The aim of this study is to determine whether funds spent on research and development are used efficiently in Association of Southeast Asian Nations (ASEAN) countries. Fifteen countries in the 2000-2016 period have been examined. Measuring the efficiency of research and development spending was performed using the non-parametric Data Envelopment Analysis (DEA) methodology, which allows for the assessment of input–output efficiency. The research includes the following input and output variables: annual public and private spending on innovation, high-technology exports as a percentage of manufactured exports, patent applications to the World Intellectual Property Organisation (WIPO) by priority year for million inhabitants, trademark applications (TA) for million inhabitants and information and communications technology (ICT) exports as a percentage of manufactured exports. Hong Kong and the Philippines are perhaps the most efficient with respect to research and development (R&D) when analysed using the constant return to scale (CRS) approach. However, according to the variable return to scale (VRS) approach, the most efficient ASEAN countries are Hong Kong, Indonesia, Singapore and the Philippines. The study also confirms that increased spending on innovation is resulting in non-proportional effects.

The main goal of this paper is to determine whether R&D funds are used efficiently in African countries. The innovativeness of a country’s economy is nowadays one of the key factors stimulating the economic growth and competitiveness. Becoming more innovative is important in particular for developing countries, whose governments are developing national innovation strategies (NIS) and assuming a steady increase in research and development spending. Efficient innovation policies are creating conditions for enterprise development and the increase of competitiveness of the country. A calculation of R&D spending efficiency for selected African economies for the years 2009-2017 was carried out using Data Envelopment Analysis methodology, which allows the evaluation of input-output efficiency. Public and private spending on R&D as % of GDP was the selected inputs indicator. The model examines three output indicators: the number of patent applications (per million inhabitants), high-technology exports (% of export), and number of technical and scientific journal articles (per million inhabitants). Among the analyzed countries, those on the efficiency frontier regarding the use of CRS methodology are South Africa and Tunisia. According to VRS methodology, the most efficient nations are South Africa, Tunisia, and Madagascar. The performed analysis has not confirmed our hypothesis regarding the non-proportional relation between higher R&D spending and innovation outputs. Considering limited innovation capacities across African countries, it appears to be reasonable to increase R&D expenditures gradually to achieve better results on the path toward innovationdriven growth and development.

Environmental protection policy is a widely discussed issue in scientific works. However, special attention should be also paid to the effectiveness of expenditures on environmental protection, and this is the main goal of this paper. The countries of the European Union were selected for this analysis due to the fact that, in recent years, this region has become an informal world leader with respect to the implementation of policy measures in the field of environmental protection. For that reason, the data envelopment analysis methodology was used, which allows the calculation of input-output efficiency for the years 2005–2015. The analysis shows that, among the 30 analyzed countries, the most effective in environmental protection actions is Finland. The hypothesis that higher environmental protection expenditures does not result in better environmental results has been confirmed. Our analysis confirmed the problem of the deteriorating efficiency of environmental expenditures across the selected European Union Member States, caused by increases in spending. This research may contribute to the discussion on environmental protection policy design and its assessment, as well as environmental policy results measurement.

Innovativeness is one of the key factors stimulating economic growth. Improving innovative capacities is especially important for developing countries. The Latin American region is characterized by a variety of innovation policies. In this article, the author attempts to answer the question of which Latin American countries most efficiently spend funds on R&D. The study presented in this article also verifies the hypothesis that increased spending on R&D does not result in a proportional increase in the intended innovative results. The main research methodology employed is data envelopment analysis (DEA), which allows for assessing input-output efficiency and indicates the efficiency frontier for the period between 2000 and 2017.

In the 21st century, there have already been a series of economic downturns, particularly the Subprime Crisis 2007–2009 and the Covid-19 pandemic in 2020. All those events triggered changes in productivity, economic performance and structure. The main objective of this study is to identify the regions left behind in the Central and Eastern European (CEE) countries and to analyse the structural and productivity changes taking place within them. In our analysis, we aim to verify the research hypothesis that all left-behind regions in CEE have similar economic structures with a high share of agriculture. The research period covers the years from 2010 until 2020 using data from the Eurostat database. In the first phase of our analysis, we analysed employment, Gross Value Added (GVA) and productivity data for 11 CEE countries. Then, we analysed the Nomenclature of Territorial Units for Statistics at level 3 (NUTS3) regions, and Poland, which is a NUTS2 region. Left-behind regions are defined as those with low productivity and low growth rates. We provide a detailed analysis of the best and worst performing regions in terms of productivity for each country using productivity data and shift-share decomposition of productivity growth rate. Left-behind regions for each CEE country have been identified, and these are BG333, BG342, CZ080, EE004, HR023, HU332, LT027, LV005, PL72, RO216, RO312, SI032, SI035, SI038 and SK032. In our analysis, our hypothesis analysing the relationship between agriculture share in total employment and the productivity level of the region was not confirmed.

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