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Building Stronger Transport Policy: An Evidence Gap Map - Dataset

By Knowledge and Learning Division (VPS/VPS/KLD); Transport Division (VPS/INE/TSP)

Efficient and reliable transport systems are central to economic growth, social inclusion, and environmental sustainability. In Latin America and the Caribbean (LAC), transport and logistics performance remains below that of advanced economies, constraining access to services, social inclusion (Scholl et al., 2021), competitiveness, and productivity (Calatayud & Montes, 2021).

The EGM, available at https://developmentevidence.3ieimpact.org/egm/transportation-evidence-gap-map, presents global effectiveness evidence on transportation interventions, including roads, regional transportation and logistics; urban mobility infrastructure; and laws, regulations, and policies governing public transit, mobility, traffic, and transportation.

Financed and co-produced by the Inter-American Development Bank (IDB), the EGM compiles, curates, and classifies studies that estimate causal effects, displaying where evidence is clustered and where gaps remain. It aims to help decision-makers identify the most promising approaches for improving transport systems, highlight priority areas for future research, and ultimately support evidence-informed policymaking, enhance the allocation of scarce resources, and contribute to safer, more inclusive, and more sustainable transport in LAC and beyond.

Know of any studies that could be included in this map? We invite you to share them with us using this form.

Note: This map includes studies published between 2005 and April 2025. Eligible studies from China—mainly focused on high-speed rail—are listed separately.

This Evidence Gap Map was co-produced by the Inter-American Development Bank’s Transport and Knowledge and Learning Divisions, and the International Initiative for Impact Evaluation (3ie). It is part of the broader collaboration between the IDB and 3ie, formalized through a Memorandum of Understanding signed in October 2023. The authors are solely responsible for any errors or omissions.

IDB project collaborators: Camilo Acosta, Leonel Borja, Agustina Calatayud, Vileydy González, Minji Kang, Indira Porto, María Eugenia Rivas, Magdalena Rossetti, Santiago Sánchez, Gonzalo Santamaría, Valentina Sequi, and Alejandro Taddia.

3ie project collaborators: María Daniela Anda, Diana Belén Córdova-Aráuz, Mark Engelbert, Tomasz Kozakiewicz, and Shannon Shisler.

What the data covers

Interventions fall under four domains: urban mobility infrastructure; roads, regional transportation and logistics; law, regulations and policy; and multi-component interventions. Outcomes fall under five: access and use, quality, affordability, service management, and socioeconomic results. Each domain resolves into named interventions and outcomes and, where the coding defines one, a third-level subtype. Every study records the regions and countries it examined and the income levels of those countries. Coverage is global rather than regional: on many interventions the available evidence comes from outside Latin America and the Caribbean. Studies of China, most of them on high-speed rail, are listed separately.

What it contains

The studies, separated into impact evaluations and systematic reviews, each carrying its citation, journal ranking and open-access status, the design and method used, and its coded interventions and outcomes. The authors of every study are published as their own tables, with the institution, department and country of each author's affiliation at the time of the study. The two framework hierarchies are published as tables with a description of each category. Every systematic review carries an overall confidence rating from a critical appraisal against the 3ie instrument, and the full appraisal is published as its own table. A data dictionary accompanies each group of tables, and the review protocol is published as a PDF.

How the data was collected

This is a secondary synthesis and contains no new fieldwork. Studies were identified through the search strategy, databases and inclusion and exclusion criteria set out in the review protocol, then screened and coded onto the framework that protocol defines.

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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 2026-10-28
Tags/Keywords Transportation · Roads · Urban Mobility · Policy · Evidence · Literature · Gaps
Language
  1. English
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
Dataset unit of observation

Publication
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. It records which studies measured what, not a combined estimate of effect: an empty cell means no eligible study was identified under the protocol's inclusion criteria.

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. 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.

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.

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.

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.

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