide crucial information to decision makers regarding the importance of incorporating spatial spillover effects in the design of agricultural policy.

Increasing the effectiveness of the Chinese grain subsidy: a quantitative analysis

PurposeThe purpose of this paper is to examine the grain production implications of alternative designs for China’s grain subsidy policy. In particular, the authors examine three subsidy designs including area-based subsidy, quantity-based subsidy and production-cost-based subsidy.Design/methodology/approachTo carry out the analysis, the authors develop a Chinese agricultural sector model (CASM) and an econometric, policy action–farmer response summary model. The CASM is used under a wide variety of subsidy level and basis experiments to generate pseudo data on farmer reactions to subsidies. Then a summary function model was estimated over those pseudo data that quantitatively summarized modeled farmer responses to different grain subsidy schemes. In turn, the summary functions were used to optimize the subsidy level such that it maximized grain production both within and across the area-based, quantity-based and cost-based subsidies. Regional implications were also developed.FindingsThe authors found that the production-quantity-based subsidy is the most cost-effective in stimulating grain production among the subsidy schemes. The authors also argue that scheme complies with WTO regulations regarding product-specific support. The authors found that the areas where grain production was most affected were the traditional grain-producing regions.Originality/valueTo the authors’ knowledge the authors have not seen a study of the Chinese grain subsidy program context that examined the effects of alternative subsidy schemes, nor one that developed estimates of the optimal subsidy level. In addition, the methodology is unique employing bottom-up, regionally disaggregated, sector modeling coupled with an aggregate pseudo data based summary function approach providing a new, original approach for analyzing agricultural policy design.

Opportunities and pitfalls for researchers to contribute to the design of evidence-based agricultural policies: lessons from Uganda

ABSTRACTAgricultural policies in sub-Saharan Africa have paid insufficient attention to sustainable intensification. In Uganda, agricultural productivity has stagnated with aggregate increases in crop production being attributed to expansion of cultivated land area. To enhance sustainable crop intensification, the Ugandan Government collaborated with stakeholders to develop agricultural policies using an evidence-based approach. Previously, evidence-based decision-making tended to focus on the evidence base rather than evidence and its interactions within the broader policy context. We identify opportunities and pitfalls to strengthen science engagement in agricultural policy design by analysing the types of evidence required, and how it was shared and used during policy development. Qualitative tools captured stakeholders' perspectives of agricultural policies and their status in the policy cycle. Subsequent multi-level studies identified crop growth constraints and quantified yield gaps which were used to compute the economic analyses of policy options that subsequently contributed to sub-national program planning. The study identified a need to generate relevant evidence within a short time 'window' to influence policy design, power influence by different stakeholders and quality of stakeholder interaction. Opportunities for evidence integration surfaced at random phases of policy development due to researchers’ ’embededness’ within co-management and coordination structures.

Economic Valuation of Ecosystem Services from Small-Scale Agricultural Management Interventions in Burkina Faso: A Discrete Choice Experiment Approach

The main purpose of this paper is to estimate farmers’ preferences and their willingness to pay (WTP) for ecosystem services derived from four agricultural water management (AWM) and resource recovery and reuse (RRR) intervention options in Burkina Faso, using a choice experiment (CE). These include; small water infrastructure, drip irrigation, recovery of organic matter from waste, and treated wastewater. The design decisions relating to attribute selection, the level of attributes, alternatives and choice tasks were guided by literature, field visits, focus group discussions, expert input and an iterative process of the STATA software to generate an orthogonal main-effects CE design. The data used was generated from a random sample of 300 farm households in the Dano and Ouagadougou municipalities in Burkina Faso. Results from conditional logit, latent class logit and mixt logit models show that farmers have positive and significant preferences for drip irrigation, treated wastewater, and organic matter. However, they are WTP on average more for drip irrigation and organic matter for agricultural sustainability. In line with economic theory, the cost of an intervention reduces demand for a given intervention. These findings can provide policy makers with evidence for agricultural policy design to build farmers’ resilience in the Sahel.

A farm level approach to explore farm gross margin effects of soil organic carbon management

This paper investigates farm gross margin effects of management measures aimed at enhancing soil organic carbon (SOC) stocks to maintain soil fertility while providing important ecosystem services. An optimising farm level model, ScotFarm, is used to investigate the farm gross margin effects of selected SOC management measures for arable farms in Scotland (UK) and Aragon (Spain). The sensitivity of model results to effects on crop yields and costs of production is tested for each measure. The results suggest that considerable regional differences in the financial viability of SOC measures exist. Tillage management is the only measure with positive effects on farm gross margins of Scottish farms at baseline levels of yield effects and input costs. In the case of farms in Aragon, Spain, fertiliser management, crop rotations (with legumes) and tillage management (in later years) show improvements in gross margins. Residue management is estimated to have a negative effect on farm gross margins for both Scottish and Spanish crop farms. Results of the sensitivity analysis indicate that effects of SOC management on farm gross margins are more sensitive to a change in crop yields than to changes in input costs. The findings point to further research needs with respect to the trade-offs between yield effects and changes in input costs arising from the adoption of SOC management measures, and have implications for agricultural policy design aimed at enhancing SOC stocks under a changing climate.

Linkage between Rural Voters and Politicians: Effects on Rice Policies in the Philippines and Thailand

AbstractThis article explains how linkages between politicians and rural voters affected the design of agricultural policies, using rice in two countries as examples. In the Philippines, colonial history bolstered an oligarchy of landed elite politicians, whose power was restored after the dictatorship of Marcos ended in 1986. Their practice of patronage brought corruption that led to dwindling rice productivity and increasing import dependence while displacing the political necessity to offer price support to farmers. In Thailand, sociopolitical development was more centralized, with new electoral rules introduced in 1997 to weaken locally confined patronage arrangements. Mass parties competing on a policy platform were favoured instead, resulting in increasing, but eventually, excessive subsidies for rice farmers. Although voter–politician linkages resulted in different rice policies in the two countries, recent instability in the world rice market showed that strategies with greater sustainability considerations are needed in addressing domestic income disparities and global food insecurity.