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This study attempts to examine the relationship between the banking sector and stock market development in India.

To analyze the relationship between banks and stock market development, the ratio of stock market capitalization to GDP is proxied by stock market development. The determinants of the stock market development are used for analysis namely domestic credit to the private sector as a ratio of GDP is used as a proxy for the development of banks, saving rate, per capita real GDP, and inflation. The autoregressive distributed lag (ARDL)-Bounds testing approach is used for the analysis. The paper also used the unrestricted error correction model and CUSUM and CUSUM square test to check the stability of the model.

The ARDL bounds test found that there is a long-run relationship between stock market development and bank-centered financial development. The results also revealed that the stock market is positively influenced by the development of banks, savings, and per capita real GDP in the short-run as well as long-run.

This paper suggests that improvement of banking sector plays an important role to increase liquidity of the capital market development in India. This paper also suggests that the economic growth and savings rate have positive impact to induce the capital market growth in both short run and long run.

The study has investigated the empirical relationship between the banking sector and the stock market development in a different methodological approach by using an ARDL model which is appropriate for a small sample size. There are few studies related to bank-centered financial development and stock market development in the context of India.

This study aims to investigate the causal relationship between external debt and inflation in Jordan over the period 1970 to 2020.

The external debt–inflation nexus is examined within a multivariate framework by including other determinants of inflation, including money supply and the nominal effective exchange rate. This study uses an ARDL bounds testing approach to cointegration to test the existence of a long-run relationship between the inflation rate and its drivers. An error correction model is estimated to reveal the short-run dynamics of the series. The direction of causality among the variables is examined using a modified version of the Granger non-causality test due to Toda and Yamamoto (1995). The analyses control for the presence of structural breaks in the underlying time series.

The empirical results show that external debt and money supply have a statistically significant positive effect on inflation in the long run. The authors also find that a nominal depreciation of the Jordanian Dinar raises inflation rates in the long run. The Toda–Yamamoto Granger non-causality test findings reveal a statistically significant bi-directional positive causality between inflation and external debt, between the nominal effective exchange rate and inflation and between money supply and inflation.

Proper management of the exchange rate policy, money supply and external debt levels is crucial to control inflation rates in Jordan.

To date, the authors are unaware of any empirical study that examines the impact of external debt on inflation in Jordan, and the current study aims to fill this gap in the literature.

This paper examines the extent to which exchange rate volatility (ERV) is crucial for small island economies. These economies by their very nature and size tend to be net importers and highly dependent on trade for their economic survival. The island of Mauritius is used as a case study.

A GARCH model has been utilized using yearly data for the period 1993–2022. The ARDL bounds cointegration approach has been used to determine the long run relationship between exchange rate volatility and the performance of exports. The ECM-ARDL model has been used to estimate the short-run relationships, that is the speed of adjustments between the variables under consideration.

The findings reveal that exchange rate volatility has a positive and significant effect on exports in the short run as well as in the long run. The study also finds out that export has a long-term relationship with world GDP per capita. Both the presence and degree of exchange rate volatility are important aspects for consideration in policy making.

The literature gap that this study attempts to close is one related to global impacts within the recent time horizon. Recently, numerous important events shaped the financial and economic landscape globally, including but not limited to the financial crisis of 2008 and the COVID-19 pandemic in 2019. Both these events stressed the global volume of trade and the exchange rate markets, and these events affects small islands comparatively more given their heavy dependence on international trade for economic development, albeit economic survival.

Over the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.

The authors utilize an autoregressive distributed lag bounds testing estimation technique.

The results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.

Governments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.

First, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

The purpose of this study is to empirically examine the impact of natural resource rents on income inequality in Ethiopia from 1981 to 2022 and investigate whether investments in manufacturing moderate this relationship.

Dynamic autoregressive distributed lag simulation and Kernel-based regularized least squares (KRLS) models are used to analyses short- and long-run relationships, as well as the potential moderating role of manufacturing.

The bounds test indicates natural resource rents have a long-run positive effect on inequality but a short-run negative impact. The KRLS model finds manufacturing conditions for this linkage in the short run. In the long run, economic growth decreases inequality following an inverted Kuznets pattern, while government expenditures reduce disparities when directed at priority social services.

