Productive Performance of Indian Food Manufacturing Industry: A Sub-Sectoral Analysis in a Stochastic Frontier Framework

Abstract

This article examines the productive performance of the Indian food manufacturing industry measured in terms of technical efficiency (TE) of its 13 sub-sectors under the organised sector. For estimating their TE, it makes the use of the Cobb–Douglas production technology with the truncated normal distribution of stochastic inefficiency term ( Stevenson, 1980 ) via Jondrow et al. (1982) estimator of cross-sectional data. Data are sourced from the Annual Survey of Industries, 2017–2018. The results show that this industry, as a whole, observed 92% TE in 2017–2018, but among its sub-sectors, it varied between 100% and 74%, that is, they exhibited differential productive performance. Modern sub-sectors, such as fruits and vegetables, edible oils, bakery and beverage products, realised frontier-level efficiency, while sugar and starch products were identified as marginal performers in the industry. The robustness of the results is confirmed by the non-parametric estimates of TE from the data envelopment analysis. The results are expected to be useful in framing specific policies for these two different groups of food processors. In the case of sub-sectors performing below the frontier, policy actions aiming at pure technical and scale efficiencies, such as capacity building, research, skill programmes, and extension activities, need to be operationalised, while for sub-sectors performing at the frontier, only technological progress needs to be prioritised.