Measuring the impacts of distortions in the European Union cotton sector: a partial equilibrium analysis using the ATPSM model framework

The “cotton issue” has been a topic of several academic discussions for trade policy analysts. However the design of trade and agricultural policy in the EU and the USA has become a politically sensitive matter throughout the last five years. This study utilizing the Agricultural Trade Policy Simulation Model (ATPSM) aims to gain insights into the global cotton market, to explain why domestic support for cotton has become an issue, to quantify the impact of the new EU agricultural policy on the cotton sector, and to measure the effect of eliminating support policies on production and trade. Results indicate that full trade liberalization would lead the four West African countries to better terms of trade with the EU. If tariff reduction follows the so-called Swiss formula, world prices would increase by 3.5%.Cotton, European Union, West African Countries, Partial Equilibrium, Trade Policy, International Relations/Trade,

The olive oil and cotton lint sectors in the European Union

This paper examines and analyzes the impacts of the reformed CAP as well as the decisions of the new round of negotiations for the olive oil and cotton sectors in the European Union. The aim of this study is to estimate the changes in supply (agricultural supply plus intermediate demand and final production), demand (consumption), price and stock formation (import, export, beginning and ending stocks, national price formation) for both the olive oil and cotton sectors. The model designed for this purpose is partial equilibrium and policy oriented. The objectives of this model are to estimate changes in the production and consumption of the two products concerned, to determine how the reformed Common Agricultural Policy (CAP) and the new round of negotiations of the World Trade Organization (WTO) affect these two sectors, to analyze the evolution of export and import volumes, and finally to determine how this evolution will influence the welfare situation of the olive oil and cotton sectors.Olive oil, Cotton CAP, Trade, socio economic effects, partial equilibrium model, dynamic, multi market, synthetic, policy oriented simulation model, Crop Production/Industries,

Measuring the impact of extreme weather phenomena on total factor productivity of General Cropping farms in East Anglia

One of the main challenges of climate change on agriculture in UK is how to adapt to the potential changes to the availability of water. Changes in rainfall distribution may potentially lead to an increase in drought frequency, magnitude and duration. In this research a Data Envelopment Analysis (DEA) and a Malmquist Index (MI) are combined with a double bootstrap methodology to measure changes in Total Factor Productivity of general cropping farms in East Anglia. More specifically, the DEA technique was used to measure the year by year efficiency score for the farms in the sample and the MI and its components used to derive information on productivity over time. Data for the input – output models was obtained from the Farm Business Survey. Climate change is taken into consideration by using data for water cost as a proxy indicator of water consumption per farm. Results reveal changes in total, technical and scale efficiency and provide information on how the 2011 drought affected the TFP of the farms in the sample

Credit sources, access and factors influencing credit demand among rural livestock farmers in Nigeria

Rural farmers’ access to farm credit in Nigeria has been very low, which affects farm performance, and credit providers have blamed for the problem in the sector. While this general perception persists, the fact may be the case of credit demand, rather than just the risk-averse attitudes of credit providers. The research, therefore, sets to investigate significant factors influencing farmers’ credit demand to ensure efficient credit provision. The research adopted mixed methods for an in-depth investigation into the problem. There were 216 research participants split into equal halves of men and women from six Local Government Areas of Nasarawa State. Data collection methods employed structured interviews, focus group discussions, close/open-ended, and key informant interviews. Analytical tools involved descriptive statistics, the logit and multinomial logit models to determine participants’ socioeconomic characteristics, sources of credit, access, factors influencing credit demand generally, and from the various sources of credit identified. Findings reveal only 47.6% of the participants accessed to credit, with fewer women accessing than men. The most accessed forms of credit are from the semi-formal credit sources, with more men accessing from formal sources and more women from non-formal sources. Factors having a significant influence on credit demand generally are education, group membership and household size. And from formal, semi-formal and non-formal credit sources are 1); education, information on sources of credit, deposits, household size and marital status, 2); education, deposits, group membership, household size, flock size, and 3); education, group membership, and gender from the non-formal credit providers, respectively. Due to time constraint, this study data were collected concurrently with both quantitative and qualitative methods and did not allow for the interrogation of findings from one method with the other. In addition, the research categorised the agency of women based on marital status only as single or married and did not interrogate the agency of women further, this may be a limitation as some of the female participants are from polygamous homes. Unlike the current concentration of Nigerian research of this kind with quantitative methods alone, this research contributes particularly to Nigerian research output and experience by triangulating both quantitative and qualitative methods to explore farmers sources of credit, access, and factors determining access to credit in the study area

