This study examines how public debt conditions inflation pass-through to observed interest-rate conditions in the European Union. Using EU country-year data for 1999–2024 and dynamic estimations for 2000–2024, we estimate reduced-form panel models in which inflation pass-through varies smoothly with lagged public debt through natural cubic splines. In the main short-rate specifications, pass-through is strongest at very low debt levels and weaker across the central and upper parts of the debt distribution, without a uniformly monotonic decline. The pattern is concentrated at impact and short annual horizons and remains visible in clean short-rate and non-euro samples. Euro-area sovereign-spread specifications do not reproduce the same baseline attenuation profile. By showing that fiscal conditions shape the strength and timing of inflation pass-through across monetary regimes, the study advances understanding of heterogeneous interest-rate adjustment in a fiscally fragmented European Union.
Existing research on Czech interest rate pass-through predominantly relies on static approaches that mask temporal dynamics and lacks systematic quantification of credit risk premiums. Using rolling 8-year windows and ARDL models over 2004–2025, we analyze time-varying transmission from the 5-year interest rate swap to housing loan rates and from 3-month PRIBOR to corporate lending rates. For housing loans, long-run pass-through ranges from 0.5 to 1.0, reaching near-completeness in the 8-year windows ending in 2015–2017 and after 2022. A one percentage point unemployment increase raises housing loan rates by approximately 0.2
Our paper assesses income convergence of 46 sub-Saharan African (SSA) countries and 10 Central and Eastern European (CEE-10) countries with the USA. We apply multidimensional approaches comprising beta, sigma and convergence clubs. The beta convergence approach examines both absolute and conditional convergence, combining regression models with system Generalized Method of Moments (GMM) models while we employ log t regression tests for the identification of convergence clubs. The results indicate absolute beta and sigma convergence between the CEE-10 countries and the USA, whereas no such convergence is found for SSA countries. Additionally, the findings reveal conditional convergence with the USA, occurring at annual speeds of 7
This paper estimates a Tobacco Kuznets Curve (TKC) for Spain on the full national series, 1957–2023, to estimate the income–consumption curvature underlying the Tobacco Kuznets hypothesis and derive the associated model-implied turning points. Understanding these model-implied turning points may contribute to discussions of tobacco control, taxation, and regulation, and to translating long-run demand patterns into operational policy benchmarks. Using annual adult cigarette consumption, real GDP per capita, and real pack prices, we estimate three nested models: (i) a simple bivariate benchmark specification included for illustrative comparison purposes only; (ii) an augmented model adding ln(real price) and post-2005/2010 indicators; and (iii) a segmented-trend specification interacting each indicator with time. Baseline estimation relies on OLS with Newey–West HAC inference, while robustness checks, such as GLS(AR1), Huber RLM, DOLS with leads/lags where available, and ARDL long-run coefficients, ensure that the identified turning points are not artifacts of persistence, outliers and dynamic adjustment. Across specifications, ln(GDP pc) is positive and [ln (GDP pc)]2 is negative, confirming an inverted-U conditional on price and policy timing. The estimated curvature parameters imply turning points between approximately €39,000 and €58,000 and the implied peak consumption (≈ 118–158 packs per adult/year). Short-run price elasticities are negative (about − 0.17), and post-reform dynamics are consistent with a persistent decline. These thresholds should be interpreted as model-implied projections rather than empirically observed policy thresholds. While they help characterize the long-run relationship between economic development and cigarette consumption, they do not by themselves imply specific excise-tax recommendations.
Income composition inequality (ICI) refers to inequality in the distribution of different income sources across the personal income distribution. Although the concept has received increasing attention in the literature, the relationship between income composition inequality and overall personal income inequality remains largely unexplored. This study examines the role of ICI in the evolution of primary and secondary personal income inequality by introducing a new measure of ICI and analysing its impact on income inequality in Spain from 2007 to 2021. The proposed approach allows ICI to be measured across multiple income sources while distinguishing between primary and secondary income. Using econometric analysis, the study links changes in income inequality to variations in ICI across the income distribution, while also controlling for other socio-economic factors. The results reveal a strong relationship between ICI and personal income inequality, showing that increases in the ICI correlate with greater inequality in primary income distribution over the analysed period. However, the increase in primary income composition inequality in Spain has not translated into higher inequality in the distribution of secondary income, largely due to the strengthened redistributive role of the state during the analysed period. These findings highlight the need for more effective policies aimed at achieving a more equitable primary income distribution, particularly through wealth and financial income taxation.
