Abstract
This study used a quantile autoregressive distributed lag (QARDL) model to capture asymmetric impact of rainfall on food production in India. It was found that the coefficient corresponding to the rainfall in the QARDL increased till the 75th quantile and started decreasing thereafter, though it remained in the positive territory. Another interesting finding is that at the 90th quantile and above the coefficients of rainfall though remained positive was not statistically significant and therefore, the benefit of high rainfall on crop production was not conclusive. However, the impact of other determinants, such as fertilizer and pesticide consumption, is quite uniform over the whole range of the distribution of food grain production.
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Acknowledgments
Authors remain thankful to the editor and the anonymous referee for their thorough and collegiate review that has added considerable value to the work. Authors also benefited from the comments of the participants of the 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence held at Ahmedabad, India. Special thank is due to Arnab K. Laha, Pulak Ghosh, and Murari Mitra for their valauble suggestion helpful for improvement of the work.
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Pal, D., Mitra, S.K. Asymmetric impact of rainfall on India’s food grain production: evidence from quantile autoregressive distributed lag model. Theor Appl Climatol 131, 69–76 (2018). https://doi.org/10.1007/s00704-016-1942-3
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DOI: https://doi.org/10.1007/s00704-016-1942-3