India`s logistics cost estimated at 7.97% of GDP in 2023-24: DPIIT report
The Department for Promotion of Industry and Internal Trade (DPIIT) in its latest report has said that India’s logistics cost is estimated at 7.97 per cent of country’s gross domestic product (GDP) in 2023-24. Estimates derived for the previous five years showed that the pace of growth in the logistics cost is gradually slowing down. It pointed that several initiatives such as PM Gati Shakti National Master Plan, dedicated freight corridors, Sagarmala project, integrated check posts, and development of the unified logistics interface platform, may have contributed in reducing the growth pace of logistics cost.
The report highlighted that rail logistics emerged as a cost-efficient mode, with an average cost of Rs 1.96 per tonne per km, which is significantly lower than road transport at Rs 11.03 per tonne per km, in cases where the first/last mile of the consignment is not taken into consideration. It noted that the air transportation is the most expensive mode of freight transportation despite being the fastest. The average logistic cost for air transportation is Rs 72 per tonne per km which largely limits its use to high-value, time-sensitive commodities. Meanwhile, citing a report, it said that logistics costs in Indonesia were relatively high at 24 per cent of GDP, while in South Korea they were much lower at around 8 per cent. In 2023, China estimated its logistics costs as 14.4 per cent of its GDP.
Earlier, a report on Assessment of Logistics Cost in India was launched by Commerce and Industry Minister Piyush Goyal. With this, the country has now a comprehensive and scientifically derived estimate of logistics costs. The report provides a comprehensive framework by capturing logistics costs across different transport modes, product categories, and firm sizes. The development is important as until now, logistics costs in India were often misrepresented, with commonly cited figures of 13-14 per cent of GDP derived from external studies or partial datasets. This led to inconsistent estimates, causing confusion among policymakers and global stakeholders.
