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This study aims to investigate the effect of monetary policy transmission on the use-based classification of manufacturing industries in India, an integral aspect influencing the overall economic growth of the nation.

The empirical study applies a panel autoregressive distributed lag model to examine the relationship/association between monetary policy transmission mechanism and the output of manufacturing industries in the long run and short run.

In the long run, the findings reveal a negative association between money supply and manufacturing industries’ output, indicating that an increase in money supply corresponds to a decrease in manufacturing output. Conversely, a positive relationship is observed between manufacturing industries’ output and banks’ credit, indicating that an increase in bank credit leads to a corresponding increase in manufacturing output. In the short run, the results highlight a significant positive relationship between manufacturing output and monetary policy transmission variables, including money supply, statutory liquidity ratio, real exchange rate and foreign direct investment. The use-based classification of manufacturing industries such as primary goods, capital goods and intermediate goods exhibits greater responsiveness to monetary policy shocks than consumer durables and non-durables goods.

Policymakers are advised to regulate credit expansion to support the industry without risking financial instability, with key recommendations including stimulating consumer demand and adopting sector-specific policies to promote sustainable growth across diverse manufacturing sectors.

India, being a developing economy, efficient monetary policy transmission is crucial for boosting manufacturing output and employment. Nevertheless, there has been a scarcity of research concentrated on this pivotal intersection. This study aims to fill that gap, providing fresh insights into how monetary policy affects the growth of the manufacturing industry.

While traditionally it was believed that shadow banking undercuts business from traditional commercial banks, the time has now arrived to examine the various innovative practices used by various shadow banks and non-banking finance companies (NBFCs) to explore various collaboration and competition possibilities. The parallel existence of the traditional and shadow banking systems creates a market environment where both the entities are inter-dependent for growth and development with their edge of advantages and snags. This study aims to investigate the development and growth of deposits in NBFCs and scheduled commercial banks (SCBs) and, through the adoption of innovative practices, highlights possible growth opportunities for both ahead.

This study uses yearly bank deposit data from 1998 to 2019. This study incorporates univariate autoregressive integrated moving average modeling to predict the future deposit growth of SCBs and NBFCs in India.

This study concludes that both the entities, i.e. NBFCs and SCBs, will experience deposit growth; however, the proportionate growth of deposits in SCBs will be higher than NBFCs.

This study concludes that the NBFCs will exhibit higher growth in the future. Thus, a strengthened regulatory framework will boost the growth of the NBFCs, providing a safe environment to the investor. Further, as this study primarily considers only deposit-taking NBFCs and commercial banks and a single variable – “deposit” to predict its future growth, it offers a scope for future research to consider and include other kinds of NBFCs like non-deposit taking NBFCs, housing finance companies, micro-finance Institutions and infrastructure finance companies.

A competently regulated financial system of an emerging economy confers tremendous growth opportunities to the financial institutions functioning in the system. Deposits are a significant parameter for the performance of the financial institution; thus, by keeping it as the underlying premise, this study forecasts the future growth in deposits for both the commercial banks and NBFCs. This forecasted growth in deposits for both entities, if analyzed and acted upon appropriately, can, apart from other opportunities for investment, be used to point at directional growth of the economy and the gross domestic product, considering that credit growth is a barometer for economic growth. The scope of this study is limited to NBFCs and SCBs of India and considers only a single variable, i.e. deposit for data analysis and growth forecasting.

The purpose of this paper is to examine the connectedness among Memecoin, Halal exchange traded funds (ETF) and environmental, social and governance (ESG) indexes in different quantiles.

The authors consider Dogecoin to measure Memecoin while Wahed FTSE USA Shariah ETF (HLAL) and SP Funds S&P 500 Sharia Industry Exclusions ETF (SPUS) are used to represent Halaf ETF. Similarly, iShares ESG Aware MSCI USA ETF (ESGU) and Vanguard ESG US Stock (ESGV) proxy the ESG index ETF. The daily price of these examined markets is considered from January 2, 2020, to January 18, 2024. The quantile vector autoregression is deployed for the empirical computation.

The result reveals that Memecoin (Dogecoin) emerges as the best diversifier irrespective of various quantiles because it is least connected in terms of recipient and transmission of shock. In addition, the authors observe an intriguing observation that the total connectedness in higher quantile is large, followed by lower quantile.

This study is undertaken considering the novelty in the form of the proxies of examined markets along with natural outbreak (COVID-19) and man-made outbreak (Russia–Ukraine invasion) periods.