Global commodity markets, due to major health crises, political tension, sanctions, growing demand, and other global supply and demand factors, are currently particularly unstable. In addition to the macro-environmental factors that drive the prices, agricultural and other commodity markets are becoming more susceptible to the continuously-growing speculation on major commodity exchanges. Therefore, the purpose of this study is to analyze the influence of financial speculation on agricultural and other commodity prices and return volatility. In our study, we use daily returns on wheat, soybean, corn, and oats futures from the Chicago Mercantile Exchange as well as two additional commodities (crude oil and gold) to compare the extent of this effect. To measure this impact, we, besides traditional tools for time-series analysis, apply the threshold autoregressive conditional heteroskedasticity (TGARCH) technique. We also provide a model using dummy variables for the season to determine whether or not financial speculation’s impact on return volatility differs among seasons, as seasonality plays an important role in return dynamics for agriculture. Our study’s findings show that financial speculation, except for the oats market, either has no impact or makes the underlying futures returns less volatile. Therefore, we draw the conclusion that either there is no relationship between the rise in short-run speculation and the volatility of agricultural commodity prices, or the link is at best questionable. Research results provide important implications for the sustainable development of commodity markets, as passive legislation measurers can be seen as more effective ones compared to more strict active ones in order to maintain these markets liquid and capable of distributing price risks for agricultural producers and manufacturers in a challenging economic and geopolitical environment.

Scientists and policy makers more often point out that pro-environmental attitudes and behaviour are related to subjective well-being, but there is a lack of deep scientific insights, as well as possible measure analysis, which would promote pro-environmental behaviour but, at the same time, lead to higher subjective well-being. The aim of this study is to investigate the relationship between pro-environmental attitudes, concerns about climate change, and subjective well-being in Central and Eastern European countries. This study employs descriptive statistics and multiple regression analysis to identify subjective well-being predictors in the case of Central and Eastern European countries. This study uses data from European Social Survey (ESS) rounds 4–10, and includes questions on pro-environmental attitudes, climate change cognition, orientation towards materialistic values, and households’ total net income. The conducted research revealed that pro-environmental attitudes were related to higher levels of subjective well-being in different ESS rounds in many Central and Eastern European countries. In addition, there is some evidence that the relationship between pro-environmental attitudes and subjective well-being is weaker among individuals who are more oriented towards materialistic values. According to the results of this study, policy makers should develop policies that not only address environmental problems but also contribute to subjective well-being.

The EU’s Common Agricultural Policy has for decades been geared towards sustainable agricultural development, not only to ensure a fair income for farmers but also to tackle climate change and environmental degradation, emphasizing the link between agricultural economic activity and the importance of greenhouse gas (GHG) emissions. The importance of research in this area is reinforced by the EU’s ever-increasing sustainability ambitions in recent years, as set out in the European Green Deal, which has found a place in the new 2023–2027 Common Agricultural Policy (CAP) policy to meet the EU’s 2050 target to achieve climate neutrality. The aim of this study is to assess the relationship between greenhouse gas emissions and economic performance for the agricultural sector in the Baltic States (Lithuania, Latvia, and Estonia) from 1998 to 2019. These three countries have similar agricultural structures and similar natural conditions, so the research provides comparable results. The relationship was analyzed by using the nonlinear autoregressive distributed lag (NARDL) model that allows the estimation of short-term dynamics using a distributed delay component and long-term dynamics using a single cointegrating vector. The analysis of the research data showed that gross value-added changes influence greenhouse gas emissions in all three countries. The results of the research, on the other hand, suggested that there is evidence supporting the reverse ‘U-shaped’ impact of the environmental Kuznets curve (ECK) when assessing data from Lithuania and Estonia, but not from Latvia. The study’s findings have significant policy consequences.

Motivated by increased agricultural commodity price volatility and surges during the past decade, we investigated whether financial speculation is to blame. The aim of this paper is to build on prior research about to what extent and in which ways financial speculation undermines agricultural commodity prices. In our analysis, we utilized the daily returns on milling wheat, corn, and soybean futures from the Euronext Commodities Paris market (MATIF) as well as the short-term speculation index. To quantify this impact, we apply Granger noncausality tests as well as the GARCH (generalized autoregressive conditional heteroskedasticity) technique. We also propose a model using seasonal dummy variables to examine whether financial speculation has a greater impact on price volatility during more volatile months. According to our results, financial speculation, as an external factor, in most cases has no effect or reduces the volatility of the underlying futures prices. The opposite is observed in the corn market, where volatility has risen in the post-2020 period and has been pushed up even more by speculation in April. However, since the influence on other commodities is limited or nonexistent, more emphasis should be focused on speculation in the European corn futures market or its interdependence with energy markets.

The main aim of this article is to empirically examine the impact of economic growth and urbanisation on environmental degradation, as well as the existence of the environmental Kuznets curve (EKC) in three Baltic States (Lithuania, Latvia, and Estonia) from 2000 to 2020. The main Kaya identity and the extended urban Kaya identity models are applied within the analysis. The multiple regression analysis made it possible to assess the influence of urbanisation and other factors on greenhouse gas (GHG) emissions in the studied countries, as well as test the hypothesis of the inverted U-shaped EKC. The main finding reveals that GDP per capita growth has the largest and increasing effect on GHG emissions in all three countries. It was also found that changes in population in urban areas in Lithuania and Latvia reduced the amount of GHG until 2020, while in Estonia, the growing urban population greatly contributed to increasing GHG emissions. As a result, processes related to urbanisation have not yet had a significant impact on environmental quality in Lithuania and Latvia. Meanwhile, in Estonia, this is a significant factor that policymakers need to focus on when solving environmental pollution reduction problems. The hypothesis of the EKC was mostly supported when analysing GHG emissions in Lithuania and Estonia and using GDP per capita as an indicator for economic growth. On the other hand, it was found that the impact of the urbanisation rate on GHG emissions is not curved, yet there is some evidence that in Estonia, a growing urbanisation rate is related to diminishing GHG emissions, according to the multiple regression analysis. The results of the study showed that policymakers should consider economic growth and, especially in Estonia, urbanisation when solving problems related to environmental degradation.

The development of a country’s economy is directly related to the use of energy in that country’s economic sectors. Therefore, the energy–environmental Kuznets curve (EEKC) is often used when analysing a country’s potential and challenges in sustainable development, green economy, and green growth. This hypothesis tests whether there is an inverse “U”-shaped relationship between energy use and economic growth and is especially important when analysing developing countries to assess if, at a certain point, energy use begins to drop, resulting in fewer greenhouse gas emissions, environmental degradation, and the consumption of fossil-based fuels. This study aims to examine the relationship between energy consumption and economic growth in the Baltic States from 1995 to 2019, with a focus on the agriculture sector. The study uses the non-linear autoregressive distributed lag (NARDL) model for individual and panel time series. Total energy use, as well as electricity use, is included in the study, whereas gross value added is employed as a measure of economic growth. Research data analysis reveals that energy use in all three Baltic countries stabilises as gross value added increases. However, there is insufficient evidence to show that after a certain point, energy use begins to drop; thus, the hypothesis for the inverse “U”-shaped energy–environmental Kuznets curve (EEKC) is rejected. Research results have important practical implications regarding countries’ policies toward energy, including the use of electricity and sustainable development.