Assessment of the impact of climate change on the productivity of cotton: empirical evidence from cotton zone, southern Punjab, Pakistan

Shabbir Ahmad, S. Akhtar, Shahbaz Bhatti, Shakeel Imran, M. S. Akhtar, Ghulam Mustafa, A. R. Aslam, Chaoqun Liu, Sidra Noreen, M. Khan
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Abstract

Climate change is one of the venerable factors of the environment. The climate of Punjab is changing over time due to global warming, increasing temperature, melting of glaciers, and changes in the rainfall pattern. Cotton crop is very sensitive and risky to climate change and intensive inputs and huge investment is required for the production of cotton. The research aims to investigate the impact of climate change on the productivity of cotton. The Secondary data was collected from meteorological departments. The general production function that will be used for the analysis where Y is cotton production per hectare, Cl is the vector of climatic indicators including temperature, humidity, and precipitation while NCI is the vector of non-climatic indicators such as fertilizer area under cotton and technological change. An autoregressive distributed lag (ARDL) approach to co-integration was applied for the estimation of long-run relationships and a short-run relationship error correction model was used. For the stability of model CUSUM and CUSUM Q test was applied. ARIMA model was used for forecasting whereas regression analysis was used for impact analysis. Evolving and disseminating cotton varieties having adaptation to climate change should be the focus of future research and development. Improving the practices of farm management, developing awareness among the farmers about climate change, and strengthening the extension department are some measures to be taken for the adaptation to climate change in the cotton zone.
气候变化对棉花生产力影响的评估:来自巴基斯坦旁遮普南部棉花区的经验证据
气候变化是环境的重要因素之一。由于全球变暖、气温升高、冰川融化和降雨模式的变化,旁遮普的气候正在发生变化。棉花作物对气候变化非常敏感和危险,棉花生产投入密集,投资巨大。该研究旨在调查气候变化对棉花生产力的影响。二级数据从气象部门收集。用于分析的一般生产函数,其中Y是每公顷棉花产量,Cl是包括温度、湿度和降水在内的气候指标的矢量,而NCI是棉花施肥面积和技术变化等非气候指标的矢量。采用自回归分布滞后(ARDL)协整方法对长期关系进行估计,并采用短期关系误差修正模型。对模型的稳定性进行了CUSUM和CUSUM Q检验。预测采用ARIMA模型,影响分析采用回归分析。培育和推广适应气候变化的棉花品种应成为今后研究和开发的重点。改进农场管理做法,提高农民对气候变化的认识,加强推广部门的工作,是棉区适应气候变化的措施。
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