Geopolitical risk, economic policy uncertainty, and dynamic connectedness between clean energy, conventional energy, and food markets.

The global financial markets suffered unprecedented shocks, leading to significantly increased uncertainty in the markets due to various economic and financial recessions and geopolitical tensions, resulting in substantial fluctuations in market prices. Therefore, this paper aims to identify the response of the clean energy, conventional energy, and food markets to economic uncertainty and political tension while considering the influence of numerous crises and political conflicts. To achieve this, we employ the DCC-GARCH-based connectedness approach and the quantile-on-quantile model on monthly data spanning from May 2008 to June 2023. The results provide evidence of the sensitivity of dynamic volatility spillovers between financial assets to GEPU and GPR during major economic and financial crises and geopolitical events. Notably, this sensitivity increases significantly during the global financial crisis (GFC), the European debt crisis, Brexit, the US presidential election, the COVID-19 pandemic, and the Russian-Ukrainian war. However, the investigation of the tail dependence structure reveals that the relationship between uncertainties and total volatility connectedness across various market conditions appears to be asymmetric and heterogeneous. Our findings assist policymakers and green investors in designing the most effective policies to mitigate the impact of uncertainties on both conventional and green investments. This is achieved through insightful knowledge about the primary drivers of contagion among these indices, all while not compromising sustainability goals.

Revisiting the relationship between business conditions, climate policy uncertainty, and environmental pollution: evidence from the USA.

This paper aims to revisit the interdependency between business conditions, climate policy change, and the environmental pollution of the USA. Interestingly, our paper represents a completion to the existing literature on three levels at least. First, we propose to analyze this issue during normal periods and periods of turmoil, particularly the COVID-19 outbreak. To do so, contrary to previous studies that used economic growth, we employ the ADS index as a real-time business conditions measurement. Second, we employ a frequency approach, based on the continuous wavelet transform, allowing us to understand the nature of the relationship. Understanding whether the relationship holds in the short- or long-term is useful for policymakers in monitoring public policies to achieve CO2 emission reduction as well as to investors interested in high value-added projects. Our analysis shows that, during the last two decades, the relationship between business conditions as well as climate uncertainty index and CO2 emissions is observed during the long- and short-term, and driven through economic conditions. However, during the crisis periods, the effect is detected across various scales and the relationship is bi-directional. Our results have several practical implications for the US policymakers to consider when setting policies for fighting pollution emissions and environmental protection.

What can we learn about the market reaction to macroeconomic surprise? Evidence from the COVID-19 crisis.

We investigate the impact of macroeconomic surprise and uncertainty on G7 financial markets around COVID-19 pandemic using two real-time, real-activity indexes recently constructed by Scotti (2016). We applies the wavelet analysis to detect the response of the stock markets to the macroeconomic surprise and an uncertainty indexes and then we use NARDL model to examine the asymmetric effect of the news surprise and uncertainty on the equity markets. We conduct our empirical analysis with the daily data from January, 2014 to September, 2020. Our findings indicate that G7 stock markets are sensitive to the macroeconomic surprise and uncertainty and the effect is more pronounced at the long term than the short term. Moreover, we show that the COVID-19 crisis supports the relationship between the macroeconomic indexes and the stock prices. The results are useful for investment decision-making for the investors on the G7 stock indices at different investment horizons.