Impact of Climate Change and Technological Advancement on Cotton Production: Evidence from Xinjiang Region, China | ||
| Journal of Agricultural Science and Technology | ||
| Article 18, Volume 24, Issue 6, 2022, Pages 1519-1531 PDF (1.07 M) | ||
| Document Type: Original Research | ||
| DOI: 10.52547/jast.24.6.1519 | ||
| Authors | ||
| M. Umer Arshad* 1; Z. Yunfeng1; S. Hanif2; F. Fatima3 | ||
| 1Inner Mongolia Honder College Arts and Sciences, Hohhot, China. | ||
| 2School of Economics and Management, Beijing Jiaotong University, Beijing, China. | ||
| 3Department of Botany, The University of Agriculture, Faisalabad, Pakistan. | ||
| Abstract | ||
| China is the largest producer of cotton crop, followed by the United States of America. China's 52% cotton is produced in Xinjiang Region. The agricultural sector depends on the climate, and it is substantially susceptible to future climate changes. Climate factors directly affect cotton production and, therefore, assessing the influence of these factors on the cotton output is imperative. This study empirically investigated the relationship between climate and non-climate variables on Xinjiang Region's cotton production over the last three decades. To this end, an econometric technique was employed and the "Autoregressive Distributed Lag Model" (ARDL) was used to analyze the long-run and short-run relation between the selected variables. Empirical results revealed that a 1% decrease in average temperature, labor force, and rainfall could decrease cotton production by 0.18, 1.94, and 0.18%, respectively, due to the significant negative relation. However, this study depicted 1% rise in average temperature, technological changes, and the cultivated area will increase cotton production by 0.07, 0.05, and 0.23%, respectively. In conclusion, the regional climate changes significantly affect cotton crop. Although the study analyzed the data from XUAR Region, this model can be applied to all developing countries. This research helps the policymakers and the respective government department to introduce, promote, and subsidize environment-friendly production inputs and make the long-term plan for farmers and stakeholders to educate, spread awareness, and help to adopt new skills to gain sustainable regional cotton productivity. | ||
| Keywords | ||
| Autoregressive Distributed Lag model; Regional cotton production; Xinjiang cotton | ||
| References | ||
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