Decomposition analysis of global value chains: Uncovering vulnerable spots in a selected economy (the example of Czechia).

Recent global turmoil has added to the importance of food security issues and the sustainability of production processes worldwide. This study aims to uncover the degree of domestic industries' dependence on the international fragmentation of production processes and identify the countries of origin of those producers who have managed to displace domestic producers in corresponding Global Value Chains. Using data retrieved from the World Input-Output Database, we studied Czechia's example via demarcation of domestic value-added (DVA) shares from foreign ones in final domestic products. A declining trend in DVA signalises an ever-increasing dependence on foreign inputs. The conducted analysis allowed a VA-structure (and its dynamics for a sequence of years) to be clearly identified for final domestic products among 30 industries that virtually cover the entire economy. The most alarming finding is the marked reduction of DVA in food manufacturing, which points to a weakening of Czech food security. Realising all the connections within GVCs may help to identify vulnerable spots in domestic production processes and prepare adequate response mechanisms in potential situations of possible interruptions from the foreign side. The detailed explanation of the decomposition technique provided in the study can be used in similar analyses of other economies to reveal noteworthy trends and prepare response measures.

Farm diversification as a potential success factor for small-scale farmers constrained by COVID-related lockdown. Contributions from a survey conducted in four European countries during the first wave of COVID-19.

This paper explores to what extent product and marketing channel diversification contributed to the economic success of small-scale agricultural producers involved in short food supply chains after the outbreak of the COVID-19 pandemic. A survey was conducted between April and July 2020 in four countries of the European Union-Estonia, Hungary, Portugal and Romania,-resulting in a relatively large sample of farmers (N = 421). The analysis was built on a semi-nonparametric approach. Approximately 19 percent of small-scale producers were able to increase sales during the first wave of the pandemic, although country-level variation was significant. Fruits and vegetables were by far the most popular products. The importance of specific channels varied across countries, but farm gate sales were among the most important marketing channels both before and during the first wave. The importance of channels that were based on digital resources and home delivery increased. Our evidence indicates that diversification was a strategy that paid off, both in terms of marketing channels and different product categories. However, the impact appears to be nonlinear; the initial advantage generated by diversification rapidly tapered off, either temporarily (in the case of products), or permanently (in the case of marketing channels). Later research may clarify whether these findings are generalizable in other socio-economic contexts, as well as in a non-COVID situation.

Investigating the dynamic eco-efficiency in agriculture sector of the European Union countries.

One of the main aims of European Common Agricultural Policy (CAP) has been established on a considerable reduction of greenhouse gas (GHG) emissions without any decline in productivity by 2030. This introduces some challenges in the assessment of agricultural technical efficiency. In particular, we can formulate at least two problems that are worth to be addressed: (i) possibility of treating undesirable outputs and (ii) panel data analysis of agricultural technical efficiency enriched by eco-efficiency assessment. In this study, we applied a Window Slack-Based Measurement Data Envelopment Analysis (W-SBM-DEA) model in the presence of undesirable outputs to evaluate the performance of agriculture sector of EU-27 countries during the period from 2008 to 2017. The country-level cultivated agricultural area, labor, specific costs, overheads, and depreciation were considered as the model inputs, and the gross value of country-level crop and livestock products represented the desirable outputs. The agricultural total GHG emissions at the country-level were accounted for as the undesirable output in the model. Having compared the results of different models, the substantial difference in the performance of the EU countries was registered mainly due to incorporating undesirable outputs and window analysis when using SBM-DEA model. The results of eco-efficiency assessment indicated that the Netherlands, Belgium, Italy, and Malta are the most eco-efficient countries with a score higher than 0.90, while the lowest eco-efficiency scores were reported for Slovakia, Latvia, and Estonia. The highest average eco-efficiency scores of all EU members were registered in 2011 (0.82), 2012 (0.83), and 2017 (0.84). A comparison of eco-efficiency performance between the old and new EU members indicated that the greater scores were obtained by old EU members. The variability assessment results showed a low variability and subsequently a high stability in the European agricultural sector, particularly in the Netherlands, Italy, and Malta. Based on our findings, it was concluded that for assessing agricultural technical efficiency in European agriculture in the context of eco-efficiency, application of a W-DEA model with undesirable output for a specified period of time reduces the impacts of temporary changes and provides more realistic results when comparing to models without undesirable output. These more realistic assessments of technical efficiency could help policy-makers to make more precise decisions.