This paper introduces the R library estimateW to estimate spatial weight matrices for Bayesian spatial econometric panel models. The approach focuses on spatial weights that are binary prior to row-standardization. However, unlike recent literature our approach requires no strong a priori assumptions on (socio-)economic distances between the spatial units. The estimation approach relies on efficient Bayesian Gibbs sampling techniques and the library supports a variety of the most common spatial econometric panel specifications. estimateW moreover supports to elicit flexible shrinkage priors, which allow to estimate spatial spillovers even in settings where the number of time period is small relative to number of cross-sectional units. An empirical illustration for European NUTS-1 regions demonstrates that the method recovers plausible spatial dependence patterns, interpretable spillover effects, and meaningful clustering in the estimated network structure.
This paper examines how the rapid increase in immigrant workers following the EU enlargements affected employment growth in Austria between 2008 and 2017. Using a shift-share instrument based on historical settlement patterns and rich administrative data, I estimate local employment responses to immigration-induced labour supply shocks over short and longer horizons. I provide robust evidence that native employment rates respond positively to local immigration shocks, with elasticities of around 0.1 percent. Heterogeneity analysis suggests that short-run employment losses are concentrated among men with vocational or upper-secondary education, while women, especially those with higher education, experience employment gains that largely offset aggregate effects. For immigrants residing in Austria for more than seven years or naturalised, mainly from Turkey or the former Yugoslavia, inflows from new EU member states reduced employment growth by about 0.1 percent in the short run. Allowing for dynamic adjustment to earlier immigration shocks, both positive and negative employment responses appear short-lived and are gradually offset through adjustment and reallocation channels. These findings suggest that immigration did not harm domestic employment overall but affected subgroups differently, highlighting the need for targeted labour market support.
During the COVID-19 pandemic and the subsequent logistical disruptions in global supply chains, the rise in chip prices had significant repercussions on the world economy. This paper simulates macroeconomic fluctuations due to changes in chip prices using a GVAR model, covering the period from 1994 to 2022 for a sample of 27 economies. The analysis reveals a statistically significant relationship between the increase in chip prices and the onset of a global recession, leading to contractions in exports and imports. The model’s estimations highlight that chip prices indirectly affect industrial production and exchange rates by altering international trade variables. These results were further reinforced by several robustness checks. This study underscores the importance of semiconductors to domestic economic stability.
This paper examines the impact of economic policy uncertainty on bank wholesale funding and explores the moderating role of the quality of political signals. Using a sample of 431 commercial banks in the United States over the period 2003–2021, we find robust evidence of a negative relationship between policy uncertainty and bank wholesale funding. Delving into this relationship, news-based policy uncertainty, government expenditure uncertainty, tax uncertainty, and inflation uncertainty appear to reduce the share of bank wholesale funding, leaving banks with higher liquidity and refinancing risks. Our results show that policy uncertainty generates noisy public signals that prompt wholesale financiers to withdraw or refrain from rolling over funds, particularly for banks with weaker asset quality and greater insolvency risk. However, this adverse effect is weaker in environments with low-quality political signals, where wholesale creditors have fewer incentives to update their investment sentiments and adjust financing decisions in response to heightened economic policy uncertainty. Overall, the findings highlight that the link between policy uncertainty and wholesale funding critically depends on the credibility of political signals.
This study examines the predictive relationship between geopolitical risk (GPR) and gold returns across quantile states, employing a quantile-on-quantile regression framework augmented with block bootstrap and scenario forecasts. By capturing nonlinear and state-dependent effects, the analysis identifies heterogeneous responses of gold returns to GPR, Dollar Index (DXY), and market volatility (VIX) across different return quantiles. The results demonstrate that gold exhibits significant safe-haven and hedge properties under high geopolitical uncertainty, with predictive patterns varying systematically across extreme and median market conditions. Robustness checks using alternative bandwidths and block lengths confirm the stability of these findings. Forecast simulations highlight the practical implications for portfolio allocation and risk management, showing that gold can provide both protective and diversifying benefits depending on market and geopolitical scenarios. The study contributes to the literature on safe-haven assets by providing a rigorous quantile-based assessment of gold return dynamics under asymmetric risk states and enhances the methodological toolkit for analyzing financial assets under uncertainty.
This study employs model averaging methods to analyze the determinants of non-performing loans (NPLs) in the Turkish banking sector. The characteristic drivers of NPL are examined separately for different loan types categorized by customer segments (consumer loans, corporate loans, SME loans, mortgage loans, credit cards, general purpose loans, vehicle loans) and sectors (manufacturing, agriculture, construction etc.). Our results confirm that asset quality, proxied by NPL ratio of different loan segments, and economic sectors present unique relations with macroeconomic and banking variables. We conclude that customized risk management practices including segment-specific early warning systems, stress tests and forward-looking provisional capital buffers may bring about significant benefits given that credit risk in different subcomponents of the economy responds to macroeconomic and banking shocks differently.
