The effect of climate change on cotton productivity - an empirical investigation in Pakistan

Abstract

Pakistan is the primary producer of cotton, which is an indispensable crop worldwide. The agriculture sector depends on the climate and may be susceptible to future climate changes, such as increasing temperature, heavy rainfall, droughts, and floods directly impacting cotton productivity. This study empirically investigates the relationship between climate change variables and non-climate change variables on cotton productivity in Pakistan. An econometric technique, the “autoregressive distributed lag model” (ARDL), was employed on time series data from 1970 to 2018 to explore the existence and nature of the relationship among variables. The findings indicated the presence of co-integration among variables which confirms the long-run relationship among the variables. At the same time, the empirical results revealed that increases in temperature and rainfall positively affected cotton productivity. However, CO2 harms cotton productivity. Moreover, infrastructural changes positively affect cotton productivity in both the long and short run, while labor is negatively related to productivity. The area, fertilizer, and seed consumption showed a significant positive effect on cotton productivity. We employed the dynamic ordinary least squares (OLS), co-integration regression estimation, and the series test to validate the robustness of the finding. The finding of this study urges policymakers to devise a comprehensive policy to mitigate the adverse effect of climate change and upsurge water conservation. Furthermore, it is imperative to adopt environmentally friendly production inputs and modern techniques, which helps to gain sustainable cotton productivity. To conclude, the cotton crop is significantly affected by climate change subject to the region. Although this study analyzed the Pakistan case, the model can be generalized to all the developing countries