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Motivated by the negative effect of external shocks on the domestic economy, this study explores the role of financial sector development in absorbing the effect of external shocks on macroeconomic volatility in Nigeria.

Autoregressive distributed lag and fully modify ordinary least square are used to examine the moderating effect of financial development in the link between external shocks and macroeconomic volatilities in Nigeria between 1986Q1 and 2019Q4. External shock is proxy using oil price shock, and financial development is proxy by domestic credit to the private sector and market capitalisation. At the same time, macroeconomic volatility is proxy by output and inflation volatilities. Macroeconomic volatilities are generated using generalised autoregressive conditional heteroskedasticity (GARCH 1,1).

The results indicate that domestic credit to the private sector significantly reduces output and inflation volatilities in Nigeria in the short and long run. However, market capitalisation promotes macroeconomic volatility. More specifically, financial development indicators play different roles in curtaining macroeconomic volatilities. The results also reveal that external shocks stimulate macroeconomic volatility in Nigeria in the short and long run. Nevertheless, the effects of external shocks on macroeconomic volatilities are reduced when the role of financial development is incorporated.

This study, therefore, concludes that strong financial sector development serves as a significant shock absorber in reducing the adverse effect of external shock on the domestic economy.

This study contributes to the extant studies by introducing a country-specific analysis into the empirical examination of how financial development can moderate the influence of external shock on macroeconomic volatilities.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Environmental protection and conservation of resources is a challenge for policymakers to attain sustainable growth and development. The current study uses the variable of inclusive growth instead of the traditional measure of growth.

The link between inclusive growth, renewable energy, industrial production, trade openness and the environment is explored by using panel data from 1995 to 2019 in Brazil, Russia, India, China and South Africa (BRICS) countries. Before applying formal techniques, unit root tests were applied to check the stationarity of each variable. The long-run relationship among factors was found by the Kao cointegration test. The panel dynamic ordinary least squares (DLOS) was employed for regression estimation.

The results verified a decrease in ecological footprint (EF) in response to a potential rise in renewable energy consumption. An upsurge in EFs was explored due to a rise in gross domestic product (GDP) per person employed and trade openness. The EF significantly decreased by 0.671% in response to a 1% rise in renewable energy consumption.

It is highly suggested to enhance renewable energy usage. To achieve this, policymakers should implement and emphasize efficient energy technologies to ensure improving the environment. Efficient use of renewable energy resources will decrease global warming effects and ensure the sustainable use of scarce resources.

It first took into account the variable of inclusive growth instead of traditional growth measures. It explored the impact of GDP per person employed as an indicator of inclusive growth.

Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.

Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.

The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.

Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.

The current analysis aims to explore the role of cash holdings in the nexus of national governance and capital investment (CIN).

To achieve this aim, the authors sample the nonfinancial enterprises from 5 Brazil, Russia, India, China, South Africa (BRICS) economies and employ system generalized method of moments(GMM) models as an estimation technique.

The empirical analysis infers that national governance has a positive relationship with CIN and a negative relationship with cash holdings. The cash holdings negatively determine CIN. However, the cash holdings show a positive relationship with CIN in the presence of the national governance index (NGI).

The important policy layout of the current analysis is that corporate managers should reduce cash holdings during better governance situations. Alternatively, corporate managers can disentangle the negative impact of bad country governance conditions on CIN by holding more cash.

The study is innovative as it explores mediating impact of cash holdings in the NGI-CIN nexus.

The purpose of this study is to check the impact of financial development on green technological innovation (GTI).

The sample size includes the 20-year (2001–2020) financial statistics of six Gulf Cooperation Council (GCC) region countries. To check the proposed relationship, this research uses a series of econometric models including fixed effect, fully modified ordinary least square and robust least square models.

The statistical results imply that financial sector development has a direct significant impact on GTI. A developed financial sector can uplift green technological development by offering more loans to industrial sectors and the import of modern technology. The statistical analysis further reveals the positive impact of gross domestic product (GDP), foreign direct investment inflow and trade volume while the negative impact of resources contribution on GTI.

The findings suggest key policy suggestions regarding the role of the financial sector in promoting GTI in the GCC region.

