Factorization of agricultural production in India: A quantile regression approach
2020
KURIACHEN, PHILIP | SEN, BISWAJIT | V, PRAVEEN K
未知. A study was undertaken at the ICAR-Indian Agricultural Research Institute, New Delhi (2017) to readdress the economic productivity of agricultural system in India with in-depth scrutiny of productivity differentials. Secondary data for the period 1999–2013 from various published sources were used for analyzing the drivers of agricultural production. It was observed that, overall economic productivity of agriculture is nearly ` 83275/ha in case of India which disperse widely over the states with standard deviation of ` 36935/ha. This variation is subjected to a broad set of ecological, socio-economic and other institutional factors. A model of nonparametric regression, viz. quantile regression approach was used to discern and measure the role of identified factors in determining agricultural economic productivity. The study provides a deeper insight in addressing spatially distributed productivity gap further. It was observed that market concentration, Wholesale price index of high value crops and land fragmentation are the decisive factors for explaining productivity differentials across the regions.
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