The linkage between fertilizer consumption and rice production: Empirical evidence from Pakistan

Abbas Ali Chandio; Yuansheng Jiang; Abdul Rehman; Rahman Dunya; Abbas Ali Chandio; Yuansheng Jiang; Abdul Rehman; Rahman Dunya

doi:10.3934/agrfood.2018.3.295

AIMS Agriculture and Food

2018, Volume 3, Issue 3: 295-305. doi: 10.3934/agrfood.2018.3.295

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Research article

The linkage between fertilizer consumption and rice production: Empirical evidence from Pakistan

1.
College of Economics, Sichuan Agricultural University, Chengdu, China
2.
Research Center of Agricultural-Rural-Peasants, Anhui University, Hefei, China
3.
College of Management, Sichuan Agricultural University Chengdu, China

Received: 31 March 2018 Accepted: 24 August 2018 Published: 08 December 2018

Rice is one of the most important staple foods for 70 percent of the population of the world. It is among the main cereal crops grown in different regions of Pakistan as food crop. Pakistan has very much potentials for growing the crop and the potential rice production sown area is estimated to be about 2724 thousand hectares. The purpose of this study is to examine the linkage between fertilizer consumption and rice production in Pakistan from 1984 to 2014. For checking the stationarity of the data, this study incorporated Augmented Dickey Fuller (ADF) and Phillips Perron (PP) unit root tests. Furthermore, the Johenson Co-integration test is used to detect the long-term relationship among the series. Likewise, on the basis of annual time series data the Autoregressive Distributed Lag (ARDL) model is employed to evaluate the impact of fertilizer consumption on the production of rice in Pakistan up to now. The results of ADF and PP unit root tests reveal that fertilizer consumption and water availability are integrated at I(0) whereas area and rice production are integrated at I(1). The empirical findings of Autoregressive Distributed Lag (ARDL) model indicate that area and fertilizer consumption for rice has a significant effect on the rice production in both short-run and long-run. In contrast, water availability has a significant effect on the rice production in the long-run but it was statistically insignificant in the short-run. The estimated equation remains stable from the period of 1984 to 2014 as showed by stability tests.
- Pakistan,
- fertilizer consumption,
- rice production,
- autoregressive distributed lag,
- co-integration
Citation: Abbas Ali Chandio, Yuansheng Jiang, Abdul Rehman, Rahman Dunya. The linkage between fertilizer consumption and rice production: Empirical evidence from Pakistan[J]. AIMS Agriculture and Food, 2018, 3(3): 295-305. doi: 10.3934/agrfood.2018.3.295

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Abstract

Rice is one of the most important staple foods for 70 percent of the population of the world. It is among the main cereal crops grown in different regions of Pakistan as food crop. Pakistan has very much potentials for growing the crop and the potential rice production sown area is estimated to be about 2724 thousand hectares. The purpose of this study is to examine the linkage between fertilizer consumption and rice production in Pakistan from 1984 to 2014. For checking the stationarity of the data, this study incorporated Augmented Dickey Fuller (ADF) and Phillips Perron (PP) unit root tests. Furthermore, the Johenson Co-integration test is used to detect the long-term relationship among the series. Likewise, on the basis of annual time series data the Autoregressive Distributed Lag (ARDL) model is employed to evaluate the impact of fertilizer consumption on the production of rice in Pakistan up to now. The results of ADF and PP unit root tests reveal that fertilizer consumption and water availability are integrated at I(0) whereas area and rice production are integrated at I(1). The empirical findings of Autoregressive Distributed Lag (ARDL) model indicate that area and fertilizer consumption for rice has a significant effect on the rice production in both short-run and long-run. In contrast, water availability has a significant effect on the rice production in the long-run but it was statistically insignificant in the short-run. The estimated equation remains stable from the period of 1984 to 2014 as showed by stability tests.

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