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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 Global Economic Uncertainty on the Financial Performance of the National Stock Exchange (NSE): A Study from 2021–2025

Abstract: The National Stock Exchange (NSE) of India plays a crucial role in trading stocks, derivatives, and debt instruments. Between 2021 and 2025, global economic uncertainty, driven by pandemic effects, fluctuating interest rates, geopolitical conflicts, and shifts in capital movements, significantly impacted financial markets, including the NSE. This research investigates how challenges like post-pandemic recovery, changes in foreign investment, and tightening monetary policies affected the NSE’s income and trading activity. By analysing secondary data from financial statements and economic reports, the study evaluates trends in revenue, net profits, and trading volumes. Increased global uncertainty led to market volatility and corrections in equity indices. Despite these challenges, the NSE's robust domestic investor base and diversified revenue helped mitigate adverse effects. The findings highlight the importance of adaptive risk management and regulatory consistency in maintaining financial performance during global instability.

By Arvind Kumar Yadav, Shamshad Khan
In Volume: 14,Issue: 2
Title: Comparative Analysis of Risk Management Strategies for Non-Performing Assets: A Case Study of SBI and ICICI Bank in India

Abstract: This study examines the differential approach to risk management strategies concerning Non-Performing Assets (NPA) within India's two foremost banks – the Indian Public Sector Bank, State Bank of India (SBI) and the Indian Private Sector Bank, ICICI Bank. While comparing the two banks, using a mixed-method approach, the research combines quantitative analysis of trends in financial indicators (Gross and Net NPA ratios, Provision Coverage Ratio and Return on Assets) and a qualitative analysis of credit appraisal and monitoring and recovery frameworks. Data from 2010-2025 were taken from RBI publications, annual reports and credible academic studies, so there was authenticity and reliability of data. Findings show that SBI's recovery centered reforms such as better provisioning (PCR increase from 70.88% to 75%), restructuring under Insolvency and Bankruptcy Code (IBC) and improved post-sanction monitoring have led to a reduction in Gross NPAs by 47% and significant improvement in profitability (ROA increased from 0.48% to 1.1%). On the other hand , ICICI Bank's proactive and technology-driven risk model, with AI-driven early warning systems, digitised credit scoring and stringent underwriting, regularly maintained low NPAs (down from 3.05% to 1.67%) and enhanced profitability (ROA doubling to 2.0%). Correlation study reports we see that there is a very strong inverse relationship between NPAs, provisioning, Net NPA ratio and profitability (r approx –0.9) which means as NPAs and provisioning go up Net NPA ratio and profitability goes down. This is proof that what we put in place for credit assessment, early identification and recovery does in fact directly improve banks’ performance. We found out that what made SBI successful was its recovery and restructurizing which made ICICI’s success was in prevention and technology based monitoring. Also brought to light is the fact that what is key in the Indian banking system is the integration between AI, data analysis and good governance which banks use in risk management and in the end in the maintenance of asset quality in a sustainable way.

By Achintya Kumar Gupta, Narendra Pal Singh
In Volume: 14,Issue: 2
Title: Minimizing the Impact of U.S. Tariffs on India’s Economic Growth: Strategic Responses and Policy Recommendations

Abstract: Due to imports of goods and particularly textiles, gems, seafood, and electronics, the United States presents tariff levels that are very high to Indian exports and this presents a great challenge to Indian trade balance and GDP. This paper will examine the economic effects of these tariffs, examine the bilateral trade pattern between India and the U.S., and provide an internal policy action to alleviate the effect. It also analyses strategic potential of the India UK Free Trade Agreement (FTA) as hedge against U.S trade headwinds. By quantitatively supported thought and sectoral knowledge, the paper draws a plan on how India can be resilient in exports and its economy.

By Nakshatra Gupta
In Volume: 14,Issue: 2
Title: The Impact of Pawnbroking on Local Communities with special reference to Bangladesh

Abstract: This study examines pawnbroking's impact on social entrepreneurship and its implications for social development. It posits that Pawnbroking aids vulnerable entrepreneurs, often excluded from formal credit, in accessing quick financial resources, thereby enhancing social entrepreneurship. Through a meta-analysis and literature review, including three case studies from Bangladesh, the findings indicate that, despite exploitative practices, pawnshops are vital for providing the impoverished with financial access and supporting social welfare. However, risks such as asset loss, debt cycles, and exploitation of desperate borrowers are also highlighted. The study emphasizes the need for regulatory oversight and more accessible financial systems that protect borrowers while maintaining accessibility. Overall, pawnbroking offers both advantages and challenges for local communities in Bangladesh, necessitating a balance between quick cash access and consumer protections to promote healthier community dynamics.

By José G. Vargas-Hernández, Amina Khatun, Csongor Czipf, Absalón J. Salmerón-Zapata
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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