Long-Run Digital–Entrepreneurial Complementarities and Sectoral Value Added: Panel Cointegration Evidence from OECD Economies

This repository provides the data and Python code supporting the article: “Digital Economy and Entrepreneurship as Joint Drivers of Sectoral Value Added: Evidence from OECD Economies.” The repository is designed to ensure transparency, replicability, and reusability of the empirical analysis. It includes the full indicator dataset, processed factor structures, and estimation outputs used in the paper. The empirical framework combines multidimensional Digital Economy and Entrepreneurship indicators, condensed via Sparse Principal Component Analysis (SPCA), and examines their joint association with sectoral Gross Value Added (GVA) across OECD economies using interaction-based panel regressions. Repository Contents The repository includes the following components: 1. Python Code Python scripts used for: Data cleaning and harmonization Construction of Digital Economy and Entrepreneurship factors using SPCA Generation of interaction terms Estimation of sector-level panel regressions with fixed effects Code is fully commented and structured to allow replication and extension of the analysis. 2. Dataset Harmonized panel dataset at the country–sector–time level. Includes: Digital Economy indicators (267 indicators) Entrepreneurship and Innovation indicators (92 indicators) Sectoral Gross Value Added (GVA) All indicators are drawn from internationally established and publicly available sources (OECD, European Commission, ITU, World Bank, WIPO, G20, IMD, GSMA, EIU). 3. Indicator Table A detailed indicator table documenting: Indicator names Source framework Conceptual dimension (e.g. infrastructure, skills, innovation, business dynamics) Facilitates transparency and traceability from raw indicators to latent factors. 4. SPCA Loadings Sparse Principal Component Analysis (SPCA) loading matrices for: Digital Economy factors Entrepreneurship factors Loadings are reported separately to enhance interpretability and to document how latent dimensions are constructed from underlying indicators. 5. Regression Results Output tables from sector-level panel regressions, including: Main effects of Digital Economy and Entrepreneurship factors Interaction terms between Digital Economy and Entrepreneurship dimensions Results are reported consistently with the empirical framework described in the paper. Purpose and Reuse This repository supports: Replication of the empirical results presented in the paper Methodological reuse of the SPCA-based factor construction approach Extension of the framework to alternative sectors, countries, or time periods Comparative studies on digitalization, entrepreneurship, and economic performance The materials are intended for academic researchers, policy analysts, and practitioners interested in the joint role of Digital Economy and Entrepreneurship in shaping sectoral economic outcomes.