This paper aims to indicate the linkages between crude oil prices and selected food price indexes (dairy, meat, oils, cereals, and sugar) and provide an empirical specification of the direction of the impact. This paper reviews the fuel–food price linkage models with consideration to the time series literature. This study adopts several methods, namely the Augmented Dickey–Fuller test, Granger causality test, the cointegration test, the vector autoregression model, and the vector error correction model, for studying the price transmission among the crude oil and five selected food groups. The data series covers the period between January 1990 and September 2020. The empirical results from the paper indicate that there are long-term relationships between crude oil and meat prices. The linkage of crude oil prices occurred with food, cereal, and oil prices in the short term. Furthermore, the linkages between the analyzed variables increased in 2006–2020.
Transport is one of the most essential sectors of the EU member state economies. Measurement of the efficiency of transport operations seems to be interesting from the perspective of both the economy as a whole and individual companies operating in the transport sector. The largest proportion of freight transport in the European Union is done by road. The purpose of this paper is to determine the efficiency of road and rail freight transport in old and new European Union countries based on the data envelopment analysis (DEA) method. To that end, the authors present a literature review reflecting the current state of research on the importance of transport and its development in relation to the economy and environmental problems. Additionally, the methods of data analysis and variables are described. The empirical part is divided into a presentation of DEA results and correlation between the transport efficiency, gross domestic product (GDP), and CO 2 emissions results. Moreover, spatial analysis was used to characterize road and rail transport efficiency in EU member states. The last section gives a summary of the study, and the obtained results are compared with data from the literature review.
Seaport efficiency and productivity are the critical factors for handling of goods in the international supply chains and plays an important role in trade exchange with other countries. It is important to evaluate efficiency and productivity of seaports to reflect their status and reveal their position in competitive environment. The main purpose of this article is to use Data Envelopment Analysis and Malmquist Productivity Index to measure the technical efficiency and total factor productivity of container ports. DEA analysis enables one to assess how efficiently a seaports uses the available inputs to generate a set of outputs relative to other units in the data set. This article presents the use CCR and BCC DEA model, to determine overall technical efficiency, pure technical efficiency and scale efficiency of container ports. The analysis gives a possibility to create a efficiency ranking of seaports. The study also applies the Malmquist Productivity Index (MPI), which was used to analyze changes in seaports productivity. The study indicated that technological progress had a greater impact on the change in productivity of container ports than changes in technical efficiency
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