Building Stronger Transport Policy: An Evidence Gap Map - Dataset
Metadata & use
| Identifier | https://doi.org/10.60966/k96ok76z |
|---|---|
| License | Creative Commons Attribution 4.0 International |
| Related Knowledge Product | |
| Citation |
Acosta, Camilo, et al. (2025). Building Stronger Transport Policy: An Evidence Gap Map - Dataset. IDB Open Data. https://doi.org/10.60966/k96ok76z |
| Published date | 2025-11-12 |
| Modified date | 2026-08-07 |
| Tags/Keywords | Transportation · Roads · Urban Mobility · Policy · Evidence · Literature · Gaps |
| Language |
|
| Temporal coverage | 2005-2025 |
| Country |
United States
India
Colombia
Singapore
United Kingdom
Nicaragua
Cambodia
Iran
Pakistan
Nepal
Mozambique
Ethiopia
Ecuador
Rwanda
Nigeria
Denmark
Spain
Zambia
Thailand
Austria
Philippines
Malawi
Australia
Israel
Egypt
Poland
Cameroon
South Africa
France
Germany
Lebanon
Haiti
Uzbekistan
Sri Lanka
Chile
Indonesia
Tajikistan
Türkiye
Kyrgyzstan
Estonia
Peru
El Salvador
Algeria
Japan
Finland
Vietnam
Uganda
Costa Rica
Netherlands
China
Georgia
Burkina Faso
Bangladesh
Papua New Guinea
Hungary
Kenya
Taiwan
Sierra Leone
Canada
Trinidad & Tobago
Paraguay
Sweden
Italy
Brazil
Norway
South Korea
Mexico
Portugal
Argentina
Switzerland
Bolivia
New Zealand
|
| Publisher |
Inter-American Development Bank
|
| Author |
Acosta, Camilo
Borja, Leonel
Porto, Indira
Anda, María Daniela
|
| Data collection type | Administrative Data |
| Statistical type | Panel Data |
| Data structure | Structured Data |
| Data notes |
What is this dataset?It is an evidence gap map (EGM) of the impact evaluations and systematic reviews that measure what transport interventions actually achieve. The IDB's Transport Division and Knowledge and Learning Division built it with the International Initiative for Impact Evaluation (3ie), following a 3ie protocol adapted for the IDB. Every study is coded onto a two-dimensional framework, so the areas where evidence has accumulated, and the areas where it is missing, can be read off directly. What does it contain?The studies themselves, separated into impact evaluations and systematic reviews; the authors of each, with the institution, department and country of their affiliation at the time of the study; the two framework hierarchies used to code them; and a full critical appraisal of every systematic review. A data dictionary accompanies each table, documenting what every column holds. How is the evidence classified?Along two axes. Interventions fall under urban mobility infrastructure; roads, regional transportation and logistics; law, regulations and policy; and multi-component interventions. Outcomes fall under access and use, quality, affordability, service management, and socioeconomic results. The intervention and outcome tables hold those hierarchies with a description of each category, and the study tables draw their values from them: a study measuring several interventions or outcomes carries one per numbered slot. Which countries and regions are covered?The map is global rather than regional, which is deliberate: on many interventions the available evidence comes from outside Latin America and the Caribbean. Each study records the regions and countries it examined and the income levels of those countries. Studies of China, most of them on high-speed rail, are listed separately. What time period does it cover?Studies published from 2005 through April 2025. How was the evidence identified and screened?Through the search strategy, databases, and inclusion and exclusion criteria set out in the review protocol, which is published alongside the data as a PDF. The protocol also defines the intervention and outcome framework and the instrument used to rate each systematic review. How were the systematic reviews appraised?Each was rated against the 3ie critical appraisal instrument, published here as its own table. Its criteria run in three sections: how the review defined its question, searched and screened; how it appraised, extracted and synthesised its evidence; and any remaining concerns together with the factors that mitigate them. Each section carries a judgement, and the review receives an overall confidence rating of high, medium or low, which is repeated in the systematic reviews table. How do the tables join together?On the study identifier. Each impact evaluation and systematic review has an id; the author tables give one row per author of that study, and the appraisal table one row per systematic review. Joining on that id links a study to its authors and, for a review, to its appraisal. Why are some columns empty?The framework reserves space for coding that is not finished yet. The intervention and outcome subtype columns, the per-outcome effect and metric columns, and several descriptive fields are present but not yet populated. They are published rather than withheld so the table structure stays stable as the coding advances, and a later update can fill them without changing the columns. How can it be used?To see where transport evidence is concentrated and where it is thin before commissioning new research or designing a programme; to find the studies that measure a particular intervention and outcome pair; and to judge how much weight a given systematic review can carry, because its appraisal is published beside it rather than summarised away. What are its limitations?It maps evidence rather than pooling it: it records which studies measured what, not a combined estimate of effect. Coverage reflects what the search found through April 2025 under the protocol's inclusion criteria, so an empty cell means no eligible study was identified, not that an intervention does not work. Coding is at the study level, so a study spanning several countries, interventions or outcomes carries several values in a single cell, separated by a vertical bar. In what format is it available, and under what licence?As a set of tables in the IDB Open Data DataStore, browsable online and downloadable as CSV, with the review protocol as a PDF. It is published under the Creative Commons Attribution 4.0 International licence, which allows reuse and adaptation provided the source is credited. How do I cite it?Use the citation shown on this page, which names the authors, the dataset title, IDB Open Data as the repository, and the persistent identifier assigned on publication. |