A Statistical Study of the Determinants of Rice Crop Production in Pakistan. | [Pakistan Journal of Agricultural Research • 2020]

Author(s):

1. Muhammad Akbar Ali Shah: Department of Statistics, The Islamia University of Bahawalpur,Pakistan

2. Gamze Özel: Department of Statistics, Hacettepe University,Turkey

3. Christophe Chesneau: Department of Mathematics, LMNO, University of Caen,Caen,France

4. Muhammad Mohsin: Department of Geography, Govt. Degree College (Boys),Choti Zareen, D.G. Khan,Pakistan

5. Farrukh Jamal: Department of Statistics, Govt. S.A. Postgraduate College,Dera Nawab Sahib, Bahawalpur,Pakistan

6. Muhammad Faheem Bhatti: Department of Statistics, The Islamia University of Bahawalpur,Pakistan

Abstract:

| Rice is the third major and second main staple crop of Pakistan. The main objective of the current research is to discover the determinants of the rice production of Pakistan to improve the production and fulfill the increasing demand. The study conducted in district Lodhran (Punjab province) and 31 villages selected as samples randomly. Time series data collected from Crop Reporting Service (CRS) for the period of last 10 years (2005-2014) containing 516 cases and 14,964 observations. Two different multiple linear regression (MLR) models are applied to study the relationship between the yield of rice (dependent variable) and the various factors (independent variables) which are effecting the rice crop production. The Model I is based on monthly average temperature and humidity during crop period and Model II is based on average temperature and humidity during crop period. The factors effecting rice crop production are also tested. Durbin-Watson test is applied to measure the serial correlation in the residuals and variation inflation factor (VIF) is also applied to test the multicollinearity. The VIF values of independent variables in Model I indicate the presence of multicollinearity and Durbin-Watson test shows autocorrelation in Model I whereas Model II is recommended due to the better value of R² with Durbin-Watson test and found no pattern of multicollinearity. The three most important factors that afect the yield per acre in mounds (1 mound= 40 kg) are DAP and Urea Fertilizer and Disease attack respectively. Thus, Model II is acceptable for the estimation of rice yield not only for district Lodhran but also for the case of Pakistan.

Page(s): 97-105

DOI: 10.17582/journal.pjar/2020/33.1.97.105

Published: Journal: Pakistan Journal of Agricultural Research, Volume: 33, Issue: 1, Year: 2020

Keywords:

Rice production , DurbinWatson test , Multiple Linear Regression MLR , Variation Inflation Factor VIF

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