Studies in Business and Economics | 2026
Authors: Filip C.; Mastac L.; Drǎghici G.; Ghencea A.; Amuza M.-G.
DOI: 10.2478/sbe-2026-0009
Journal: Studies in Business and Economics
Year: 2026
Publisher: Sciendo
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 0
This study examines how building permits predict next-year construction outcomes across Europe's main subsectors, Building Construction(BC), Civil Engineering(CE), and Specialized Construction(SC), from 2005 to 2023. Using Eurostat data for 28 European countries, the analysis applies dynamic panel Fixed-Effects(FE) models with Driscoll-Kraay standard errors to estimate elasticities linking permit volumes to turnover, employment, and profitability. Results reveal substantial heterogeneity across subsectors and countries. Building Construction and Specialized Construction show strong responsiveness to permit activity, particularly in employment and turnover, while Civil Engineering effects are mainly labor-related. Beyond permit volumes, the study evaluates the role of project composition. The findings indicate that smaller, more numerous projects generate higher economic returns per m², emphasizing the relevance of average project size for cost management efficiency and resource allocation. A structural break emerges after 2020, as the COVID-19 shock intensified the traditional permit-performance transmission mechanism, leading to higher elasticities. Country-specific results diverge markedly, suggesting that institutional capacity and market structure shape how permits translate into realized activity. Findings underscore permits not only as planning indicators but also as strategic tools for forecasting, cost management, and portfolio optimization, offering relevant insights for construction firms, policymakers, and regulators operating in various European markets. © 2026 Cosmin Filip et al., published by Lucian Blaga University of Sibiu.
Building Permits; Construction; Economic forecasting; Management; Panel Data