CCEA approves amendments to 'Toll Operate Transfer' model for national highways
The Cabinet Committee on Economic Affairs (CCEA) has given its approval to the amendments proposed in the TOT model by the National Highways Authority of India (NHAI), Finance Minister Nirmala Sitharaman said.
Public-funded national highway (NH) projects that are operational and have toll revenue generation history of one year after the commercial operations date (COD) will be monetised through the TOT model, she said after the CCEA meeting.
The monetisation will be subject to approval of the competent authority in the Ministry of Road Transport and Highways/NHAI on a case to case basis, she added.
The corpus generated from proceeds of such project monetisation will be used by the government to meet its fund requirements regarding future development and O&M (operations and maintenance) of highways in the country.
The model would facilitate efficient toll realisation through private sector.
Around 75 operational NH projects have been identified for potential monetisation using the TOT model, and bundled into 10 separate bids to attract economics of scale for the private sector.
This approval would ensure a wider set of assets for monetisation and providing a more attractive model for the investors.
Further, the fund generated from such monetisation will be utilised for development/O&M of highways in the country, which would benefit highway users throughout the country.
The approved TOT model authorised NHAI to monetise public funded NH projects, such as EPC/BOT (Annuity) projects, which are operational and have a proven toll collection history of at least two years.
The approved TOT model provides for a fixed 30-year concession period, she said.
NHAI has already monetised one bundle of projects under TOT Model, generating a revenue of Rs 9,681.50 crore for the government.
However, the second bundle saw deviation in the market valuation of assets from NHAI's valuation. NHAI has conducted several rounds of discussions with the private sector to reduce uncertainty in the model. DP SR MKJ