Search Results (1,870)

Given the significant shifts in rural labor mobility patterns and their continuous influence on the transformation of the land factor market, it is crucial to understand the relationship between labor factor prices and land factor prices. This understanding is essential to keep land factor prices within a reasonable range. This study establishes a theoretical framework to investigate how migrant workers’ return shapes land price formation mechanisms. Using 2023 micro-level survey data from eight counties in Jiangsu Province, China, this study empirically examines how migrant workers’ return affects land transfer prices and its underlying mechanisms through OLS regression and instrumental variable approaches. The findings show that under the current pattern of labor mobility, the outflow factor alone is no longer sufficient to exert substantial downward pressure on land transfer prices. Instead, the localized return of labor has emerged as a key driver behind the rise in land transfer prices. This upward mechanism is primarily realized through the following pathways. First, factor substitution effect: this effect lowers labor prices and increases the relative marginal output value of land factors. Second, supply–demand effect: migrant workers’ return simultaneously increases land demand and reduces supply, intensifying market shortages and driving up transfer prices. Lastly, the results demonstrate that enhancing the stability of land tenure security or increasing local non-agricultural employment opportunities can mitigate the effect of rising land transfer prices caused by the migrant workers’ return. According to the study’s findings, stabilizing land factor prices depends on full non-agricultural employment for migrant workers. This underscores the significance of policies that encourage employment for returning rural labor. Full article

This study introduces a novel tripartite evolutionary game model to analyze the strategic interactions among electric vehicle (EV) aggregators, local governments, and EV users in vehicle–grid interaction (VGI) markets. The core novelty lies in capturing bounded rationality and dynamic decision-making across the three stakeholders, revealing how policy incentives and market mechanisms drive the transition from disordered charging to bidirectional VGI. Key findings include the following: (1) The system exhibits five stable equilibrium points, corresponding to three distinct developmental phases of the VGI market: disordered charging (V0G), unidirectional VGI (V1G), and bidirectional VGI (V2G). (2) Peak–valley price differences are the primary driver for transitioning from V0G to V1G. (3) EV aggregators’ willingness to adopt V2G is influenced by upgrade costs, while local governments’ subsidy strategies depend on peak-shaving benefits and regulatory costs. (4) Increasing the subsidy differential between V1G and V2G accelerates market evolution toward V2G. The framework offers actionable policy insights for sustainable VGI development, while advancing evolutionary game theory applications in energy systems. Full article

In vitro meat presents a promising alternative to conventional meat production by addressing environmental and animal welfare concerns. However, broader market adoption depends on increasing consumer acceptance. Labels on product packaging have been shown to be effective in influencing consumer behavior in previous studies. This paper examines the impact of different front-of-package labels on German consumers’ choices regarding in vitro chicken meat, with the goal of identifying effective labeling strategies. To investigate this, an online choice experiment was conducted with 200 participants from Germany. In addition to the label, products varied in terms of price, origin, and calorie content. The data were analyzed using latent class analysis, which identified four distinct consumer segments characterized by their preferences, attitudes, and personal characteristics. The results were used to simulate market scenarios, evaluating the effectiveness of different labeling strategies for in vitro chicken meat. These insights provide a foundation for targeted marketing approaches that promote consumer acceptance and inform the introduction of in vitro meat products in Germany. Full article

Housing prices have recently risen sharply in many countries, primarily linked to the global credit cycle. Although various factors play a role, the ability of developing countries to navigate this cycle and maintain autonomous monetary policies is crucial. This paper introduces a dynamic macroeconomic model featuring a housing production sector within an imperfect banking framework. It captures key housing and economic dynamics in advanced and emerging economies. The analysis shows domestic liquidity policies, such as bank capital requirements, reserve ratios, and currency devaluation, can stabilize investment and production. However, their effectiveness depends on foreign interest rates and liquidity. Stabilizing housing prices and risk-free bonds is more effective in high-interest environments, while foreign liquidity shocks have asymmetric impacts. They can boost or lower the effectiveness of domestic policy, depending on the country’s level of financial development. These findings have several policy implications. For example, foreign capital controls would be adequate in the short term but not in the long term. Instead, governments would try to promote the development of local financial markets. Controlling debt should be a target for macroprudential policy as well as promoting saving instruments other than real estate, especially during low interest rates. Full article

This paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of two-asset financial derivatives. The multivariate models are built to ensure two conditions. First, marginals follow desirable processes, e.g., we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one-dimensional process. These conditions lead to a specific choice of the dependence structure in the form of a local-correlation model. Two popular multi-asset options are entertained: a spread option and a basket option. Full article

The phenomenon of rising forward price volatility, both historical and implied, as maturity approaches is referred to as the Samuelson effect or maturity effect. Disregarding this effect leads to significant mispricing of early-exercise options, extendible options, or other path-dependent options. The primary objective of the research is to identify a practical way to incorporate the Samuelson effect into the evaluation of commodity derivatives. We choose to model the instantaneous variance employing the exponential decay parameterizations of the Samuelson effect. We develop efficient calibration techniques utilizing historical futures data and conduct an analysis of statistical errors to provide a benchmark for model performance. The study employs 15 years of data for WTI, Brent, and NG, producing excellent results, with the fitting error consistently inside the statistical error, except for the 2020 crisis period. We assess the stability of the fitted parameters via cross-validation techniques and examine the model’s out-of-sample efficacy. The approach is generalized to encompass seasonal commodities, such as natural gas and electricity. We illustrate the application of the calibrated model of instantaneous variance for the evaluation of commodity derivatives, including swaptions, as well as in the evaluation of power purchase agreements (PPAs). We demonstrate a compelling application of the Samuelson effect to a widely utilized auto-callable equity derivative known as the snowball. Full article

This study aims to explore the factors and mechanisms influencing the low-carbon development of Green Port Collection and Distribution Systems (GPCDSs) and to identify effective pathways and policy approaches to promote such development. Given the limited prior research integrating low-carbon policies, energy structure, and transportation systems, this study combines these three dimensions into a unified analytical framework. A scenario-based system dynamics model of GPCDS low-carbon development is established, incorporating factors such as low-carbon policies, energy structure, and transportation structure. The control variable method is employed to examine system behavior under 13 scenarios. The results indicate that freight subsidy policies and the internalization of carbon emission costs make the most substantial contributions to low-carbon development in GPCDS, yielding CO₂ emission reductions of 14.3% and 15.7%, respectively. Additionally, improvements in port railway infrastructure contribute to a 6.4% reduction in CO₂ emissions. In contrast, carbon taxes and energy structure adjustments have relatively limited effects, likely due to the delayed responsiveness of fossil fuel-dependent transportation sectors to pricing signals and the inherent inertia in transitioning energy systems. Full article

This study examines Poland’s agricultural land market between 2009 and 2023 through fixed effects and spatial econometric models, highlighting economic and spatial determinants of land prices. Key results show that GDP per capita strongly increases land values (β = +0.699, p < 0.001), while agricultural gross value added (–2.698, p = 0.009), soil quality (–6.241, p < 0.001), and land turnover (–0.395, p < 0.001) are associated with lower prices. Spatial dependence is confirmed (λ = 0.74), revealing strong regional spillovers. The volume of state-owned WRSP land sales declined from 37.4 thousand hectares in 2015 to 3.1 thousand hectares in 2023, while non-market transfers, such as donations, exceeded 49,000 annually. Although these trends support farmland protection and family farms, they also reduce market mobility and hinder generational renewal. The findings call for more flexible, sustainability-oriented land governance that combines ecological performance, regional equity, and improved access for young farmers. Full article

The fast expansion of cloud computing has raised carbon emissions and energy usage in cloud data centers, so creative solutions for sustainable resource management are more necessary. This work presents a new algorithm—Carbon-Aware, Energy-Efficient, and SLA-Compliant Virtual Machine Placement using Deep Q-Networks (DQNs) and Agglomerative Clustering (CARBON-DQN)—that intelligibly balances environmental sustainability, service level agreement (SLA), and energy efficiency. The method combines a deep reinforcement learning model that learns optimum placement methods over time, carbon-aware data center profiling, and the hierarchical clustering of virtual machines (VMs) depending on resource constraints. Extensive simulations show that CARBON-DQN beats conventional and state-of-the-art algorithms like GRVMP, NSGA-II, RLVMP, GMPR, and MORLVMP very dramatically. Among many virtual machine configurations—including micro, small, high-CPU, and extra-large instances—it delivers the lowest carbon emissions, lowered SLA violations, and lowest energy usage. Driven by real-time input, the adaptive decision-making capacity of the algorithm allows it to dynamically react to changing data center circumstances and workloads. These findings highlight how well CARBON-DQN is a sustainable and intelligent virtual machine deployment system for cloud systems. To improve scalability, environmental effect, and practical applicability even further, future work will investigate the integration of renewable energy forecasts, dynamic pricing models, and deployment across multi-cloud and edge computing environments. Full article

Electric vehicles (EVs) have been the most dependable and feasible choice for decarbonizing road transport over the last decade. To ensure the advancement of EVs and establish them as a sustainable alternative to internal combustion engine (ICE) vehicles, the EV sector and technological growth have largely relied on government subsidies. A significant challenge for EVs is their faster depreciation compared to ICE vehicles, primarily owing to swift technological advancements that propel the market while simultaneously rendering older EV models outdated too soon. Another factor that leads to the quicker depreciation of EVs is subsidies. The anticipated cessation of subsidies is expected to provide the required leverage to mitigate the rapid value decline in EVs, given the larger price disparity between new and used EVs. Batteries, which enable EVs to be a viable option, significantly contribute to the depreciation of EVs. In addition to the potential decline in EV battery performance, advancements in technology and reduced prices provide newer models with improved range at a more affordable cost. The used EV market accurately represents the rapid devaluation of EVs; consequently, the two topics are tightly related. Though it might not be immediately apparent, it seems evident that the pace of depreciation of EVs significantly contributes to the small size of the second-hand EV market. Depreciation is a key factor influencing the used EV market. This manuscript outlines the key aspects of depreciation and sustainability in the EV transition, especially those linked to rapid technological advancements, such as batteries, in addition to subsidies and the used EV market. The objective of this manuscript is to expose and analyze the relation between the drivers of the second-hand EV market, such as the cost of ownership, technology, and subsidies, and, on the other hand, present the interplay perspectives and challenges. Full article

Indonesia’s dependence on fossil fuel exports, particularly coal and crude oil, presents a dual challenge: sustaining economic growth while addressing rising CO₂ emissions. Despite significant attention to domestic energy consumption, the environmental implications of export activities remain underexplored. This study examines the dynamic relationship between energy exports, crude oil prices, and CO₂ emissions in Indonesia using a Vector Autoregressive (VAR) model with annual data from 2002 to 2022. The analysis incorporates Impulse Response Functions (IRFs) and Forecast Error Variance Decomposition (FEVD) to trace short- and long-term interactions among variables. Findings reveal that coal exports are strongly persistent and positively linked to past emission levels, while oil exports respond negatively to both coal and emission shocks—suggesting internal trade-offs. CO₂ emissions are primarily self-driven yet increasingly influenced by oil export fluctuations over time. Crude oil prices, in contrast, have limited impact on domestic emissions. This study contributes a novel export-based perspective to Indonesia’s emission profile and demonstrates the value of dynamic modeling in policy analysis. Results underscore the importance of integrated strategies that balance trade objectives with climate commitments, offering evidence-based insights for refining Indonesia’s nationally determined contributions (NDCs) and sustainable energy policies. Full article

