Measuring the Digital Economy for Policy Modeling: Evidence from Sectoral Value Added in OECD Economies

Data Description The empirical analysis is based on a multi-dimensional panel dataset combining sectoral economic outcomes with national Digital Economy indicators for OECD economies. Dependent variable.The main outcome variable is sectoral Gross Value Added (GVA), measured in real terms for 20 ISIC Rev.4 sectors across OECD countries. The data are sourced from OECD Structural Analysis (STAN) and National Accounts databases and reported in constant national currency. For cross-country comparability, all series are converted into PPP-adjusted constant US dollars using World Bank purchasing power parity conversion factors. The inverse hyperbolic sine transformation is applied to GVA in the econometric analysis to accommodate zero and low values while preserving a log-type interpretation. Digital Economy indicators.The core explanatory variables consist of a large set of Digital Economy–related indicators drawn from eight internationally recognized measurement frameworks:(i) the Digital Economy and Society Index (DESI),(ii) the G20 Toolkit for Measuring the Digital Economy (DETF),(iii) the International Telecommunication Union (ITU) digital development indicators,(iv) the IMD World Digital Competitiveness Index,(v) the Digital Intelligence Index (DII),(vi) the Inclusive Internet Index (EII),(vii) the GSMA Mobile Connectivity Index (MCI), and(viii) the OECD Digital Well-Being indicators. In total, more than 350 indicators are initially collected from these sources. A structured screening procedure is applied to ensure temporal coverage, cross-country comparability, and consistent definitions. Indicators with limited time series, insufficient cross-sectional variation, or inconsistent measurement across countries are excluded. After this filtering process, 267 Digital Economy indicators are retained for empirical analysis. All indicators are measured at the national level and capture different dimensions of digitalization, including infrastructure, connectivity, affordability, usage, skills, institutional readiness, and digital ecosystem development. Control variables.The dataset also includes a set of 29 macroeconomic and structural control variables commonly used in sectoral growth and value-added analysis. These variables account for broader economic conditions that may jointly influence digitalization and sectoral performance, including macroeconomic stability, investment, trade exposure, labor market conditions, and structural characteristics of the economy. Panel structure.The final dataset forms an unbalanced country–sector–year panel covering OECD economies, 20 economic sectors, and multiple years depending on data availability per indicator. Digital Economy indicators vary at the country–year level, while GVA varies at the country–sector–year level, allowing the analysis to exploit within-country variation over time and heterogeneous sectoral responses to changes in national digital conditions. Data sources and availability.All Digital Economy indicators are obtained from publicly available databases maintained by the European Commission, ITU, G20, IMD, OECD, GSMA and related institutions. Sectoral GVA data are taken from official OECD and World Bank sources. The data are harmonized, cleaned, and merged using consistent country and time identifiers. Replication datasets and Python code can be made available by the authors upon request.