Accounting for rainfall and the length of growing season in technical efficiency analysis

The physical environment of farming systems is rarely considered when conducting farm level efficiency analysis, which is likely to lead to bias of performance measurements based on benchmarking methods such as Data Envelopment Analysis (DEA). We incorporate variations of the physical environment (rainfall and length of growing season) through the specifications of the linear programming in DEA to investigate performance measurement bias. The derived technical efficiency estimates are obtained using a sub-vector DEA which ensures farms are compared in a homogenous environment (i.e. accounting for differences in rainfall levels amongst distinct farm units). We use the Farm Business Survey to analyse a representative sample of 245 cereal farms in the East Anglia region between 2009 and 2010. Efficiency rankings obtained from a standard DEA model and a non-discretionary DEA model that incorporates the variations in the physical environment. We show that incorporating rainfall and the length of the growing season as non-discretionary inputs into the production function had significantly altered the farm efficiency ranking between the two models. Hence, to improve extension services to farmers and to reduce biased estimates of farm technical efficiency, variations in environmental conditions need to be integral to the analysis of efficiency

Drivers of production performance and profitability of the livestock sector in the less favoured areas of England: the impact of distance, financial dependency and machinery

Agricultural production in Less Favoured Areas (LFAs) is more difficult since farming faces certain natural challenges. Such barriers may lead to a reduction or suspension of agricultural activities resulting in a series of environmental pressures such as loss of biodiversity and land abandonment. Thus, maintenance and sustainable development of the agricultural systems within the LFAs emerges as a prerequisite for preserving the environment of the English uplands. Towards this direction, the identification of factors that enhance or hinder agricultural performance in the LFAs is required to enable the design of future development strategies and policy interventions. Principal Component Analysis (PCA) is employed here to group into core underlying factors variables related to climate and landscape characteristics as well as management choices. Multiple Linear Regression (MLR) was then used to test the explanatory power of the independent variables in explaining variations in business performance. Financial and physical data used in the study were derived from the Farm Business Survey dataset whereas climate variables were obtained from the Met Office climate monitoring. The results provide evidence to support that remoteness, climate, financial aid and technological level are drivers of good performance of the grazing livestock systems. Hence, the results suggest areas of policymaking interventions in the livestock sector of the LFAs that aim towards sustainable intensification of production

The impact of financial leverage on farm technical efficiency during periods of price instability

The main purpose of this work is to provide empirical evidence on the relationship between capital structure and technical efficiency for Italian cereal farms during the 2008 – 2014 period. Emphasis is given in the understanding of the relationship between the level of financial leverage for cereal farms and their production performance. The methods employed in this research article are based on non-parametric techniques in order to derive technical efficiency estimates for a sample of Italian cereal farms based on available Farm Accountancy Data Network data to explore in depth the relationship amongst the financial exposure of the sector and the capacity to utilise an efficient and effective production technology. Furthermore, subsidies are considered in the model as a non-discretionary variable and therefore, as an input that farmers cannot directly influence within the production function. Hence, the non-discretionary Data Envelopment Analysis model is a more appropriate framework since it is not penalising farms at a lower level of Pillar I payments when benchmarked with farms that receive higher level of payments. The results show that significant improvements could be achieved for most of the farms in the sample by improving production and management practices. Furthermore, results provide an empirical support of the adjustment theory by showing a negative impact of debt to asset ratio to technical efficiency. This research article provides a first insight on the evolution of the Italian cereal farms debt-technical efficiency relationship in periods where high price instability has been observed

