This study attempts to estimate the effects of climate change variables, such as average temperature, CO2 emissions and average rainfall, on cereal production in Malaysia from 1969 to 2018. After preliminary tests on time series data, we employed a novel autoregressive distributed lag (ARDL) method known as the dynamic ARDL simulations technique. The results showed that a long-run co-integration relationship exists between cereal production and climatic and non-climatic factors. All climate variables have a negative impact on cereal yield, while energy consumption and cultivated land have a positive effect on cereal yield in the short- and long-run. Granger causality analyses also showed that a unidirectional causality link exists between rainfall and temperature with cereal production and between CO2 emissions and cereal production. Energy consumption, as a proxy for technology, has a one-way Granger cause with cereal production. The results of the dynamic ARDL simulations suggest that cereal yield was most sensitive to CO2 emissions, rainfall and temperature. In the long run, a 1% increase in temperature is associated with a 2.87% and 3.52% decrease in general and predicted estimates of cereal production, respectively. The dynamic ARDL simulations methodology provides a better understanding of the variability of cereal production in Malaysia as a result of climate change.
