Using monthly panel data over the period 2007–2019 for seven Latin American countries, we empirically test the impact of climate shocks, here strong ENSO events (El Niño Southern Oscillations), on sovereign risk. Local Projections are computed to assess the dynamic response of sovereign spreads to ENSO events. Results show that strong El Niño and La Niña shocks lead to a significant increase in sovereign spreads, but with different timing. Strong El Niño shocks are associated with a significant short-term increase in sovereign spreads, while strong La Niña events are associated with a delayed but significant increase in sovereign spreads after a short-term decrease. Thus, our results suggest a potential asymmetry in the effect of these strong ENSO events on sovereign risk. We also highlight high volatility in the dynamics of sovereign spreads, which may reflect an overreaction of investors faced with the high degree of uncertainty generated by the economic and financial consequences associated with strong ENSO events. Complementary time-series estimates suggest that Costa Rica and Peru are especially subject to these effects. Overall, our results provide a warning about the fact that, in the case of Latin American countries, weather shocks associated with strong ENSO events have adverse macroeconomic and financial consequences that can lead to an increase in sovereign risk, hinder their government's ability to act as a ‘climate rescuer’ of last resort, and may be aggravated in the future by climate change.

The contemporary world faces significant challenges in energy crises and climate change. To analyze the relationship between energy and climate, we explore the influence of the climate-related attention of G20 countries on renewable energy stock volatility forecasting under the framework of the extended GARCH-MIDAS model. In the context of COP26, we further adopt natural language processing technology and shrinkage approach to obtain Google search volume for 107 climate-related keywords and then construct new climate risk attention indicators. The in-sample parameter estimation results show that the climate attention of G20 countries has a remarkable positive effect on the renewable energy stock market volatility. The out-of-sample results demonstrate that the climate attention of different countries exerts varying influences on the volatility of the renewable energy stock market. Climate risk and energy issues are among the serious challenges facing the 21st century, and reducing greenhouse gas emissions and finding cleaner energy is an urgent task. As the response to climate change necessitates diverse strategies in various countries, our research can offer valuable guidance and serve as a reference for national energy transitions and the selection of alternative energy solutions.

This paper contributes to the new climate-society literature (Carleton and Hsiang, 2016) by analyzing the role of climate in conflicts over the pre-industrial period in Europe, in the vein of the recent literature initiated by Tol and Wagner (2010) and Burke and Hsiang (2014). As far as we know, this study is the first to apply a (time-varying) copula analysis to climate-economics literature and to investigate the dependence between climate and conflicts in a historical time series context. Both social disturbances and wars are considered and their interrelationships are taken into account. The main contributions of the paper are: (1) the use of copula analysis compared to previous correlational approaches; (2) the analysis of the temporal heterogeneity of climatic effects via a time varying approach; (3) the introduction of agricultural and fiscal pressure channels to investigate the interrelationships between climate, social disorders and warfare; (4) the investigation of El Niño Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) Teleconnections effects whereas previous long-term historical studies have only focused on precipitation and temperature data. Time varying Copula analysis enabled us to identify a positive dependence between temperatures and conflicts, and negative or positive dependences between anomalous precipitation and conflicts, by explicitly focusing on the joint distribution of our variables. We were also able to precisely identify the periods/regimes during which the link between climate and conflict was genuinely active and then stress on the agricultural and fiscal revenues channels.

Using a panel of more than 156 000 firms surveyed in 140 countries over the 2003-2019 period, this paper addresses the issue of the financial resource curse through a new channel that thus far has not been accounted for in the literature, namely, firms' access to finance. To do this, our econometric analysis is based on an original approach combining microeconomic level data on firms' access to finance and macroeconomic level data on countries' level of natural resource rents, with a focus on energy rents (oil, gas and coal). By doing so, we are able to investigate in a more precise and disaggregated way the mechanisms explaining why resource-based countries are associated with less developed financial systems. Using panel regressions, we find significant and robust evidence that firms operating in countries characterized by a high level of natural resource rents suffer from less access to external financing. Moreover, depending on two important transmission channels, namely, the quality of institutions and the extent of supply constraints, we find heterogeneities in the relationship between firms' access to finance and countries' level of natural resource rents. In addition, we show that the countries' level of natural resource rents has a significant and negative correlation with firms' access to finance only for firms that do not operate in the natural resource sector. This provides new evidence of the Dutch disease phenomenon, since the lack of firms' financing can also be an explanation for the atrophy of sectors unrelated to the natural resource sector.

This study examines the dynamic impact of face mask use on both infected cases and fatalities at a global scale by using a rich set of panel data econometrics. An increase of 100% of the proportion of people declaring wearing a mask (multiply by two) over the studied period lead to a reduction of around 12 and 13.5% of the number of Covid-19 infected cases (per capita) after 7 and 14 days respectively. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. Our results hold when using the rigorous controlling approach. We also document the increasing adoption of mask use over time and the drivers of mask adoption. In addition, population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. However, individualism index is negatively correlated with mask adoption. Finally, strict government policies against Covid-19 have a strong significant effect on mask use.