The novelty of this study lies in its examination of the relationship between FD and GTI in the GCC countries, a region with its unique economic and environmental dynamics.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

This study investigates (1) whether democratization drives sovereign credit ratings (SCR) changes (the “democratic advantage”) or whether SCR changes affect democratization, (2) whether the degree of democratization in sub-Saharan African (SSA) countries affects the associations and (3) whether the associations are significantly affected by resource dependence.

This study investigates the effects of SCR changes on democracy in 22 SSA countries over the period of 2000–2020 VEC Granger causality/block exogeneity Wald tests, and impulse responses and variance decomposition analyses with Cholesky ordering and Monte Carlo standard errors in a panel VECM framework.

The full sample impulse responses find that a SCR shock has a long-run detrimental effect on the democracy and political rights but only a short-run positive impact on civil liberties. Among the sub-samples, it is found that the extent of natural resource dependence does not affect the magnitude of SCR shocks on democratization mentioned above but it is found that a SCR shock affects long-run democracy in SSA countries that are relatively more democratic but is more likely to drive democratic deepening in less democratic SSA countries. The full sample variance decompositions further finds that the variance of SCR to a political rights shock outweighs the effects of all the macroeconomic factors, whereas in more diversified SSA countries, the variances of SCR are much greater for democracy and political rights shocks, which suggests that democratization and political rights in diversified SSA economies are severely affected by SCR changes. In the case of the high and low democracy sub-samples, it is found that the variance of SCR in the relatively higher democracy sub-sample is greater than in the low democracy sub-sample.

These results have three implications for democratization in SSA. First, the effect of a SCR change is not a democratically agnostic and impacts political rights to a greater extent than civil liberties. Second, SCR changes have the potential to spark a negative cycle in SSA countries whereby a downgrade leads to a deterioration in socio-political stability coupled with increased financial economic constraints that in turn drive further downgrades and macroeconomic hardship. Finally, SCR changes are potentially detrimental for democracy in more democratic SSA countries but democratically supportive in less democratic SSA countries. Thus, SSA countries that are relatively politically sophisticated are more exposed to the effects of SCR changes, whereas less politically sophisticated SSA countries can proactively shape their SCRs by undertaking political reforms.

This study is the first to examine the associations between SCR and democracy in SSA. This is critical literature for the Africa’s scholarly work given that the debate on unfair rating actions and claims of subjective rating methods is ongoing.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

The purpose of this study is to empirically investigate the asymmetric effects of financial risk on Sukuk market development for a sample of Malaysian countries over the period of 2010–2021.

This study refers to the International Country Risk Guide (ICRG) in determining the financial risk factors to be studied in addition to the Malaysia financial stress index (FSI) to capture changes in financial risk level. The authors use the nonlinear autoregressive distributed lag (NARDL) model to tackle the nonlinear relationships between identified financial risk variables and Sukuk market development.

The results suggest the existence of a long-run relationship between foreign debt service stability, international liquidity stability (ILS), exchange rate stability (ERS) and financial stress level with the Sukuk market development in Malaysia. Indeed, higher ILS and ERS will boost Sukuk market size, whereas higher foreign debt services and financial stress are negatively related to Sukuk market development. Findings also indicate that the long-run positive and negative impacts of identified financial risk components on Sukuk market development are statistically different. Taking into account the role of the Sukuk market in facilitating Malaysia’s economic growth, the country should aim to keep the foreign debt-to-GDP ratio at a sustainable level.

This study points to three possible directions for future research. The first is the differential impact of financial risk components on Sukuk issuance for different Sukuk structures. As more data becomes available in the future, this area could be further explored by conducting the above analysis for different combinations of Sukuk structures and currency denominations. In addition, future researchers could also consider exploring the variability of financial risk impacts through comparative studies of the leading Sukuk-issuing countries to account for differences in regulatory frameworks and supporting infrastructure.

This study provides valuable practical and policy implications for strengthening the growth of the Sukuk market. While benefiting from the diversification benefits of funding sources to finance private or government projects and developments, Malaysia should remain vigilant to global economic conditions, foreign exchange markets and financial stress levels, as all of these factors may significantly influence investor sentiment and the rate of return offered by Sukuk issuance.

The use of the NARDL approach, which investigates the long-run effects of financial risk factors on Sukuk market development in Malaysia, makes this study a valuable addition to the literature, as there has been little research into the asymmetric effects of those variables on Sukuk market development using samples from emerging Asian markets.