Tracking the effect of climatic and non-climatic elements on rice production in Pakistan using the ARDL approach.

The present study aims to investigate the effect of climatic and non-climatic factors on rice production by employing an annual time series data from the period of 1970 to 2018. The study employed an ARDL (Autoregressive Distributed Lag) approach, and the long-term equilibrium linkages between the variables have been discovered. Additionally, the study also used a regression model to determine the robustness for the authentication of results.

How climate change is impacting the major yield crops of Pakistan? an exploration from long- and short-run estimation.

This research attempts to evaluate the linkage among climatic change factors such as average temperature and rainfall patterns and non-climatic factors such as the area under major yield crops, fertilizer consumption, and formal credit on major food crop yield from 1985 to 2016 in Pakistan. For the first step, we checked the stationarity of the series by utilizing the unit root tests. An autoregressive distributed lag (ARDL) model was employed to identify the linkages between variables after verifying the properties over a specific period of time.