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This research investigates the intricate relationship between Human Resource Management (HRM) and Economics, emphasizing their combined impact on organizational productivity and macroeconomic growth. By addressing critical research objectives and hypotheses, the study integrates theoretical perspectives, empirical evidence, and econometric analyses to explore wage dynamics, human capital development, and workforce management. The findings provide actionable insights for businesses and policymakers to align HRM practices with economic objectives, fostering sustainable growth.

Keywords: Human Resource Management, Economics, Labor Market Dynamics, Organizational Productivity, Human Capital, Wage Elasticity, Economic Policy Integration

Mergers in the Indian banking sector, especially among public sector banks, represent a strategic initiative to form larger, stronger institutions that can better withstand economic fluctuations. These mergers aim to tackle persistent challenges, such as elevated levels of NPAs, which can significantly affect profitability and liquidity. Therefore, it is crucial to thoroughly assess how these mergers impact asset quality to evaluate their effectiveness and long-term viability. This study used a descriptive research design to analyze the Net NPA ratios of five selected banks—PNB, CB, UBI, IB, and BOB—before and after their mergers, aiming to highlight changes in asset quality. A quantitative approach was adopted, utilizing secondary data from financial reports on the banks’ official websites, and the analysis involved trend analysis using MS Excel and paired t-tests along with descriptive statistics via SPSS version 25. The analysis reveals varying impacts of mergers on the Net NPA ratios of selected banks. While PNB and BOB showed no significant improvements post-merger, CB and UBI experienced substantial reductions, and IB faced an increase, highlighting the diverse outcomes of merger strategies across these institutions. This study implies that merger effectiveness in enhancing asset quality can vary significantly, necessitating tailored strategies.

Keywords: Asset Quality, Non-performing assists, Mergers, Banks, Performance

The Micro, Small, and Medium Enterprises (MSME) sector plays a vital role in India’s economic growth, contributing significantly to GDP, employment, industrial output, and exports. This study explores the relationship between MSME exports and total national exports in India from 2000-01 to 2019-20, analyzing their influence on export fluctuations. Using secondary data from government sources, the research applies regression analysis and the Autoregressive Integrated Moving Average (ARIMA) model to examine the trends and variations in MSME exports.The results demonstrate a strong positive correlation, with MSME exports accounting for approximately 91.53% of the variation in total exports. The regression analysis shows that an increase in MSME exports leads to a substantial rise in total exports, emphasizing the sector’s crucial role in India’s trade framework. The ARIMA model-based volatility analysis reveals that while MSME exports contribute to export fluctuations, external factors also play a significant role. Dickey-Fuller test confirms that both MSME exports and total exports are non-stationary, requiring differencing for proper time series analysis. However, ARIMA regression results suggest that past values and forecast errors have a limited impact on current total exports. These insights highlight the importance of targeted policy interventions to enhance MSME competitiveness, address financial and technological constraints and mitigate external volatility effects. Despite their considerable contribution, MSMEs continue face challenges like restricted access to credit, technological challenges and stiff global competition. Addressing these issues is necessary for the development of MSMEs growth. This study provides valuable recommendations for policymakers to boost MSME exports and enhance economic stability.

Keyword: MSMEs exports, total exports, Regression analysis, ARIMA model, volatility, economic growth.

For estimating finite population mean, an efficient difference and regression type estimator using prior information in the form of population mean and coefficient of variation of auxiliary variable is proposed, its bias and mean square error are found, estimator based on estimated optimum values is obtained and its comparative study with the usual linear regression estimator is made. A simulated empirical study has also been conducted to support the theoretical findings.

Keywords: Difference and Regression type estimator, Auxiliary information, Bias, Mean Square Error (M.S.E).