Agricultural Economics, 2024 (vol. 70), issue 11
Unravelling risk factors in Turkish wheat in a changing global landscapeOriginal Paper
Huseyin Tayyar Guldal, Ozdal Koksal, Osman Orkan Ozer, Onur Terzi, Erdogan Gunes, Aysegul Selisik
Agric. Econ. - Czech, 2024, 70(11):527-540 | DOI: 10.17221/173/2024-AGRICECON 
This study comprehensively examines multifaceted risk factors influencing wheat production among Turkish farmers, aiming to deepen understanding of how these factors shape farmers’ perceptions and decision-making processes. Utilising Structural Equation Modeling (SEM), we analysed the interplay of climate-related issues (F1), market dynamics (F2), and external events (F3), like COVID-19 and wars, alongside socio-demographic factors such as education, income, and land ownership. Findings revealed that higher education and increased agricultural income reduced price-related risks while expanding wheat cultivation areas heightened risk perceptions....
Credit evaluation and rating system for farmers’ loans in the context of agricultural supply chain financing based on AHP-ELECTRE IIIOriginal Paper
Shangjia Guo, Rong Niu, Yanbo Zhao
Agric. Econ. - Czech, 2024, 70(11):541-555 | DOI: 10.17221/434/2023-AGRICECON
Farmers, often vulnerable within the agricultural supply chain, frequently encounter difficulties accessing and affording loans. This study introduces an innovative credit risk evaluation framework for farmers tailored to the agricultural supply chain. It includes three key aspects: farmers’ credit characteristics, the operational status of the agricultural supply chain, and overall credit conditions. Initially, the analytic hierarchy process (AHP) was used to assign weight coefficients to indicators. Then, the Elimination et Choix Traduisant la Réalité III (ELECTRE III) model was employed to determine farmers’ credit ratings. To demonstrate...
Did the COVID-19 pandemic disturb intra-EU trade in agrifood products? Evidence from a counterfactual forecasting approachOriginal Paper
Mariusz Hamulczuk, Karolina Pawlak, Daniel Sumner, Grzegorz Szafrański
Agric. Econ. - Czech, 2024, 70(11):556-564 | DOI: 10.17221/253/2024-AGRICECON
In this study, we attempt to infer the effect of the COVID-19 pandemic on the intra–European Union (EU) agrifood trade from out-of-sample forecasts. We compare the actual level of trade during the COVID-19 period with counterfactual values derived from univariate forecasting models [regARIMA (Linear regression with autoregressive integrated moving average errors) and Holt-Winters methods]. We analyse agrifood imports and exports of specific EU countries and the EU-27 aggregate on the basis of monthly data for the period from January 2010 to February 2022. The findings reveal a significant decrease in trade activity in the first year of the pandemic...
Micro-data efficiency evaluation of agricultural companies: The case of Germany and neighbouring countriesCase Study
Kevin Nowag, Jitka Janová
Agric. Econ. - Czech, 2024, 70(11):565-576 | DOI: 10.17221/190/2024-AGRICECON
This study uses micro-financial data to examine the efficiency of agricultural enterprises in Germany and its neighbouring countries. The aim of the study is to introduce a model for the agricultural sector and conduct an efficiency analysis using these data, interpreting the results with specific knowledge in the management of an agriculture company. Both technical and allocative efficiencies were determined, and the companies were ranked. Possible correlations between company size, measured by turnover, and the determined efficiency were analysed. At present, there is a lack of studies in the agricultural sector with high aggregated financial data,...