Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

This study examines the economic feasibility of the environment-friendly farmland use policy to improve water quality. Conventional highland farming, polluting the Han River basin in South Korea, can be converted into environment-friendly farming through land acquisition or application of pesticide-free or organic farming practices. We estimate the welfare measures of improvement in water quality and the costs of policy implementation for economic analysis. To estimate the economic benefit of improvement in water quality experienced by the residents residing in mid-and-downstream areas of the Han River, the choice experiment was employed with a pivot-style experimental design approach. In the empirical analysis, we converted the household perception for water quality grades into scientific water quality measures using Water Quality Standard to estimate the value of changes in water quality. To analyze the costs required to convert conventional highland farmlands into environment-friendly farmlands, we estimated the relevant cost of land acquisition and the subsidy necessary for farm income loss for organic agricultural practice. We find that the agri-environmental policy is economically viable, which suggests that converting conventional highland farming into environment-friendly farming would make the improvement in water quality visible.

The present study is designed to analyse how the Public-Private Partnership (PPP) model is helping to create sustainable livelihood opportunities for women. It draws an inference from ‘Marudhara Rangsaaz’, a producer company operating in the textile sector in Rajasthan, India. It explains how this woman-based organisation operates in a PPP model to create economic value for women. It also tries to understand the specific role of the Rajasthan Grameen Aajeevika Vikas Parishad (RAJEEVIKA), The Rajasthan Government partner and ‘Rang Sutra’, the private partner, and the women members of ‘Marudhara Rangsaaz’ in the PPP model. The paper adopted a case study research design. The data was collected using in-depth interviews with all stakeholders and analysis of the documents. The findings indicate that in the said PPP model, Government took the role of mobilizer, financer, mentor, and private player, took the responsibility of building up capacity and arranging market links, and the women members worked together to help themselves sustain the project.

This study focuses on the effectiveness of systematic approaches to achieve business success, through integrated digital marketing strategies with the use of mobile applications. Focused on contemporary digital markets, the research highlights the transformative potential of these strategies about improving the quality of services and products, while promoting business sustainability. The objective of this research is to develop and evaluate a mobile application, designed to optimize customer orders within communities on the move. Through a mixed approach that includes semi-structured interviews with community members and digital marketing experts, along with quantitative surveys, assessed user perceptions and effectiveness of the app. The results indicate great acceptance and effectiveness of this digital tool, facilitating direct interactions, and improving accessibility to the service despite physical and digital limitations, reducing digital gaps and promoting economic empowerment among marginalized communities.

Purpose: Today’s challenges underscore the importance of energy across all segments of life. This scientific paper investigates the multifaceted relationship between energy efficiency, energy import reliance, population heating access, renewable energy integration, electricity production capacities, internet utilization, structural EU funds, and education/training within the framework of economic development. Methodology: Using data from selected European countries and employing self-organizing neural networks (SOM) and linear regression, this research explores how these interconnected factors influence the journey toward a sustainable and prosperous economic future. Results: The analysis revealed a strong connection between energy efficiency and numerous socioeconomic factors of modern times, with most of these connections being non-linear in nature. Conclusion: As countries work toward sustainable development goals, prioritizing energy efficiency can contribute to improved quality of life, economic growth, and environmental sustainability.

This study investigates the impact of digital payment infrastructure accessibility on the social influence of microenterprises in Barranquilla, Colombia, while examining the mediating roles of financial inclusion, digital literacy, social support networks, and collaboration with social innovation initiatives. Employing a mixed-methods approach, the study analyzes data from a sample of 25 microenterprises operating in various sectors. The findings, based on statistical techniques such as multiple regression, path analysis, and structural equation modeling (SEM), provide strong evidence for the positive influence of digital payment infrastructure accessibility on the social relationship of microenterprises. The results also highlight the crucial roles played by financial inclusion and social support networks in mediating this relationship. The study contributes to the growing body of literature on the factors driving the social effect of microenterprises and offers valuable insights for policymakers and practitioners aiming to foster inclusive economic development in the region. The findings suggest that investing in the development and expansion of digital payment systems, alongside efforts to promote financial inclusion and strengthen social support networks, can have far-reaching benefits for microenterprises and their communities.