IASB Due Process Participation and Governance Structure: Comprehensive Datasets on Stakeholder Involvement and Comment Letter Submissions (2001–2024)
Description
This dataset collection comprises two complementary databases that provide a comprehensive and structured record of stakeholder participation in the due process procedures of the International Accounting Standards Board (IASB), as well as in matters related to the governance structure of the IFRS Foundation. Together, these datasets enable detailed empirical analysis of global engagement in standard-setting processes from 2001 to 2024. The first dataset, IASB Due Process Participants Database, documents all identifiable participants involved in IASB projects from 2001 onward. From 2006, the dataset is considered complete in terms of including all mandatory due process consultations across the various stages of standard development. It provides core descriptive information on each participant, such as country or region of origin, jurisdiction type, stakeholder group classification, and the year of first participation. It also records which projects each participant contributed to, the total number of participations, their share of total project involvement, and the percentage of project participation since their first intervention. Furthermore, it offers a time-series view of the intensity of participation over the years. This dataset is particularly useful for studying patterns and trends in stakeholder engagement, the geographical and institutional origin of participants, and their evolution over time. It also supports research into the influence of external events—such as the year a jurisdiction adopts IFRS—on stakeholder participation levels. The second dataset, IASB Comment Letter Submissions Database, offers a refined unit of analysis by focusing on each comment letter submission individually. Unlike the first dataset, in which collective submissions are attributed to the group of participating entities, this dataset treats each submission (individual or joint) as a separate participation unit. It enables the analysis of both individual and collective behaviors across projects and facilitates more granular research into the dynamics of stakeholder influence through formal feedback mechanisms. Both datasets provide aligned and comparable information, and their structure allows for cross-referencing and aggregation. They support a wide range of academic research questions in the fields of accounting regulation, standard-setting governance, stakeholder analysis, and global policy diffusion.
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Steps to reproduce
The datasets were developed through systematic archival research of publicly available documents published by the International Accounting Standards Board (IASB) and the IFRS Foundation. The primary sources of data include comment letters submitted in response to IASB consultations, project pages detailing due process steps, and official documentation related to the governance structure of the IFRS Foundation. To build the Participants Database, we manually collected information on every identifiable participant in IASB due process consultations between 2001 and 2024. For each project, we recorded participation events, identified organizations or individuals involved, and categorized them by type (e.g., preparer, regulator, professional body), geographical origin, and jurisdictional classification. We also recorded the year of first participation and tracked longitudinal participation trends. The Comment Letters Database was compiled using the same primary sources, but with a focus on each individual submission. In this dataset, each comment letter is treated as a separate observation. In cases of joint submissions, a distinct entry was created to preserve the collaborative nature of the feedback. The metadata for each letter includes the project to which it corresponds, the identity of the submitter(s), and the temporal characteristics of the submission. No automated scraping tools were used; all data was manually reviewed and coded to ensure accuracy and consistency. Data cleaning and structuring were performed using Microsoft Excel and Python, facilitating further analysis and export to standard research formats. The methodology is transparent and replicable using the same sources. Future researchers may reproduce or update the datasets by consulting the IASB’s official website and systematically tracking comment letter submissions and project participation records over time.