The relationship between climate risk, climate policy uncertainty, and CO2 emissions: empirical evidence from the US

This paper examines the relationship between climate risk and climate policy uncertainty, and CO2 emissions in the US over the 2000–2022 period using a structural Factor- Augmented Vector AutoRegression (FAVAR) model with a two-step principal component analysis based on monthly observations. We employ a very recent measure to proxy for uncertainty regarding climate policy based on the Climate Policy Uncertainty Index (CPU) of Gavriilidis (2021), while Climate Risk is proxied by financial cost of natural disasters and number of deaths. We use different variables for CO2 emissions, based on total and sectoral emission (commercial, electric power, residential sector, transportation, and industrial sector). The results indicate that a significant percentage of the variance of CO2 emissions in the US, is explained by Natural Disasters Cost, which also seem to account for a significant percentage of the US Total Renewable Energy Consumption variance. Shocks to disaster costs seem to decrease all type of emissions significantly and also increase renewable energy use significantly. Natural disasters increase political disagreement among U.S. politicians, as well as, the climate policy uncertainty, highlighting the need for efficient policymaking and regulations. In further results, we find that an increase in Partisan Conflict decreases emissions and explains a significant amount of renewable energy variance

External validation of risk prediction models for incident colorectal cancer using UK Biobank.

BACKGROUND: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS: External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. RESULTS: There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. CONCLUSIONS: Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening

Crude oil prices in times of crisis: The role of Covid-2019 and historical events

International audienceCrude oil prices in times of crisis: The role of Covid-19 and historical event

The European Central Bank and green finance: How would the green quantitative easing affect the investors' behavior during times of crisis?

In July 2021, the European central bank (ECB) announced the application of new environmental criteria to purchase private assets as part of its Quantitative Easing (QE) program. Using a Bayesian VAR model with time varying parameters and stochastic volatility (TVP-BVAR-SV), we investigate the transmission of Green bond shocks to the stock market during the pre-and-post COVID-19 pandemic. We document a nonlinear relation between the green bonds and the green equities. Our findings suggest that the ECB's Green QE can drive investors towards green investment in the stock market through the green bond market during the non-crisis period. However, we show that the proper transmission of Green QE shocks to the stock market depends on the economic conditions and could not be effective during the crisis period. Our results also support previous findings that state the growing demand for sustainable investing after COVID-19. These findings have important implications for investment professionals, policymakers, and environmentally concerned actors

Precious metals and currency markets during the Russia-Ukraine conflict’s inflationary periods

International audienceThe contemporary conflict between two countries Russia and Ukraine has caused intensification in the increasing prices of commodities and energy owing to the supply chain disruption and the sanctions imposed on both countries. The previous literature has validated that Russia-Ukraine conflict substantially affects financial and economic operations of other countries. Therefore, the key aim of conducting this study is to inspect the dynamic spillover connectedness between the four leading precious metals (such as Gold, Palladium, Platinum, and Silver) and seven major currency markets (including Euro, British Pound, Australian Dollar, Swiss Franc, Japanese Yen, Canadian Dollar, and Chinese Yuan). The study includes the dataset from 24 January 2022–31 May 2022 to cover the inflationary period. Accordingly, the Time-Varying Parameter Vector Autoregression framework is applied. Granger linear causality and BDS nonlinear causality techniques are also employed to examine the causal effect of geopolitical risk in aforementioned connectedness. The findings reveal that Platinum has a strong spillover towards all the considered currencies except the Japanese Yen. The increasing demand for Platinum during the conflict secured it to receive the spillover. While the Japanese Yen is a net transmitter of spillover indicating the Japanese Yen as sturdiest currency during the conflict. The causality test reveals that geopolitical risk causes spillover connectedness across the precious metals and the currency markets during inflationary period. This study is significant for policymakers, investors, and portfolio managers while developing strategies or making critical investment decisions

The importance of climate policy uncertainty in forecasting the green, clean and sustainable financial markets volatility

International audienceThis research represents the first empirical evidence highlighting the significant role of climate policy uncertainty in predicting the green, clean, and sustainable financial markets volatility. The analysis incorporates Gavriilidis's (2021) recently introduced news-based climate policy uncertainty index. To conduct this investigation, an advanced econometric approach, namely GARCH-MIDAS, has been employed, considering two sample periods: (i) full period (ii) COVID-19 period. Furthermore, the study reveals that climate policy uncertainty amplifies volatility of the S&P Green Bond Index, S&P Global Clean Energy Index, and Dow Jones Sustainability Index, rendering these indices highly sensitive to such uncertainty. Additionally, the out-of-sample analysis demonstrates climate policy uncertainty as a strong predictor, with the GARCH-MIDAS model displaying superior predictive accuracy. The findings of this research bear significant implications for strategies related to risk mitigation and diversification of portfolio particularly for investors, policymakers, and portfolio managers

Improved method of S-alkylation of 2-mercaptobenzimidazole derivatives with trialkylphosphite

International audienceA new method of S-alkylation of 2-mercaptobenzimidazole derivatives has been developed by the condensation of these heterocycles with trialkylphosphite in the presence of phosphorus oxychloride giving the corresponding 2-S-alkylbenzimidazoles. The structure of the obtained products has been established by spectroscopic data

Condensation of 7-nitroindole-2-carbohydrazide derivatives with ethyl acetoacetate

International audiencePyrazolylindolyl ketone derivatives were obtained by cyclization of the condensation products 7-nitroindole-2-carbohydrazide derivatives with ethyl acetoacetate. We have shown careful examination of spectroscopic data and the open-chain intermediate isolation as well as the identification of the formed compound structure