Agricultural machinery, irrigation systems and food grains: A symmetric novel analysis

Abstract

Agriculture provides a living for a huge proportion of Pakistan’s people, making it one of the country’s most vital sectors. In this paper, we investigated the impact of irrigation sources (IS), agricultural machinery (AM), total food grains (TFG), and total cropped area (TCA) on the agriculture sector of Pakistan by using the annual data from 1991 to 2020. Using the symmetric (ARDL) approach, short-run and long-run estimations were employed to illustrate the connection between variables. A unidirectional linkage for the variables was checked through the VECM (Vector Error Correction Model) based Granger causality that is extracted. Further, FMOLS (Fully Modified Least Squares) and DOLS (Dyngamic Least Squares) techniques were also employed to encounter the robustness of the analysis. Results during the short-run and long-run show that the variables total irrigation sources (IS), agriculture machinery (AM), and total food grains (TFG) show the constructive impact on the agriculture sector of Pakistan, while the variable total cropped area (TCA) demonstrate the negative impact on the agriculture sector. Similarly, the consequences of VECM-based Granger causality show that all variables have unidirectional linkages. Furthermore, the findings of the FMOLS and DOLS explore that the variables irrigation sources (IS), agricultural machinery (AM), and total food grains (TFG) show the productive impact on the agriculture sector of Pakistan. But, unfortunately, the variable total cropped area (TCA) demonstrates the negative impact on the agriculture sector. No doubt, the agricultural sector significantly contributes to the growth of any economy. The government of Pakistan has to adopt new policies and plans that place a greater emphasis on the country’s irrigation network and arable land in order to increase agricultural output.