Energy mix with technological innovation to abate carbon emission: fresh evidence from Mexico applying wavelet tools and spectral causality.

The global warming issue arises from climate change, which draws scientists' attention toward cleaner energy sources. Among clean sources, renewables and nuclear energy are getting immense attention among policymakers. However, the significance of nuclear energy in reducing CO2 emissions has remained ambiguous, necessitating further research. Therefore, the present study draws impetuous attention to the United Nations Sustainable Development Goals-7 (affordable clean energy) & 13 (climate change mitigation) by looking at the relationship between energy mix (fossil fuels, renewables, and nuclear), economic growth, technological innovation, and CO2 emissions in Mexico from 1980 to 2019 using the autoregressive distributed lag (ARDL) model. In addition, to assess the direction of causality, this study applied wavelet techniques and spectral causality. The findings affirm that renewable and nuclear energy use and technological innovation tend to curb CO2 emissions, whereas fossil fuel consumption and economic expansion trigger CO2 emissions. The study lends support to the environmental Kuznets curve (EKC) phenomenon in Mexico. The FMOLS and DOLS tests show that our long-run estimates are reliable. In different time scales, the wavelet coherence result is also consistent. Finally, the results of the spectral causality approach demonstrate a significant causal association between the variables tested at various frequencies. As a result, in order to achieve SDGs 7 and 13 and support an environmentally friendly ecosystem, Mexico's energy mix must be changed to renewables and nuclear.

Simultaneous adoption of diversification and agricultural credit to manage catastrophic risk for maize production in Bangladesh.

Risk management strategies are made up of response variability that may lessen the likeliness of an unfavorable event occurring and/or decrease the damaging consequences if that event happens. To minimize the risk, farmers respond in three ways which are considered to be risk managing tools; these are production, marketing, and financial responses. This study aimed to look at the potential associations and effects of implementing multiple risk management techniques at the same time, as very limited number of research is available in this field. Stratified random sampling technique was used to collect 350 farmer's responses from four different agro-ecological districts of Bangladesh. This study applied bivariate and multinomial probit models to investigate the effects of social and farm features, farmers' views of disastrous risk, and their attitudes toward risk sources, as well as potential associations between diversification and agricultural credit as a risk management tool. The outcomes identified the correlation between adoptions of multiple risk management strategies and concluded that one risk management approach can convince farmers to follow another at the same time. Moreover, the outcomes observed that age, educational status, farm size, family returns, land ownership, and risk-opposed character of farmers were the most persuading aspects for adopting different risk management strategies. Besides, the results presented other interpretations and information which will clarify farmer's actions when it comes to handling various devastating risks and will also provide the policymakers with a platform to prepare for appropriate risk managing plans concerning farmers.

Assessing farmers' intention towards conservation agriculture by using the Extended Theory of Planned Behavior.

Conservation agriculture is considered as an agro-ecological approach to the sustainable and resource-saving crop production system. Previous studies on the adoption of agricultural innovation often consider socio-economic characteristics and overlook underlying psychological factors influencing farmers' behavioral intention. This study adopted three socio-psychological constructs, Attitude, Subjective Norm (SN), and Perceived Behavioral Control (PBC), which originated from the Theory of Planned Behavior (TPB), and proposed two new constructs, Knowledge (K) and Perceived Climatic Threats of Conventional Farming (PCTCV). Using the Extended Theory of Planned Behavior Model (ETPBM), this study analyzed factors affecting the intention of farmers to continue Conservation Agriculture (CA) for the following year (2020) in three districts located in the northern part of Bangladesh. This research found evidence from the hierarchical regression analysis that variables of ETPBM could explain 7% more variation (change in R2) in intention than variables of TPB, while the socio-economic characteristics of farmers can explain only 0.5% more than the variables of ETPBM. Structural Equation Modelling (SEM) was used to determine and examine the extended theory and indicated that farmers' knowledge (K) had the highest total impact, while attitude had the highest direct impact on intention. The results indicated that factors including Attitude, SN, PBC, Knowledge (K), and PCTCV are positively significant when attempting to understand farmers' intentions to adopt CA. This study presented evidence about the effectiveness of ETPBM when assessing the farmers' intentions towards conservation farming. Based on these findings, we concluded that the combination of extension services for upgrading the level of knowledge concerning the importance of CA could significantly affect farmers' attitudes on intention towards the application of CA.