RESUMEN
The primary purpose of this research is to examine the impact of climate change on maize production in Pakistan. This research studied the impact of climate change on maize production in Pakistan from 1990 to 2020 using the Auto Regressive Distributed Lag (ARDL) technique and draws implications for the future of Pakistan's sustainable agricultural industry. According to ARDL's short-run and long-run analyses, variables such as average temperature (AVEGTP), carbon dioxide (CO2), precipitation (PRPT), and tube well irrigation (TWL) all have a significant short-run and long-run impact on maize yield at the 1 %, 5 %, and 10 % significance levels. The estimated findings were also affirmed through FMOLS and DOLS. The study's key findings indicated that variables such as average temperature, carbon dioxide, precipitation, and tube well irrigation had significant short-run and long-run impacts on maize yield. Climate change's impacts on maize yield underline the crucial need for action to address this global issue and ensure agriculture's future. A recent study has emphasized the significant impact of climate change on Pakistan's maize production, stressing the importance of addressing this global issue for food security. The study recommends selecting crop varieties and managing fertilizer applications based on projected climate change to mitigate the impending crisis. Policymakers can use the study's findings as valuable insights to formulate effective policies that ensure the resilience and sustainability of Pakistan's agricultural industry.
RESUMEN
The work cognition of public employees lays importance on tackling an escalating health crisis situation. At the micro-level and macro-level, different factors contribute to different degrees of public employees' work cognition. However, there are limited studies examining the work cognition of public employees and its influencing factors, particularly in situations such as a public health crisis. Our research takes China's response to COVID-19 as an example. The data have been taken from six Chinese provinces, Hunan, Hubei, Jiangsu, Shanxi, Henan, and Shandong, through a total of 738 questionnaires and telephonic interviews. Furthermore, this study used a logistic multiple regression model to analyze the factors that influenced the public employees' work cognition when working under a public health crisis. The results of our study showed that at a micro-level, the educational background, attitudes, and actions (initiative, responsibility, administrative capacity, and timeliness of feedback), and their level of concern with work influenced the work cognition of the public employees. At a macro-level, we found that it was the anti-epidemic measures that most influenced public employees' work cognition. Our findings provide important policy implications for emergency preparedness and handling of major emergencies, and have important reference value for the management of public employees and the improvement of national governance capabilities under similar major challenges in the future.