Conducting Traffic And Demand Studies

When To Use

• Reviewing an independent traffic consultant's demand forecast for a toll road, managed lane, bridge, or tunnel concession
• Evaluating passenger or cargo throughput projections for airport or port financings
• Stress-testing revenue assumptions in a P3/PPP financial model prior to financial close
• Assessing ramp-up risk during construction-to-operations transition
• Comparing competing demand studies submitted by sponsor vs. lender's independent engineer (IE)

Inputs To Gather

• Traffic/demand study report from the independent traffic consultant (e.g., Steer, CDM Smith, AECOM)
• Base-case financial model with revenue line items linked to volume assumptions
• Socioeconomic data inputs used in the model (population growth, employment, GDP, vehicle registrations)
• Network and route assumptions — competing facilities, planned capacity additions, toll/tariff schedules
• Historical traffic data (if brownfield) — at least 5 years of monthly volumes by vehicle class or passenger type
• Concession/PPP agreement sections on toll escalation, revenue sharing, and minimum traffic guarantees
• Independent engineer report and any lender technical advisor commentary on the demand study
• Comparable asset benchmarks — ramp-up curves and mature-year volumes from similar facilities [VERIFY jurisdiction-specific data availability]

Workflow

1. Validate methodology and model structure

   • Confirm the demand model type (four-step transport model, stated-preference survey, gravity model, econometric regression) and whether it is appropriate for the asset class
   • Check that the model's zone system, network coding, and assignment algorithm are consistent with the study area
   • For airports: verify air traffic movement forecasts use unconstrained demand adjusted for capacity constraints
   • For ports: confirm TEU/tonnage projections account for hinterland competition and shipping route shifts

2. Audit socioeconomic assumptions

   • Compare population and employment growth rates against independent government or third-party forecasts (e.g., census bureau, state demographer, Woods & Poole)
   • Assess whether GDP elasticity assumptions are within accepted ranges for the asset type (typically 0.8–1.2 for toll roads, 1.5–2.5 for airports) [VERIFY against current industry benchmarks]
   • Flag any assumption that deviates materially from the IE's independent view

3. Evaluate ramp-up profile

   • For greenfield assets, benchmark the ramp-up curve against comparable facilities — typical toll road ramp-up is 3–5 years to reach stabilized demand
   • Assess whether the study accounts for induced demand, mode shift, and traveler learning curves
   • Check that Year 1 volumes reflect realistic day-one capture, not annualized mature-year demand

4. Test toll/tariff sensitivity

   • Verify price elasticity values used in the model (typical range: −0.1 to −0.4 for toll roads) [VERIFY asset-specific elasticity ranges]
   • Confirm that toll escalation assumptions (CPI-linked, fixed schedule, dynamic pricing) match the concession agreement
   • Run or review scenarios with +/−20% volume variance and corresponding revenue impact

5. Perform scenario and downside analysis

   • Base case: consultant's central forecast
   • Rating agency case: typically 70–80% of base-case volumes (S&P/Moody's/Fitch methodology) [VERIFY current rating agency haircut conventions]
   • Bankable case / P90: downside used for debt sizing, often 80–90% of base
   • Stress case: recession scenario with GDP contraction and demand drop of 20–30%
   • Calculate DSCR under each scenario and confirm covenant compliance

6. Cross-check against comparable assets

   • Compile volume data from comparable toll roads, airports, or ports at similar stages of maturity
   • Identify whether the study's forecasts sit within the reasonable range of comparables
   • Flag outlier assumptions (e.g., per-capita trip rates significantly above peer facilities)

7. Assess independent engineer and lender advisor positions

   • Summarize the IE's haircuts or adjustments to the sponsor's traffic study
   • Note any unresolved disagreements between the traffic consultant and the IE
   • Identify conditions precedent tied to traffic study acceptance

Output

• Demand Study Review Memo containing:
  • Executive summary of forecast reasonableness (supportable / conditionally supportable / not supportable)
  • Methodology assessment with identified strengths and weaknesses
  • Socioeconomic assumption comparison table (study vs. independent sources)
  • Ramp-up benchmarking chart against comparable assets
  • Scenario matrix: volumes, revenues, and DSCRs across base/downside/stress cases
  • Elasticity sensitivity table showing revenue impact of toll/tariff changes
  • Risk register of key demand-side risks (competing routes, policy changes, autonomous vehicles, remote work trends)
  • Recommendations for structuring protections (reserve accounts, minimum revenue guarantees, traffic band mechanisms)

Quality Checks

• All socioeconomic inputs are cross-referenced against at least two independent data sources
• Elasticity values fall within published ranges for the asset class; outliers are justified or flagged with [VERIFY]
• Ramp-up assumptions are benchmarked against at least three comparable facilities
• DSCR calculations under the rating agency case confirm the project meets minimum coverage thresholds (typically 1.20x–1.40x for investment-grade toll roads) [VERIFY lender/rating agency specific thresholds]
• The financial model's revenue line items reconcile to the traffic study's volume and toll/tariff outputs
• Competing facility analysis reflects committed and funded projects, not speculative proposals
• Any assumption inherited from the sponsor without independent verification is explicitly marked