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Title: An Analytical Study of the Legal Position and Role of Securities & Exchange Board of India (SEBI)

Abstract: This paper highlights a long journey towards regulatory enhancement within the SEBI ecosystem through the lens of data analysis. The objective is to clear amalgamate existing SEBI systems with those deemed desirable according to the fundamental principles of regulation. It also provides the whole outcome of the research study based on the analysis. It also suggest various policy implications to the researcher and government for an efficient and transparent regulatory environment in the country. In conclusion, it provides a thorough analysis of the enforcement procedures employed by the Securities and Exchange Board of India (SEBI), elucidating their effectiveness, equity, and efficiency. Through rigorous data analysis and empirical inquiry, we have dissected the regulatory landscape, uncovering insights that transcend mere statistics. Our findings add to the current conversation about how well regulations work, how accountable institutions are, and how safe investors are in India's financial markets. They also aim to make SEBI's regulatory system more open, accountable, and trustworthy.

By M.P. Verma, Deepa Singh Yadav
In Volume: 14,Issue: 2
Title: The Inflation-Unemployment Trade-Off in Bangladesh: Empirical Insights for Accelerating Progress towards Zero Poverty (SDG 1)

Abstract: This study empirically investigates the inflation-unemployment trade-off in Bangladesh and assesses its implications for achieving Sustainable Development Goal 1 (SDG 1) of zero poverty. High inflation erodes the real income of the poor, while unemployment directly limits earning capabilities, making the interplay between these variables a central determinant of poverty reduction. Using annual time-series data from 1990 to 2024, we employ an Autoregressive Distributed Lag (ARDL) model to test for the existence and stability of a long-run relationship. Our findings confirm a significant short-run trade-off but reveal that this relationship is unstable and weakens in the long run, suggesting that other structural factors dominate. The results indicate that unanticipated inflationary shocks disproportionately harm the poor, and persistent unemployment remains a formidable barrier to inclusive growth. The study concludes that a singular focus on either price stability or employment generation is insufficient for attaining SDG 1. Instead, Bangladesh requires an integrated policy framework that combines prudent monetary policy to control the inflation rate with targeted fiscal measures, investments in human capital, and productive sector diversification to generate new employment opportunities. This holistic approach is essential to effectively manage the trade-off and accelerate progress towards eliminating poverty.

By Shuvongkor Kumar Datta, S.K.S. Yadav, Jubair Ansary, Ariful Islam
In Volume: 14,Issue: 2
Title: Impact of Generative AI (ChatGPT, Gemini, Copilot) on Learning Efficiency in the Indian Education System

Abstract: Generative Artificial Intelligence (GenAI) has emerged as one of the most influential technological developments shaping modern learning environments. Tools such as ChatGPT, Google Gemini, and Microsoft Copilot are increasingly being used by Indian students and teachers for explanation, summarization, content generation, and academic support. This study examines how these tools influence learning efficiency in the Indian education system. Using a mixed-method design consisting of a structured student–teacher survey and focused interviews, the study explores changes in understanding, productivity, doubt-clearing, academic confidence, and skill development. Findings reveal that GenAI significantly enhances conceptual clarity, reduces learning time, and supports self-paced learning. However, concerns remain regarding over-dependence, misinformation, ethical use, and unequal access. The paper concludes with recommendations for responsible AI integration in Indian classrooms.

By Shantam Babbar, Rajesh Kumar Raju, Monika Kumari
In Volume: 14,Issue: 2
Title: Components of the Money Supply Process in Bangladesh: An Analysis

Abstract: This study provides a comprehensive assessment of the components and effectiveness of the money supply process in Bangladesh, with a particular focus on its underlying determinants, trends, and policy implications. The primary objective is to evaluate whether the existing money supply mechanism, as implemented by the Bangladesh Bank, is effective in meeting the country’s macroeconomic objectives of price stability, economic growth, and financial stability. The research adopts a mixed-method approach, integrating both descriptive and econometric analyses. Descriptive statistics and trend analysis are used to examine the historical patterns of monetary aggregates namely the monetary base (H), money multiplier (m), narrow money (M1), and broad money (M2) over the past two decades. The results reveal that the money supply process in Bangladesh exhibits both short-run volatility and long-run stability, with the monetary base and money multiplier jointly influencing the expansion of M2. Co-integration tests confirm the existence of long-term equilibrium relationships among monetary aggregates, while ECM results suggest a moderate speed of adjustment toward equilibrium following shocks. However, structural break analysis indicates that global financial crises, domestic policy shifts, and recent pandemic-related disruptions have caused significant short-term deviations. The findings highlight that although the Bangladesh Bank’s monetary policy framework has been largely effective in steering the long-run trajectory of the money supply, challenges remain in managing short-run fluctuations and in aligning monetary expansion with real economic growth. The study concludes with policy recommendations aimed at enhancing the effectiveness of the money supply process, including improving forecasting models, strengthening monetary transmission mechanisms, and enhancing coordination between monetary and fiscal policy.

By Sabiha Akter
In Volume: 14,Issue: 2
Title: Digital Trade and E-commerce Reshaping Global Trade Architecture in the 21st Century

Abstract: The rapid proliferation of digital technologies has fundamentally transformed the global trade landscape, with e-commerce and digital trade emerging as dominant forces reshaping traditional trade architectures. This paper examines the multifaceted impact of digital trade and e-commerce on global trade structures, analyzing key trends, challenges, and policy implications. Through comprehensive analysis of empirical data and theoretical frameworks, we demonstrate how digital platforms have reduced transaction costs, democratized access to international markets, and created new regulatory challenges. Our findings indicate that digital trade now accounts for a significant portion of global GDP, with cross-border e-commerce growing at unprecedented rates. However, this transformation has also highlighted critical issues including digital divides, data governance concerns, and the need for updated international trade frameworks. This research contributes to understanding how digital trade is reconfiguring global value chains and what policy interventions are necessary to ensure inclusive and sustainable growth in the digital economy.

By Pankaj Yadav
In Volume: 14,Issue: 2
Title: Impact of Generative AI (ChatGPT, Gemini, Copilot) on Learning Efficiency in the Indian Education System

Abstract: Generative Artificial Intelligence (GenAI) has emerged as one of the most influential technological developments shaping modern learning environments. Tools such as ChatGPT, Google Gemini, and Microsoft Copilot are increasingly being used by Indian students and teachers for explanation, summarization, content generation, and academic support. This study examines how these tools influence learning efficiency in the Indian education system. Using a mixed-method design consisting of a structured student–teacher survey and focused interviews, the study explores changes in understanding, productivity, doubt-clearing, academic confidence, and skill development. Findings reveal that GenAI significantly enhances conceptual clarity, reduces learning time, and supports self-paced learning. However, concerns remain regarding over-dependence, misinformation, ethical use, and unequal access. The paper concludes with recommendations for responsible AI integration in Indian classrooms.

By Shantam Babbar, Rajesh Kumar Raju, Monika Kumari
In Volume: 14,Issue: 2

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