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The challenge of predicting changes in aggregate income and stock prices is one that has occupied the research agendas of economists. This paper aims to use the consumption–income ratio and the dividend–price ratio to predict future income and stock prices.

To examine the stability of the consumption–income ratio and the dividend–price ratio, the authors run a two-variable, two-lag reduced-form VAR in the vein of Cochrane (1994), using a lag of each respective ratio as exogenous to the VAR. Additionally, the authors estimate an AR(4) model for income and prices.

The consumption–income ratio and the dividend–price ratio remain key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. The dividend–price ratio does not significantly predict future price growth. Consumption and dividend shocks have lasting impacts on income and prices.

The consumption–income ratio and the dividend–price ratio are still key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. However, the dividend–price ratio does not significantly predict future price growth, a change from previous research from the 1990s, despite the increasing complexity of stock markets. Consumption and dividend shocks have lasting impacts on income and prices and appear to be significant drivers in both the short- and long-run variance in income and prices.

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.

Motivated by the 2030 UN Sustainable Development Goals (SDG-7: clean and affordable energy, SDG-8: sustainable economic growth, SDG-13: climate action), this study aims to investigate the role of economic complexity, disaggregated energy consumption in addition to economic growth, financial development, globalization and urbanization on the ecological footprint of United Arab Emirates (UAE).

This study adopts unit root tests (with and without a structural break), autoregressive distributed lag (ARDL) bounds test and dynamic ordinary least squares.

The results obtained from the ARDL model suggest that economic complexity (EC), nonrenewable energy and economic growth increase the ecological footprint in both the short and long run, thus deteriorating the environment. However, renewable energy and urbanization reduce the ecological footprint in UAE during the two periods, thus improving environmental quality. Globalization and financial development have different influences on ecological footprint during these periods. These findings are robust to other estimation techniques.

Based on these results, this study offers significant policy implications such as increasing renewable energy supply, particularly solar energy and aligning the product manufacturing structure and complexity toward producing environmentally friendly products which can be used to realize the nation’s agenda of reducing fossil fuels consumption to 38% by 2050 and achieving sustainable environment and growth.

This study provides an empirical attempt to investigate the influence of EC and renewable and nonrenewable energy on the ecological footprint of the UAE.

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.

This paper analyses the direct relationship between budget deficits and economic growth, the channels through which budget deficits inhibit growth and finally, the Granger causality between budget deficit and economic growth in South Africa over the period 1975 to 2020.

In a bid to control for endogeneity that is common in economic growth regressions, the author employed the dynamic ordinary least squares (DOLS) approach.

Towards analysing the direct relationship between budget deficit and economic growth, results show that a 10-percentage rise in the budget deficit slows economic growth by 0.2 percentage points. Results show that the growth inhibiting consequences of the budget deficit in South Africa are principally driven by negatively affecting private and public physical capital accumulation growth, as well as a drop in gross national savings. However, results show no evidence of a deficit reduction effect through long term-real interest rate. The findings reveal a one-way Granger causality running from budget deficits to economic growth.

Based on the findings in this article, expanding the fiscal deficit to support growth is not a viable policy option for the South African economy.

The originality of this paper lies in establishing the Granger causality between budget deficit and economic growth, thus adding to the scant literature, as well as establishing the channels through which budget deficit retards economic growth for the South African economy.

This study aims to examine the effects of industrial production (IP), inflation and investment on suicide mortality in Turkey as a developing country over the 1988–2018 period.

Fourier cointegration test and dynamic ordinary least square regression were used in this study.

IP and investment have a statistically significant and negative impact on suicide mortality, whereas inflation has a statistically significant and positive effect on suicide mortality.

The results of this study have important implications for policymakers and potentially the creation and implementation of suicide prevention policies. Not only do investment promotion, IP and disinflation policies in developing countries have a significant effect on economic growth but they also have a substantial impact on mental health.

Although previous studies have investigated the impact of economic growth and unemployment on suicide deaths in Turkey, no research has probed the effect of economic factors, except for unemployment and gross domestic product, on suicide. Thus, given the hidden unemployment and informal sector in developing economies, it is vital to examine the impact of IP, inflation and investment on mental health.

It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

Due to an increase in energy demands, it has become vital to devise efficient energy policies. Literature has suggested multiple factors influencing the consumption of specific energy types. Among others, institutional quality (INQ) is another factor that can determine energy consumption. Given this, the current study aimed to investigate the impact of INQ on fossil fuel energy (FFE) and renewable energy consumption (REC).

The empirical analysis was conducted on 20 years (2000–2019) of data from South Asian economies, and regression among variables was established by employing the dynamic ordinary least square and fully modified ordinary least square models. The selection of both techniques is subject to the existence of cointegration identified by the Johansen cointegration test. Other pre-estimation techniques include cross-section dependence and unit root testing validating the estimation of coefficients in the long run.

The analysis mainly reveals the negative impact of INQ on FFE and the positive impact of INQ on REC. The authors further find the asymmetric impact of control variables including foreign direct investment inflow, economic growth, inflation rate, financial sector development and energy investment on the consumption of both types of energy.

Given the positive influence of INQ on REC, it is recommended to focus on improving the efficiency of institutions specifically those that are directly linked with energy-related policies. A better INQ can ensure environmental sustainability by enhancing the consumption of renewable energy. Therefore, it is advised to exert more efforts to improve the INQ.

In view of the positive influence of INQ on REC, it is recommended to focus on improving the efficiency of institutions specifically that are directly linked with energy-related policies. A better INQ can ensure environmental sustainability by enhancing the consumption of renewable energy. Therefore, it is advised to exert more efforts for improving the INQ.

This study offers robustness to the empirical findings of existing literature on the INQ-REC nexus and complements the underdeveloped literature on the INQ-FFE relationship.