ABSTRACT
PurposeThe paper analyzes the relative technical efficiency of the transition economies of the Western Balkans in the period 2007-2021, in comparison with the former countries with a socialist state system, today members of the European Union (EU), based on selected macroeconomic indicators and panel data.Design/methodology/approachData envelopment analysis (DEA), i.e. its extension, DEA Window analysis, is applied. Total technical efficiency, as a prerequisite of economic efficiency, is decomposed into pure technical efficiency (PTE) and scale efficiency (SE). Bootstrapping method and Mann-Whitney U test were used to check the robustness of the obtained results, i.e. efficiency values.FindingsThe results show that in 2020, all observed countries recorded a significant drop in economic efficiency as a result of a general, disproportionate drop in the value of selected macroeconomic variables, which occurred due to the global economic crisis and the slowdown in economic activity caused by the COVID-19 pandemic. This drop in efficiency was significantly greater in the former socialist states, now members of the European Union, which showed their greater sensitivity to global crises. None of the observed economies in the observed period was relatively efficient, that is, at the level of best practice, which occurred primarily as a consequence of the inefficiency of business conditions expressed in the economies of scale.Research limitations/implicationsThe main limitation of this study stems from the very nature of the concept of DEA efficiency, which is relative in nature. Also, the results and their interpretation are also significantly influenced by the choice of model variables, as shown by Labaj et al. (2013), as well as a small number of decision-making units (DMUs). The mentioned limitations prevent unambiguous interpretation and generalization of the obtained results.Practical implicationsThe study may be of importance to economic policy makers in macroeconomic decision-making. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage on the international market.Originality/valueSince research of this type is very limited, the results of this study make a theoretical and empirical contribution to the literature, creating a basis for future research and reexamination. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage in the international market.
ABSTRACT
In December 2019, the virus SARS-CoV-2 responsible for the COVID-19 pandemic was detected in the Chinese city of Wuhan. The virus started to spread from China and dispersed over the rest of the world. In March 2020, WHO (World Health Organization) declared COVID-19 a pandemic. The transmission path of the pandemic was accelerated by different types of transportation. With complete analysis of spatial data, population density, types of traffic networks, and their properties, the spatial distribution of COVID-19 was estimated. GIS (Geographical Information System), numerical methods, and software for network analysis were used in this research to model scenarios of virus distribution on a global scale. The analyzed data included air, railway, marine, and road traffic. In the pandemic research, numerous models of possible trajectory of viruses can be created. Many have a stochastic character. This study includes all countries in the world affected by the COVID-19 up to date. In this study, GIS methods such as buffer, interpolations, and numerical analysis were used in order to estimate and visualize ongoing COVID-19 pandemic situation. According to the availability of new data, trajectory of virus paths was estimated. On the other hand, sparsely populated areas with poorly developed and small traffic networks (and isolated island territories) tend to be less or not affected as shown by the model. This low-cost approach can be used in order to define important measures that need to be addressed and implemented in order to successfully mitigate the implications of COVID-19 not only on global, but local and regional scales as well.