An Application of Stochastic Nonparametric Envelopment of Data to Estimate the Efficiency of Rice Milling Industry in Sri Lanka

Abstract

The Rice milling industry is the biggest agro-based processing industry in Sri Lanka which convert the paddy into a consumable form. The present study utilized the StoNED method to estimate the technical efficiency (TE) of the rice milling industry in the Ampara district. The data of rice mill’s inputs, outputs, cost of production, and availability of modern machinery were mainly collected from 102 randomly selected commercial rice mills with aid of a structured questionnaire. The significant factors that influence the TE of rice milling were estimated by employing Tobit regression analysis. The results of the TE indicated that this industry achieved more than 90% efficiency in rice milling with productive operational size. The estimated TE scores by input-output and cost functions were significantly (p<0.05) different. The empirical results reveal that the experience of owners and labours in rice milling, availability of paddy dryers, weighing bridge, parboiling units, auto paddy feeders, paddy separators, and own transports were the significant (p<0.05) factors that impacted the efficiency of producing rice. The present study recommends that providing practical oriented training and increasing capital investment by rice millers or providing credit facilities to implement modern processing units would improve the TE of rice mills.

J Bangladesh Agril Univ 23(2): 222-230, 2025