Although the current covid-19 pandemic was neither the first nor the last disease to threaten a pandemic, only recently have studies incorporated epidemiology into macroeconomic theory. This paper uses a dynamic stochastic general equilibrium (dsge) model with a financial sector to study the economic impacts of epidemics and the potential for unconventional monetary policy to remedy those effects. By coupling a macroeconomic model with a traditional epidemiological model, we can evaluate the pathways by which an epidemic affects a national economy. We find that no unconventional monetary policy can completely remove the negative effects of an epidemic crisis, save perhaps an exogenous increase in the shares of claims coming from the Central Bank (“epi loans”). To the best of our knowledge, our paper is one of the first to incorporate disease dynamics into a dsge-sir model with a financial sector and examine the use of an unconventional monetary policy.

In this new era of energy transition, access to reliable and correctly functioning electricity markets is a huge concern for all economies. The restructuring path taken by most electricity markets involves the movement towards green generation structures and the increasing integration of wind and solar photovoltaic energy sources. Furthermore, it involves the electrification of energy systems, which implies a substantial increase in electricity demand levels. It is also important to add that electricity use has been pivotal in achieving efficient productivity levels in many sectors and is thus crucial to boosting economic activity. Nevertheless, this shift in generation structures has raised several challenges in electricity markets, mainly because the electricity produced from wind and solar photovoltaics is intermittent. In turn, adopting green power sources has been claimed to increase electricity price volatility and thus increase pricing risks. Therefore, to ensure that the right market signals are being sent to investors, the behaviour of electricity prices should be carefully assessed. There are three main types of pricing mechanisms commonly used in electricity markets: zonal, uniform and nodal. This study provides a short literature survey on these three pricing mechanisms. Our analysis has revealed that the assessment of the behaviour of nodal electricity price volatility is rarely studied in the literature. This fact has motivated the exploration of this topic and the consideration of the New Zealand electricity market case. The New Zealand electricity market is an energy-only system with no interconnections with other electricity markets. Furthermore, it has plenty of electricity produced from hydropower, which has a high potential to reduce price volatility through its backup role. The nodal pricing mechanism is complex, and data on it are hard to process. This paper elucidates the main challenges in processing electricity big data. Three different procedures to make this data more useable are described in detail. The main conclusions of this paper highlight the need to access easy-to-manage data and identify certain variables that significantly affect nodal prices for data which are unavailable.

This paper aims to explore the impact of political factors on the performance of state-owned banks in 50 African countries over the 2005–2012 period. We use panel data methods (fixed effects and quantile regression models) with unique hand-collected data concerning political factors and ownership structures of African banks. Our main results confirm the social and political view of state-owned banks for the African countries, but the results are somewhat heterogeneous according to the level of banking performance: ownership structure significantly affects the performance of banks with low profitability compared to those with high profitability. However, we find no significant political interference in banking activity. Finally, our results confirm that politicians do not prioritize monetary policy or banking regulation in their electoral programs in African countries.

The transition to a cleaner and greener energy production requires storing the energy produced from renewable energy sources. Hydrogen is an promising vector for storing the surplus energy from RES for use at a later time. The present study uses a discrete choice experiment and a mixed logit model to analyse consumer preferences for hypothetical hydrogen-based energy storage systems. This is the first study considering the behavior of households vis-à-vis hydrogen as a new energy carrier at home. The results show a preference for power-to-gas-to-power over power-to-gas systems, as well as strong preferences for greater energy self-sufficiency. Consumers prefer management by consumer collectives over private companies and are indifferent concerning the location of the systems in relation to their homes. Respondents who consume only electricity prefer a power-togas-to-power system whereas as respondents who also consume gas are indifferent.

Electricity markets are becoming increasingly interconnected, in part, to deal with unpredictability and imbalances in electricity prices. This paper assesses how electricity flows and generation from wind and solar photovoltaic (PV) power impact the volatility and mean of day-ahead electricity prices in Spain. It finds there is a merit order effect from wind and solar PV power at most times of the day, which varies in magnitude for each of the 24 h. Electricity production from wind power is also found to play a clear role in increasing price volatility at all hours. Electricity inflow is shown to decrease both the mean and volatility of the electricity prices. The volatility of electricity prices is revealed to be highly persistent, and thus prone to large transmission shocks. This volatility is also susceptible to new shocks, which may indicate a tendency by market participants to overreact to unexpected shocks in electricity prices, possibly due to the relatively small size of the Iberian electricity market.