Central banks conduct monetary policy to achieve price stability, but decisions also have effects on labor-market outcomes. This paper investigates the short-run effects of monetary policy on labor demand in three small European economies—Estonia, Latvia, and Lithuania—using high-frequency identification and daily online job vacancy data over 2018–2024. Monetary shocks are measured as unanticipated changes in forward-looking interest rates around policy announcements. We find that contractionary (expansionary) monetary policy shocks induce immediate and persistent declines (increases) in job vacancy postings. On average, a 1 percentage point unanticipated rise in short-term interest rates reduces vacancies by roughly 2 percent within two weeks, with substantial heterogeneity across countries: the cumulative effect ranges from 0.5 percent in Latvia to 3.2 percent in Lithuania. These results highlight the speed and magnitude of labor demand responses to monetary policy and underscore the role of structural differences in shaping transmission. By combining daily vacancy data with high-frequency shocks, the paper provides novel evidence on the labor market channels of monetary policy, offering timely insights for policymakers evaluating the near-term employment consequences of interest rate decisions in small open economies.
This study re-examines the Feldstein–Horioka puzzle using Adaptive Elastic Net regression with ten-year rolling-window estimation, applied to a panel of over 100 countries observed between 1960 and 2022. The Feldstein–Horioka puzzle has proved remarkably durable, yet uniform specifications may conflate structural capital immobility with transitory policy effects—particularly in emerging markets characterised by frequent regime changes. The global savings-retention coefficient falls substantially below the original Feldstein–Horioka estimate, but this aggregate attenuation conceals a sharp dichotomy. OECD economies exhibit a gradual secular decline consistent with progressive financial integration. Emerging markets, in contrast, display pronounced within-country volatility driven by discrete policy regime changes and crisis episodes rather than smooth liberalisation. Türkiye exemplifies this regime dependence, with its coefficient moving sharply across phases of pre-liberalisation, post-liberalisation instability, crisis, and post-crisis restructuring; India, Thailand, Brazil, and Argentina display comparable policy-driven trajectories. Two-way fixed-effects estimation, PCA-augmented specifications that partial out common macroeconomic shocks, lead-savings placebo tests, within-country permutation exercises, and sensitivity analyses across alternative regularisation configurations confirm the robustness of these dynamics. The findings indicate that the emerging-market ‘puzzle’ reflects transitory policy configurations rather than genuine capital immobility, and that time-varying estimation is a methodological necessity—not an optional refinement—for capturing capital mobility in economies characterised by structural discontinuity.
This paper examines whether government size and fiscal composition are associated with macroeconomic stability in the EU-27 over 1980–2024. We construct medium-run volatility measures for GDP growth and the output gap using five-year windows and relate them to aggregate and disaggregated fiscal variables. The baseline results suggest that fiscal composition matters more than overall size: indirect and capital taxes are associated with lower growth volatility, whereas direct taxes are associated with higher volatility. On the expenditure side, current expenditure, especially public wages and interest payments, is negatively associated with volatility. These patterns remain broadly intact across a range of robustness checks, with expenditure-side results proving particularly stable; revenue-side estimates become more conservative once common shocks are absorbed via the Augmented Mean Group estimator. We also report evidence on output losses during the Great Recession and the COVID-19 shock and relate them to pre-crisis fiscal conditions.
Sovereign debt crises can be self-fulfilling, as borrowing rates rise in expectation of default, thereby increasing the likelihood of default. To determine whether the Portuguese sovereign debt crisis of 2010–2013 was primarily driven by self-fulfilling expectations or macroeconomic fundamentals, this paper brings to the data a multiple equilibria model in which default expectations can influence the probability of default independently of fundamentals. To do this, we estimate the probability of default for the period 2000–2020, covering both tranquil and crisis episodes, using a Markov-switching regime framework, following the Jeanne and Masson (J Int Econ 50(2):327–350, 2000. https://doi.org/10.1016/S0022-1996(99)00007-0 ) approach. The results reveal: (i) the presence of two distinct regimes—tranquil and crisis—with significantly different default probabilities; (ii) the transition from a low to a high default probability regime is unrelated to macroeconomic fundamentals, highlighting the role of expectations, and suggesting that the debt crisis was partially self-fulfilling; and (iii) the default probability is jointly determined by fundamentals (debt-to-GDP, growth, international risk aversion), and market expectations, with their relative influence depending on whether the economy is in a tranquil or crisis regime.
