Purpose Amid the global transition toward sustainable energy systems, this study examines the determinants of energy intensity across 27 OECD countries from 1990 to 2022, with particular emphasis on technological innovation and demographic dynamics, providing novel insights for energy policy. Design/methodology/approach A dynamic panel framework employing common correlated effects (DCCE) estimators is utilized to account for cross-sectional dependence and slope heterogeneity inherent in interdependent country-level data. Complementary quantile regressions capture heterogeneous effects across the conditional distribution of energy intensity. Findings Empirical results indicate that technological innovation significantly reduces energy intensity through efficiency gains and cleaner technology adoption. Economic openness and GDP per capita are associated with lower energy intensity, whereas higher fertility rates are linked to increased energy intensity, reflecting greater demand for energy-intensive services. Quantile estimates reveal that innovation and credit access exert stronger effects at lower and median quantiles, while fertility’s impact diminishes at higher quantiles. Practical implications The findings underscore the need for integrated policies promoting innovation, financial accessibility and demographic considerations to enhance sustainable energy efficiency. Originality/value The study advances the literature by combining dynamic panel and quantile-specific approaches to elucidate the heterogeneous impacts of technological, economic and demographic factors on energy intensity – nuances often overlooked in prior empirical research.
Το λεύκωμα συνοψίζει το σύνολο του ζωγραφικού και χαρακτικού έργου του Λάμπρου Ορφανού, αποτελώντας την πρώτη ουσιαστική προσπάθεια καταγραφής και ανάδειξής του με συστηματικό τρόπο.
This paper asks whether the digital economy is becoming the new economy: not because traditional economic functions disappear, but because they are increasingly reorganised through digital infrastructure, digital finance and algorithmic capability. We introduce an open-data Digital Architecture framework and build a fully reproducible panel of 38 OECD economies for 2010 to 2024 from World Bank sources. The framework constructs transparent composite indices for digital infrastructure, FinTech, AI/ML capability, the traditional economy, and a clean new economy. Using two-way fixed-effects panels, we provide a descriptive answer: in OECD economies, the digital economy coincides with the new economy mainly through digital infrastructure. First, digital infrastructure is the load-bearing pillar of the digital economy’s association with the new economy: it accounts for about 24 per cent of within-country variation in new-economy outcomes, although its coefficient is imprecise under country-clustered errors. Second, the Digital Architecture Index is useful as a benchmarking construct, but it does not improve the within-country fit because the digital pillars are collinear and infrastructure carries most of the signal. Third, the evidence does not support a robust three-way configuration effect among digital infrastructure, FinTech and AI/ML capability; the association is sensitive to error structure, dynamics, outcome definition and true survey-year estimation. A future-dated placebo loads for the infrastructure block as well, so even the descriptive associations cannot be cleanly separated from slow-moving common trends. The paper therefore contributes a reusable open-data measurement framework and a clear empirical benchmark: in OECD economies, the digital economy aligns with the new economy primarily through digital infrastructure, the pillar that carries the strongest within-country association with productivity and entrepreneurship. The AI/ML capability proxy is externally validated against Eurostat enterprise-AI adoption data, with a cross-country correlation of 0.80.
This paper studies the long-run dynamics of real house prices in Greece and their structural drivers. We develop a Bayesian VAR model with time-varying unconditional means that allows to decompose real house prices into a slow-moving structural trend and a transitory cyclical component. The proposed empirical framework accounts for structural changes in the housing market and episodes of heightened macroeconomic volatility. Applied to Greece over 2002-2025, it identifies a pronounced and persistent upward shift in the long run house price trend from 2017 onward. Historical decomposition of the structural shocks attributes this shift mainly to self-reinforcing house price dynamics, but also to the joint effect of strong demand and constrained supply in the housing market. Allowing for time variation in the long run equilibrium of house prices yields a more appropriate assessment of potential housing market imbalances compared with a constant steady state benchmark.
This paper investigates to what extent the strengthening of Greece’s social safety net since the recent sovereign debt crisis has weakened work incentives for benefit recipients. Using the tax-benefit microsimulation model EUROMOD and its Hypothetical Household Tool (HHoT), we estimate participation tax rates (PTRs) and marginal effective tax rates (METRs) in 2024 for several stylised household types, accounting for the interaction between income taxes, social insurance contributions and means-tested benefits. Our results suggest that PTRs can reach near-prohibitive levels, particularly when transition into employment is associated with the withdrawal of the unemployment benefit. METRs are similarly distorted, exhibiting sharp kinks where means-tested benefits are abruptly withdrawn rather than gradually tapered. The paper concludes with some policy recommendations to improve work incentives, while preserving the anti-poverty gains achieved over the past decade.