The findings provide mixed support for theories while highlighting nuances not fully captured without local analyses. Strategic sectoral investments may help optimize outcomes from resource dependence.

The results imply Ethiopia should prudently govern resources, productively invest revenues and prioritize social spending to equitably manage industrialization and uphold stability.

Reducing disparities through inclusive development aligned with empirical evidence could help Ethiopia sustain peace amid transformation and realize its goals of shared prosperity.

This study applies innovative econometrics to provide novel insights into Ethiopia's experience, resolving inconsistencies in the literature on relationships between key determinants and inequality.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

The paper assesses the role of natural resource rents in Nigeria's economy through the channel of institutional quality.

The analysis is done with the use of autoregressive-distributed lag (ARDL) bounds testing approach to cointegration, vector error correction model (VECM), Granger causality test and cointegrating regression over the period 1996–2019.

Findings support the notion that overreliance on natural resources could exacerbate the growing number of dysfunctional economic outcomes in the country. The study confirms that a mix of weak governance quality and natural resource rents could have a negligible effect on economic growth and possible retardation impact on the economy in the long run as well as in the short run. The evidence further reveals that there is unidirectional causality running from the interaction term to growth, suggesting that growth trajectory could be jointly determined by natural resource rents and the quality of institutions.

The divergent arguments associated with the mechanisms of resource curse in each of the resource-rich countries offer ample support for the contention that economic outcomes in resource-abundant states may not be a product of resource windfalls per se, but rather the quality of governance or ownership structure. Hence, the ultimate aim of the analysis is to further understanding on the link between resource rents and growth in Nigeria via governance channel.

This paper aims to empirically examine the impact of economic development and energy consumption in Saudi Arabia (the leading OPEC giant and the Arab energy icon country) between 1971 and 2015, whilst incorporating globalization, financial development and capital accumulation.

This study uses econometric tools and the analytical framework based on the autoregressive distributed lag (ARDL) model.

The study found that, unlike economic development, globalization and financial development increased energy consumption. Also, capital accumulation created a boost in the country’s energy consumption. Results of variance decomposition indicate that the innovative shocks in globalization and financial development affected energy consumption at the rates of 15.28% and 28.98%, respectively, over 15 years’ period, while shocks in capital accumulation affected energy consumption at a rate of only about 1.24%. In addition, the results of impulse response function show that globalization and economic development were highly responsive to shocks in financial development, and capital accumulation greatly spurred financial development.

The findings of this study have implication for promoting an efficient and sustainable energy systems that enhance sustainable development based on the accrued benefits of globalization, financial development and capital accumulation.

Given the increasing level of globalization, financial development and energy consumption, our study uses econometric tools and the analytical framework based on the ARDL model to revisit how energy consumption is influenced by economic development in Saudi Arabia by incorporating other determinants of energy consumption such as globalization, financial development and capital accumulation. The results were validated based on the innovative accounting.

This study examines the effect of foreign direct investment (FDI) on employment and economic growth in Ghana and examines the role of technology in these relationships.

This study applied the autoregressive distributed lag (ARDL) bounds testing approach to cointegration and Granger causality tests to data from 1995 to 2017.

Based on the empirical analysis, the key findings are as follows: FDI does not affect economic growth or employment in Ghana. However, technology moderates the relationship between FDI and economic growth and FDI and employment in the short run. The study also finds that technology exerts a positive effect on economic growth in both short and long run, whereas trade has a significantly negative effect on economic growth in Ghana.

The greatest constraint that faced the authors is the nonavailability of data,.

The transfer of technology agreement enshrined in the GIPC Act should be made more robust and unambiguous, to make it a strict requirement for MNEs to be allowed to operate in Ghana. This increases Ghana's gains from FDI inflow.

The GIPC should tighten its monitoring regime so that MNEs do not exceed their expatriate employment quotas. This will ease the burden of unemployment among the youth in Ghana.

This study adds a new dimension to the literature on the impact of FDI on emerging economies by examining the role of technology in the association between FDI and growth, and FDI and employment.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.