ABSTRACT This article presents an empirical investigation of factors influencing local renewable energy (RE) deployment. The existing literature has mainly focused on the global contribution of RE at the macro-country level. The particularity of this study resides in the extension of the analysis to the local level, and it was motivated by the fact that the targets for RE deployment are partly defined at the national level, but the establishment of the means of production and the organization is delegated to the local level. Using French data for 95 administrative divisions (départements), we estimate a spatial panel data econometric model by considering serial correlation in the remainder errors. The results reveal strong spatial spillovers and high time persistence, suggesting that the presence of proximity between French local governments conducts local RE policies. The RE deployment of a given department is thus affected by its neighbours. Some determinants of RE deployment are finally identified to help authorities to increase RE supply in the future. Income effect is significant and derived for solar energy and bioenergy and is supplemented by indebtedness that seems to be a favourable strategy to increase solar RE investments. Political ideology is likely to partly explain wind and bioenergy deployment. Finally, geographical factors remain important drivers: solar energy is more developed in southern regions while wind power is more deployed in the north. Based on these results, policy coordination between departments is required to maximize their natural potentialities and increase RE deployment in the future.

In the vein of recent empirical literature, we reassessed the impact of weather factors on Covid-19 daily cases and fatalities in a panel of 37 OECD countries between 1st January and 27th July 2020. We considered five different meteorological factors. For the first time, we used a dynamic panel model and considered two different kinds of channels between climate and Covid-19 virus: direct/physical factors related to the survival and durability dynamics of the virus on surfaces and outdoors and indirect/social factors through human behaviour and individual mobility, such as walking or driving outdoors, to capture the impact of weather on social distancing and, thus, on Covid-19 cases and fatalities. Our work revealed that temperature, humidity and solar radiation, which has been clearly under considered in previous studies, significantly reduce the number of Covid-19 cases and fatalities. Indirect effects through human behaviour, i.e., correlations between temperature (or solar radiation) and human mobility, were significantly positive and should be considered to correctly assess the effects of climatic factors. Increasing temperature, humidity or solar radiation effects were positively correlated with increasing mobility effects on Covid-19 cases and fatalities. The net effect from weather on the Covid-19 outbreak will, thus, be the result of the physical/direct negative effect of temperature or solar radiation and the mobility/indirect positive effect due to the interaction between human mobility and those meterological variables. Reducing direct effects of temperature and solar radiation on Covid-19 cases and fatalities, when they were significant, were partly and slightly compensated for positive indirect effects through human mobility. Suitable control policies should be implemented to control mobility and social distancing even when the weather is favourable to reduce the spread of the Covid-19 virus.

To confront the global Covid-19 pandemic and reduce the spread of the virus, we need to better understand if face mask use is effective to contain the outbreak and investigate the potential drivers in favor of mask adoption. It is highly questionable since there is no consensus among the general public despite official recommendations. For the first time, we conduct a panel econometric exercise to assess the dynamic impact of face mask use on both infected cases and fatalities on a global scale. We reveal a negative impact of mask wearing on fatality rates and on the Covid-19 number of infected cases. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. We also document the increasing adoption of mask use over time. We find that population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. Surprisingly, government effectiveness and income level (GDP) have an unexpected influence. However, strict government policies against Covid-19 have the most significant effect on mask use. Therefore, the most effective way of increasing the level of mask wearing is to enforce strict laws on the wearing of masks.

Despite the fact that the current covid-19 pandemic was neither the first nor the last disease to threaten a pandemic, only recently have studies incorporated epidemiology into macroeconomic theory. In our paper, we use a dynamic stochastic general equilibrium (dsge) model with a financial sector to study the economic impacts of epidemics and the potential for unconventional monetary policy to remedy those effects. By coupling a macroeconomic model to a traditional epidemiological model, we are able to evaluate the pathways by which an epidemic affects a national economy. We find that no unconventional monetary policy can completely remove the negative effects of an epidemic crisis, save perhaps an exogenous increase in the shares of claims coming from the Central Bank (“epi loans”). To the best of our knowledge, our paper is the first to incorporate disease dynamics into a dsge-sir model with a financial sector and examine the effects of unconventional monetary policy.

Electricity interconnections have become increasingly common as a means of integrating electricity markets, expediting the exchange of electricity, and thereby creating balanced electricity systems. These interconnections also facilitate the incorporation of intermittent renewable energy sources, ensuring greater energy security and reliability in electricity markets. In this study, an assessment is made of the impact of both electricity produced from wind power, and the cross-border flow of electricity, on the mean and volatility of the day-ahead electricity price. To do this, we studied the Swedish bidding zone with the highest flow of electricity imports and exports between 2016 and 2019 – the SE3 bidding zone (BZ). Using a SARMAX/GARCH approach, every hour of the day was assessed individually, by estimating up to 24 different models from 1 January 2016 to 30 April 2020. The results confirm the Merit-Order Effect from wind power, and that its impact is similar in magnitude throughout the day. Furthermore, the flow of electricity from both import and export appear to increase the day-ahead electricity price. This study also suggests that the volatility of electricity prices is primarily increased by unexpected shocks. This may be related to the high dependence of the SE3 BZ electricity system on electricity imports, which makes the system extremely susceptible to larger transmission of shocks.