Dynamic linkages between climatic variables and agriculture production in Malaysia: a generalized method of moments approach

Resilience in maize production for food security: Evaluating the role of climate-related abiotic stress in Pakistan

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.

How Has Climate Change Driven the Evolution of Rice Distribution in China?

Estimating the impact of climate change risks on rice distribution is one of the most important elements of climate risk management. This paper is based on the GEE (Google Earth Engine) platform and multi-source remote sensing data; the authors quantitatively extracted rice production distribution data in China from 1990 to 2019, analysed the evolution pattern of rice distribution and clusters and explored the driving effects between climatic and environmental conditions on the evolution of rice production distribution using the non-parametric quantile regression model. The results show that: The spatial variation of rice distribution is significant, mainly concentrated in the northeast, south and southwest regions of China; the distribution of rice in the northeast is expanding, while the distribution of rice in the south is extending northward, showing a spatial evolution trend of "north rising and south retreating". The positive effect of precipitation on the spatial distribution of rice has a significant threshold. This shows that when precipitation is greater than 800 mm, there is a significant positive effect on the spatial distribution of rice production, and this effect will increase with precipitation increases. Climate change may lead to a continuous northward shift in the extent of rice production, especially extending to the northwest of China. This paper's results will help implement more spatially targeted climate change adaptation measures for rice to cope with the changes in food production distribution caused by climate change.

Measuring the Effects of Climate Change on Wheat Production: Evidence from Northern China

The current study examines the long-run effects of climatic factors on wheat production in China's top three wheat-producing provinces (Hebei, Henan, and Shandong). The data set consists of observations from 1992 to 2020 on which several techniques, namely, fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical co-integrating regression (CCR) estimators, and Granger causality, are applied. The results reveal that climatic factors, such as temperature and rainfall, negatively influenced wheat production in Henan Province. This means that Henan Province is more vulnerable to climate change. In contrast, it is observed that climatic conditions (via temperature and rainfall) positively contributed to wheat production in Hebei Province. Moreover, temperature negatively influenced wheat production in Shandong Province, while rainfall contributed positively to wheat production. Further, the results of Granger causality reveal that climatic factors and other determinants significantly influenced wheat production in the selected provinces.

The Impact of Technological Progress and Climate Change on Food Crop Production: Evidence from Sichuan-China

Agriculture is an integral sector in China mandated to feed over 1.3 billion of its people and provide essential inputs for many industries. Sichuan, a central grain-producing province in Southwest China, is a significant supplier of cereals in the country. Yet, it is likely to be threatened by yield damages induced by climate change. Therefore, this study examines the effects of technological progress (via fertilizers usage and mechanization) and climatic changes (via temperature and precipitation) on the productivity of main food crops, such as rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays) in Sichuan province. We employ the generalized method of moments (GMM) model to analyze Sichuan provincial data from 1980 to 2018. Our findings show a positive nexus between fertilizers use and yields of main food crops. Only rice and maize yields are significantly improved by mechanization. Increased average temperature reduces rice and wheat yields significantly. Rainfall is unlikely to have a significant impact on agricultural production. The study suggests that the Chinese government should consider revising its strategies and policies to reduce the impact of climate change on food crop production and increase farmers' adaptive ability.

Modeling the Impact of Climatological Factors and Technological Revolution on Soybean Yield: Evidence from 13-Major Provinces of China

In recent years, the changing climate has become a major global concern, and it poses a higher threat to the agricultural sector around the world. Consequently, this study examines the impact of changing climate and technological progress on soybean yield in the 13 major provinces of China, and considers the role of agricultural credit, farming size, public investment, and power of agricultural machinery from 2000 to 2020. Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied to assess the long-run effect, while Dumitrescu and Hurlin's (2012) causality test is used to explore the short-run causalities among the studied variables. The results revealed that an increase in the annual mean temperature negatively and significantly affects soybean yield, while precipitation expressively helps augment soybean yield. Furthermore, technological factors such as chemical fertilizers accelerate soybean yield significantly, whereas pesticides negatively influence soybean yield. In addition, farming size, public investment, and power of agricultural machinery contribute remarkably to soybean yield. The causality results endorse that chemical fertilizers, pesticides used, agricultural credit, public investment, and power of agricultural machinery have bidirectional causality links with soybean yield. This study suggests several fruitful policy implications for sustainable soybean production in China.