This paper analyses theoretical and empirical scientific literature about the impact of technological innovations on unemployment, considering the former as a key driver of long-term productivity and economic growth. Using panel data from 25 European countries for the period of 2000–2012, we aim to examine whether technological innovations affect unemployment. We used triadic patent families per million inhabitants as our main proxy for technological innovations, as well as other unemployment controls, in our model, which were estimated using System Generalized Method of Moments (SGMM). Finding no significant relationship between technological innovations and unemployment in our base estimation, we re-estimated it testing the impact with a time lag as well as using alternative proxies for technological innovations. Overall, the research estimations do not suggest that technological innovations have an effect on unemployment.

Research background: Unemployment is a huge topic for policymakers, scholars, and, in general, society. Historically, there have always been a lot of discussions about this phenomenon. It is already acknowledged that unemployment is closely related to economic activity: when the economy is growing, more people are employed, and when economic activity is low, employment decreases, and unemployment rises. This relation is well-researched in the framework of Okun’s law. However, it is far less known how this relationship holds if international economic relations are introduced. Thus, the motivation for the research was to examine the role of international trade and foreign direct investment (FDI) on the growth-unemployment nexus. Purpose of the article: To assess how trade and FDI affect growth and gender-, age-, and educational attainment level-specific unemployment relationship and on what scale this effect varies over different business cycle phases. Methods: Scientific literature review, comparative analysis, and panel regression. Findings & value added: Given the lack of research examining what effect FDI and trade have on the growth-unemployment nexus, this paper estimates modified Okun’s equation on the European Union (EU) countries (EU–28, by the composition of the EU until 31/01/2020) for the period from 2000 to 2019 while incorporating international aspects that can have an impact on this nexus. Also, this study develops a specification that can be useful to monitor the potentially different effects of FDI and trade on the growth-unemployment nexus during different business cycle phases. The estimations of the panel regression for unemployment disaggregated by age, gender and education level has showed that import, export, inward FDI, and outward FDI have a negative effect on the growth-unemployment nexus. It means that with an increase in the intensity of international economic relations, the influence of gross domestic product (GDP) growth on unemployment becomes less significant. Thus, the effectiveness of expansionary fiscal policy to reduce unemployment becomes less effective in more open economies, which in the case of the EU are the smallest member states with relatively small domestic markets.

Growing concerns over ecosystem degradation, climate change, loss in biodiversity, and rapid depletion of natural resources have urged societies of the developed countries all over the world to encounter the challenge of shifting from fossil-based to bio-based economies. With European Green Deal priorities on a transition to a climate-neutral economy with net-zero GHGs emissions by 2050, projected demand for biomass is 40–100% higher, relative to its supply. To provide an overview on the capacity of the European Union countries to satisfy its demand for biomass through the organic materials extracted directly from the domestic natural environment, the study aimed to assess the biomass self-sufficiency based on its domestic extraction-domestic consumption balance. Both the spatial and temporal variability of the self-sufficiency ratio are used to characterise the stability of capacity to satisfy our own needs for biomass in the EU economy as a whole, and at the level of individual member states. The findings indicate that the differences in biomass self-sufficiency ratios are quite high among the European Union member countries (i.e., in the range of 15% in Malta and 33% in Cyprus; up to 184% in Estonia and 224% in Latvia (on average in 2016–2018)). GMM analysis (EU-28, 2000–2018 period) is provided in this study to define the main statistically significant factors that have an impact on the biomass self-sufficiency ratio. This study contributes to the debate on the issues of biomass self-sufficiency in the context of ecological constraint and the EU’s Green Deal.

This article describes a strategic concept for the Lithuanian bioeconomy that was developed as a deliverable of the Task 1.5 in the BIOEAST’sUP H2020 project. We aimed to create a conceptual basis for the preparation of a national bioeconomy strategy and/or action plan in order to initiate a deeper discussion about the strategically oriented development of a knowledge-based circular bioeconomy in Lithuania. Our strategic insights are focused on two niche energy sectors like biofuels and biogas. The results of the SWOT analysis reveal that, in Lithuania, a synthesis of the biofuels and biogas sectors' strategic directions is necessary to develop over-arching national bioeconomy-appropriate strategic actions, such as market intervention actions, research, innovation and education actions, as well as governance and policy actions.

The aim of the article is to identify the relationship between time allocation for work and personal life and happiness by reviewing the theoretical aspects of time allocation for work and personal life and happiness and by presenting an empirical research methodology. A review of the scientific literature is carried out using a comparative analysis and a generalisation method. Empirical research was conducted using statistical data, correlation analyses, non-parametric Mann-Whitney U test, X2 criterion, and data collection methods: questionnaire and time diary. The number of respondents is 1073, the studied population is self-employed persons in Lithuania. Empirical evidence shows that in 2019, self-employed people in Lithuania spent 77.5 percent of their daily time on their personal life (mostly to sleep and leisure) and 22.5 percent on work. With a 95 percent probability, it was found that the time spent on sleep (08:41) by 15-24-year-olds is statistically significantly different from other age groups (H11 confirmed). Although self-employed individuals were most likely to be happy, satisfied with work and satisfied with their personal life in 2019, but those aged 15-24 were the happiest. However, men were more satisfied with work and women were more satisfied with their personal life. There was a statistically significant relationship at a 95 percent confidence level between the level of work-life balance of the self-employed person and happiness (H21 confirmed).

This study aims to assess the impact of public spending on education on unemployment. The study also considers other factors affecting unemployment, such as gross domestic product (GDP), exports, foreign direct investment, and inflation. Hypotheses are proposed for each factor affecting unemployment. This empirical study analyses Lithuanian data from 2000 to 2023 using the ordinary least squares method. The results showed that public spending on education and foreign direct investment significantly reduces unemployment. The results also revealed that net exports have a very insignificant effect on increasing unemployment, and inflation does not have a statistically significant effect on unemployment. GDP was removed from the model due to issues encountered when testing the regression model’s assumptions.