Economic analysis of agricultural enterprises in Turkey according to their level of success Análise econômica de empresas agrícolas na Turquia de acordo com seu nível de sucesso

In this study, agricultural enterprises in Turhal, Tokat were grouped based on their degree of success, their structural characteristics have been identified and their outcomes of activities discussed. The objective of the study was to determine the aspects that render successful agricultural enterprises different from other agricultural enterprises. The point to be achieved through the study is to assist agricultural enterprises with a more effective utilization of existing means in order to help them to develop. Data has been collected from 71 agricultural enterprises, which have been determined by Neyman's Method that is a stratified sampling method, via questionnaires. The Criterion of Agricultural Income Per Enterprise Land Decar has been applied for the classification of the enterprises according to their level of success. When the agricultural income was sufficiently examined in the enterprises, moderate successful and unsuccessful enterprises cannot obtain agricultural income to meet family labor force cost. Their agricultural level is quite below the sum of the family labour wage equivalent and the real interest of the equivalent capital. Therefore, the agricultural income of the examined enterprises is considered insufficient. The rate of the net product to the active capital is 3.45% in successful enterprises, 0.57% in those with moderate success, and for the unsuccessful ones, it has a negative value of -2.22%. This ratio for successful enterprises is close to 5%. Accordingly, the successful enterprises work more efficiently in comparison to the other enterprise groups.<br>Neste estudo, empresas agrícolas de Turhal, Tokat foram agrupadas com base em seu grau de sucesso, suas características foram identificadas e seus resultados de atividades discutidos. O objetivo do estudo é determinar os aspectos que diferenciam empresas agrícolas de sucesso das demais. O ponto a ser alcançado pelo estudo é assistir as empresas agrícolas com um uso mais efetivo. O ponto a ser alcançado pelo estudo é assistir as empresas agrícolas com um uso mais efetivo dos meios existentes, para ajudar a desenvolvê-las. Foram utilizados dados de 71 empresas selecionadas pelo método estratificado de Neyman, através de questionários. O "Criterion of Agricultural Income Per Interprise Land Decar" foi aplicado para a classificação em relação ao nível de sucesso. Quando a renda agrícola foi suficientemente examinada, as empresas de sucesso moderado e as sem sucesso não podem obter renda agrícola suficiente para atender ao custo do trabalho familiar. Seu nível agrícola está muito abaixo da soma dos salários familiares e do juro real do capital equivalente. Por isso, a renda agrícola das empresas examinadas é considerada insuficiente. A relação entre o produto líquido e o capital ativo é 3,45% nas empresas de sucesso, 0,57% nas de moderado sucesso e -2,22% nas sem sucesso. Nesta relação, o limite do juro normal é de 5% para empresas de sucesso. Assim, empresas de sucesso trabalham mais eficientemente em comparação a outros grupos empresarias

Agricultural technologies and carbon emissions: evidence from Jordanian economy

Theoretically, agriculture can be the victim and the cause of climate change. Using annual data for the period of 1970–2014, this study examines the interaction between agriculture technology factors and the environment in terms of carbon emissions in Jordan. The results provide evidence for unidirectional causality running from machinery, subsidies, and other transfers, rural access to an improved water source and fertilizers to carbon emissions. The results also reveal the existence of bidirectional causality between the real income and carbon emissions. The variance error decompositions highlight the importance of subsidies and machinery in explaining carbon emissions. They also show that fertilizers, the crop and livestock production, the land under cereal production, the water access, the agricultural value added, and the real income have an increasing effect on carbon emissions over the forecast period. These results are important so that policy-makers can build up strategies and take in considerations the indicators in order to reduce carbon emissions in Jordan

Approaches for modelling the energy flow in food chains

© 2015 Gowreesunker and Tassou; licensee Springer. "This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. "Background: The heavy reliance of the global food chain on the use of fossil fuels and anticipated rise in global population threatens future global food security. Due to the complexity of the food and energy systems, the impact of adequate food, climate or energy policies should be carefully examined in a modelling framework which considers the interaction of the food and energy systems. However, due to the different modelling approaches available, it can be very difficult to identify which method best suits the required purpose. Method: This paper presents the three main modelling approaches as ‘top-down’, ‘bottom-up’ and hybrids. It reviews different models under each category in terms of the practicality, benefits and limitations with reference to different past studies. Results: Bottom-up approaches generally tend to provide high levels of details, but their specificity to particular products/processes detracts their application to holistic models. On the other hand, top-down approaches consider the holistic aspects of the food chain, but the limited level of disaggregation prevents the identification of energy and environmental hot-spots. As a result, hybrid models seek to reduce the limitations of the individual approaches. Conclusions: This paper shows that the choice of one modelling approach over another depends on a variety of criteria including data requirements, uncertainty, available tools, time and labour intensity. Furthermore, future models and studies have to increasingly consider the inter-dependence of implementing social, demographic, economic and climate considerations in a holistic context to predict both short- and long-term impacts of the food chain.This study is a result of funding from the Research Councils UK to set up the RCUK National Centre for Sustainable Energy Use in Food Chains (CSEF), grant no. EP/K011820/1