This study empirically investigates how energy costs, environmental policy, and history of innovation (path dependency) influence energy innovation in Europe over the period 2000-2020. Using panel data for 17 European countries we analyze clean and dirty energy patenting behavior in relation to energy prices, energy taxes, carbon pricing mechanisms, and energy R D subsidies. We estimate Poisson count data models, with robustness assessed using negative binomial specifications. The results indicate that higher energy prices are robustly associated with increased clean energy innovation, whereas energy costs do not suggest a significant effect on fossil-based innovation. Instead, dirty innovation is largely explained by accumulated fossil knowledge stocks, pointing to strong path dependence and persistent carbon lock-in. Moreover, the adoption of EU ETS is associated with higher patenting activity in both clean and fossil technologies, consistent with engaging in defensive innovation by extending existing fossil-based technological capabilities. Overall, the findings suggest that carbon pricing, while necessary, has historically been insufficient to weaken fossil innovation trajectories when path dependence is strong, leaving the energy transition constrained by carbon lock-in. Effective climate policy, therefore, requires a complementary mix in which EU-wide price signals are combined with tightly targeted public R D subsidies for breakthrough zero-carbon technologies and deployment policies that accelerate learning and scale-up in clean niches.
This paper examines the role of finance and asset prices in enhancing the real-time reliability of output gap estimates. In a structural unobserved components model, financial indicators are embedded in the cyclical component alongside unemployment and inflation. The results show that incorporating finance and asset prices not only explains a large share of cyclical fluctuations in economic output but also improves real-time reliability by producing estimates that are less prone to ex-post revisions.
This paper investigates the role of lifestyle in determining life expectancy across European countries using spatial regression analysis. In addition to lifestyle variables, our model includes three other groups of determinants: socioeconomic, environmental, and health system characteristics. Alcohol consumption and insufficient intake of fruits and vegetables are significant in all model specifications. Notably, their importance is comparable to income and health expenditure which remain the main drivers of life expectancy. Other lifestyle variables, including smoking, physical activity, and being overweight, exhibit statistically significant effects in alternative model specifications. On the other hand, tertiary education, CO2 emissions, and freshwater resources are not statistically significant. These findings emphasize the need for policymakers to promote healthier lifestyles to enhance population longevity while encouraging individuals to adopt healthier habits to improve their life expectancy. Additionally, the results suggest that European efforts in environmental protection are yielding positive outcomes, as environmental factors do not negatively affect life expectancy.
Households’ preferences, market perception and future expectations play a crucial role in shaping housing market dynamics. We conduct a survey in a period of rising inflation, high interest rates and large increases in real estate prices to study how these factors influence homebuying sentiment and decision-making. Our findings indicate that households do not exhibit systematic underreaction or overreaction to price changes. However, they hold strong expectations about future price trends, perceiving relatively low risk in the market. Notably, their short-term expectations are shaped by individual characteristics and current market sentiment, while long-term expectations remain closely aligned with actual market dynamics. Moreover, the study provides some evidence that in transition economies, homebuyers are not primarily driven by speculation or investment motives. These insights contribute to a deeper understanding of household behaviour in evolving housing markets, offering valuable implications for policymakers and market analysts.
This paper examines the evolution of trade concentration and diversification in a small open economy from 2010 to 2024, with a particular focus on the post-2020 shock environment. Using UN Comtrade data, we analyze exports and imports by partner and product, distinguishing changes in trade scope from changes in exposure. Concentration is measured using partner- and product-level Herfindahl–Hirschman Indices, effective numbers of partners and products, and top-five product shares at the HS4 level (four-digit Harmonized System). Trade scope is captured by extensive-margin indicators based on the number of active HS4 product lines. We benchmark Slovenia against comparable small open economies in Central and Eastern Europe, the Nordics, and the Baltics, with Austria as an upper-regional benchmark, and complement the descriptive analysis with panel regressions. This yields three main results. First, partner concentration is consistently higher on the import side than on the export side across benchmarks. Second, the post-2020 period is marked by increased concentration in core products and, in some cases, partners, alongside modest expansion in extensive margins. Third, while broader product scope is associated with lower concentration, this relationship is economically small and does not offset the observed post-2020 reconcentration in Slovenia. Overall, the findings highlight that changes in trade scope and exposure may diverge, underscoring the importance of jointly interpreting concentration and extensive-margin indicators for small open economies under heightened global uncertainty.
