Template-Type: ReDIF-Article 1.0 Author-Name: Tamara Rudinskaya Author-Workplace-Name: Agricultural Market Department, Institute of Agricultural Economics and Information, Prague, Czech Republic Author-Name: Iveta Boskova Title: Asymmetric price transmission and farmers' response in the Czech dairy chain Abstract: The standard economic price theory of working with efficient source allocation is being confronted with a series of empirical findings of asymmetric price responses. The objective of the research was to examine whether the distribution of prices within the dairy chain in the Czech Republic was fair and whether farmers progressed in a collective approach to strengthen their position in the supply chain. We used the pre-cointegration and cointegration approach to test for asymmetry in the transmission of farm milk prices throughout the supply chain. Furthermore, we measured the development of market concentration by means of the Herfindahl-Hirschman index and discussed the background of the figures with producer organisation representatives. The results proved there were asymmetric price transmissions. In response, farmers consolidated and concentrated their milk sales. The concentration should not yet be understood as a goal but as a means to the next steps. Keywords: cooperation, market power, market structure, producer organisations, supply chain Journal: Agricultural Economics Pages: 163-172 Volume: 67 Issue: 5 Year: 2021 DOI: 10.17221/22/2021-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/22/2021-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202105-0001.txt Handle: RePEc:caa:jnlage:v:67:y:2021:i:5:id:22-2021-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Pavla Vrabcová Author-Workplace-Name: Economics Department, University of Economics and Management, Prague, Czech Republic Author-Name: Hana Urbancová Author-Workplace-Name: Department of Human Resources, University of Economics and Management, Prague, Czech Republic Title: Use of human resources information system in agricultural companies in the Czech Republic Abstract: High-quality information systems explicitly focused on working with people help companies meet the increasingly complex requirements for registration of attendance, forms, employment contracts, and much more. The article's main goal is to identify areas of human resources management for which agricultural companies in the Czech Republic use information systems to increase the efficiency of processes and evaluate the development of their usage with regard to the support of digitisation. The data, which were subjected to factor analysis, were obtained via a questionnaire survey from selected 70 agricultural companies in the Czech Republic and via qualitative research (focus group, n = 7). The largest share of monitored agricultural holdings is using IT systems in the area of personal data, while the smallest share of monitored agricultural holdings is using software for monitoring education and knowledge transfer. Factor analysis identified 4 factors that characterise agricultural companies according to the use of information and communication technologies (ICT) in human resource management. The results show that in terms of the current shift of the entire agriculture towards digitisation, the use of ICT in staff management of companies cannot be neglected. The outbreak of the COVID-19 pandemic exacerbates the use of ICT. Keywords: digitisation in human resources, employee development, employee training, human resources information system, registration of personal data Journal: Agricultural Economics Pages: 173-180 Volume: 67 Issue: 5 Year: 2021 DOI: 10.17221/452/2020-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/452/2020-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202105-0002.txt Handle: RePEc:caa:jnlage:v:67:y:2021:i:5:id:452-2020-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Renata Grochowska Author-Workplace-Name: Institute of Agricultural and Food Economics - National Research Institute, Warsaw, Poland Author-Name: Aleksandra Pawłowska Author-Workplace-Name: Institute of Rural and Agricultural Development, Polish Academy of Sciences, Warsaw, Poland Author-Name: Aldona Skarżyńska Author-Workplace-Name: Institute of Agricultural and Food Economics - National Research Institute, Warsaw, Poland Title: Searching for more balanced distribution of direct payments among agricultural farms in the CAP post-2020 Abstract: The study aimed to examine the changes in income inequalities in Polish farms and the impact of introducing the threshold of direct payments for farms (EUR 60 000) to form these inequalities. The research was based