Journal of Economic Research & Reviews(JERR)
ISSN: 2771-7763 | DOI: 10.33140/JERR
Impact Factor: 1.3
Henry Efe Onomakpo Onomakpo
Faculty of Economics and Business, Universities Gadjah Mada, Indonesia
Publications
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Review Article
National ESG Performance and Economic Implications for the Global Construction Industry: Evidence from Panel, Cross-Sectional, and Machine Learning Analyses
Author(s): Henry Efe Onomakpo Onomakpo*
The global construction industry's significant economic and environmental footprint drives the need for sustainability, making Environmental, Social, and Governance (ESG) criteria pivotal. This study empirically investigates national-level ESG impacts on construction value-added and housing costs, addressing knowledge gaps. A multi-method approach analyzed global data (2009–2023 panel, N=588; 2022 cross-section, N=33). Panel analysis employed a Two-Way Fixed Effects (LSDV) model. The cross-sectional 2022 housing cost analysis used ordinary least squares (OLS) regression and correlation. Complementary machine learning (Random Forest, XGBoost) explored predictive relationships for value added. The panel model identified GDP Growth (Annual %) as a significant positive predictor of construction value added (Coef. 0.01, p=0.02). Cross-sectionally, higher Control of Corruption cor.. Read More»