Sugar price determination in India: an econometric analysis

Malaiarasan, Umanath; Felix, K. Thomas; Paramasivam, R.; Balaji, S.J.

doi:10.5958/0974-0279.2019.00025.9

Cited by 1 publication

(1 citation statement)

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“…The sugar demand of the country is growing consistently with population growth. Without the contribution of efficient sugarcane production, meeting such a huge domestic demand for sugar is impossible and would have warranted massive sugar import (Malaiarasan et al, 2019). Production of sugarcane depends on the use and combination of inputs.…”

Section: Introductionmentioning

confidence: 99%

Technical efficiency of Indian farmers in sugarcane production- A panel stochastic frontier approach

Felix¹,

Umanath²,

Kumar³

et al. 2020

JEB

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Aim: To estimate the technical inefficiency of Indian farmers in sugarcane production. Methodology: Although various stochastic frontier models for panel data are available, six of them were considered for the study, which is frequently applied in empirical research. Based on the log likelihood ratio, results are interpreted only for kumbhakar, lien and hardaker (KLH) model. Results: Indian farm?s overall technical efficiency ranged from minimum 0.11 to maximum 0.93 with a mean value of 0.70, it means that with same resource based average sugarcane growers can increase their yield up to 23% and most technical inefficient grower can increase their yield up to 82% in order to achieve overall technical efficiency level (93%) of efficient fellow grower in study area. Though, Tamil Nadu has the highest overall technical efficiency score in sugarcane production (0.76), the negative growth rate indicates its decline in technical efficiency. Haryana has a negative growth rate in persistent, residual and overall technical efficiency in sugarcane production. Interpretation: Among the seven states, Uttaranchal showed the highest scope of improving the sugarcane yield with 36%, followed by Uttar Pradesh (34%), Haryana (33%), Maharashtra (30%), Karnataka (30%), Andhra Pradesh (25%) and Tamil Nadu (24%). Results of parameter estimates confirmed that area in hectare, machine usage in hours, seed quantity in kilograms, manure usage in quintals and total fertilizer usage in kilograms are significant and positively influence the sugarcane production. The coefficients of dummy for farm size reveals that medium and large sugarcane farms are less efficient compared to small farms. Similarly, the share of own machine-hours has a negative impact on sugarcane production. Based on the empirical results appropriate policy is suggested for the study.

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Section: Introductionmentioning

confidence: 99%