on data from the Farm Accountancy Data Network (FADN) for the years: 2006, 2013 and 2018. In each year, the sample included at least 10 000 observations that represented over 700 000 farms. The results were verified using statistical tests relating to the comparisons of averages and distributions of farm income for two samples and the Gini coefficient. The study noted deepening income inequalities in Polish farms, as evidenced by the increasing value of the Gini coefficient in the subsequent years and the growing share of payments in the formation of these inequalities. Neither for the sample analysed nor the field of observation of farms will introduce the threshold for direct payments per farm of at least EUR 60 000 (including labour costs) change the polarisation of income. Keywords: capping, farm income inequality, Gini coefficient Journal: Agricultural Economics Pages: 181-188 Volume: 67 Issue: 5 Year: 2021 DOI: 10.17221/417/2020-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/417/2020-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202105-0003.txt Handle: RePEc:caa:jnlage:v:67:y:2021:i:5:id:417-2020-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Fachry Husein Rosyadi Author-Workplace-Name: Faculty of Agriculture, Gadjah Mada University, Yogyakarta, Indonesia Author-Name: Jangkung Handoyo Mulyo Author-Name: Hani Perwitasari Author-Workplace-Name: Faculty of Agriculture, Gadjah Mada University, Yogyakarta, Indonesia Author-Name: Dwidjono Hadi Darwanto Author-Workplace-Name: Faculty of Agriculture, Gadjah Mada University, Yogyakarta, Indonesia Title: Export intensity and competitiveness of Indonesia's crude palm oil to main destination countries Abstract: Palm oil is a superior product from Indonesia that is continuously and widely used for daily needs such as cooking, grooming, and manufacturing. However, this potential must be supported by oil palm business actors' performance to maintain its intensity and competitiveness. This study investigates how various factors affect Indonesia's crude palm oil (CPO) export intensity and competitiveness by employing panel regression and the basic gravity model. The panel data used here is a 20-year time series with cross-sections from five major importers from 1999 to 2018. The results show that the importer's gross domestic product (GDP) and quantity of export significantly and positively affect Indonesia's CPO export intensity, while the exporter's GDP and economic distance has a significant and negative effect. The factors that positively and significantly influence competitiveness are soybean's import value and Roundtable on Sustainable Palm Oil (RSPO) certification, while Malaysian CPO's export and population of importing countries negatively affect Indonesian CPO competitiveness. Keywords: bilateral trade, export, gravity model, panel data, revealed comparative advantage Journal: Agricultural Economics Pages: 189-199 Volume: 67 Issue: 5 Year: 2021 DOI: 10.17221/371/2020-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/371/2020-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202105-0004.txt Handle: RePEc:caa:jnlage:v:67:y:2021:i:5:id:371-2020-AGRICECON Template-Type: ReDIF-Article 1.0 Author-Name: Tao Yin Author-Name: Yiming Wang Author-Workplace-Name: School of Economics, Peking University, Beijing, China Title: Nonlinear analysis and prediction of soybean futures Abstract: We use chaotic artificial neural network (CANN) technology to predict the price of the most widely traded agricultural futures - soybean futures. The nonlinear existence test results show that the time series of soybean futures have multifractal dynamics, long-range dependence, self similarity, and chaos characteristics. This also provides a basis for the construction of a CANN model. Compared with the artificial neural network (ANN) structure as our benchmark system, the predictability of CANN is much higher. The ANN is based on Gaussian kernel function and is only suitable for local approximation of nonstationary signals, so it cannot approach the global nonlinear chaotical hidden pattern. Improving the prediction accuracy of soybean futures prices is of great significance for investors, soybean producers, and decision makers. Keywords: artificial neural network (ANN), chaos, forecasting, long-range dependence, multifractal Journal: Agricultural Economics Pages: 200-207 Volume: 67 Issue: 5 Year: 2021 DOI: 10.17221/480/2020-AGRICECON File-URL: http://agricecon.agriculturejournals.cz/doi/10.17221/480/2020-AGRICECON.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/age-202105-0005.txt Handle: RePEc:caa:jnlage:v:67:y:2021:i:5:id:480-2020-AGRICECON