Conventional ammonia production uses fossil-based hydrogen, resulting in high greenhouse gas emissions. Given the growing demand for sustainable solutions, it is essential to replace fossil hydrogen with renewable alternatives. This study assessed the technical, economic, and environmental viability of renewable ammonia production in Minas Gerais. To this end, an optimization model based on mixed integer linear programming (MILP) was developed and implemented in LINGO 20^® software. The model incorporated investment costs; raw materials; transportation; emissions; and indicators such as NPV, payback, and minimum sale price. Hydrogen production routes integrated into the Haber–Bosch process were analyzed: biomass gasification (GS_WGS), anaerobic digestion of vinasse (Vinasse_BD_SMR), ethanol reforming (Ethanol_ESR), and electrolysis (PEM_electrolysis). Vinasse_BD_SMR showed the lowest costs and the greatest economic viability, with a payback of just 2 years, due to the use of vinasse waste as a raw material. In contrast, the electrolysis-based route had the longest payback time (8 years), mainly due to the high cost of the electrolyzers. The substitution of conventional hydrogen made it possible to avoid 580,000 t CO₂ eq/year for a plant capacity of 200,000 t NH₃/year, which represents 13% of the Brazilian emissions from the nitrogenated fertilizer sector. It can be concluded that the viability of renewable ammonia depends on the choice of hydrogen source and logistical optimization and is essential for reducing emissions at large scale. Full article

This paper investigates the optimal planning of high-speed rail (HSR) freight operations, pricing strategies, and government carbon tax policies. The primary objective is to enhance the market share of HSR freight, thereby reducing carbon dioxide (CO₂) emissions associated with freight activities. The modal shift problem is formulated as a bi-level multi-objective model and solved using a specifically designed hybrid algorithm. The upper-level model integrates multiple objectives of the government (minimizing tax while maximizing the emission reduction rate) and HSR operators (maximizing profits). The lower-level model represents shippers’ transportation mode choices through network equilibrium modeling, aiming to minimize their costs. Numerical analysis is conducted using a transportation network that includes seven major central cities in China. The results indicate that optimizing HSR freight services with carbon tax policies can achieve a 56.97% reduction in CO₂ emissions compared to air freight only. The effectiveness of the government’s carbon tax policy in reducing CO₂ emissions depends on shippers’ emphasis on carbon reduction and the intensity of the carbon tax. Full article

Rising population, combined with declining home food production, in Arab nations has resulted in increased food imports that intensifies their dependence on international markets for vital food supplies. These nations face challenges in achieving food security because crude oil price volatility creates difficulties in managing the expenses of imported food products. This research calculates the income and price elasticities of imported food demand to understand consumer behavior changes in response to income and price variations, which helps to explain their impact on regional food security. To our knowledge, this research presents the first analysis of imported food consumption patterns across Arab countries according to their income brackets. This study employs the static Almost Ideal Demand System model to examine food import data spanning from 1961 to 2020. The majority of imported food categories demonstrate inelastic price and income demand, which means that their essential food consumption remains stable despite cost fluctuations. The need for imports makes Arab nations vulnerable to external price changes, which endangers their food security. This research demonstrates why governments must implement policies through subsidies and taxation to reduce price volatility risks while ensuring food stability, which will lead to sustained food security for these nations. Full article

Addressing the stock market forecasting as a classification problem, where the model predicts the direction of stock price movement, is crucial for both traders and investors, as it can help them to allocate limited resources to the most promising investment opportunities. In this study, we propose a hybrid system that uses a Long Short-Term Memory (LSTM) network and sentiment analysis for predicting the direction of the movement of the stock price. The proposed hybrid system is fed with historical stock data and regulatory news announcements for producing more reliable responses. LSTM networks are well suited to handling time series data with long-term dependencies, while the sentiment analyser provides insights into how news impacts stock price movements by classifying business news into classes. By integrating both the LSTM network and the sentiment classifier, the proposed hybrid system delivers more accurate forecasts. Our experiments demonstrate that the proposed hybrid system outperforms other competing configurations. Full article