2024 - Volume 126

This paper aims to investigate the factors influencing the international beef market’s trade flows by applying the gravity model. We focus on the effects of trade networks, non-tariff measures, and natural disasters on the beef trade. This is the first study to incorporate network analysis eigenvector scores into the gravity approach with a view to examining the impact of trade network improvements on trade. Eigenvector centrality scores reveal the prominent role played by the European and Southern Common Market countries and show a well-connected beef network. The results of our gravity model show that beef trade increases more when an importer improves its position in the trade network, shedding light on the importance of strategic network engagement. We also show that Sanitary and Phytosanitary measures are more trade-restrictive than tariffs, a finding which emphasises the need for trade policy to pay attention to such measures. Meteorological (hydrological) catastrophes hurt beef imports (exports); this highlights the importance of implementing safeguarding measures on beef farms.

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Access to finance poses a significant challenge for smallholder farmers, influencing the prospects for improving their livelihoods. Financial literacy stands out as a pivotal factor in overcoming this hurdle, playing a crucial role in attaining access to finance, maintaining creditworthiness and fostering economic stability. The objective of this study is to enable an understanding of the financial literacy level of smallholder farmers and to explore empirically the factors that can be associated with their financial literacy. The study is based on a field survey using structured questionnaires targeting 506 smallholder farmers located in different parts of Albania. Descriptive analysis and logit regression analyses are carried out in order to study the relationship between farmers’ capacity to calculate credit obligations and their farm assets, access to knowledge, access to financial services and behaviours related to financial record keeping. The ability to correctly calculate the value of the credit costs has been found to be positively associated with access to previous training, experience with application for accessing subsidies, access to a bank account, and their habit of financial keeping records.

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This study compares the impact of economic uncertainty, climate change, Covid-19, and the Russia-Ukraine conflict on 27 European countries (EU27) food prices. The author used panel data that combines cross section data from January 2019 – March 2023 and time series data from 27 European countries. The error correction model (ECM) and Autoregressive Distributed Lag (ARDL) were used to analyse the data. The domestic energy consumer price index, real broad exchange rate, climate change, and Russia-Ukraine armed clashes are the drivers of the short and long run rise in the EU27 domestic food consumer price index. New domestic cases of Covid-19 can increase the EU27 domestic food consumer price index in the short run but not in the long run. Meanwhile, an increase in the unemployment rate has the potential to lower the EU27 domestic food consumer price index in both the short and long run. Among all the global shocks examined in this study, changes in the real broad exchange rate have the greatest impact on the EU27 domestic food consumer price index.

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This research, focusing on Hungary, aims to analyse the comprehensive economic impact of proposed changes in daily weight gain and stocking density for broilers, as outlined in the European Food Safety Agency’s (EFSA) 2023 Scientific Opinion “Welfare of Broilers on Farm”. Hungary is a significant player in the Central and Eastern European (CEE) poultry industry and was the second-largest chicken meat producer and exporter in the CEE region in 2022. Utilising the dynamic econometric model AGMEMOD for impact assessment, we explore the economic repercussions on not only the broiler sector but also on the maize and pork sectors in Hungary. Our findings indicate that simultaneous implementation of the EFSA recommendations - reducing the growth rate to 50 g/day and lowering the stocking density to 11 kg/m² - could result in a substantial 72.4% reduction in chicken meat production in Hungary from the presumed enforcement year of 2023 through 2032, the end of the AGMEMOD baseline projection period. This reduction could not only impact the broiler industry but also have ripple effects on related sectors such as pork and maize. However, if only EFSA’s recommendation to reduce the growth rate to 50 g/day is considered, an 18% reduction in chicken meat...

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Farm-level benchmarking and comparative analysis provide a basis for orientation on national, regional and global level. In the agri benchmark global network, we compare beef and sheep farms (as well as other branches) from more than 30 countries. In a partnership approach with researchers, producers and local experts, we collect and validated farm-level data using a standard operating procedure and a farm-level simulation model. In cow-calf farms, winter housing is associated with higher live weight production. Profitability is mainly driven by weaner prices and their variation and to a lesser extent by costs. In the EU, government payments play a crucial role in determining profitability. In sheep farming, performance and economic framework conditions differ across production systems and countries. Sheep profitability shows large variations with higher profits being achieved outside of Europe. The global outlook for beef and sheep production remains positive, with declining numbers in Europe and challenges related to workforce and environmental regulations.

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The importance of Precision Livestock Farming (PLF) technologies in agricultural practices is widely recognised, yet the actual adoption rate remains low. To address this issue, research with several interconnected sub-studies was initiated across seven countries to encourage PLF technology utilisation. Initially, 15 farms received PLF tools to showcase their benefits. Despite successful deployment, challenges such as animal behaviour, sensor positioning, and internet connectivity affected operational efficiency. Concurrently, surveys were conducted to assess livestock producers’ attitudes and identify adoption barriers. Subsequently, a sophisticated cloud-based ICT tool was developed to integrate research outcomes. The findings have highlighted concerns regarding the cost, complexity, maintenance, and perceived benefits of PLF technologies, exacerbated by internet connectivity issues in rural areas. Machine learning analysis identified the technological readiness levels of farmers, providing information for the development of the new PLF Compass tool. This integrated application facilitates technology adoption by offering personalised recommendations and benefit assessments.

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This paper presents the outcome from a case study analysis for a Canadian farm that does site-specific fertilisation (SSF), a precision farming approach which takes into consideration the spatial variability of soils. The economic results for three years of wheat and canola production are compared to a neighbouring farm, which is practicing conventional broadcast application of fertilisers. Since no additional investments in machinery are needed, the annual variable cost is 6 CAD/acre. In the standard case, the average profit is 30 CAD/acre. The rather pronounced difference in the effects from SSF application in wheat vs. canola leads one to question whether this is a crop-related systematic outcome or instead represents something more random. Sensitivity analyses generated two main insights. First, the economics of SSF are sensitive to a modification in commodity prices – a 50 % cut would reduce the average profit to about 9 CAD/acre. Second, another scenario calculation in which no-till is assumed to generate a 5% increase in yields suggests that the net profit would be just 7 CAD/acre. Given the existence of so many uncertainties, this paper calls for more farm-based economic analysis of SSF, one which should also include a comparison of different service providers...

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  • Scopus SJR (2023): 0.29
  • Scopus CiteScore (2022): 2.0
  • WoS Journal Impact Factor (2022): 1.2
  • WoS Journal Citation Indicator (2022): 0.45
  • ISSN (electronic): 2063-0476
  • ISSN-L 1418-2106



Publisher Name: Institute of Agricultural Economics Nonprofit Kft. (AKI)

Publisher Headquarters: Zsil utca 3-5, 1093-Budapest, Hungary

Name of Responsible Person for Publishing:        Dr. Pal Goda

Name of Responsible Person for Editing:             Dr. Attila Jambor

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The publication cost of the journal is supported by the Hungarian Academy of Sciences.

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