This study seeks to investigate how climate change affects actual output in African countries, using greenhouse gas emission as a case study. This paper uses the actual output of Nigeria, Ghana, Liberia, The Gambia, Cabo Verde, and Sierra Leone for the analysis. Climate change is proxied by greenhouse gas emission, which are extracted from the International Monetary Fund (IMF) database, for the period, 1980 to 2022. Descriptive statistics, unit root, and panel System Generalized Method of Moments 1(SGMM1) are estimated, and the result shows that agricultural greenhouse gas emission reduces the output of the selected African Countries, while other greenhouse gases such as building and other sector’s greenhouse gas emission, energy industries greenhouse gas emissions, mineral industry greenhouse gas emission and road transport greenhouse gas emission increase output. For actual output to increase, the paper suggests policy remedies such as sustainable farming practices and adoption of climate-smart technologies.

The determinants of production-based carbon emission (PCE) have been extensively examined in the literature. However, PCE only accounts for emissions generated within the territory of a country and does not capture emissions embedded in imported goods. The rapid growth in Consumption-based Carbon Emissions (CCE) in Sub-Saharan Africa (SSA), driven by increasing imports and economic activities, highlights the need for a comprehensive understanding of these emissions. This motivates us to examine the impact of Renewable Energy Consumption (REC) on CCE in SSA. We employed a two-step system Generalized Method of Moments (GMM) methodology, utilizing data from 1995 to 2020. The results show a negative effect of REC on CCE, suggesting that increases in renewable energy consumption tend to reduce CCE. In contrast, the positive impact of real GDP and population indicates that economic growth and population expansion tend to bolster carbon emissions. These findings underscore the importance of implementing policies harmonizing economic growth with sustainable energy strategies. They provide valuable insights for informed environmental and economic planning decisions.

Microfinance loans have long been associated with relatively high interest rates. There is a wide variation of interest rates charged by microfinance institutions (MFIs) across countries, as well as some dispersion of interest rates across MFIs within the same country. The source of interest rate variation can result from institution specific characteristics such as, average loan size and the composition of female borrowers. The dispersion in prevailing interest rates in the formal financial sector across countries may partially contribute to the variation of microfinance interest rates across countries. I use yield on gross loan portfolio as a proxy for the average interest rate on loans, the average loan balance as a measure of average loan size, and lending rate for commercial loans to represent the interest rate in the formal financial sector. This study attempts to analyze the dispersion of interest rates on microfinance loans by showing its association with loan size, female composition of borrowers, and the prevailing lending rates. Using a large panel of 1,531 MFIs, I show that microfinance interest rates have a statistically significant negative relationship with loan size, and a positive association with commercial lending rate and the female composition of borrowers.

This is the first study to examine how Nigerian output is affected by the news-based Economic Policy Uncertainty Index by Tumala et al. (2023) and Climate Uncertainty Index by Salisu et al. (2023). Using ARDL and Granger causality on quarterly data from 2016Q2 to 2024Q1, the findings show that increased economic and climate uncertainties result in decreased output. Additionally, the study reveals that climate uncertainty has a more significant effect on output compared to economic policy uncertainty. The Granger causality indicates one-way causality from climate uncertainty to output, thereby reinforcing the substantial influence of climate uncertainty on output in Nigeria.

In recent years, as global climate change intensifies and ESG investment concepts gain prominence, climate risk has become a crucial factor for investors and financial markets. Investigating how climate risk is priced in the Chinese capital market is both theoretically and practically important for promoting the sustainable development of China's capital markets and advancing green finance. This study employs natural language processing (NLP) to quantify the proportion of climate risk-related content in the annual reports of listed companies, creating an indicator to assess their climate risk level. The study uses climate risk of listed companies as the explanatory variable and annual stock returns as the dependent variable, applying a fixed-effects model to empirically examine the impact of climate risk on investment returns. The study finds that: first, the climate risk of listed companies shows a clear trend of change over time; second, there is a significant positive correlation between the climate risk of listed companies and investment returns.

We propose a theoretical model that underlines the implications of a non-linear Phillips curve for the difficulty of monetary policy to fight against inflationary tensions similar to those encountered in 2021 and 2022 at a worldwide level, due to the resumption of demand after the COVID crisis and to the war in Ukraine. In such non-linearities, the interest rate becomes an asymmetric and convex function of an inflationary supply shock variation. In the case of inflationary tensions, the nominal interest rate can then strongly increase above its long-term equilibrium value. Economic recession is exacerbated, whereas inflationary tensions are more accentuated. Then, the risk is a more than proportional increase in public expenditure to compensate for the decrease in private consumption, which could not be achieved without a strong growth in the public indebtedness level.