This article attempt to answer the question "whether the dynamic relationship between climate change and rice productivity is symmetrical or asymmetrical" using data from 1990-2017 in India. First, we test the symmetrical and long-run dynamic relationship using the Autoregressive Distributed Lags (ARDL) model and test the asymmetrical and cointegration relationship based on Nonlinear Auto-Regressive Distributed Lag (NARDL) technique. The results of the ARDL model indicates that no symmetrical relationship between the variables in long-run. Whereas outcomes of the NARDL bound test reveal that there is long-run asymmetrical impact of climate change on rice productivity. The positive and negative shock of climate change has affected the rice productivity by different magnitude in India. The Wald statistics confirm asymmetric relationship between rice productivity and climate change in the long-run while only short-run asymmetrical relationships exist between rainfall and rice productivity in India.
Furthermore, dynamic multipliers indicate that negative component of rainfall and temperature has a dominant effect over the positive component on rice productivity. To the best of the author's knowledge, no studies have been done to assess both symmetrical and asymmetrical dynamic relationships between climate change and rice productivity using ARDL and NARDL cointegration approaches in India's context. This study will help frame the environmental policies and strategy to cope with climate change in India's agriculture productivity.