Bus fares from journeys

The model prices supplied person-level local-bus journeys from 2024 onwards. person_bus_fare_spending sums London and other-local-bus spending; bus_fare_spending sums it across household members. These outputs describe spending. transport_consumption already includes bus spending, so consumers must not add it to the consumption total again. This implementation does not change transport consumption, disposable income or government subsidy totals.

Inputs and fallback¶

The Microcosm nts_bus_travel stage supplies bus_in_london_trips, other_local_bus_trips, their sum local_bus_trips, bus_pass_eligible and local_bus_single_fare_share at Person level. Trips are annual quantities. A supplied zero counts as journey data. A cached default does not. If only local_bus_trips is supplied, London residents’ trips use the London series and other residents’ trips use the other-local-bus series. When either split series is supplied, that split takes precedence and the absent series is zero. Supply consistent splits for cross-boundary travel.

The model treats a person flagged bus_pass_eligible as travelling free, matching Microcosm’s pricing assumption. The dataset owns that eligibility flag; the model does not infer concessionary eligibility from age or change it when a concessionary scheme is reformed. Supply bus_pass_eligible alongside journey inputs, including in household calculators; an omitted flag defaults to false and the person pays fares even if eligible for a statutory concession. For fare-paying passengers, local_bus_single_fare_share is the share of boardings bought as singles, bounded to [0, 1]. Its fallback is 0.70, the 2024 NTS other-local-bus estimate. An optional local_bus_uncapped_single_fare overrides the representative uncapped fare described below. Negative quantities and fares price at zero.

On loading a UK Simulation, a supplied household bus_fare_spending moves to bus_fare_spending_reported. The stored total therefore cannot freeze the journey formula in a reform. Without journey inputs, the model retains this reported total and allocates it using fare_allocation_weight_by_age. Reported totals retain CPI uprating. Wales and unknown regions retain the reported total even when journey inputs exist, following Microcosm’s decision to leave areas without published receipts unpriced. Before 2024 the model also uses this legacy route. Direct core/YAML tests can still override the household output explicitly.

Published price benchmark¶

Microcosm prices journeys using FY2024–25 published facts. The model uses the same inputs. For each area, receipts R, boardings B, concessionary boardings C, annual trips per resident T and population P give:

• Fare-paying yield per boarding: y = R / (B - C).

• Boardings per resident trip: k = B / (T * P).

Sources: DfT BUS01 and BUS05i, NTS0705a, Scottish Transport Statistics 2025, tables 2.2a and 2.8, NI Public Transport Statistics 2024–25, figures 3, 4 and 6, and Microcosm’s fact extraction and pricing implementation. Population denominators use ONS mid-2024 estimates. London uses all English residents because non-residents also travel there. Scotland and Northern Ireland use the English other-local-bus trip rate as a proxy, as Microcosm does. These translations include interchanges and differences between operator boardings and resident trips; they are not counts of legs for a known trip.

Caps and the uncapped counterfactual¶

gov.dft.bus.fares.cap records the national cap on participating single-ticket services in England outside London: £2 from January 2023, £3 from January 2025, and £2 from January through December 2027. After December 2027 it is infinite, representing the end of the announced scheme. These dates follow the DfT evaluation, £3 scheme guidance and 2027 announcement. The cap does not affect the London series, Scottish or Northern Irish fares. England outside London uses a representative participating-service assumption; route-level participation and local lower caps require caller-supplied fares.

The published yield already includes ticket discounts and the benchmark cap. For an English fare-paying person’s other-local-bus boardings, the model uses:

current_yield = max(0, benchmark_yield + single_share *
                   (annual_min(uncapped_fare, current_cap) -
                    annual_min(uncapped_fare, reference_cap)))
spending = trips * boardings_per_trip * current_yield

annual_min caps the fare in each date interval, then weights the intervals from 6 April to 5 April, assuming uniform journeys through the year. It does not cap a fare using the average cap. Both fares and reference_fares preserve calendar dates. reference_year is 2024 and reference_fares holds the benchmark schedule fixed when the policy cap changes. The source receipts use 1 April to 31 March; this approximation treats them as the corresponding model year’s benchmark. Annual Scenario changes apply to the full model fiscal year.

The default uncapped fare is £2.748019953976. This is an aggregate assumption, not an observed fare distribution. The FY2024–25 cap grant is £515,693,216.60. With F = B - C outside London and single share s = 0.70, the assumption solves s * (u - annual_min(u, reference_cap)) = grant / F. Since 2 < u < 3, the reference year has 270 days at £2 and 95 at u, giving:

u = 2 + grant / (F * 0.70 * 270/365)

Removing the cap therefore raises the benchmark yield from about £1.55 to £1.94 at the representative share, matching the grant-addback calculation in issue #1871. This assumes full grant pass-through and no demand response. Individual shares can differ, so a dataset aggregate need not recover the published grant. Caps at or above £2.75, including the £3 cap, have no effect relative to uncapped travel under the default £2.748 representative fare. The default has no fare distribution above these caps, so it cannot estimate the savings those caps give to passengers with higher fares. Supply person-specific local_bus_uncapped_single_fare values above a cap to model its effect on those passengers. Very large reductions can reach the zero-yield floor.

Other reform controls and limits¶

fare_index / prior_law_fare_index multiplies both journey-priced and legacy spending. Both default to one; they are neutral reform controls rather than historical index series. Keep the denominator positive. ridership_index defaults to one and multiplies journey-priced spending, leaving supplied journey inputs intact. The model includes no demand elasticity or automatic ridership growth. Benchmark yields and trip translations stay nominally constant after 2024 unless changed explicitly. Dataset CPI-uprated household bus totals do not determine prices where journeys are available.

A proportional scenario can set gov.dft.bus.fare_index to 0.9 for a 10% reduction. A cap scenario changes gov.dft.bus.fares.cap; leave the reference schedule and benchmark yield unchanged. Set the cap to infinity to remove it. The fixture-scale tests exercise both routes through UK dataset loading and Scenario, including baseline isolation and the January cap transitions.