Simulating and resilience in cotton productivity due to climate change of Sindh, Pakistan | ||
| Archives of Agriculture Sciences Journal | ||
| Article 11, Volume 1, Issue 1, April 2018, Pages 142-153 PDF (423.51 K) | ||
| Document Type: Research article | ||
| DOI: 10.21608/aasj.2018.23578 | ||
| Authors | ||
| M. Joyo* 1; N. Ram2 | ||
| 1Department of Agricultural Economics, Sindh Agriculture University, Tandojam, Pakistan | ||
| 2Department of Economics, University of Sindh, Jamshoro, Pakistan | ||
| Abstract | ||
| The present research is to primarily focused on to meet the upcoming dilemma due to rapid shifting in the climate pattern specifically in the south Asian region where most of the under developing countries and they secure their essential part of routine life need that broadly is Agriculture. Secondly, to estimation of dependent variable i.e. most probably the cause of climate change calamity are temperature and precipitation that directly effect on Cotton productivity due to single Pakistan's export earning source and that share was almost 71 percent in the export base products. Similarly to check the resilience and simulating strategies for the concern of climate change in Sindh because the most effected province of Pakistan due to Climate Change since last decade. The results show that the first shock of (VAR) resulted average mean temperature in the period one somewhat increased crop productivity to 07.879032 points whereas; after next shock decreases in productivity to -10.7116 units, in sequence another third shock decreases further productivity up to (negative) -14.8236 units finally remaining shocks were also makes decreasingly going to negative impact on crop productivity. The time series data of last twenty (20) years (1994-95 to 2014-15) has been processed by using Vector Auto Regression (VAR) model. VAR study model estimation with lag 2 that Akaike AIC and Schwarz Sc for data using lag 2 is smaller than lag 3, lag 4 and lag 5, so the lower values Akaike AIC 7.058830 and Schwarz Sc 7.491843 for lag 2 make the model more fitted. It was observed comprehensively that the implication of climate change is the key threat to food security and its growth. The predicted values overall crop production and productivity/yield growth rate will be reported as -1.673 and -0.587. Likewise, the parameters of the study viz; β0, β1, β2, β3 describes the dependent study variable and its change per unit for the independent study variables (Production practices) were damaged due to shifting weather trend. In addition projected climate change factors that affecting on cotton indicated that the higher temperature and unexpected shifting of weather activities such as; unwanted rainfall, higher temperature has impact badly on production practices and resultantly the productivity goes into uncertain due to climate change. Overall the 01°C to 01.8°C temperature will be increase and 10% to 18% precipitation will be decrease in the upcoming years up to 2050. | ||
| Keywords | ||
| Climate Change; Cotton; productivity; vector autoregression; Sindh | ||
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