Testing long-run relationship between agricultural gross domestic product and fruits production: evidence from Pakistan

Abstract

This paper analyses the long-run relationship between agricultural gross domestic product (GDP) and fruits production of Pakistan’s economy over a period of 1961-2015 by employing Johansen and autoregressive distributed lag (ARDL) modern econometric technique. Three fruits were selected namely mango, apple and peach in this study. Augmented Dickey-Fuller and Phillips-Perron tests were used to check the data stationarity and conclude that the series are integrated of order one. The Johansen approach was applied to check the joint evolution of all the variables for co-integration. The Johansen test suggests that a long-run co-integration exists between agricultural GDP and fruits production. Results of the ARDL model (Bound test) detect the existence of long-run relationship between agricultural GDP and fruits production. The coefficient of the short-run form of ARDL model reveals that all the fruits have a positive impact on agricultural GDP. Moreover, the coefficients of the long-run form of ARDL model have apositive and significant influence on agricultural GDP of Pakistan. These results suggest that a 1% increase in mango, apple and peach production will increase agricultural GDP by 0.06%, 0.03% and 0.03% respectively. Finally, forecast error variance decomposition and impulse response function results depict that mango, apple and peach production significantly contributes to agricultural GDP in the case of Pakistan.

Asymmetric effects of cereal crops on agricultural economic growth: a case study of India

“…where AGDP, MP, RP, and WP indicate India's agricultural gross domestic product (AGDP), maize, rice, and wheat crop production, respectively, throughout a time period t. The long-run coefficients are denoted by β i , while the error term is denoted by µ t . This method was also used in related works by Khan et al (2019), Ahmad et al (2020), Ullah et al (2018), Liao and Baek (2020), and Kumar et al (2021b). Rewrite of Eq.…”

“…(Awokuse and Xie 2015;Oyakhilomen and Zibah 2014;Anwer et al 2015;Awoyemi et al 2017;Mohammed et al 2020). Some paper used different cereals crops, namely maize, wheat, rice, cotton by employing the ARDL model to examine the linear association between the independent and dependent variable (Mapfumo 2013;Rauf et al 2017;Ullah et al 2018). Lastly, Ali et al (2020) exhibited a different perspective by employing a nonlinear autoregressive distributed lag model to examine the long-run and short-run shock between cereals crops and Pakistan's agricultural gross domestic product.…”

Drought Prediction with Raw Satellite Imagery and Ensemble Supervised Machine Learning

“…These effects are far more severe in Pakistan, which is among the most vulnerable regions to drought given the enormous reliance on agriculture. In Pakistan, almost 43% of the national workforce is working in agriculture [9]. Prediction of drought is one of the most serious concerns of meteorologists so that various techniques are used to predict drought by different researchers.…”

Asymmetric Effects of Cereals Crops on Agricultural Economic Growth: A Case Study of India

“…(Awokuse and Xie, 2015;Oyakhilomen and Zibah, 2014;Anwer et al,2015;Awoyemi et al,2017;Mohammed et al,2020). Some paper used different cereals crops, namely maize, wheat, rice, cotton by employing the ADRL model to examine the linear association between the independent and dependent variable (Mapfumo,2013;Rehman and Jingdong,2017;Rauf et al, 2017;Ullah et al, 2018). Lastly, Ali et al (2020) exhibited a different perspective by employing a non-linear autoregressive distributed lag model to examine the long run and short-run shock between cereals crops and Pakistan's agricultural gross domestic product.…”