Evaluating the sustainable intensification of arable farms

Sustainable Intensification (SI) of agriculture has recently received widespread political attention, in both the UK and internationally. The concept recognises the need to simultaneously raise yields, increase input use efficiency and reduce the negative environmental impacts of farming systems to secure future food production and to sustainably use the limited resources for agriculture. The objective of this paper is to outline a policy-making tool to assess SI at a farm level. Based on the method introduced by Kuosmanen and Kortelainen (2005), we use an adapted Data Envelopment Analysis (DEA) to consider the substitution possibilities between economic value and environmental pressures generated by farming systems in an aggregated index of Eco-Efficiency. Farm level data, specifically General Cropping Farms (GCFs) from the East Anglian River Basin Catchment (EARBC), UK were used as the basis for this analysis. The assignment of weights to environmental pressures through linear programming techniques, when optimising the relative Eco-Efficiency score, allows the identification of appropriate production technologies and practices (integrating pest management, conservation farming, precision agriculture, etc.) for each farm and therefore indicates specific improvements that can be undertaken towards SI. Results are used to suggest strategies for the integration of farming practices and environmental policies in the framework of SI of agriculture. Paths for improving the index of Eco-Efficiency and therefore reducing environmental pressures are also outlined

Improving productivity and water use efficiency: a case study of farms in England

The idea of Sustainable Intensification comes as a response to the challenge of avoiding resources such as land, water and energy being overexploited while increasing food production for an increasing demand from a growing global population. Sustainable Intensification means that farmers need to simultaneously increase yields and sustainably use limited natural resources, such as water. Within the agricultural sector water has a number of uses including irrigation, spraying, drinking for livestock and washing (vegetables, livestock buildings). In order to achieve Sustainable Intensification measures are needed that enable policy makers and managers to inform them about the relative performance of farms as well as of possible ways to improve such performance. We provide a benchmarking tool to assess water use (relative) efficiency at a farm level, suggest pathways to improve farm level productivity by identifying best practices for reducing excessive use of water for irrigation. Data Envelopment Analysis techniques including analysis of returns to scale were used to evaluate any excess in agricultural water use of 66 Horticulture Farms based on different River Basin Catchments across England. We found that farms in the sample can reduce on average water requirements by 35% to achieve the same output (Gross Margin) when compared to their peers on the frontier. In addition, 47% of the farms operate under increasing returns to scale, indicating that farms will need to develop economies of scale to achieve input cost savings. Regarding the adoption of specific water use efficiency management practices, we found that the use of a decision support tool, recycling water and the installation of trickle/drip/spray lines irrigation system has a positive impact on water use efficiency at a farm level whereas the use of other irrigation systems such as the overhead irrigation system was found to have a negative effect on water use efficiency

Optimising the spatial and production input features to improve efficiency of hill farms production systems

Integration of crop and livestock production systems (ICLS) represents a method for enhancing the sustainability of agricultural systems. Introducing more diversified farm production plans increases profitability and resilience by minimising the negative environmental impacts of agricultural production. Examining farm businesses located in Less Favoured Areas (LFAs) of England, we investigate how conversion into more integrated systems impacts on profitability. Thus, providing knowledge that can enable structural changes on the farm level towards enhancing financial performance and the sustainable intensification of the production system. Through Linear Programming (LP), four distinct optimisation scenarios are estimated, demonstrating the different dynamics between more specialised and more integrated-diversified (intensified) production systems. Data regarding physical and financial performances of 139 farm businesses were derived from the Farm Business Survey (FBS) for the accounting year of 2013-2014. Our findings suggest that there is a lot of potential for increasing profitability of hill farms through optimisation of ICLS. Policy interventions may accommodate productivity challenges within the LFAs via the construction of networks of transferrable knowledge to enable farmers gain knowledge on benefits emerging from ICLS. Hence, promote strategies and risk mitigation practices that could allow hill farmers to develop a sustainably intensified production system that is maximising the production capacity of the available natural resources