Gul Amber, Xiumin Wu, Chandio Abbas Ali, Rehman Abdul, Siyal Sajid Ali, Asare Isaac
College of Management, Sichuan Agricultural University, Chengdu, 611130, China.
College of Economics, Sichuan Agricultural University, Chengdu, 611130, China.
Environ Sci Pollut Res Int. 2022 May;29(21):31886-31900. doi: 10.1007/s11356-022-18541-3. Epub 2022 Jan 11.
The present study aims to investigate the effect of climatic and non-climatic factors on rice production by employing an annual time series data from the period of 1970 to 2018. The study employed an ARDL (Autoregressive Distributed Lag) approach, and the long-term equilibrium linkages between the variables have been discovered. Additionally, the study also used a regression model to determine the robustness for the authentication of results. The Fully Modified Ordinary Least Squares (FMOLS), Canonical Cointegration Regression (CCR) methods, and the VECM (Vector Error Correction Model) technique confirmed the long-run causal relationships amid the variables. The empirical results further revealed that climatic factors including annual temperature negatively affect the rice crop production, while carbon dioxide emission positively influenced via long-run. Similarly, non-climatic factors like area under rice crop, fertilizer consumption, labor force, and water availability affect the rice production positively in the long-run analysis. Finally, the pairwise Granger causality test revealed that both climatic and non-climatic variables had a substantial impact on rice yield in Pakistan. Based on the study's findings, the government and policy makers should formulate alleviation polices to tackle with harsh effects of climate change and consistent adoption of measures to secure overall agricultural production including rice crop because it is a country stable food.
本研究旨在利用1970年至2018年的年度时间序列数据，调查气候和非气候因素对水稻生产的影响。该研究采用了自回归分布滞后（ARDL）方法，并发现了变量之间的长期均衡联系。此外，该研究还使用回归模型来确定结果验证的稳健性。完全修正普通最小二乘法（FMOLS）、典型协整回归（CCR）方法和向量误差修正模型（VECM）技术证实了变量之间的长期因果关系。实证结果进一步表明，包括年温度在内的气候因素对水稻作物产量有负面影响，而二氧化碳排放从长期来看有积极影响。同样，在长期分析中，诸如水稻作物种植面积、化肥消费量、劳动力和水资源可利用量等非气候因素对水稻生产有积极影响。最后，成对格兰杰因果检验表明，气候和非气候变量对巴基斯坦的水稻产量都有重大影响。基于该研究的结果，政府和政策制定者应制定缓解政策，以应对气候变化的严峻影响，并持续采取措施确保包括水稻作物在内的整体农业生产，因为水稻是该国的稳定粮食。
