Does choosing BART station closures by fares beat the staff's "10 lowest ridership" list? A pre-registered test finds only a small gain

BART staff proposed closing the ten lowest-ridership stations if a regional tax measure fails. We ask whether choosing the ten closures by origin-destination fares loses fewer list-fare dollars. Using public BART ridership data and published list fares, we pre-registered the rule on 2025 data and scored it once on nine held-out 2026 months (January to September). The fare-based set differs from the staff list by one station (Colma closed instead of San Bruno) and loses 0.63% fewer list fares (95% interval 0.48% to 0.80%, about $0.23 million), far below the pre-registered 5% bar. An exact solve finds no better set of ten. The swap reverses if more than about 6% of riders at a closed station switch stations, and the gain fell from 1.47% in 2025 to 0.63% in 2026. Operating costs and real revenue were not measured. Eight of 13 predictions hit. The regional measure passed in November 2026 (unofficial results), so closures are now unlikely; the comparison is about the ranking rule, not an imminent decision. Data credit: ridership data from the San Francisco Bay Area Rapid Transit District (BART) monthly origin-destination workbooks (bart.gov/about/reports/ridership, Creative Commons Attribution License), used in aggregated form; list fares and station locations from BART's GTFS feed under BART's Developer License Agreement. This work is not endorsed by BART. Paper: CC BY 4.0. Code in supplement.zip: MIT licence.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-06
DOI
https://doi.org/10.5281/zenodo.24011650
Primary Topic
Transportation Planning and Optimization
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

Does choosing BART station closures by fares beat the staff's "10 lowest ridership" list? A pre-registered test finds only a small gain

Jayden Ling
1 links
Zenodo (CERN European Organization for Nuclear Research)
Transportation Planning and Optimization
preprint

Does choosing BART station closures by fares beat the staff's "10 lowest ridership" list? A pre-registered test finds only a small gain

Jayden Ling
preprint en

Abstract

BART staff proposed closing the ten lowest-ridership stations if a regional tax measure fails. We ask whether choosing the ten closures by origin-destination fares loses fewer list-fare dollars. Using public BART ridership data and published list fares, we pre-registered the rule on 2025 data and scored it once on nine held-out 2026 months (January to September). The fare-based set differs from the staff list by one station (Colma closed instead of San Bruno) and loses 0.63% fewer list fares (95% interval 0.48% to 0.80%, about $0.23 million), far below the pre-registered 5% bar. An exact solve finds no better set of ten. The swap reverses if more than about 6% of riders at a closed station switch stations, and the gain fell from 1.47% in 2025 to 0.63% in 2026. Operating costs and real revenue were not measured. Eight of 13 predictions hit. The regional measure passed in November 2026 (unofficial results), so closures are now unlikely; the comparison is about the ranking rule, not an imminent decision. Data credit: ridership data from the San Francisco Bay Area Rapid Transit District (BART) monthly origin-destination workbooks (bart.gov/about/reports/ridership, Creative Commons Attribution License), used in aggregated form; list fares and station locations from BART's GTFS feed under BART's Developer License Agreement. This work is not endorsed by BART. Paper: CC BY 4.0. Code in supplement.zip: MIT licence.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Transportation Planning and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon