Efficiency and its determinants in India’s textile firms using two stage bootstrap DEA and tobit model

India’s textile industry stands at a crossroads, poised between immense potential and significant challenges. A longstanding pillar of the economy, textiles contribute substantially to employment, exports, and industrial output. Despite its rich heritage and vast production capacity, the industry grapples with hurdles that threaten its global competitiveness. The country’s trade position in textiles has been increasingly challenged by nations like China, Vietnam, Bangladesh, and Pakistan in cotton textile which hold competitive advantages in lower production costs and supply chains. China dominates the global market, but other low-cost countries are poised to catch up with targeted policies. India’s textile industry has a natural competitive edge, bolstered by a robust multi-fibre base and an abundance of skilled, cost-effective labour. The end of the Multi-Fibre Agreement was expected to boost India’s textile exports by removing quotas in developed countries, but this alone has not been enough. Several factors are influencing growth, and addressing them promptly is crucial to stay ahead of the competition. This study presents a comprehensive firm-level analysis of the Indian textile industry, examining efficiency trends from 2011 to 12 to 2020-21. Using panel data for 2011-12, 2016-17, and 2020-21, bootstrap Data Envelopment Analysis (DEA) is applied to assess technical and scale efficiency across 647 textile firms, categorized by industrial classification. The analysis is based on data from the CMIE Prowess database. The study also uses a tobit regression model to identify determinants of technical efficiency. Overall, the efficiency score suggests that the current condition of the textile industry in India is characterised by persistently low technical efficiency and wide disparities in firm performance. The findings imply that the primary source of inefficiency lies in weak managerial practices, inadequate utilisation of inputs, and limited adoption of advanced technology rather than solely in suboptimal scale of operations.