Toll Road PPPs Identifying Mitigating and Managing Traffic

Toll Road PPPs: Identifying, Mitigating and Managing Traffic Risk OLC Webinar 31 st October 2017

• • Forecasting and Traffic risk Where does it come from? How can it be reduced? How can it be managed? 2

The Importance of Forecasting • Forecasting is vital for all fields of science, social science and human endeavor • Forecasting is particularly vital for infrastructure – forecasts allow us to plan, design, dimension and finance infrastructure • BUT the world is becoming more complex and interdependent and the human skill of forecasting is becoming more difficult • This is a particular problem when forecasts are relied upon to raise scarce public and private capital for infrastructure as is often the case in PPP projects • Toll road PPPs are the enfant terrible in this respect with a history of project failures resulting from inaccurate financing TEXAS TOLL-ROAD OPERATOR FILES FOR BANKRUPTCY Wall Street Journal, March 2 nd 2016 AUSTRALIA: ANOTHER TOLL ROAD GOES BANKRUPT The Newspaper. com, SPANISH COURT REJECTS STATE BAILOUT FOR BANKRUPT MOTORWAYS REUTERS, FEBRUARY 26 TH 2015

What is Traffic Risk? • Where demand revenue for an infrastructure project is over-estimated • Has led to financial distress through defaults, bankruptcies, renegotiations and government bail outs • Recurring issue in transport projects (particularly toll road PPPs) • Only 1 of 14 US toll roads studied by JP Morgan (1997) exceeded original revenue forecasts • On average, actual traffic was 60% of the forecast • Standard & Poors (2005) found actual traffic averaged 77% of forecast levels in a study of 104 international toll roads

The Traffic Forecasting Process • Forecasts can be produced by various project parties • Typically developed using a Travel Demand Model (TDM) • TDM is the forecasting base which replicates existing travel demand road network • Consists of trip matrix, network and key behavioral parameters • New projects are inserted into this model to predict how travel changes into the future

• • Forecasting and traffic risk? Where does it come from? How can it be reduced? How can it be managed? 6

Where does traffic risk come from? It’s part of the human condition – 3 key sources • Error: our technical limitations in understanding the current demand for travel • Uncertainty: our imperfect knowledge of the future • Bias: our pursuit of incentives – Optimism bias – Strategic Misrepresentation – The Winner’s Curse Example of Traffic Risk in Road Traffic Forecasting

• • Forecasting and traffic risk? Where does it come from? How can it be reduced? How can it be managed? 8

How can it be reduced? Error Uncertainty Bias Better Modeling Sensible Long-Range Better Alignment of Forecasting and Stable Policy Incentives Environment - - - Deep data collection to understand the existing/base market for a project Long-term monitoring of traffic trends Adhere to industry standards in traffic modeling Focus on willingness to pay, bring in specialist expertise - - Realism in forecasting assumptions Stability in policy environment so as to not threaten the competitive position of the project (e. g. toll/tariff policy) Be explicit on ramp-up forecasts and time period Sensitivity test key errors to understand size of risk -Set a benchmark/reference case forecast by undertaking high quality public sector demand studies -Independent review/ benchmarking of demand studies -Provide base models to bidders -Encourage due diligence -Penalize aggressive forecasting in bid evaluation -Ensure concession agreement is robust BETTER PROJECT PREPARATION & STRUCTURING

• • Forecasting and traffic risk? Where does it come from? How can it be reduced? How can it be managed? 10

How can it be managed? : Risk and Reward • Traffic risk can never be fully eliminated • The question of how to manage remaining risk depends on: – The underlying profitability/cost recovery of the project (e. g. NPV) – The impact of downside risk • Generally only government has the control and financial resources to manage high risk/low profitable projects Options for managing demand risk in toll road projects

Measuring Risk and Reward STEP 1 – BUILD A FINANCIAL MODEL OF THE PROJECT STEP 2 – SCENARIO TEST TRAFFIC AND THE FINANCIAL IMPACT

Key Takeaways • Error can be reduced through better data collection and modeling • Uncertainty can be reduced by sensible long-range forecasting and creating a stable policy environment • Bias can be reduced through better alignment of incentives in the bidding process • Residual traffic risk can be managed through careful project structuring that considers risk/reward tradeoffs • Governments should hire experienced technical and transaction advisors to support the due diligence, structuring and procurement of projects 13

Thank you! Click Here for link to the new GIF/PPIAF Publication on Traffic Risk 14