Abstract
Agriculture Productivity is an important measure of the agricultural performance in developing countries, which measures the quantity of output that can be produced from a given quantity of inputs. However, agriculture output is affected by the rainfall and temperature. In the literature on emerging economies, rainfall and temperature are found to have a significant impact on the agriculture productivity in different regions of the world. The goal of this study is to assess the impact of rainfall and temperature variations, as a result of climate change, on Pakistan’s agriculture output. Time series data from 1984 to 2019 is used to investigate this issue. An Autoregressive Distributed Lag (ARDL) model with Bound Testing Cointegration and Error Correction Model (ECM) are used to analyze the relationship between the variables of interest. Unit Root tests were used to check the stationarity of time series data which revealed that some variables are stationary I (0) while others are integrated at level 1. The findings of the study show that temperature increase has a positive and significant impact on agriculture productivity, both in the short and long run. Moreover, rainfall has a negative and significant impact on agriculture productivity in the short and long-run. The stability tests have confirmed the stability of the econometric model.
Keyword(s)
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