Toward Economics Statistics On: Own-Account Data and Databases Assets for 1997–2024

Apr 7, 2026·
Dr. José Bayoán Santiago Calderón
Dr. José Bayoán Santiago Calderón
· 0 min read
Abstract
This article describes the proposed methodology and experimental estimates for capitalizing own-account data as part of the updates to the System of National Accounts from the 2008 standard to the 2025 revision. The methodology explains how the U.S. Bureau of Economic Analysis estimates annual industry-level nominal values, prices, and volume for gross fixed capital formation, consumption of fixed capital, and net stock for a new asset class: own-account data and databases. Additionally, it illustrates the impact of the change across the National Economic Accounts. The work spans the period from 1997 to 2024. The economy grew at an average rate of seven basis points faster from 2002 to 2024 when own-account data and databases were capitalized.
Type
Publication
U.S. Bureau of Economic Analysis Working Paper Series
Status
Peer-reviewed
publications
Dr. José Bayoán Santiago Calderón
Authors
Research Economist

José Bayoán Santiago Calderón is a senior research economist in the national economic accounts research group at the U.S. Bureau of Economic Analysis. Before joining the federal statistical system, Dr. Santiago Calderón had years of experience in the private sector as a research scientist at various companies. Bayoán also held academic appointments with the Biocomplexity Institute and Initiative at the University of Virginia, where he started his career in public service.

His research has centered on improving decision-making. His transdisciplinary research approach has enabled him to routinely collaborate across disciplines and develop a diverse set of domain knowledge and methodological toolset. He also participates in various open-source software communities (e.g., JuliaLang) and civic activism (e.g., Code4PR, Mentes Puertorriqueñas en Accion).

In his non professional life, Bayoán enjoys spoiling his dog (Sadaharu), playing video games, watching TV, reading manga, and programming.

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