Dairy futures price volatility plays an important role in dairy farmers' risk management as well as dairy commodities price discovery. Trading activity as a factor for agricultural futures price volatility has been studied extensively since the emerge of commodity index traders followed by commodity markets becoming more volatile in the last decade. However, the majority of research papers investigate major cereal future contracts whereas the research on dairy futures is not yet analyzed. The aim of this review is to present the current situation in the research of dairy futures trading activity effect on their price volatility, focusing on methodological progress and related issues. This review provides a comparative analysis of empirical research articles on dairy futures price volatility and its determinants published in 2005 and later. Dairy futures markets compared to other agricultural commodity markets were less liquid and more fragmented, however, they likewise experienced a significant price volatility and seasonality during observed time periods. High price volatility was especially present in cash settled butter futures. Even though there is an indication among selected studies that trading activity correlate with price volatility, this should be supplemented by an analysis of causal relationships. Therefore, a further research on dairy futures should provide necessary tools to measure the exact effect of trading activity on price volatility in order to provide better insights on using dairy futures as an effective means for managing price risk in dairy sector.

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 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.

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.

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.