Template-Type: ReDIF-Article 1.0
Author-Name: Luboš Smutka
Author-Workplace-Name: Department of Trade and Finance, Faculty of Economics and Management, Czech University of Life Sciences Prague, Prague, Czech Republic
Author-Name: Josef Abrhám
Author-Workplace-Name: Department of Tourism, Metropolitan University Prague, Prague, Czech Republic
Title: The impact of the Russian import ban on EU agrarian exports
Abstract: The main goal of the paper is to evaluate the impact of the Russian import ban on the development of agricultural exports from EU member states. The study is based on a time-series analysis of empirical statistical indicators. The analysed period is between 2009 and 2019. The source of data for individual analyses is UN Comtrade (2021). The evaluation of export performance is extended by hierarchical cluster analysis. The study quantifies the effects of the import ban on the EU and individual member states through two scenarios. Scenario 1 is based on the cumulative loss of the value of exports. Scenario 2 assumes a continuous development of the value of agricultural exports. Based on the results, it is possible to confirm that the application of the Russian food import ban had a significant impact on EU countries. The impact of sanctions varies across EU countries. Four specific clusters could be identified in the period under investigation. In the period after the ban, the distribution of individual countries among individual clusters changed significantly. The applied ban could be understood not only as an attempt at counter-sanctions. Import restrictions also aim to reduce Russia's dependence on food imports and promote national food security.
Keywords: agricultural trade, European Union, Russia, sanction
Journal: Agricultural Economics
Pages: 39-49
Volume: 68
Issue: 2
Year: 2022
DOI: 10.17221/351/2021-AGRICECON
File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/351/2021-AGRICECON.html
File-Format: text/html
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Handle: RePEc:caa:jnlage:v:68:y:2022:i:2:id:351-2021-AGRICECON

Template-Type: ReDIF-Article 1.0
Author-Name: Carlotta Penone
Author-Workplace-Name: Department of Land, Environment, Agriculture and Forestry, School of Agricultural Sciences and Veterinary Medicine, University of Padua, Padua, Italy
Author-Name: Samuele Trestini
Title: Testing for asymmetric cointegration of Italian agricultural commodities prices: Evidence from the futures-spot market relationship
Abstract: The volatility of food prices still raises concerns among agricultural market players, increasing interest in the futures markets, thus calling for a better understanding of the connection between the futures and the Italian spot prices. This study uses symmetric and asymmetric vector error correction models to investigate the relationship between futures and spot prices for the Italian agricultural markets of soybean, corn, and milling wheat. The results confirm the leading role of the futures contract prices for all the considered commodities. Moreover, the non-linear cointegration analysis results suggest price transmission's asymmetries for all the agricultural commodity prices. This research provides critical insight into the shape of the futures-spot price transmission.
Keywords: hedging, price discovery, price transmission, threshold vector error correction model, vector error correction model
Journal: Agricultural Economics
Pages: 50-58
Volume: 68
Issue: 2
Year: 2022
DOI: 10.17221/226/2021-AGRICECON
File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/226/2021-AGRICECON.html
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Handle: RePEc:caa:jnlage:v:68:y:2022:i:2:id:226-2021-AGRICECON

Template-Type: ReDIF-Article 1.0
Author-Name: Aleksander Grzelak
Author-Workplace-Name: Department of Macroeconomics and Agricultural Economics, Institute of Economics, Poznań University of Economics and Business, Poznań, Poland
Title: The income-assets relationship for farms operating under selected models in Poland
Abstract: The aim of this paper is to outline the relationship between income and assets when taking into account selected models of farms' functioning. The following farm models are examined: traditional, industrial, sustainable, and organic. Panel models were used that were based on the results of individual unpublished data for farms in Poland that undertook agricultural accounting according to the Farm Accounting Data Network (FADN) principles from 2004 to 2019. It was found that industrial farms had the clearest income-assets relationship, while traditional farms had the least clear relationship. The value of land, as a component of assets, was found to weaken the income-assets relationship. In consequence, the value of assets increased faster than income. Thus, the farmers are becoming wealthier in terms of the value of their assets, but this is not reflected in their income.
Keywords: agriculture, Common Agricultural Policy (CAP), economic situation, panel models, wealth effect
Journal: Agricultural Economics
Pages: 59-67
Volume: 68
Issue: 2
Year: 2022
DOI: 10.17221/361/2021-AGRICECON
File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/361/2021-AGRICECON.html
File-Format: text/html
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Handle: RePEc:caa:jnlage:v:68:y:2022:i:2:id:361-2021-AGRICECON

Template-Type: ReDIF-Article 1.0
Author-Name: Jindřich Špička
Author-Workplace-Name: Department of Strategy, Faculty of Business Administration, Prague University of Economics and Business, Prague, Czech Republic
Author-Name: Zdeňka Náglová
Author-Workplace-Name: Department of Economics, Faculty of Economics and Management, Czech University of Life Sciences Prague, Prague, Czech Republic
Title: Consumer segmentation in the meat market - The case study of Czech Republic
Abstract: The paper responds to the ongoing trends in meat consumption in developed countries and fills the gap in empirical studies on consumer segmentation by preferences in the purchase of meat and meat products in the Czech Republic. The paper aims to assess the differences between the consumer segments according to their preferences in purchasing meat and meat products. The data source was a quantitative questionnaire survey conducted among a representative sample of 992 respondents. An exploratory latent class analysis segmented consumers according to the decision-making criteria when buying meat and meat products. The results complete the picture of the meat and meat products market in terms of consumer behaviour and contribute to a better understanding of meat consumption. The segmentation of consumers according to their preferences resulted in three different categories of consumers, which differ in their purchase decision criteria and socio-demographic characteristics. The segments do not differ significantly in terms of occupation status, region, community size or income level of the respondents. The differences between the generations are much more critical, which were evident in the respondents' average age and household composition. Producers and retailers should better target their marketing activities and communication to different segments.
Keywords: behaviour, consumer groups, latent class analysis, meat consumption, meat products, preferences, questionnaire survey
Journal: Agricultural Economics
Pages: 68-77
Volume: 68
Issue: 2
Year: 2022
DOI: 10.17221/334/2021-AGRICECON
File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/334/2021-AGRICECON.html
File-Format: text/html
X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202202-0004.txt
Handle: RePEc:caa:jnlage:v:68:y:2022:i:2:id:334-2021-AGRICECON